Assistive Technology and\
Information Technology Use and Need\
by Persons With Disabilities\
in the United States, 2001

August 2005

U.S. Department of Education

National Institute on Disability and Rehabilitation Research

**Assistive Technology and\
Information Technology Use and Need\
by Persons With Disabilities\
in the United States, 2001**

August 2005

Dawn Carlson

*National Institute on Disability and Rehabilitation Research*

Nat Ehrlich

*University of Michigan, Ann Arbor*

U.S. Department of Education

National Institute on Disability and Rehabilitation Research

**U.S. Department of Education**

Margaret Spellings

*Secretary*

**National Institute on Disability and Rehabilitation Research**

Steven James Tingus

*Director*

**August 2005**

This report is in the public domain. Authorization to reproduce it in
whole or in part is granted. While permission to reprint this
publication is not necessary, the citation should be: Carlson, D., &
Ehrlich, N. U.S. Department of Education, National Institute on
Disability and Rehabilitation Research, *Assistive Technology and
Information Technology Use and Need by Persons With Disabilities in the
United States,* Washington, D.C., 2005.

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######## Contents

[Figures iv](#figures)

[Tables vii](#tables)

[Executive Summary 1](#executive-summary)

[Part I. Legislative Background, Need for the Study and Study Design
5](#part-i.-legislative-background-need-for-the-study-and-study-design)

[1. Overview of Legislation and Policy Related to Assistive Technology
and Information Technology
5](#overview-of-legislation-and-policy-related-to-assistive-technology-and-information-technology)

[2. Review of the Literature and Comparable Surveys
11](#review-of-the-literature-and-comparable-surveys)

[3. Survey Design 35](#survey-design)

[Part II: Descriptive and Bivariate Analyses
55](#part-ii-descriptive-and-bivariate-analyses)

[4. Respondent Characteristics and Patterns of Assistive Technology Use
55](#respondent-characteristics-and-patterns-of-assistive-technology-use)

[5. Assistive Technology Use at Home, in School, at Work and in the
Community
79](#assistive-technology-use-at-home-in-school-at-work-and-in-the-community)

[6. Attitudes and Opinions About Assistive Technology-Related Services,
Policies and Legislation
95](#attitudes-and-opinions-about-assistive-technology-related-services-policies-and-legislation)

[7. Assistive Technology Use and Personal Assistance Services
103](#assistive-technology-use-and-personal-assistance-services)

[8. Assistive Technology Use and Community Integration
109](#assistive-technology-use-and-community-integration)

[Part III: In-Depth Analyses 119](#part-iii-in-depth-analyses)

[9. Severity of Impairment and Assistive Technology Use and Need
119](#severity-of-impairment-and-assistive-technology-use-and-need)

[10. Education As a Predictor of Assistive Technology Use and Need
129](#education-as-a-predictor-of-assistive-technology-use-and-need)

[11. Sources of Information About Assistive Technology
137](#sources-of-information-about-assistive-technology)

[12. Sources of Payment for Assistive Technology
145](#sources-of-payment-for-assistive-technology)

[Summary and Conclusion 159](#summary-and-conclusion-4)

[References 163](#references)

[Appendix A: Screening Instrument 177](#appendix-a-screening-instrument)

[Appendix B: Simplified Questionnaire---Content Only
181](#appendix-b-simplified-questionnairecontent-only)

# Figures

[3.1 Assistive Technology Use: Probing Pattern
41](#__RefHeading___Toc114975402)

[3.2 Assistive Technology Need: Probing Pattern
42](#__RefHeading___Toc114975403)

[3.3 Telephone and Computer Use: Probing Pattern
43](#__RefHeading___Toc114975404)

[3.4 Access to the Environment: Probing Pattern
44](#__RefHeading___Toc114975405)

[3.5 Disposition of Sample Telephone Numbers
47](#__RefHeading___Toc114975406)

[3.6 Negative Codes 48](#__RefHeading___Toc114975407)

[4.1 Age Category of Respondents, by Sample
56](#__RefHeading___Toc114975408)

[4.2 Household Income, Year 2000 58](#__RefHeading___Toc114975409)

[4.3 Personal Income and Household Income for 2000
59](#__RefHeading___Toc114975410)

[4.4 Personal Income, Year 2000 59](#__RefHeading___Toc114975411)

[4.5 Households With a Person With Impairment, by Type: RDD vs. List
60](#__RefHeading___Toc114975412)

[4.6 Percent of Households With a Person With Functional Limitation, by
Type: RDD vs. List 61](#__RefHeading___Toc114975413)

[4.7 Respondent Status, by Type of Sample
61](#__RefHeading___Toc114975414)

[4.8 Percent of Households Reporting AT Device Use
62](#__RefHeading___Toc114975415)

[4.9 Sources of Information About AT 64](#__RefHeading___Toc114975416)

[4.10 Source of Supply of AT 64](#__RefHeading___Toc114975417)

[4.11 Source of Payment for AT 65](#__RefHeading___Toc114975418)

[4.12 Level of Satisfaction With AT 65](#__RefHeading___Toc114975419)

[4.13 Telephone Availability Outside the Home
67](#__RefHeading___Toc114975420)

[4.14 Computer Availability 67](#__RefHeading___Toc114975421)

[4.15 Need for Assistance to Access the Environment
69](#__RefHeading___Toc114975422)

[4.16 Need for Environmental Modifications
69](#__RefHeading___Toc114975423)

[4.17 Unmet Need for AT and Level of Education
74](#__RefHeading___Toc114975424)

[4.18 Unmet Need for AT and Attitudes and Opinions About AT
75](#__RefHeading___Toc114975425)

[4.19 Unmet Need for AT and Age 75](#__RefHeading___Toc114975426)

[4.20 Unmet Need for AT and Personal and Family Income
76](#__RefHeading___Toc114975427)

[4.21 Gender and Unmet Need for AT 76](#__RefHeading___Toc114975428)

[5.1 Use of AT by Enrolled Students 83](#__RefHeading___Toc114975429)

[5.2 Use of AT by Employed Respondents 86](#__RefHeading___Toc114975430)

[6.1 Amount of Information Received About AT
95](#__RefHeading___Toc114975431)

[6.2 Amount of Information About How to Obtain AT
96](#__RefHeading___Toc114975432)

[6.3 Impact of Information About AT 97](#__RefHeading___Toc114975433)

[6.4 Awareness Raised Through Information About AT
98](#__RefHeading___Toc114975434)

[6.5 AT Use and Decreased Need for Personal Assistance
98](#__RefHeading___Toc114975435)

[6.6 Impact of Better Designed Environmental Access Features
99](#__RefHeading___Toc114975436)

[6.7 Increased Awareness of Need for AT
99](#__RefHeading___Toc114975437)

[6.8 Systems' Changes Helped to Get AT
100](#__RefHeading___Toc114975438)

[6.9 Increased Awareness About AT 100](#__RefHeading___Toc114975439)

[6.10 Availability of Technical Assistance
101](#__RefHeading___Toc114975440)

[7.1 Use of AT and Personal Assistance Services
104](#__RefHeading___Toc114975441)

[7.3 Use of Personal Assistance and Race
105](#__RefHeading___Toc114975442)

[7.4 Use of Personal Assistance and Education
105](#__RefHeading___Toc114975443)

[7.5 Use of Personal Assistance and Family Income
106](#__RefHeading___Toc114975444)

[7.6 Use of Personal Assistance and Personal Income Level
107](#__RefHeading___Toc114975445)

[7.7 Percent Within Age Groups Using Personal Assistance RDD vs. List
Sample Respondents 107](#__RefHeading___Toc114975446)

[7.8 Percent Within Age Groups, All Respondents RDD vs. List
Sample Respondents 108](#__RefHeading___Toc114975447)

[8.1 Days Out of the Home 14 Days Prior to Interview
109](#__RefHeading___Toc114975448)

[8.2 AT Use and Number of Days Spent Out of the Home
110](#__RefHeading___Toc114975449)

[8.3 Days Out of the Home and AT Use 110](#__RefHeading___Toc114975450)

[8.4 Leaving Home, Level of Impairment and AT Use
111](#__RefHeading___Toc114975451)

[8.5 Race and Days Out of the Home 112](#__RefHeading___Toc114975452)

[8.6 Proportion of Respondents Below Median in Number of Days Out of the
Home, by Race and Age 113](#__RefHeading___Toc114975453)

[8.7 Proportion of Respondents Below Median in Number of Days Out of the
Home, by Gender and Age 113](#__RefHeading___Toc114975454)

[8.8 Respondent Level of Personal Income and Days Out of the Home
114](#__RefHeading___Toc114975455)

[8.9 Respondent Level of Education and Days Out of the Home
115](#__RefHeading___Toc114975456)

[9.1 AT Used by Respondents, by Severity of Impairment
122](#__RefHeading___Toc114975457)

[9.2 Unmet Need for AT, by Severity of Impairment and Domain of Living
122](#__RefHeading___Toc114975458)

[9.3 Expressed Need for More AT 123](#__RefHeading___Toc114975459)

[9.4 Level of Educational Attainment and Severity of Impairment
124](#__RefHeading___Toc114975460)

[9.5 Severity of Impairment and Level of Educational Attainment
124](#__RefHeading___Toc114975461)

[9.6 Severity of Impairment and Major Activity Status
125](#__RefHeading___Toc114975462)

[10.1 Distribution of Respondents, by Severity and Educational Level
131](#__RefHeading___Toc114975463)

[10.2 AT Use as a Joint Function of Education and Personal Income
134](#__RefHeading___Toc114975464)

[11.1 Sources of Information About AT 138](#__RefHeading___Toc114975465)

[11.2 Opinions About the Usefulness of Information About AT As a
Discriminant Factor Across Information Sources
139](#__RefHeading___Toc114975466)

[11.3 Attitudes and Opinions About AT, by Persons With Disabilities
Using Personal Assistance (PAS) vs. Non-PAS Users
141](#__RefHeading___Toc114975467)

[12.1 Types of AT Used 148](#__RefHeading___Toc114975468)

[12.2 Sources of Payment for AT 149](#__RefHeading___Toc114975469)

[12.3 Share of Out--of--Pocket Expenses, by Type of AT
150](#__RefHeading___Toc114975470)

[12.4 Source of Payment for AT, Normalized Mention vs. DF
152](#__RefHeading___Toc114975471)

[12.5 Discriminant Function Analysis: Working, Not Working
152](#__RefHeading___Toc114975472)

[12.6 Discriminant Function Analysis: Working, Unable to Work
153](#__RefHeading___Toc114975473)

[12.7 Discriminant Function Analysis: High Education, Low Education
154](#__RefHeading___Toc114975474)

[12.8 Discriminant Function Analysis: Impairment, Severe--Mild
154](#__RefHeading___Toc114975475)

[12.9 Discriminant Function Analysis: AT Opinion, Positive--Negative
155](#__RefHeading___Toc114975476)

[12.10 Discriminant Function Analysis: Personal Income, High--Low
156](#__RefHeading___Toc114975477)

[12.11 Discriminant Function Analysis: Age, Older--Younger
156](#__RefHeading___Toc114975478)

# Tables

[1.1 Tech Act Appropriations, Including Title III
7](#__RefHeading___Toc114975684)

[2.1 Overview of National Surveys With Assistive Technology Components
13](#__RefHeading___Toc114975685)

[3.1 Completed RDD Interviews per 1,000 Telephone Numbers (Est.)
39](#__RefHeading___Toc114975686)

[3.2 Completed List Interviews per 1,000 Telephone Numbers (Est.)
39](#__RefHeading___Toc114975687)

[3.3 Call Statistics 47](#__RefHeading___Toc114975688)

[3.4 Response Rates 49](#__RefHeading___Toc114975689)

[4.1 Gender, by Type of Sample 55](#__RefHeading___Toc114975690)

[4.2 Race and Ethnicity, by Type of Sample
57](#__RefHeading___Toc114975691)

[4.3 Level of Education, by Type of Sample
57](#__RefHeading___Toc114975693)

[4.4 Most Mentioned AT Devices Used 63](#__RefHeading___Toc114975694)

[4.5 Number of Conditions Coded, by Type of Sample
70](#__RefHeading___Toc114975695)

[4.6 List of Frequently Mentioned Health Conditions
71](#__RefHeading___Toc114975696)

[4.7 Type of AT Device Used at Home, School, Work and in the Community
72](#__RefHeading___Toc114975719)

[4.8 AT Use in the Home 73](#__RefHeading___Toc114975720)

[5.1 Sources of Information (AT at Home)
79](#__RefHeading___Toc114975721)

[5.2 Sources of Supply (AT at Home) 80](#__RefHeading___Toc114975722)

[5.3 Sources of Payment (AT at Home) 80](#__RefHeading___Toc114975723)

[5.4 Level of Satisfaction With AT (AT at Home)
81](#__RefHeading___Toc114975724)

[5.5 Level of Satisfaction With Advice (AT at Home)
81](#__RefHeading___Toc114975725)

[5.6 Sources of Help (AT at Home) 82](#__RefHeading___Toc114975726)

[5.7 Source of Information (AT in School)
83](#__RefHeading___Toc114975727)

[5.8 Source of Supply (AT in School) 83](#__RefHeading___Toc114975728)

[5.9 Source of Payment (AT in School) 84](#__RefHeading___Toc114975729)

[5.10 Level of Satisfaction With AT (AT in School)
84](#__RefHeading___Toc114975730)

[5.11 Sources of Help (AT in School) 85](#__RefHeading___Toc114975731)

[5.12 Source of Information (AT at Work)
86](#__RefHeading___Toc114975732)

[5.13 Source of Supply (AT at Work) 87](#__RefHeading___Toc114975733)

[5.14 Source of Payment (AT at Work) 87](#__RefHeading___Toc114975734)

[5.15 Level of Satisfaction with AT (AT at Work)
87](#__RefHeading___Toc114975735)

[5.16 Source of Help (AT at Work) 89](#__RefHeading___Toc114975736)

[5.17 Source of Information (AT in the Community)
90](#__RefHeading___Toc114975737)

[5.18 Source of Supply (AT in the Community)
90](#__RefHeading___Toc114975738)

[5.19 Source of Payment (AT in the Community)
91](#__RefHeading___Toc114975739)

[5.20 Level of Satisfaction (AT in the Community)
91](#__RefHeading___Toc114975740)

[5.21 Satisfaction With Advice (AT in the Community)
92](#__RefHeading___Toc114975741)

[5.22 Sources of Help (AT in the Community)
92](#__RefHeading___Toc114975742)

[8.1 Race, Age and Disability 112](#__RefHeading___Toc114975743)

[8.2 Need for Personal Assistance and Environment Modifications
116](#__RefHeading___Toc114975744)

[8.3 Need for Environmental Modifications and Major Activity
116](#__RefHeading___Toc114975745)

[9.1 Type of Devices Used, by Level of Impairment
123](#__RefHeading___Toc114975746)

[9.2 Severity of Impairment, by Gender
125](#__RefHeading___Toc114975747)

[10.1 AT Use and Level of Education, by Severity of Impairment
130](#__RefHeading___Toc114975748)

[10.2 Source of Information, by Level of Impairment
133](#__RefHeading___Toc114975749)

[10.3 Number of AT Devices Used, by Level of Impairment
133](#__RefHeading___Toc114975750)

[11.1 Sources of Information About AT, by State Population
Characteristics 142](#__RefHeading___Toc114975751)

[12.1 Sources of Payment, by Type of Device
149](#__RefHeading___Toc114975753)

[12.2 Sources of Payment, by Type of Assistive Device in Percent
150](#__RefHeading___Toc114975754)

[12.3 Respondent Characteristics and Sources of Payment
151](#__RefHeading___Toc114975755)

# Executive Summary

The 2001 Survey of Assistive Technology and Information Technology Use
and Need by Persons With Disabilities in the United States (AT Survey),
was conducted over a nine-month period from March through December 2001.
Each respondent was screened in as a person with a disability based on a
screening instrument developed by the National Institute on Disability
and Rehabilitation Research (NIDRR), the Rehabilitation Engineering and
Assistive Technology Society of North America (RESNA), and the Survey
Research Center (SRC) in the Institute for Social Research at the
University of Michigan. The screener used questions from the 2000 U. S.
Census and the National Health Interview Survey. Respondents were asked
about personal characteristics, including disability status, followed by
questions about assistive technology (AT) and information technology
(IT) use and need in the home, at school, at work, and in the community.
Attitudes and opinions about the availability and usefulness of AT
(devices, technologies and services) were explored, as well as other
factors believed to affect AT use and need, such as the severity of the
impairment and the need for personal assistance services.

The respondents were drawn from two sources: a targeted list of persons
with disabilities and random-digit dialing. A total of 1,414 individuals
were interviewed by telephone: 1,002 from the list sample and 412 from
the random-digit dial sample. The overall response rate exceeded 90
percent for both samples. Analysis showed no systematic selection bias
in the random-digit dial portion of the survey, but there was
over-representation of respondents from states with smaller populations
in the list sample. Also, a series of reliability tests was performed to
test for differences in response patterns between the two samples. No
statistically significant differences were detected. We believe that the
data and information gathered with this survey accurately represent the
experiences of persons with disabilities who use or need AT, and how
they went about obtaining and paying for the devices.

### Findings

#### Demographics

The survey gathered information about gender, race, education, income
levels and employment status of respondents. Sample characteristics
were: 58 percent female, 42 percent male and 81 percent white. About 45
percent of respondents had gone to or had completed high school, 33
percent had some college, and 15 percent graduated from college or did
some post graduate work, or both. Overall:

-   The modal occupational status was "unable to work because of a
    disability."

-   More than 100 conditions were mentioned as causing the respondents'
    limitations. The most frequently mentioned ailments were
    osteoarthritis, hearing loss, lingering effects of injury, back
    disorders, multiple sclerosis, diabetes and heart disease.

#### Type of Assistive Technology Used 

-   Of all respondents, 901 (64 percent) used some assistive technology.
    The prevalence of AT and IT use at school and at work was 36
    percent; use at home was 49 percent; and use in the community was 50
    percent. (These estimates are based on an 18.6 percent prevalence
    rate of disability among persons age 18 and older in the United
    States in 2001).

-   Most of the assistive devices used were designed to enhance
    mobility: canes, crutches, walkers, scooters and wheelchairs.
    Hearing aids, oxygen tanks and other personal-use devices were also
    among the most frequently used devices.

-   Most respondents who used AT said it made them more productive and
    more aware of their rights. In contrast, more than 24 percent of
    respondents reported that AT had not substantially reduced their
    dependence on other people.

#### Factors Influencing Assistive Technology Use 

The main determinants of AT use and need were the severity of the
impairments and the levels of education. Respondents whose conditions
were more severe were found to have the following characteristics, when
compared to less impaired respondents:

-   Greater use of assistive technology, both in likelihood of use and
    number of devices used;

-   More likely to have had their AT paid for by Medicare or the
    Veterans Administration;

-   Less likely to pay for it themselves or from private medical
    insurance;

-   Lower education levels;

-   A greater likelihood of having been unable to work because of their
    conditions;

-   Lower family incomes;

-   More likely to be males than females; and

-   More likely to be black than white.

Analysis of a number of factors influencing the use of AT revealed that
AT use was not related to gender, age, race or level of impairment.
Respondents with higher levels of education were more likely users of
AT. Overall, 72 percent of the variance within the amount of AT use
could be attributed to the amount of education attained by the
respondent. In addition:

-   Respondent age, race, sex, severity of respondent condition or the
    perceived need for more assistance were unrelated to the level of
    education achieved (thereby eliminating these variables as sources
    of confounding).

-   Persons with higher levels of education made use of more sources of
    information to obtain AT, were more likely to contact another person
    or agency to obtain more help, were more aware that help is
    available in obtaining AT, and were more satisfied with their AT and
    the assistance they got in obtaining it.

-   There was no effect of education level on the likelihood of having
    tried, and failed, to obtain AT.

-   There was a strong, positive relationship between level of education
    and both personal and family incomes---but the level of income and
    AT use were negatively correlated.

#### Factors Influencing Assistive Technology Need

The influence of severity on perceived need for additional AT was more
complicated. The greatest unmet need occurred among the moderately
impaired in the home, while the smallest unmet need for AT occurred
among the severely impaired in the workplace. A likely explanation is
that respondents who were severely impaired were not only less likely to
be gainfully employed, but even when they were working, were more likely
to already be using AT than the other, less severely impaired
respondents.

On the attitude and opinion questions, persons with severe impairments
were more positive in their responses about the information they had
received, the use of that information, and the help they received from
improved products and AT in general, but more negative in judging
improvements over the past decade.

#### Sources of Information About How to Obtain Assistive Technology

Our findings show that the source of information had a major effect on
respondents' attitudes about the utility of the information and of AT.
For example, the information respondents obtained from family and
friends was seen less positively than from other sources in general, and
vocational rehabilitation counselors in particular. In addition:

-   Most respondents learned about AT devices from their doctors and
    obtained them from medical or orthopedic supply houses.

-   More than one-half of the respondents (52 percent) said that they
    received little or no information about AT, and 62 percent said they
    received little or no information on how to obtain it.

-   Those who had received information said that it was useful.

#### Sources of Payment and Funding for Assistive Technology

Respondents were asked a series of questions about the process of
acquiring AT. Most respondents (51 percent) said they learned about AT
devices from doctors and other health care providers and obtained the
devices from medical or orthopedic supply houses. More than one-third of
respondents (37 percent) said they paid for the devices themselves or
had a family member pay for them. A similar number (38 percent) paid for
the devices primarily through private insurance, Medicare and Medicaid.
Regarding help in the selection and purchase of AT, only about 1 in 5
respondents said they received assistance. Most who asked for help said
they received it, but the most common response was that the respondents
did not feel the need to ask for help.

Funding of AT can present a barrier to some persons who need to acquire
AT or IT. Almost 40 percent of respondents said they paid for the AT or
IT themselves or with help from a family member, and a similar
percentage relied on a third-party payer, such as private health
insurance, Medicare or Medicaid, to pay for the needed AT or IT.

*Information Technology Use*

Although respondents said they encountered virtually no difficulties in
using information technology such as telephones, a significant number
said that they had problems with computer use. The survey showed that 36
percent of the respondents required the assistance of another person to
use the computer, and 14 percent of respondents required special
modifications to use the computer. However, the majority of respondents
said they believed that they were well served regarding their need,
ability and opportunity to use telephones and computers.

*Attitudes and Opinions About AT and IT Use*

Respondents were asked four questions to obtain their opinions on
whether awareness of the need for AT, laws regarding AT, awareness of
the benefits of AT, and assistance for purchasing AT, have changed
compared to 10 years ago. Respondents were largely in agreement with the
statements that, compared to 10 years ago, people are more aware of the
need for AT, that they understand AT, that the laws have changed, and it
is easier to get assistance in obtaining AT. In all cases, the responses
of persons who are using AT were more positive than those of the non-AT
users.

### Conclusions

The major shortfall of all studies about technical assistance on AT has
been the lack of state-based data on how well the technical assistance
programs have worked in the past, and if there are reasons to believe
that future investment in these programs will yield measurable benefits
for persons with disabilities. Such information is crucial for
understanding how the various state-based programs have worked,
considering that each state had a large amount of independence and
control over what services were provided, to whom, by whom, when, where
and how. States and territories provided different amounts of additional
funding in addition to federal funds, but more importantly, the
population size of the states and their political, economic and
geographic characteristics may have affected the quality and amount of
AT services provided to persons with disabilities as well. There is no
evidence today that can tell us how well the 56 programs have worked as
a whole or individually when compared to each other.

Finally, the effectiveness of a federal program to assist persons with
disabilities in the selection and purchase of AT should be measured in
terms of specific outcomes, such as employment and higher levels of
social integration. There is anecdotal evidence of how AT has helped
persons with disabilities and their families, but AT alone is not the
sole contributor to such success. Other factors such as adequate
education and job training of AT users play a major role as well. In
that regard, more research that measures the direct and indirect
benefits resulting from the purchase and use of AT in conjunction with
these other factors is needed.

# Part I. Legislative Background, Need for the Study and Study Design

## 1. Overview of Legislation and Policy Related to Assistive Technology and Information Technology

### Legislative Background 

Assistive technology devices, including adaptations to existing products
and devices that are part of daily living, significantly benefit persons
with disabilities of all ages.[^1] Such devices and adaptations can
increase the involvement of persons with disabilities in programs and
activities such as early intervention, education, rehabilitation,
training, employment, residential living, independent living, recreation
and other aspects of daily living and reduce the costs associated with
such program participation.

The importance of assistive technology in the lives of people with
disabilities was appropriately acknowledged with the passage of the
*Technology-Related Assistance for Individuals with Disabilities Act of
1988* (29 U.S.C. 2201 et seq.) also called the *Tech Act*.

Assistive technology device is defined by the *Tech Act* as "any device,
piece of equipment, or product system, whether acquired commercially or
off the shelf, modified or customized that is used to increase, maintain
or improve functional capabilities of individuals with disabilities."
This broad definition of assistive technology encompasses the vast
number of everyday and specialized devices that can provide assistance
to individuals with disabilities.

The *Tech Act of 1988* authorized systems change grants to states to
increase access to assistive technology devices and services. This
legislation, along with the *Americans with Disabilities Act*, brought
an increased awareness of assistive technology to the general public and
to people with disabilities; placed a greater emphasis on the rights of
people with disabilities to obtain needed technology; and initiated the
beginning of systems changes to remove barriers to obtaining assistive
technology.

Subsequent legislation, including the 1994 amendments to the *Tech Act*,
placed greater emphasis on state responsibility, advocacy, systems
change and consumer responsiveness as well as providing additional
funding for assistive technology services (Flippo, 1995). The *Assistive
Technology Act of 1998*, or *AT Act* (Public Law 105-394), provided
additional funding to states, territories and outlying areas; expanded
national activities and increased government coordination; and increased
alternative financing efforts. The *AT Act* consists of three titles:

**Title I** authorized funding for multiple continuity grants and grants
for protection and advocacy systems, as well as funding for a technical
assistance program. The law specified activities that states are
required to undertake: establishing public awareness programs; promoting
interagency cooperation; providing technical assistance and training;
and conducting community outreach. State grantees are expected to set
measurable goals in connection to their use of *AT Act* funds, and both
the goals and the approach to measuring the goals had to be based on
input from individuals with disabilities in the state.

**Title II** promoted increased coordination of federal efforts related
to assistive technology and universal design, a strengthening of the
mandate of the Interagency Committee on Disability Research (ICDR) to
include assistive technology and universal design research, and
authorization for funding joint research projects by ICDR members. In
addition, Title II authorized funding for:

-   Small Business Innovative Research grants (an existing program under
    the *Small Business Act*) related to assistive technology;

-   Grants to commercial or other organizations for research and
    development related to universal design concepts;

-   Grants or other mechanisms to address the unique assistive
    technology needs of urban and rural areas, and of children and the
    elderly;

-   Grants or other mechanisms to improve training of rehabilitation
    engineers and technicians; and

-   The President's Commission on the Employment of People With
    Disabilities to work with the private sector to promote the
    development of accessible information technologies.

**Title III** established alternative financing programs for people with
disabilities to purchase assistive technology devices and services
through grants to states and outlying areas. These funds could be used
to establish specified types of loan programs for individuals with
disabilities, but could not be used simply to purchase assistive
technology for individuals.

The *Tech Act of 1988*, the *Tech Act* reauthorization of 1994, and the
*AT Act of 1998* included a "sunset" provision that reduced federal
funding to states in their ninth year by 25 percent of their eighth-year
allocation, and in their tenth year by 50 percent less than their
eighth-year allocation. The *AT Act* authorized states to receive an
additional three years at the 50 percent level for a total of 13 years
of federal support, but after 13 years, no more funds could be obtained.
Since the *AT Act* was authorized through FY 2004, the states funded in
1989, 1990 and 1991 were expected to gradually phase out of the program.

Since the enactment of the *Tech Act* in 1988, a total of over \$475
million in federal funds have been appropriated. Table 1.1 contains the
annual amounts. Please note that 1995 was the first year that all 56
states and territories participated in the program.

[]{#__RefHeading___Toc114975684 .anchor}Table 1.1 Tech Act
Appropriations, Including Title III[^2]

  ----------------------- ----------------------- -----------------------
  **Fiscal Year**         **State Projects**      **Appropriation**

  1989                    9                       \$5,150,000

  1990                    23                      \$14,814,000

  1991                    31                      \$20,982,000

  1992                    42                      \$28,000,000

  1993                    53                      \$34,068,000

  1994                    55                      \$27,744,000

  1995                    56                      \$39,239,000

  1996                    56                      \$36,109,000

  1997                    56                      \$36,109,000

  1998                    56                      \$36,109,000

  1999                    56                      \$34,000,000

  2000                    56                      \$34,000,000\*

  2001                    56                      \$41,100,000\*

  2002                    56                      \$60,884,000\*

  2003                    56                      \$26,824,000

  *\* These amounts                               
  include appropriations                          
  for Title III.*                                 
  ----------------------- ----------------------- -----------------------

### Legislative Update: *Assistive Technology Act of 2004*

Since this survey was conducted, the *Assistive Technology Act of 2004*
was enacted on Oct. 25, 2004 (Public Law 108-364). This law renews
federal assistive technology aid to states and requires states to spend
the bulk of state grants on direct services for individuals with
disabilities.

The 2004 act updates the purpose of the *Assistive Technology Act* to
reflect the priority of increasing access to needed devices for
individuals with disabilities. The Assistive Technology State Grant
Program was established in 1988 as a 10-year program to provide seed
money to enable states to create systems for improving access to
assistive technology devices for individuals with disabilities. However,
this program has been extended beyond the original 10-year window. In
the 16 years since the inception of this program, states have
established the needed infrastructure to effectively administer
assistive technology resources. The new law redefines the primary
purpose of this program from establishing systems to directly helping
the individuals with disabilities who need assistive technology devices.

Under the *Assistive Technology Act of 2004*, states would be required
to use a majority of federal funds to directly help individuals. States
would chose between two options for assistive technology state grants.
States would be required to:

-   Use 60 percent of assistive technology state grants on direct aid
    programs, including assistive technology reutilization programs,
    assistive technology demonstration programs, alternative financing
    programs and device loan programs; or

-   Use 70 percent of assistive technology state grants on direct aid
    programs, but have full discretion on how to allocate funds for at
    least two, and up to all four, of the programs listed above.

The law creates greater accountability for how states use assistive
technology grants. It requires states to submit an application with
detailed descriptions of planned activities and measurable goals
relating to education, employment, telecommunication or information
technology, and community living. The law also includes detailed
criteria for the Department's annual report to Congress to determine the
effectiveness of the program.

### Other Legislation Related to Assistive Technology and Information Technology

Section 504 of the *Rehabilitation Act of 1973* (29 U.S.C. §794)
requires that the services, programs and activities, including
information services, of a covered entity which receives federal funds
must be accessible to and usable by persons with disabilities, with or
without "reasonable modifications." It further provides that such
entities not discriminate in the hiring, placement and advancement of
persons with disabilities, and shall make "reasonable accommodation" for
their otherwise qualified employees with disabilities.

Section 508 of the *Rehabilitation Act of 1973* (29 U.S.C. §794d)
requires that employees with disabilities and citizens with disabilities
have comparable access to electronic and information technology.
"Electronic and information technology" means any equipment, software,
interface systems, operating systems, or interconnected system or
subsystem of equipment used in the acquisition, storage, manipulation,
management, movement, control, display, switching, interchange,
transmission, or reception of data or information. "Comparable access"
means that individuals with disabilities must be able to produce and
have access to the same or equivalent information processing resources,
with or without special peripherals, as individuals without
disabilities.

The *Telecommunications Act of 1996* (47 U.S.C. §255) requires
telecommunications products and services to be accessible to people with
disabilities. Manufacturers must ensure that products are "designed,
developed and fabricated to be accessible to and usable by individuals
with disabilities" when it is "readily achievable" to do so. Section 255
applies only to products designed, developed and fabricated after the
law took effect on Feb. 8, 1996.

The *Hearing Aid Compatibility Act of 1988* (47 U.S.C. §610) requires
that the Federal Communications Commission (FCC) ensure that all
telephones manufactured or imported for use in the United States after
August 1989 and all "essential" telephones are hearing aid compatible.
"Essential" phones are defined as "coin-operated telephones, telephones
provided for emergency use, and other telephones frequently needed for
use by persons using such hearing aids." These might include workplace
telephones, telephones in confined settings (like hospitals and nursing
homes), and telephones in hotel and motel rooms. Secure telephones, as
well as telephones used with public mobile and private radio services,
are exempt from the *HAC Act*. In June 1996, the FCC adopted rules to
address the needs of telephone users with hearing disabilities. To be
hearing-aid compatible, the telephone receiver must contain an
electromagnetic coil that emits a magnetic field. At present, the FCC's
HAC requirements only apply to wireline and cordless telephones, not to
telephones used with mobile services, such as cellular telephones.

The *Individuals with Disabilities Education Act* (20 U.S.C. §1400 et
seq.) mandates the provision of assistive technology devices and
services if they are required as part of a child's individualized
education program. On Dec. 3, 2004, the president signed the
*Individuals with Disabilities Education Improvement Act* into law. Most
provisions of the new law take effect on Jul. 1, 2005.

The *Americans with Disabilities Act* (42 U.S.C. §12101 et seq.)
addresses access to the workplace (Title I), state and local government
services (Title II), and places of public accommodation and commercial
facilities (Title III). Title IV addresses assistive technology
specifically as it requires phone companies to provide
telecommunications relay services for people who have hearing or speech
impairments.

### Current Federal Policy Efforts

Effective use of AT depends on the availability of trained service
providers. Persons with disabilities require assistance in selecting
appropriate devices, training in the proper use of equipment, and access
to maintenance and repair work and replacements when equipment becomes
nonfunctional or obsolete. Two questions that frequently arise in this
context are:

1.  Who should provide technical assistance services for persons with
    disabilities?

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1.  Who should pay for these services?

Medicare and Medicaid provide funding for some forms of assistive
technology but the implications for access posed by coverage rules
related to "medical necessity" are not entirely clear. Differences
across states in interpretation of medical need limitations have given
rise to equity concerns (Seelman, 1993). For instance, in a 1993 study
published by the National Council on Disability, respondents complained
about the complexity of the system, poor information on how to access
devices, lack of coordination among funding agencies, lack of training
and maintenance resources, lack of individual choice over assistive
technology services, and the significant numbers of people who remained
unserved or underserved.

Seelman (1993) noted the following additional access barriers: lack of
consumer information on technology, lack of ties to the technology
culture, language differences, and institutional living situations. Such
observations have raised questions---particularly among disability
rights advocates---if the use of technology-related services should be
based solely on one's ability to pay, and if the forces of supply and
demand should regulate the quantity, quality and price of such services.
Opponents of such a solution maintain that the majority of persons with
disabilities have very low incomes and depend on other sources of
support. A market-based ability to pay solution would likely be
imperfect as well. Some income would have to be redistributed, either by
way of taxes and expenditures, insurance premiums and benefit payments,
or charitable giving. In view of these arguments, administrative and
legislative efforts continuously address a more equitable distribution
of AT and technology-related services for persons with disabilities.
These efforts are briefly discussed below.

As part of his New Freedom Initiative launched Feb. 1, 2001, President
Bush offered a comprehensive package of initiatives to increase research
in, and access to, assistive technologies, including \$35 million in
funding for low-interest loan programs to help people with disabilities
purchase assistive technology.

The federal government promotes the interests of Americans with
disabilities as it works closely with the high-tech industry and
disability community to ensure full and successful implementation of
Section 508. Section 508 ensures that information technology purchased
by the federal government is accessible to Americans with disabilities;
its implementation is critical in an era of reliance on information
technology. For example:

-   In 1997, about 19 million Americans were using the Internet. That
    number tripled in one year, and then passed 100 million in 1999. In
    the first quarter of 2000, more than five million Americans joined
    the online world---roughly 55,000 new users each day.

-   Every 24 hours, the Web increases by more than 3.2 million new pages
    and more than 715,000 images.

-   The number of electronic mailboxes worldwide reached almost 570
    million in 1999. In 1998, the U.S. Postal Service delivered 101
    billion pieces of paper mail; estimates of e-mails transmitted that
    year range as high as four trillion.

In 2000, an estimated 54 million Americans reported having some level of
disability. Persons with disabilities are more likely to need software
and hardware modifications in order to use computers and access the
Internet. Section 508 compliance throughout the federal government will
make the benefits of e-government available to all Americans, regardless
of disability.

### Summary

This overview of assistive technology related legislation shows that the
federal government has recognized the importance of technology-related
assistance for persons with disabilities. Embedded in a framework of
laws that promote greater inclusion and participation of persons with
disabilities in all aspects of home, school, work and community life,
the *Assistive Technology Act* and other laws promote the use of
assistive technology and environmental accommodations. This is
accomplished through federal grants to state and community
organizations. Increased availability and use of assistive technology
can lead to increased access to the built environment and to the social
environment, which in turn promotes independence and inclusion for
persons with disabilities and their families.

## 2. Review of the Literature and Comparable Surveys

### Background

Increased awareness and service provision has given rise to an
ever-increasing list of issues and topics surrounding the use of
assistive technology. Issues such as assessment, evaluation, funding,
access to services, underserved populations, outcomes, product
development and device selection have emerged as important topics.
Thousands of articles and materials that document these issues were
found on the Internet, in professional journals, and in consumer
education and training materials. Yet few of the materials document the
extent of assistive technology use and the long-term impact of assistive
technology legislation.

The growing awareness and availability of assistive technology over the
last decade has provided a greater level of independence and community
participation for people with disabilities. The *Technology-Related
Assistance for Individuals with Disabilities Act of 1988* created a
structure for growth in assistive technology use. Research conducted
since that time confirmed an increase in assistive technology use. This
literature review documents relevant research on assistive technology
use, including the issues surrounding assistive technology and the
people who use it. The following are highlights of the review's
findings:

-   Mobility devices constituted the bulk of AT used by persons with
    disabilities. Estimated rates of mobility device use from various
    surveys ranged from 2.6 percent to 90 percent, depending on the
    population that was studied, how assistive technology was defined
    and how use was measured.

-   Older adults represented the most studied group of individuals and
    demonstrated the highest assistive technology use rates among
    disability groups.

-   Trends in assistive technology use from national surveys showed an
    increase in the use of assistive devices over time which can be
    attributed in part to an aging population.

-   Assistive technology was widely used in the home, and these
    modifications often contributed to greater independence and
    increased levels of functioning.

-   Along with national surveys, state and local surveys reported
    funding as a significant barrier to assistive technology use,
    contributing to many unmet needs*.*

-   Assistive technology use in postsecondary education and in the
    workplace was limited despite the reported needs.

-   Computer use and information technology access was acknowledged in
    the research as important emerging issues in assistive technology.

### Scope of Literature Review

In an effort to increase the understanding of assistive technology use,
an extensive review of literature was conducted using the Internet and
electronic bibliographic databases to identify published research
documenting the use of assistive technology among people with
disabilities. Because of the vast number of issues surrounding assistive
technology, the focus of this literature review was limited to: 1)
adults with disabilities; 2) research published since the *Tech Act of
1988*; 3) research that used survey methods to determine assistive
technology use; 4) research with sample sizes of about 30 and larger;
and 5) research conducted in the United States.

This review provides a comprehensive look at assistive technology use
estimates from national, state and local surveys, encompassing areas
such as satisfaction, unmet needs and barriers to use, as they relate to
specific surveys. The extensive scope of research identified for this
literature review is organized into the following categories:

-   Demographic and Geographic Scope of Assistive Technology Use

-   Assistive Technology Use Among Specific Populations

-   Assistive Technology Use by Type of Device

-   Assistive Technology Use in Various Settings

The section Demographic and Geographic Scope of Assistive Technology Use
addresses the broader picture of utilization rates, types of devices
used, and trends in assistive technology use with an emphasis on
national population-based research, supplemented by state-level
research. Sections on assistive technology use among specific
populations and use of specific devices include many local surveys that
document specific research interests and issues. Because of the unique
nature of assistive technology use in various settings, the final
category addresses assistive technology at home, school, work and in the
community.

### Demographic and Geographic Scope of Assistive Technology Use

National surveys typically provided the most reliable means of
determining the demographic and descriptive variables of assistive
technology use among a geographically representative sample. Though
limited in number, these national surveys provide the basis for overall
utilization rate estimates as well as trends and other issues of
assistive technology use. National surveys were supplemented with
multi-state or small national surveys and single-state surveys and are
discussed in the later part of this section. Small sample studies that
provided a more descriptive analysis of assistive technology use among
the various demographic and geographic characteristics are also
discussed.

#### Assistive Technology Use Estimates From National Surveys

Table 2.1 includes the national surveys that estimated the use of
assistive technology among persons with disabilities since the enactment
of the *Tech Act of 1988*. This overview summarizes national surveys
that provide some documentation of assistive technology use among adults
and older adults with disabilities. Most surveys captured assistive
technology use among older adults. Only the National Health Interview
Survey and Survey of Income and Program Participation documented
assistive technology use across the lifespan.

[]{#__RefHeading___Toc114975685 .anchor}Table 2.1 Overview of National
Surveys With Assistive Technology Components

+-------------+---------------+-----------------------------+---------+
| Surveys     | Population    | Assistive Technology Used   | Source  |
+=============+===============+=============================+=========+
| National    | Functionally  | 12.0% equipment only        | Manton  |
| Long Term   | impaired      |                             | et al., |
| Care        | elderly, age  | 65.1% equipment and         | (1993)  |
| Survey\     | 65+           | personal assistance to      |         |
| 1989        |               | accommodate difficulty with |         |
|             |               | ADL and/or IADL             |         |
+-------------+---------------+-----------------------------+---------+
| National    | Noninst       | 6.4 million (2.6%) mobility | L       |
| Health      | itutionalized | devices                     | aPlante |
| Interview   | population    |                             | et al., |
| Survey-     | screened for  | 3.8 million (1.6%) hearing  | (1992)  |
| --Assistive | assistive     | devices                     |         |
| Device\     | device use    |                             |         |
| Supplement\ |               | 3.7 million (1.5%)          |         |
| 1990        |               | anatomical devices          |         |
|             |               |                             |         |
|             |               | 1.5 million (0.6%) vision   |         |
|             |               | devices                     |         |
|             |               |                             |         |
|             |               | 7.1 million (2.9%) home     |         |
|             |               | modifications               |         |
+-------------+---------------+-----------------------------+---------+
| Survey of   | Noninst       | 4.0 million (2.0%) canes,   | McNeil, |
| Income and  | itutionalized | crutches or walkers for 6   | J. 1994 |
| Program     |               | months                      |         |
| Par         | population    |                             |         |
| ticipation\ |               | 1.5 million (0.8%)          |         |
| 1991--1992  |               | wheelchairs                 |         |
+-------------+---------------+-----------------------------+---------+
| Survey of   | Noninst       | 2.1 million (1.0%) use a    | McNeil, |
| Income and  | itutionalized | wheelchair                  | J. 1997 |
| Program     | population    |                             |         |
| Par         |               | 6.3 million (3.1%) canes,   |         |
| ticipation\ |               | crutches or walkers for 6   |         |
| 1994--1995  |               | months                      |         |
+-------------+---------------+-----------------------------+---------+
| National    | Noninst       | 7.4 million mobility        | Russell |
| Health      | itutionalized | devices                     | et al., |
| Interview   |               |                             | (1997)  |
| Survey--    | population    | 4.5 million anatomical      |         |
| -Disability | screened for  | devices                     | Kaye et |
| Supplement\ | any           |                             | al.,    |
| 1994--1995  | disability    | 4.2 million hearing devices | (2000)  |
|             |               |                             |         |
|             |               | 0.5 million vision devices  |         |
+-------------+---------------+-----------------------------+---------+
| National    | Elderly       | 39.0% assistive devices     | K       |
| Health      | persons,      |                             | ramorow |
| Interview   |               |                             | et al., |
| Survey--    | Age 55+       |                             | (1999)  |
| -Supplement |               |                             |         |
| on Aging    |               |                             |         |
+-------------+---------------+-----------------------------+---------+
| National    | Nursing home  | 86.0% mobility devices      | Gabrel  |
| Nursing     | facilities    |                             | & Jones |
| Home        | and residents | 65.8% eyeglasses            | 2000a   |
| Survey\     |               |                             |         |
| 1995        |               | 11.5% toileting equipment   |         |
|             |               |                             |         |
|             |               | 12.9% transfer equipment    |         |
|             |               |                             |         |
|             |               | 2.0% no devices             |         |
+-------------+---------------+-----------------------------+---------+
| National    | Nursing home  | 90.0% mobility devices      | Gabrel  |
| Nursing     | facilities    |                             | & Jones |
| Home        | and residents | 64.2% eyeglasses            |         |
| Survey\     |               |                             | 2000b   |
| 1997        |               | 13.3% transfer equipment    |         |
|             |               |                             |         |
|             |               | 7.9% toileting equipment    |         |
+-------------+---------------+-----------------------------+---------+
| National    | Agencies      | Of current patients:        | Haupt & |
| Home and    | providing     |                             | Jones\  |
| Hospice     | home health   | 84.0% used mobility devices | 1999    |
| Care        | and hospice   |                             |         |
| Survey\     | care          | 46.9% eyeglasses            |         |
| 1996        |               |                             |         |
|             |               | 12.7% hospital beds         |         |
|             |               |                             |         |
|             |               | 12.1% shower chairs         |         |
|             |               |                             |         |
|             |               | 5.2% hearing aids           |         |
|             |               |                             |         |
|             |               | 22.4% no devices            |         |
|             |               |                             |         |
|             |               | Of discharged patients:     |         |
|             |               |                             |         |
|             |               | 60.0% used mobility devices |         |
|             |               |                             |         |
|             |               | 43.7% eyeglasses            |         |
|             |               |                             |         |
|             |               | 5.2% hearing aids           |         |
|             |               |                             |         |
|             |               | 6.3% hospital beds          |         |
|             |               |                             |         |
|             |               | 7.5% shower chairs          |         |
|             |               |                             |         |
|             |               | 31.7% no devices            |         |
+-------------+---------------+-----------------------------+---------+
| Survey of   | Persons age   | 23.0% equipment to get      | Rodgers |
| Asset and   | 70 and older  | across rooms                | &       |
| Health      |               |                             | Miller\ |
| Dynamics of |               | 4.7% equipment to get out   | 1997    |
| the Oldest  |               | of bed                      |         |
| Old\        |               |                             |         |
| 1994        |               |                             |         |
+-------------+---------------+-----------------------------+---------+

One of the most striking differences found among national surveys was
the variability in how disability was defined and assistive technology
use was measured. Surveys measured and defined disability based on
impairment, functional limitation, activity limitation, or
self-perception of disability (LaPlante, 1991). Each survey also used
different questions to identify assistive technology use. Some surveys
asked about broad types of devices and some listed specific devices,
creating room for the respondents' own definitions of assistive
technology. Jones and Sanford (1996) questioned the effect of the
different ways of reporting and defining AT use based on personal
perception of what constitutes an AT device and the way in which a
question is posed. They reported that many respondents answered "No" to
the use of aids for getting around, but reported using specific devices
such as leg braces or the presence of a ramp into the house. This kind
of variability in reporting assistive technology use, coupled with the
limited number of national surveys, limits the ability to compare
utilization rates.

#### Trends in Assistive Technology Use From National Surveys

Despite the limitations discussed above, many researchers have used
national data sets to document trends in assistive technology use among
individuals with disabilities. This research provides important
information on the changes and trends in assistive technology use among
adults with disabilities including: 1) demographic characteristics of
those who used assistive technology; 2) changes in assistive technology
utilization rates over time; 3) unmet technology needs; and 4) the
relationship between assistive technology and activities of daily
living.

##### [Demographic Trends]{.smallcaps}

Age-specific patterns of AT use were among the most common demographic
trends reported by researchers; older adults were most likely to use AT
(LaPlante et al., 1992, Russell et al., 1997). Persons over the age of
65 were more likely to use mobility devices (61.5 percent), hearing
devices (68.6 percent) and vision devices (51 percent). In contrast,
54.6 percent of those using an anatomical device were 44 years of age or
younger. The percent of people with home modifications also increased
with age, from about 1.6 percent among those under 25 years to 14.3
percent of those 75 and older (LaPlante et al., 1992). Results from the
NHIS-Supplement on Aging from the 1999 Health and Aging Chartbook
reported persons 85 and older were five times as likely to use a walker
and three times as likely to use hearing aids as persons 70--74 years
old (Kramarow, Lentzner, Rooks, Weeks, & Saydah, 1999).

Jones and Stanford (1996) also discussed the inevitable increase in the
number of people with mobility impairments. They reported the number of
people using manual wheelchairs or assistive walking devices would be
likely to increase dramatically over the next 20 years as the baby
boomers age and people live longer. Further demonstrating higher use
rates among older adults, Watts et al., (1996) used a subsample of 3,297
people from the NHIS Assistive Device Supplement who were over the age
of 65 and who reported using assistive devices. Of the 23.1 percent of
those over 65 years old who reported using assistive devices, the mean
number of devices reported was 1.48. Further analysis showed that a
greater number of total devices correlated with poorer health status and
greater activity limitations, and the greater numbers of devices used
correlated with lower incomes and higher ages. Females reported more
limitations and more devices than males, with 36 percent of females
reported using two or more devices. The most frequently owned devices
were canes, manual wheelchairs, walkers, and hearing aids (Watts et al.,
1996).

##### [Changes in assistive technology use over time]{.smallcaps}

Confirming the assistive technology use patterns of an aging population,
Russell and colleagues (1997) found that the use of assistive devices
increased rapidly when compared to the typical population growth. The
use of walkers, braces and wheelchairs almost doubled between 1990 and
1994. Some of the increase in assistive devices could be attributed to
an aging population (Russell et al., 1997). Changes in assistive
technology use over time were also documented by Manton, Corder, and
Stallard (1993) using data from the 1982 and 1989 National Long Term
Care Survey. The authors examined questions about activities of daily
living (ADL) and instrumental activities of daily living (IADL) as they
related to equipment use among the population over the age of 65.
Dependence on equipment only increased from 6.5 percent in 1982 to 12.0
percent in 1989, and dependence on equipment in conjunction with
personal assistance also increased from 60.7 to 65.1 percent. During
this time period, there was a 10 percent decline in dependence of
personal assistance only. He also attributed some of these changes to an
aging population (Manton et al., 1993).

##### [Unmet need for assistive technology]{.smallcaps}

The literature revealed that unmet technology needs were frequently
associated with, or resulted from, barriers to acquiring desired
assistive technology devices. LaPlante, Hendershot, and Moss (1992)
reported as many as 13.1 million or 5.3 percent of population were using
assistive technology to accommodate physical impairments, and 2.5
million or 1 percent expressed a need for assistive technology they did
not have. Thus, 15.6 million either used assistive technology or had
some awareness that they needed to use assistive technology. These unmet
needs were often related to increasing age and lower incomes, as the
greatest barrier to assistive technology use was often lack of funding.
Of those with unmet needs, 60 percent said they could not afford the AT
device. When asked how respondents pay for their assistive technology,
of those who bought the devices, 48 percent said that they or their
families paid for the devices with no assistance from third parties
(LaPlante et al., 1992).

Unmet needs also were reported as residual difficulty with activities of
daily living. Agree (1999) used data from the Survey of Asset and Health
Dynamics of the Oldest Old (AHEAD) to describe how assistive technology
use and personal care were related to residual difficulty (unmet ADL
need). The study did not measure overall AT use among the sample, but
suggested possible patterns of use among older adults. Of the
respondents, 9.5 percent reported sufficient care to meet ADL needs and
20.3 percent reported residual disability because of an unmet ADL need.
The number with residual disability increased to 37.4 percent of those
age 85 and older. The reported residual disability varied according to
the type of limitation and the severity of the limitation, indicating
some benefit from personal assistance only, some from equipment only,
and some from a combination. Those who used only equipment to meet ADL
needs reported less residual difficulty with mobility than those who
used personal assistance, either alone or in combination with equipment.
The use of equipment alone was most effective for those with the least
severe limitations (Agree, 1999).

##### [Activities of daily living and assistive technology use]{.smallcaps}

Assistive technology use was often linked directly to the performance of
ADLs and IADLs, especially when estimating AT use among older adults. In
many surveys, difficulty with ADLs and IADLs were an indication of
disability or limitation. Kaye, Kang, and LaPlante (2000) reported a
significant relationship between the presence of an ADL or IADL
limitation and the use of an assistive device for mobility. In addition,
the presence or absence of equipment affected the use of personal
assistance. These interrelationships are described in more detail in the
articles discussed below.

The National Survey of Self-Care and Aging (Norburn et al., 1995)
examined self-care and assistance from others in coping with functional
limitations in a sample of 3,485 community-dwelling Medicare
beneficiaries, aged 65 and older. Self-care coping strategies included
the following categories: "use equipment or assistive devices" (43.2
percent); "change behavior" (75.4 percent); "make adaptations to living
environments" (31.9 percent); and "seek/receive help from others" (69.4
percent). It is not clear if "make adaptations to living environments"
indicated the presence or use of accessibility modifications. Elderly
people who lived alone were more likely to use equipment related to
mobility. The study found that those who received assistance from others
were more likely to report using equipment. For severely impaired
individuals, most of the help received was from another person, and
equipment use was often supplementary.

Manton et al., (1993) reported that a person's reliance solely on
equipment was most prevalent for persons with either one IADL or one to
two ADL impairments, was higher for women than for men, and was highest
at younger ages. Equipment use increased over a period where
institutionalization rates were stable and mortality and chronic
disability prevalence rates declined. Use of personal assistance or
equipment alone appeared not to be sufficient to support individuals in
the community. Those persons with impairment in five to six ADLs who
used personal assistance services were likely to use equipment as a
supplement according to the 1989 National Long Term Care Survey.
Equipment was necessary to supplement active personal assistance and
could reduce long-term care costs by replacing recurrent costs from
personal assistance with non-recurrent equipment costs.

Agree and Freedman (2000) used NHIS-D to examine ways in which assistive
devices combined with formal and informal personal care to meet specific
functional needs and attempt to identify circumstances in which AT may
have the potential to substitute for or supplement personal care. They
found that of those who had difficulty with one or more ADLs, 65 percent
reported the use of assistive devices to meet their needs. There was a
strong relationship between personal care and technology use: Those with
complex equipment were more likely than those using no equipment to have
formal caregivers. In addition, those using simple technology were less
likely than those not using equipment to receive informal care. It
appeared that simple technology substituted for personal care for those
who have difficulty toileting, whereas complex technology supplemented
personal care for those who have difficulty walking.

#### Research Documenting Assistive Technology Use at the State Level

Surveys with small samples and limited geographic reach provide
additional data that can supplement larger surveys. The literature
review revealed that efforts to document AT use and need at the state
level had grown, but still vary in terms of research design, sample size
and areas of study.

##### [Small national or multi-state surveys]{.smallcaps}

This section reviews surveys that provide insight into: 1) types of
assistive technology; 2) settings of assistive technology use; 3) issues
of use and abandonment; and 4) the positive effects of assistive
technology in the lives of people with disabilities.

Chewning and Hayward (2000) surveyed 220 consumers who had contacted a
state AT project and found that respondents had a wide range of
disabilities. The most common was a non-orthopedic physical condition
(30 percent). Over 62 percent reported having a secondary disability.
After receiving assistive technology services, 94.3 percent planned to
obtain or had already obtained at least one device, and 79 percent were
currently using a device. The most frequent sources of funding were
consumers and their families (26 percent). With 60 percent of consumers
currently using high cost devices such as computers and communication
devices, funding was a significant issue. The respondents reported
moderate to high level of satisfaction with their assistive devices and
74 percent reported that the device they used most often was important
to their increased independence.

Schact and colleagues (1999) described a two-phase community-based needs
assessment of American Indians conducted in four cities. The Phase 1
sample included 532 adults from Texas, Minnesota and Colorado, of which
107 from Texas and Minnesota participated in the Phase 2 follow-up.
Assistive technology use ranged from approximately 60 percent for
glasses and contact lenses to 14 percent for crutches or canes. Strong
and Maralani (1999) surveyed 201 farm workers with disabilities. When
asked about the use of assistive devices, respondents reported using
mobility devices, but often needed a device they did not have. Glasses
were the most commonly reported device, used by 40 percent of
respondents. Of those with glasses, 75 percent needed new ones and 18
percent of those without glasses reported needing them.

Brooks (1991) surveyed 595 highly educated, employed scientists and
engineers with disabilities. The study showed that personal care devices
were more likely to be used by those with neuromuscular disorders and
limb loss. Employment devices were more likely to be used by those with
visual impairments. Transportation devices were more likely to be used
by those with neuromuscular impairments. People with hearing and visual
impairments used communications aids more, but reported never using them
in public settings. Individuals with visual impairments used educational
devices more often. Patterns suggest that persons with sensory
disabilities used devices for social tasks while those with non-sensory
disabilities were more likely to use devices for general living. In
general, respondents were satisfied with their devices, but 32 percent
said they could be inconvenient and restricting. They reported negative
attitudes toward use in public, but their actual use in public differed
from the reported attitudes of those with vision and hearing
impairments, as they rarely used AT in public settings. In addition,
those with hearing impairments rarely used devices in employment
settings (Brooks, 1991). More studies documenting AT use in various
setting were included in a later section of this review.

Issues of abandonment were documented in a small national study by
Phillips and Zhao (1993), who surveyed 227 adults with physical
disabilities to determine how technology users decided to accept or
reject assistive devices. Of the 1,732 different devices mentioned, the
most frequently used were wheelchairs, followed by canes, bath chairs
and walkers. Twenty-nine percent of devices were abandoned; splints,
crutches, braces and walkers were more frequently abandoned. The
predictors of abandonment included a change in need by the user, ease of
obtaining the device, performance of the device, and the user's
involvement in the selection process.

The National Council on Disability (1993) surveyed 136 individuals with
disabilities from seven states funded under the *Tech Act* to evaluate
the benefits associated with the use of different kinds of
technology-related assistance. The council found that 96 respondents
identified specific types of assistive technology that would make a
difference in their lives. Specifically, 62 percent of working-age
persons were able to reduce dependence on family members, 58 percent
were able to reduce dependence on paid assistance, and 37 percent were
able to increase earnings with the use of AT. Eighty percent of elderly
persons were also able to reduce dependence on others, half were able to
reduce dependence on paid persons, and half were able to avoid entering
a nursing home. Of the 42 respondents who reported having paid jobs, 92
percent reported that the assistive technology enabled them to work
faster or better, and 67 percent reported that the equipment enabled
them to obtain employment. Assistive technology also enabled 38 percent
to pursue additional schooling.

##### [Single-state surveys]{.smallcaps}

Like the small national studies, state surveys varied in terms of areas
of evaluation or needs assessment and survey methods.

Riemer-Reiss and Wacker (2000) examined assistive technology use and
factors associated with discontinued use among 115 assistive technology
recipients in Colorado. The study participants received 136 assistive
devices from Colorado *Tech Act* agencies. The most readily obtained
devices included computers (21 percent), communication devices (16
percent) and adapted software (7 percent). The survey found that 67.6
percent of the participants were still using the AT devices received
from the provider and 32.4 percent discontinued use of their devices. Of
those who no longer used the devices, 46.7 percent used the devices for
one to three years; but 6.4 percent never used the devices at all. A
significant inverse relationship was found between consumer involvement
and discontinuance of assistive technology.

The Ability Program in North Carolina demonstrated multiple methods for
improving access to assistive technology and documenting assistive
technology use. Data from the program provided information about the
scope of this privately funded statewide effort to improve access to
assistive technology and measure outcomes of assistive technology use.
Direct services were provided to 1,300 consumers; 40 percent had
multiple disabilities, half were age 65 or older, 21 percent were age
45--64, and 64 percent were female. Of the 502 individuals who responded
to an evaluation, 86 percent reported that the assistance and
information provided improved their access to, ability to use, or
understanding of assistive technology (Trachtman, Jones, Sauer, & Yoder,
1998).

The Kentucky Assistive Technology Network (2000) implemented a consumer
and professional satisfaction survey in 2000 that included information
on AT use in Kentucky. The majority of the 225 respondents had two or
more disabilities (66 percent). Mobility devices were the most widely
used (65 percent), followed by devices for reading or writing (62
percent), communication devices (53 percent), and personal care devices
(52 percent). Approximately half of the respondents received some type
of technology service and the most commonly reported problem with
technology services involved funding.

The Nebraska Assistive Technology Project (1992) interviewed 244 clients
and found that as many as 11 percent of individuals living in Nebraska
had a disability that required the use of assistive technology. Most of
those requiring assistive technology had mobility impairments (42.5
percent). Fifteen percent of those requiring assistive technology had
less than an 8th-grade education, and 30 percent were unable to work.
The most frequently reported needs for AT included home modifications,
vehicle modifications, computers and mobility devices. An examination of
the respondents' disposable income showed a very limited amount of
income available to purchase assistive technology devices or services.

As a part of the Oregon Statewide Assistive Technology Needs Assessment,
a total of 818 people responded to a questionnaire. Most of the
respondents had some kind of physical disability; 42 percent were
between the ages of 36 and 50 years old. Second to vocational services,
assistive technology represented an unmet need among 20 percent of the
respondents. Specific areas of need included funding, information,
opportunities to try devices and training (Brodsky, Wilson, & Fink,
1991).

Using national data and information from focus groups, Hanson and Lester
(2000) reported that, of the 6.6 million Californians with a disability,
about 1.7 million used some kind of assistive device. Mobility devices
were the most frequently used. It was also reported that individuals
with cognitive impairments have less access to assistive technology and
may need more support to use it. Focus group participants reported lack
of knowledge of available assistive technology services and resources.

#### Summary

National surveys provided information on the general variables of
assistive technology use among a large geographically and
demographically representative sample, providing the greatest insight
into the overall percentages and changes in AT use. In addition to
utilization rates, national data sets provided information to estimate
and predict trends in assistive technology use, such as an increase in
use with age and over time. Though few national surveys provided a
comprehensive picture of assistive technology use across the lifespan,
many provided information on assistive technology use among older
adults.

The multi-state or small national surveys provided some important
insights into patterns of AT use, but in many cases they were grounded
in small convenience samples that contained descriptive data about the
types of assistive technology used in addition to some demographic
characteristics that were lacking in the national surveys. These
state-level surveys also provided some important insight into types of
AT used, specific benefits, issues of AT abandonment, and funding as a
significant barrier to use.

### Assistive Technology Use Among Specific Populations

While national and state surveys often sampled individuals with various
disabilities, many local surveys focused on the role of assistive
technology among specific groups. A large number of the studies involve
older adults. Additional studies included individuals with physical
disabilities, individuals with developmental disabilities, and
individuals with hearing and visual impairments.

#### Assistive Technology Use Among Older Adults 

Our review of national disability surveys provided a picture of
assistive technology use among older adults, but there were several
local and regional research projects that supplement the findings of
these larger surveys. Research on the elderly represents a large pool of
data on assistive technology use. The longitudinal data obtained from
the Rehabilitation Engineering Research Center (RERC) on Aging, for
instance, have been used in numerous articles documenting specific
issues related to assistive technology use in the population of older
adults. Smaller individual studies have also documented assistive
technology use patterns in this growing population. These studies are
discussed in this section.

Mann and colleagues at the RERC on Aging have been conducting a 10-year
longitudinal study, the Consumer Assessment Study (CAS), to determine
the need for assistive devices and home modifications among older adults
with disabilities. At the time of this review, over 500 interviews had
been completed with home-based elderly over the age of 60 recently or
currently receiving services from 19 human service agencies and five
rehabilitation hospitals in the western New York area, and considered at
risk for needing assistive devices or home modifications (Mann &
Tomita*,* 1998). The study measured multiple dimensions of health,
disability, psychosocial issues, use of assistive technology and home
modifications.

To determine the representativeness of the findings, Mann, Hurren,
Tomita, and Charvat (1997) compared the CAS to the 1986 NHIS and 1987
NMES. The CAS sample was found to be older, more female than male, and
with more functional limitations than the NHIS and NMES. The authors
concluded that the data set only represents older persons with
disabilities from a single geographic region. In another article, Mann
and Tomita (1998) presented overall results of assistive technology use
among this sample of 508 respondents. They explored issues of ownership,
use and satisfaction with devices, as well as the problems consumers
were having with the devices they used. Results showed that older adults
owned an average of 13 devices and reported using 91 percent of the
devices they owned. Although the overall satisfaction rate of 89 percent
was very high, satisfaction varied among specific device types. Hearing
aids, magnifiers, canes and wheelchairs were reported to be the most
problematic devices when assessed relative to the number of users. Some
of the reported problems included: the device did not help with the
intended task; it was not affordable; it is dangerous in some
situations; it created unwanted attention; it causes discomfort; it is
difficult to maintain; it is difficult to use; it requires additional
assistance; or it was not installed properly (Mann & Tomita, 1998).

Several articles based on the CAS sample compared AT use among the
participants according to variables such as race, type of impairment and
disability. Tomita, Mann, Fraas, and Burns (1997) found that black
elders owned a total of 11 devices and white elders owned an average of
14 devices. White elders owned more than twice as many devices for
vision and hearing as black elders, and white elders reported more home
modifications. Although the findings revealed differences in AT use,
living status and number of illnesses were more important predictor
variables.

Mann, Hurren, and Tomita (1993) compared AT use between seven groups:
minimally impaired; physically impaired; vision impaired; vision and
physically impaired; cognitively impaired; cognitively and physically
impaired; and cognitively and vision impaired. Across groups, subjects
owned an average of 13.7 devices. Those with cognitive impairments owned
the fewest number of devices (5.7), and those with vision and physical
impairments owned an average of 20.1 devices. Device use ranged from 89
percent among the cognitively and vision impaired group to 70 percent
among the other, mostly physically impaired group. Those with vision and
physical impairments reported the highest number of problems with
devices and one of the lowest satisfaction rates (67 percent).
Physically impaired respondents reported the greatest number of devices
needed. The authors noted the complexities that exist with the use of AT
among older adults with multiple impairments.

Mann, Karuza, Hurren, and Tomita (1993) identified and categorized 86
subjects according to major impairment, visual, cognitive, hearing and
physical disabilities. Older persons with visual impairments used the
most assistive devices with an average of 12.4 devices per persons.
Those with cognitive impairments used 5.8 devices per person.
Respondents reported needing a total of 145 devices, or 1.7 devices per
person that they did not currently own. Visually and physically impaired
older adults reported dissatisfaction with one out of every five devices
and those with cognitive impairments reported problems with one out of
every three devices they own.

In addition to the work of Mann and colleagues, we found a number of
studies that drew information from relatively small convenience samples,
highlighting the role of professionals in the selection of devices and
professional implications of nonuse. Cutrona, Russell, McCombs, and
Losch (1991) surveyed 680 elderly persons from two counties in Iowa. The
sample consisted primarily of white women between the ages of 60 and 95
years of age. At least one assistive device was reported by 8.1 percent
of respondents, and 44.7 percent of those reported at least one
functional limitation. The study found that those with arthritis were
more likely to use an assistive device and reported difficulty using a
telephone. Most devices were paid out-of-pocket. Lack of knowledge and
reliance on others were the most frequent reasons for not using an
assistive device that helped with a functional limitation.

Gitlin, Schemm, Landsberg, and Burgh (1996) used samples of older adults
discharged from hospitals or rehabilitation units to describe assistive
technology use, nonuse and perceptions of AT. While studying 86 older
adults with a diverse range of diagnoses including stroke, orthopedic
injury, and amputation they found that each person used an average of
eight devices. Of the devices provided, 50 percent were used frequently,
3 percent were used occasionally, and 47 percent were seldom or never
used. A follow-up of this sample revealed that the devices used in the
first month after discharge were also used in later months. A smaller
sample of 13 patients discharged from a rehabilitation hospital showed
similar results. At one month after discharge, 45 percent of the devices
were not being used (Gitlin, Levine, & Geiger, 1993). Initial
perceptions of AT use after an acute illness were explored in a sample
of 103 stroke survivors. The respondents reported highest satisfaction
with dressing devices and lowest satisfaction ratings with seating
devices (Gitlin, Luborsky, & Schemm, 1998).

A small community-based study by Klinger and Spaulding (2001) explored
the use of assistive technology among a sample of 30 older adults with
chronic pain. They found that 97 percent of respondents owned a total of
133 AT devices, but only 63 percent ever used those adaptive devices.
The most common devices used were mobility devices, followed by bathroom
devices. Many respondents reported finding and obtaining their devices
without any professional help.

#### Individuals With Primarily Physical Disabilities

The studies documenting assistive technology use among individuals with
primarily physical disabilities focused on changes in function and the
types of assistive technology used as a result of these changes. Several
studies reported AT use among individuals with specific physical
disabilities such as cerebral palsy and spinal cord injury. This section
also included research on individuals discharged from hospitals because
many of the respondents had a physical disability associated with an
acute illness or injury.

Campbell, Sheets, and Strong (1999) surveyed 301 people with polio,
stroke and arthritis. In this study of secondary conditions, one of the
variables was change in the use of assistive technology over time. Those
with polio reported significantly more changes of mobility devices; as
many as 47 percent of the study participants needed a new orthotic
device, wheelchair or scooter. Stroke survivors reported the lowest
levels of assistive technology use; only 10 percent used a mobility
device. The study also reported home modifications as the greatest unmet
need across all impairment groups. Another study of functional changes
focused on 150 persons aging with spinal cord injury. The use of
assistive technology was evaluated at three points in time, showing that
the use of self-care devices increased over time, the use of hospital
beds and pill organizers decreased over time, and the use of mobility
devices remained constant (Thompson, 1999).

Fridie, Ferguson-Pell, and Davis (1998) sampled 246 people with multiple
sclerosis. The mean age of the sample was 48.7 years, and the majority
of respondents were female (71 percent.) A surprisingly large portion
(48 percent) had not heard about AT before completing the survey. Of
those who used AT, 54 percent used a wheeled mobility device, 35 percent
used a low-tech mobility device, 20 percent made building modifications,
and 18 percent used vehicle modifications. A small number of respondents
used augmentative communication and environmental controls (5 percent)
and computer access devices (4 percent.) The most helpful devices were
powered mobility devices such as scooters or power wheelchairs.

A study of 110 adults with cerebral palsy by Murphy (1999) examined the
overall health of the individuals, including the use of mobility
devices. Sixty-seven percent were using a wheelchair at the time of the
research, and much of the equipment showed signs of wear and improper
fit. Of those using devices for ambulation, 90 percent of the canes and
crutches were in disrepair or did not fit the individual. Hammel,
Heller, and Ying (1998) explored the long-term use of assistive
technology among 35 individuals with cerebral palsy. Of the average of
eight devices per subject obtained originally, 77 percent used the
devices when surveyed. Communication devices were used most commonly (33
percent), followed by transportation AT (29 percent) and self-care
devices (22 percent). Over half of the assistive devices were funded by
state public aid (Hammel, Heller, & Ying, 1998). Garber and Gregorio
(1990), in a study of upper extremity assistive device use by 56
randomly selected individuals with quadriplegia from local areas in
Texas, found that a total of 250 devices were prescribed. Twenty-five
percent were feeding devices, 45 percent were splints and slings, 7
percent were dressing devices, 11 percent were communication devices,
and 6 percent were grooming devices. Only between 29--39 percent of
devices were still being used after the end of year two of the study.
Most of the change in use was due to regained or increased function and
alternative solutions.

Studies of individuals with physical disabilities discharged from a
hospital or rehabilitation facility, such as the one by Geiger (1990),
examined the use of prescribed assistive technology among 40 subjects
with orthopedic impairments. Of the 140 self-care and dressing devices
issued by an occupational therapist, 77 (54 percent) were never or
rarely used. Cushman and Scherer (1996) examined the use of assistive
devices recommended to maximize the independence of 47 persons
discharged from an acute inpatient rehabilitation unit. There, the most
common diagnoses were spinal cord injury and stroke, and the most
commonly used devices were wheelchairs and commode chairs (over 60
percent). Of the 128 devices recommended, an average of 2.7 devices per
person, 33 percent were not being used three months later. Adapted
grooming aids had the highest overall rate of nonuse followed by quad
canes. Fifty-nine percent of the respondents reported that the devices
were "no longer needed." Other reasons for nonuse included difficulty
obtaining equipment or receiving correct equipment. The abandonment of
grooming and locomotion aids was tied to functional improvement in
self-care and locomotion (Cushman and Scherer, 1996). Neville-Jan and
her colleagues (1993) studied a sample of 50 patients discharged from a
local hospital. They reported that of the equipment provided at
discharge, 15 percent was never used. Twenty-one percent of the
equipment was only used for a period of time. Of the equipment not
utilized, tub and toilet equipment were the most prevalent. Reasons for
nonuse included poor fit; did not know how to use; not installed; not
needed; only needed for a short time; did not feel safe; or did not like
using special equipment (Neville-Jan, Piersol, Kielhofner, & Davis,
1993).

In a study similar to the previously discussed hospital discharge
studies, Bynum and Rogers (1988) interviewed 30 of recipients of home
health care services. The participants had received 54 devices with an
average of 1.8 devices per person. Bedside commodes and shower chairs,
mobility aids were the most commonly used devices, but approximately
half reported needing help to use the equipment. Participants used 82
percent of the devices prescribed, but only 69 percent were used on a
regular basis.

#### Assistive Technology Use Among Adults With Developmental Disabilities

A limited number of surveys focused on AT use among adults with
intellectual and developmental disabilities. Some of the studies focused
on individuals living in nursing homes or residential facilities. In
both cases, caregivers provided many of the survey responses.

Wehmeyer (1998) studied 1,218 family members of adults with mental
retardation from 47 states and the District of Columbia. He found that
mobility devices were used most frequently (at a rate of 12.7 percent),
followed by hearing and vision devices (8.9 percent), communication
devices (4.9 percent), home adaptations (9.7 percent), and environmental
controls (5.5 percent). The need for AT ranged from 9.3 percent for
communication devices and 8.4 percent for home modification, to 2.5
percent of the respondents who needed mobility devices. Cost and
information were the most reported barriers to AT next to assessment and
training needs. Funding for most devices came from personal sources,
with government being the second most common funding source. In general,
AT was underutilized, with less than 10 percent of adults using an AT
device except in the area of mobility. Barriers of cost and lack of
information about devices contributed to this underuse as families were
not aware of the potential benefits of AT.

Parrette and Vanbiervliet (1992) surveyed 680 persons with mental
retardation in a region of Arkansas. A large percentage of respondents
reported other disabilities, such as speech impairments, physical
disabilities or visual impairments. Seventy-three percent used mobility
devices to get around and 21 percent used computers. Medicare and
Medicaid were the primary sources of funds for assistive technology, and
30 percent of participants reported personal or family purchases of
assistive technology. Respondents reported unmet needs in the areas of
hearing aids, reading, writing, typing, building accessibility,
communication and artificial limbs.

Hewitt, Larson, and Lakin (2000) reported that 33.3 percent of persons
with mental retardation in Minnesota used assistive technology.
Approximately 21 percent reported using an environmental adaptation or
home modification. Of those who used an assistive device, 68.9 percent
used mobility devices, 37.7 percent used augmentative and alternate
communication, and 14.8 percent used prostheses. Of those with
environmental modifications, 67.3 percent had bathroom modifications,
51.7 percent had a ramp and 4.9 percent had a vehicle lift.

Mendelson, Heller, and Factor (1995) reported results from a
longitudinal study of 268 nursing home residents with developmental
disabilities in Illinois. During the study, 67 subjects moved into the
community (movers) and 201 remained in the nursing home (non-movers.)
The non-movers had a greater prevalence of multiple functional
limitations. Seventy percent of the non-movers used some type of
assistive device compared to 55 percent of those who moved out of the
nursing home. Among both groups the need for additional AT was
significant. Only 85 percent of people with mobility impairment used AT
to help with mobility and only 6 percent of people with ADL limitation
and 4 percent of people with communication limitations used AT to
improve those areas. In Massachusetts, Tello (1993) found that 1,738
devices were purchased for 177 consumers living in various residential
settings. The majority of devices purchased (71.2 percent) were used to
enable the consumer to get ready for work each day. Of the remaining
devices, 18.6 percent were purchased for safety, 5.6 percent of the
devices improved health and functioning, and 4.7 percent helped with
money management.

#### Assistive Technology Use Among Individuals With Hearing and Visual Impairments

A small number of surveys focused on the assistive technology needs and
uses among individuals with hearing and visual impairments.

Wendt-Harris, Pollack, and Lassere (2001) surveyed 261 members of the
Self-Help for the Hard of Hearing organization. Most of the respondents
(78 percent) had severe or profound hearing loss. Ninety-seven percent
reported bilateral hearing loss. Almost all of the respondents used some
kind of hearing devices such as a hearing aid, a cochlear implant or a
vibrotactile aid. Three-fourths used a hearing aid. Background noise was
the most common problem associated with the hearing devices. The most
common alerting devices used included FM, amplified phone, infrared
system, and alerting clock or phone.

The Lighthouse National Survey of Vision Loss (Stuen, 1997) of 1,219
respondents, with oversampling of adults over age 75, showed that among
those aged 45 and over who reported a vision problem, only 30 percent
were using devices to enhance vision. The percentage of those who used
optical devices increased with age and severity of visual impairment.
Thirty-two percent of those with severe visual impairment used a device
compared with 28 percent of those with a moderate visual impairment.
Only a small number of those with a visual impairment were using an
adaptive device such as large print (21 percent), talking books (4
percent), and other voice output devices (5 percent).

Uslan (1992) discussed the barriers to acquiring assistive technology by
individuals with visual impairments. Respondents from a sample of 30
low-income individuals with visual impairments revealed that 47 percent
owned no assistive technology. More than 50 percent reported a lack of
information about assistive technology and 33 percent could not afford
assistive technology. Only 10 percent of this sample were employed and
most were living below the poverty line. In a second survey of 39
individuals, respondents reported owning a median of 10 assistive
devices. Twenty-six percent reported needing to upgrade their equipment.
Though affordability was still a significant issue in this sample of
employed individuals, they seemed more willing to take out a loan to
purchase the equipment.

#### Summary

This section showed that older adults represent a population of frequent
AT users. Mann and colleagues found that assistive technology use rates
in this group varied according to impairment, race, cognitive status,
income and age. Other studies of older adults showed varying numbers of
devices and high rates of nonuse. A significant amount of assistive
technology use and unmet need among those with physical disabilities
related to areas of mobility and home modification. The studies of
individuals with developmental disabilities showed limited assistive
technology use in this population. The few studies of individuals with
visual and hearing impairments showed minimal AT use by those with
visual impairments.

### Assistive Technology Use by Type of Device

The *Tech Act of 1988* and the subsequent funding of rehabilitation
engineering research centers increased the rate of development of many
new technologies and created a greater recognition of existing assistive
devices. Rehabilitation engineering research centers are funded by the
National Institute on Disability and Rehabilitation Research, of the
U.S. Department of Education, to develop and disseminate innovative
methods of applying advanced technology, scientific achievement, and
psychological and social knowledge, with the goal of solving
rehabilitation problems and removing environmental barriers. The
authority for rehabilitation research engineering centers is contained
in section 204(b)(3) of the *Rehabilitation Act of 1973*, as amended (29
U.S.C. 762(b)(3)).

Numerous articles on the use of devices have been written to evaluate
their effectiveness and explain their capacity to increase independence.
Because many of these articles were not designed to document AT use,
only those articles that document widespread use of a type or group of
devices within a survey were included in this review. The devices most
frequently studied are computers, augmentative and alternate
communication, prostheses and mobility devices.

#### Computers, Internet and Accessible Information Technology

Computers and the Internet represent forms of assistive technology with
a unique potential to increase the independence of people with
disabilities (Kaye, 2000a, 2000b). According to the 2000 National
Organization on Disability/Harris Survey on Community Participation
(2001), these technology and information tools were reported as
increasingly important as a means for people with disabilities to gather
information and feel more connected. Computer skills were found to be
essential for employment, according to the National Council on
Disability (1998) report on barriers to using multimedia technology.

The significant gaps in computer use among people with and without
disabilities were described in a report from the National
Telecommunications and Information Administration (2000) using data from
the 1999 Survey on Income and Program Participation. The results showed
that only 20.9 percent of those with a disability regularly used a
personal computer and 59 percent had never used a computer. Thirty-one
percent of those with a learning disability reported using a computer on
a regular basis, but this percentage was significantly less for those
with a walking problem or difficulty using their hands. Fewer people
with disabilities used computers at home and work compared to the
general population. The gaps between the computer use of people with and
without disabilities are also influenced by income, age, employment
status and gender.

Kaye (2000a, 2000b) analyzed 1998 data from the Current Population
Survey and found that 23.9 percent of people with disabilities had
access to a computer at home and 9.9 percent of people with disabilities
were connected to the Internet. Using the same data, the Research and
Training Center on Rural Rehabilitation Services (Rural Institute on
Disability, 2000) found that people with disabilities in rural areas
were less likely to own computers and use the Internet. While 28.7
percent of those with a disability living in a suburban area owned a
computer and 11.6 percent used the Internet, only 19.8 percent of those
living in a rural area owned a computer and 6.8 percent used the
Internet. This significant difference in access between rural and urban
living situations can be linked to lower educational attainment and to
household income of those living in rural areas.

The National Council on Disability (1998) studied the barriers to
computerized multimedia technology for people with visual and hearing
disabilities and found significant gaps in access. The report noted that
there were few accessible features for those with visual and hearing
impairments in the area of multimedia technology.

#### Alternative and Augmentative Communication Devices

Alternative and augmentative communication (AAC) devices were used
primarily by individuals with severe disabilities involving cognitive or
speech impairments. This group of users represented a small number of
individuals with disabilities. Use rates from the NHIS-Assistive Device
Supplement reported that as many as 34,000 people with disabilities used
a speech device in 1991, but these estimates have low statistical
reliability.

Jinks and Sinteff (1994) surveyed 76 AAC device users and found 23
different devices used by individuals with cerebral palsy, traumatic
brain injury, neurological conditions and other disabilities. Low
technology devices accounted for 36 percent of the devices used, while
high technology devices totaled 64 percent. Third party payers funded 81
percent of the AAC devices. All respondents with cerebral palsy reported
using their devices often or sometimes, while 30 percent of those with
TBI and 43 percent of those with neurological diagnoses reported rarely
or never using their devices. A separate and smaller study of 17 AAC
device users (Bryen, Slesaransky, & Baker, 1995) showed that the use of
AAC device had substantially helped them with several major life
activities such as working (64.7 percent), learning (58.8 percent) and
communication (82.4 percent). For more than 75 percent of respondents
their AAC device helped them communicate with unfamiliar people, writing
and giving presentations.

#### Use of Prostheses by Individuals With Limb Loss

Studies on the use of prostheses covered many types of upper and lower
limb prostheses and the problems participants had with their individual
prosthesis, including the role of the prosthesist. Atkins, Heard, and
Donovan (1996) studied 2,477 individuals with upper-limb loss who, when
asked to identify the type of prostheses used, identified body-powered
hooks in 63 percent of cases, and 37 percent used an electric hand. Of
the original sample, 1,575 responded to a long survey. In the long
survey, when asked to rate the cost of their prosthesis with respect to
its function, adults with body-powered prostheses reported them to be
"about right" (17.4 percent), compared to 5.6 percent of adults with
electric prostheses. Electric users reported their prostheses to be "too
expensive/unreasonable" more often than users of other prostheses.
Respondents identified areas for improvement for different types of
prostheses, and identified wrist movement, coordinated function and the
ability to hold small and large objects as very important.

A survey of 45 veterans with traumatic limb amputation reported 11 upper
limb and 51 lower limb amputations. Of the 43 respondents using a
prosthesis, 32 percent felt their prosthesis was half as good as their
original limb, while 22 percent reported the prosthesis was not very
good at all. Most had problems using the prosthesis. Ten veterans did
not use their prosthesis regularly because it was painful. All those who
used the prosthesis reported limitations in its usefulness, specifically
related to problems with fit and attachment. Another study of 109
amputees demonstrated more of the problems with the use of prosthetics.
Of the 67 percent of participants who wore the prosthesis all day, 57
percent reported moderate to severe pain while wearing the prosthesis.
The study emphasized the importance of the role of the prosthesist,
especially as a source of information (Nielsen, Psonak, & Kalter, 1989).
Nielsen (1991) surveyed an additional 21 amputees, finding similar
concerns about comfort and fit of the prosthesis. However, the
respondents of this survey appeared to be satisfied with the services
provided by the prosthesists.

#### Mobility Devices

Despite the presence and awareness of assistive devices for mobility
enhancement and the reported use by people with disabilities, we found
few local surveys that dealt specifically with the issues of mobility
devices. The most comprehensive information on utilization rates of
mobility devices was found in national surveys. Kaye (1997) reported 6.8
million people used mobility devices according to the 1994 National
Health Interview Survey. This included 1.7 million wheelchair users and
6.1 million users of canes, crutches or walkers.

Information on specific mobility devices was found in several studies,
including that of Dunn and his colleagues (1998). They surveyed 99
individuals with a spinal cord injury on the use of standing mobility
devices. Eighty-four percent of the respondents were currently using a
standing device, while 14 percent reported nonuse of the device. There
was no correlation between the use of the standing device and health
issues, but respondents reported numerous positive benefits derived from
using the standing device. A survey of 42 people with Amyotrophic
Lateral Sclerosis (ALS) who use wheelchairs reported that 57.1 percent
used an assistive device other than a wheelchair. Use of bathroom
equipment, including 69 percent using shower seats, 61.9 percent using
elevated toilet seats, and 57.1 percent using grab bars, was reported.
Those using motorized wheelchairs reported a higher level of
satisfaction with activity level, comfort and ease of maneuvering
(Trail, Nelson, Van, Appel, & Lai, 2001).

### Use of Assistive Technology in Specific Settings

Many national, state and local surveys addressed the different settings
in which AT was used when reporting data on assistive technology use,
but focused studies provided detailed information on AT use in specific
settings. AT use in the home, school, work and community represented the
major locations found in the literature. In addition to providing more
depth of understanding, these studies pointed out some limitations in AT
use and service provision.

#### Assistive Technology Use in the Home 

Home modifications documented in national and state-level surveys
(discussed in previous sections) were often considered types of
assistive technology. Studies focusing on home modifications typically
included older adults and showed how the use of these modifications
increased independence by accommodating functional limitations, as the
examples cited below will show.

A national survey of 2,000 individuals age 45 and over by the American
Association of Retired People (Bayer & Harper, 2000) found that 80
percent of respondents reported that at least one member of the
household had difficulty getting around the home. Because most of the
respondents want to remain in their homes, one-third were concerned
about being able to afford home modifications, being forced into a
nursing home because they cannot get around, or having problems with
features in their homes as they get older. Eighty-six percent of
respondents have made at least one simple change, and 70 percent have
made a more major change. Safety features were among the most common
modifications.

Mann, Hurren, Tomita, Bengali, and Steinfeld (1994) interviewed 127
older adults to identify environmental problems in their homes that
could potentially limit their functional abilities. A total of 500
environment-related problems were identified in the 127 homes and
included stairs, lighting, counter height, and problems with switches
and handles. Participants reported the kitchen and bathroom as the
greatest problem areas, with over 60 different problems reported in each
room. Many of the problems identified represented those that could be
fixed easily with a change in design or maintenance task (Mann et al.,
1994). In another study, the environment was used to manage problems
experienced by older adults and their caregivers. A total of 17
participants used an average of 3.5 environmental solutions prior to the
intervention by an occupational therapist who offered additional
solutions, including the use of assistive devices, which gave the
caregivers strategies for handling problems with bathing and
incontinence more effectively (Gitlin & Corconan, 1993). In a study of
49 individuals in North Carolina with home modifications, Connell,
Turner, and Gruber (1996) identified 122 total features. A family member
or provider identified 77 percent of modification needs. Family and
friends also paid for 67 percent of the modifications, but much of the
labor was donated.

While there has been some research on the use of home modification
devices and equipment by older adults with disabilities who were
homeowners, Gitlin, Miller, and Boyce (1999) looked at the equipment use
by older adults who rent their homes. The study found older adults who
rent their homes tend to be African-American, Hispanics and female, with
lower incomes. This study of 34 clients with chronic conditions had an
occupational therapy (OT) evaluation and received needed bathroom
equipment and modifications. Prior to the OT evaluation, 41 percent had
grab bars and 27 percent had a tub chair. Five additional devices were
prescribed and participants reported significant improvement in the
ability to bathe and transfer and in overall ADL performance. In the
same study, a telephone survey of 75 clients (including 20 who received
OT evaluation) who received services in the last three months, 86
percent reported equipment had made tasks easier. Since receiving the
equipment, 63 percent required less personal assistance. Problems with
equipment were reported by 65 percent of the clients, with the
installation, safety and appropriateness of equipment being the most
commonly reported (Gitlin, Miller, & Boyce, 1999).

To determine knowledge of assistive technology and home modification
resources among providers, Sheets, Emerman, and LaBuda (1997) surveyed
342 Area Agencies on Aging (AAA) and 42 State Units on Aging (SUA). The
study found that the AAAs were much less aware of state technology
assistance programs than the SUAs. The AAAs received more inquiries, but
less than 25 percent felt staff had the training needed to handle AT
requests, and they reported little to no ability to handle home
modification referrals and requests.

#### Assistive Technology Use in Postsecondary Education

With the enactment of the *Individuals with Disabilities Education Act
of 1990* and more focus on the inclusion of students with disabilities
in school settings, a number of studies examined the use of assistive
technology in classrooms in primary and secondary educational settings.
In comparison, there were few articles that documented assistive
technology use among those in post secondary education, despite the fact
that approximately 6 percent of all undergraduate students reported
having a disability (National Center for Education Statistics, 1999). An
even fewer number of surveys included the students as respondents. The
majority of surveys reporting any assistive technology use among
postsecondary students with disabilities were conducted with educational
institutions and service providers and not with students with
disabilities.

Rumrill, Kock, Murphy, and Jannarone (1999) asked 14 recent college
graduates about the extent to which the technology resources utilized in
college had prepared them for employment. Of the 14 graduates, 43
percent used specialized equipment and accessible buildings, and 36
percent had accessible housing. A total of 6 out of the 14 respondents
reported needing accommodations that were not provided. Although
respondents reported using university accommodations, 79 percent
indicated that they did not receive any information about technology or
accommodations in the workplace and 57 percent reported no help with job
placement.

According to the National Center for Education Statistics, the majority
of post secondary institutions and providers of services to students
with disabilities reported high rates of environmental accommodations,
but technology and adaptive equipment was often provided at a lower rate
than other accommodations (National Center for Education Statistics,
1999). Seventy two percent of all institutions enrolled students with
disabilities, but only 58 percent reported providing technology and
adaptive equipment. The provision of AT services was highest among
public two- and four-year institutions with 10,000 or more students. A
study by the National Center for the Study of Postsecondary Educational
Supports (2000) of 650 disability coordinators revealed that AT supports
for students were not readily available. The report showed that 35
percent of the study participants never provided equipment or software
and 71 percent never provided captioning services to students with
disabilities in need of them. In addition, 52 percent of schools did not
have accessible library services; and more than 60 percent did not have
other alternate means of accessing courses, course materials or
registration services.

Houghins (2001) interviewed 27 AT experts to determine the top 10
barriers and facilitators to a successful transition. The top three
barriers were: 1) a lack of early transition planning; 2) insufficient
AT training in high school; and 3) a lack of collaboration between
secondary and postsecondary institutions. Likewise, the top three
facilitators were: 1) adoption of AT early in school; 2) having AT
follow the individual; and 3) systematic AT evaluation and assessment.
The top three barriers reported when moving from postsecondary education
to adult life were very similar to the barriers reported in the research
of AT barriers among adults. The barriers included lack of funding, lack
of awareness and lack of community infrastructure to respond to needs.

#### Assistive Technology and Environmental Accommodations in the Workplace

Assistive technology use in the workplace was found to be a major issue
for individuals with disabilities. The 1994 NHIS reported that 11.6
percent of working-age adults were restricted in their ability to work,
and more than half of this group were unable to work because of an
activity limitation (Kaye, 1997).

According to the 1994 National Organization on Disability/Harris Survey
of Americans With Disabilities, 26 percent reported needing equipment or
technology to perform a job. Of the 10 percent that reported needing a
computer, screen enlarger, special keyboard or input device, speech
synthesizer, or voice recognition software to perform a job, only 1.3
percent owned such equipment (Kaye, 1997). Additionally, 18 percent of
those working and 11 percent of those not working reported needing a
computer to work effectively, and, among those not working, 10 percent
needed a wheelchair.

Assistive technology used in the workplace can take many different forms
based on the functional needs of the individual. A group of 96 people
with post-polio or spinal cord injury was interviewed to determine
problems with workplace accommodations (Inge, Wehman, Strobel, Powell, &
Todd, 1998). The two problems mentioned most frequently were "using
equipment/tools/furniture" and "access," with 30.8 percent among persons
with post-polio and 24.3 percent among persons with spinal cord injury
reporting problems with access. Approximately 21 percent of persons with
post-polio and 40 percent of persons with spinal cord injury reported
problems with equipment and furniture, especially desks. Of the problems
reported, 71.5 percent of the problems experienced by those with
post-polio and 85.7 percent of those with spinal cord injury were
accommodated, but only 55.7 percent of persons with post-polio found the
accommodations to be satisfactory. Of the accommodations provided for
those with spinal cord injury, 45.1 percent involved equipment and 10.8
percent involved architectural modifications. Twenty-nine percent of the
accommodations for those with post-polio involved equipment, and 14
percent involved architectural modifications. Eighty percent of the
accommodations cost less than \$500.

Granger, Baron, and Robinson (1997) interviewed 194 job coaches and job
developers to determine the types of job accommodations needed by their
clients with psychiatric disabilities. Use of a job coach and flexible
scheduling were among the most widely used accommodations. Physical
space accommodations were used "sometimes."

The Rehabilitation Research and Training Center on Aging With a Spinal
Cord Injury (Kemp, 1999) surveyed 46 individuals with spinal cord
injuries. The most commonly reported problems related to worksite
accommodations were difficulty using equipment (34 percent) and access
(23.8 percent). Eighty-five percent of problems were accommodated, but
accommodations were not always satisfactory. The most common
accommodations were equipment or furniture (40 percent) followed by
assistance from others (28 percent).

In many other areas of AT use, funding is often the greatest barrier to
obtaining assistive technology. Yet, in the case of workplace
accommodation, the Job Accommodation Network (JAN) reported that the
recommended accommodations are often very low or no cost. In 52 percent
of the cases, JAN's recommended accommodations cost employers less than
\$500 (Kaye, 1997). An evaluation of 392 calls to the Job Accommodation
Network was used to demonstrate the pattern of needs for people who are
deaf or hard-of-hearing. The study found 38 percent of accommodations
recommended were some type of product or equipment. Over 50 percent of
the product options discussed were related to communication (Dowler &
Hirsh, 1994).

#### Assistive Technology Use in the Community 

In many studies, assistive technology and accessible design of the
environment were interdependent. If an individual could not realize the
increased independence offered by a particular assistive device because
of a barrier in the environment such as facility access or
transportation, then the device was of little benefit. Environmental
barriers were often measured by self-report of an individual's
perception of such barriers. Facility access, communication barriers and
transportation represented the more common community access issues.

Kaye (1997) reported that one-third of wheelchair users encountered
accessibility problems outside the home. Twenty-four percent of people
responding to the 1994 National Organization on Disability/Harris Poll
reported that a lack of access to public buildings was a problem. The
1998 National Organization on Disability/Harris Poll reported 31 percent
of respondents felt that access to public facilities was a problem.
Despite the lack of access, 35 percent reported that the *Americans with
Disabilities Act* made their lives better. Little improvement was seen
in the perspective of individuals with disabilities related to
accessibility. A survey by the General Accounting Office in 1993
documented the continued lack of access for individuals with
disabilities in the community. Barriers such as tight spaces in store
aisles and bathrooms, lack of accessible telephones, and lack of
accessible signage created problems for individuals with disabilities.
As many as 82 percent of buildings lacked signs and signals accessible
to those with visual and hearing impairments (Kaye, 1997).

Doden, Redelsperger, and Long (1997), in a study of 90 business and
government offices and 60 hotels, assessed TTY accessibility and
presence of accessibility features for individuals who are deaf or
hard-of-hearing. The study indicated that 59 percent of business or
government offices called using TTY resulted in no communication; this
included 47 percent of calls to emergency services. The accessibility of
hotels was greater among those that were more expensive (77 percent)
when compared to the accommodation rate of budget hotels (36 percent).
Accessibility was determined by the presence of TTYs, closed-captioning,
phone lights, and smoke alarms.

Transportation was also among the most often cited barriers to community
participation by individuals with disabilities. Kaye, Kang, and LaPlante
(2000) reported that 82 percent of wheelchair users had difficulties
with public transportation systems because of difficulty using or
getting to the transit options. Other problems included too few
accessible transit vehicles and lack of schedules and signs in
alternative formats, according to the 1993 survey by the General
Accounting Office (Kaye, 1997). A study by Linden, Kamper, Reger, and
Adams (1996) examined the transportation needs of 100 individuals with
disabilities. Half of the respondents did not drive, and 56 percent used
public transit. Of those who did drive, 47 percent drove cars and 32
percent drove modified vans (Linden et al., 1996). Springle, Morris,
Nowacek, and Karg (1994) interviewed 128 consumers and 123 equipment
vendors in a study of adaptive transportation technology. Of the 98
percent of consumers who drove before their injury, only 45 percent
drove at the time of the interview. Personal funds were used by 92
percent of consumers to purchase vans. Ninety-five percent of consumers
used a lift to enter the vehicle, but almost half reported problems with
the lift in the past year. Seventy percent of passengers and drivers who
remained seated in their wheelchair used a tie-down, but only 50 percent
used occupant restraint (Springle et al., 1994).

#### Summary

Assistive technology use can take a variety of forms and purposes
depending on context and setting. Assistive technology used in the home
was associated with increased independence and found to compensate for
functional limitations, but funding is a significant barrier to AT use.
When compared with needs, assistive technology was not used in
postsecondary education or in the workplace to its full potential. This
was especially true of AT use in the workplace. Assistive technology in
the community was strongly related to access.

### Conclusion

This literature review discusses the many trends and issues surrounding
assistive technology use. Individuals with disabilities reported many
barriers, and AT use varied according to the type of disability, the
types of AT devices, or the settings where AT was needed. In addition to
the vast number of topics and issues addressed in AT research,
limitations and missing information highlighted the need to continue and
expand efforts to document AT use and need among individuals with
disabilities.

Some of the major limitations of the studies examined here involved
sample size, research design and definitions. Most of the research
consisted of smaller convenience samples, with a large number of
articles on older adults. In many cases, utilization rates and other
information on AT use had to be extrapolated from studies with a wide
variety of research designs and methods and many different research
questions. Even large national studies used various definitions and
methods to measure assistive technology. The differences in the way AT
was defined limited the comparisons that could determine the potential
impact of increased services and the heightened level of awareness
brought about by the *Tech Act* and similar legislation, the aging of
the population, or emerging technologies on the use of AT by people with
disabilities.

Many areas of assistive technology research had a limited number of
published studies with adequate samples and research designs. Areas of
weakness included: data on AT use in individual states; AT use among
specific disability groups, such as those with vision or hearing
impairments; and data on the use of specific types of AT. Additional
areas that lacked adequate research coverage were AT use in recreational
settings and survey research involving universal design. Although a
small number of articles and materials addressed these subjects, they
were not included in this review because they lacked a rigorous research
design, an adequate sample, or sufficient empirical evidence.

## 3. Survey Design 

### Background

In the last decade, there have been a few reports of AT use and need
based on the National Health Interview Survey, such as a study by
LaPlante, Hendershot, and Moss (1997) that measured *use and need*, and
a more recent study by Russell, Hendershot, LeClere, Howie, and Adler
(1997) that also reported on *use.* Carlson, Ehrlich, Berland, and
Bailey (2001) revisited the Disability Followback Survey administered
between 1994 and 1997 (National Center for Health Statistics, 1999a,
1999b) and found that based on a weighted sample of 41.8 million
Americans with disabilities aged 18 years and older:

-   8.3 million Americans with disabilities needed special equipment or
    aids to perform basic activities of daily living (ADLs) such as
    bathing or showering, dressing, eating, getting in and out of bed or
    chairs, walking, getting outside and using the toilet, including
    getting to the toilet.

-   15.4 million Americans with disabilities reported using assistive
    devices or technologies (primarily medical), such as tracheotomy
    tubes, ostomy bags, catheterization equipment, glucose monitors,
    diabetic equipment and supplies, inhalers, nebulizers, hearing aids,
    crutches, canes, walkers, wheelchairs, scooters and feeding tubes.

-   16.6 million Americans with disabilities used special equipment,
    aids or assistive technology (either one or more of the above).

-   7.4 million Americans with disabilities had surgical implants such
    as shunts to drain away fluid, artificial joints, implanted lenses,
    pins, screws, nails, wires, rods or plates, artificial heart valves,
    pacemakers, silicone implants, infusion pumps, implanted catheters,
    organ implants and cochlear implants.

-   14 million Americans with disabilities lived in homes modified to
    meet their special needs. Among these, over 1.5 million persons
    reported needing further home modifications to already existing
    ones. An additional 1 million persons with disabilities who did not
    have any home modifications indicated that they needed such
    accommodations.

-   511,000 Americans with disabilities reported using modified cars or
    vans, and 369,000 persons with disabilities reported needing
    modifications to their cars or vans. Of these, 60,000 persons needed
    modifications in addition to the ones they already had, and the
    remaining 309,000 persons used vehicles that had no modifications
    but needed them.

-   15.1 million Americans with disabilities worked at the time of the
    interview. In this group, 4.2 million persons reported being limited
    in the kind or amount of work they could do.

-   714,000 Americans with disabilities reported having an accessible
    work environment that included: hand rails or ramps; accessible
    parking or an accessible transportation stop close to the building;
    elevators (including elevators designed for persons with special
    needs); specially adapted work stations; restrooms designed for
    persons with special needs; automatic doors; voice synthesizers;
    TDDs; infrared systems or other technical devices; Braille; enlarged
    print; special lighting or audiotape devices; and special pens or
    pencils, chairs or other office supplies.

-   1.3 million Americans with disabilities working at the time of the
    interview reported needing one or more of the abovementioned
    workplace designs and accessories.

-   402,000 Americans with disabilities were provided with special
    accommodations that included: readers; oral and sign language
    interpreters; job coaches; personal assistants; job redesign or
    slowing the pace of tasks; reduced work hours and more breaks;
    part-time work and other types of equipment; help; and work
    arrangements not named above.

-   531,000 Americans with disabilities, working at the time of the
    interview, indicated a need for one or more of the previously
    mentioned special accommodations.

However, due to the narrow scope of questions and the dated information
provided by the survey data, these figures may substantially
underestimate the full scope of AT use and need in the United States.

As the review of the literature presented in 2 revealed, smaller surveys
and studies on AT use that have been conducted were of less general
interest. Either they measured certain selected aspects of the use of AT
by persons with disabilities, such as wheelchair use, or they focused on
select populations with varying types of impairments.

Given the limitations of existing surveys, a national survey of persons
with disabilities using or needing AT was necessary to give a detailed,
comprehensive picture of how persons with disabilities function in their
daily lives, with particular attention to how they may benefit from
assistive technology.

### Survey Purpose

The Rehabilitation Engineering and Assistive Technology Society of North
America (RESNA) operates the Technical Assistance Project, an activity
funded by the National Institute on Disability and Rehabilitation
Research (NIDRR) under the *Assistive Technology Act of 1998*. In August
2000, RESNA contracted with the Survey Research Center at the University
of Michigan Institute for Social Research (ISR) to conduct the
comprehensive survey.

The survey was designed to add a dimension to the existing framework of
information about the lives of persons with disabilities. Previously,
surveys of persons with disabilities put primary emphasis on identifying
the conditions that cause impairment and disability. In these surveys,
disability was measured by self-reported functional impairments (e.g.
visual impairment, blindness, hearing loss, deafness or other conditions
that limit a person's ability to perform daily tasks and activities).
The key to this definition is the phrase "ability to perform." Two
important aspects of a person's ability to perform that are often
overlooked are: 1) the presence of environmental barriers and
constraints that can *reduce* ability to perform; and 2) the existence
of assistive devices and technologies that can *enhance* it. Indeed,
inhospitable environments and helpful technologies influence the
abilities of all persons, regardless of any limiting health conditions.

The added dimension provided by the survey was the inclusion of
questions that allowed quantifying the impact on the lives of persons
with disabilities of AT devices and services and environmental barriers
and constraints. The areas investigated in the survey included:

-   How persons with disabilities learned about, selected and paid for
    the AT devices and services that they used;

-   How well the AT they were presently using met their needs;

-   The ease or difficulty they had in learning about and acquiring
    their assistive technology;

-   Their thoughts about what AT they would use *in addition to any they
    were presently using*;

-   The agencies they had contacted and used, or tried to use, to learn
    about and acquire AT in the past, and those they would contact or
    use in the future;

-   Whether they were aware of the possibility of getting help;

-   Why they had not sought help, if they were aware of the possibility
    and did not avail themselves to it;

-   The limits of their ability to use telephones and computers in their
    daily lives;

-   Their occupational status---employed, retired, homemaker, able to
    work but unemployed, in school, or not able to work; and

-   Their opinions as to the extent that AT had improved various aspects
    of their lives, and whether there had been improvement in their
    ability to function more independently as a result of developments
    over the past decade.

### Method

#### Sampling: The Dual-Frame Approach

The major impediment to conducting survey research among persons with
disabilities who use or need AT is their relative scarcity in the
general population. On the one hand, the most representative sample
frame for telephone research is the random-digit dial (RDD) frame. Since
this was designed to be a national survey, the use of an RDD frame comes
closest to allowing all respondents an equal chance at participation. On
the other hand, RDD telephone surveys are the most costly procedure
available, regardless of the target group. Since the numbers are
computer generated, a purchased list will, by necessity, contain a large
percentage of numbers that are not valid targets for a household survey.
These include the following categories:

-   Numbers Never Issued

-   Non-Residential Listings

-   Non-Working Numbers

-   Non-Telephone (e.g., computer modem, fax modem, etc.)

The costs involved will be a function of the calling algorithms used by
the researchers. In this survey, the number of attempts was not limited
to a fixed number; interviewers kept calling each number until a final
disposition could be established---a procedure which ensures the most
accurate assessment of response rate, but at considerable cost.

Sirken and Casady (1988) wrote, "When the available sampling frame is
complete but requires a costly data collection mode, efficiency
considerations suggest the joint use of the complete frame and an
incomplete frame." The dual-frame design is accomplished by combining
names, addresses and phone numbers obtained from targeted list samples
with phone numbers generated for RDD samples. Dual-frame designs are in
use in the Health and Retirement Survey (HRS) sponsored by the National
Institute on Aging (Heeringa and Connor, 1995 \[mail survey, area
probability and Medicare enrollees\]), The 8th Annual Hispanic
Federation Survey (Hispanic Federation, 1999 \[telephone survey, listed
and RDD\]), and the annual National Health Interview Survey (Benson and
Marano, 1998 \[face-to-face, area probability and list\]), and many
others, to increase cost efficiency.

To obtain the targeted list sample, we purchased a list of telephone
numbers and addresses from Survey Sampling, Inc. from their SSI-LITe^TM^
(SSI's Low Incidence Targeted Sampling) data sets based on self-reported
household information gathered via mail questionnaires, warranty cards
and online surveys. The largest LITe file consists of over 48 million
names, making it one of the most extensive survey-based files in the
country. The following is a description of how SSI developed the LITe
file:

In order to sift out rare populations in quantity, literally millions of
survey forms are distributed each year. To enhance recruitment,
respondents are offered an incentive, most typically an entry into a
contest or a small gift. Questionnaires take advantage of a variety of
mass-distribution media in order to reach all the sectors of the
national population and uncover very small subgroups. The emphasis is on
large quantities (over 50 million are distributed each wave), the use of
multiple distribution vehicles (product inserts, coupon mailers,
magazine inserts, free standing inserts, etc.), and quantity response
such as to make sampling by category practicable. Surveys are national
in coverage.

The objective was to collect a sufficient number of respondents
(1,000--1,500) to make statistically reliable statements about the
various areas addressed in the survey. The following factors were
considered in estimating the cost: the estimated prevalence of persons
with disabilities in the population; the desired response rate; the
estimated percentage of working numbers in a list; and the screening
response rate. Table 3.1 shows the estimate of the number of completed
interviews per 1,000 RDD numbers (MOR in the table refers to
middle-of-the-road estimates):

[]{#__RefHeading___Toc114975686 .anchor}Table 3.1 Completed RDD
Interviews per 1,000 Telephone Numbers (Est.)

+---------------------------+-------------+-------------+-------------+
|                           | ###         | **MOR**     | **Best      |
|                           |  Worst case |             | case**      |
+---------------------------+-------------+-------------+-------------+
| Prevalence                | 7%          | 12%         | 20%         |
+---------------------------+-------------+-------------+-------------+
| Response rate             | 70%         | 70%         | 70%         |
+---------------------------+-------------+-------------+-------------+
| Residential number        | 60%         | 70%         | 80%         |
+---------------------------+-------------+-------------+-------------+
| Screening response rate   | 65%         | 75%         | 85%         |
+---------------------------+-------------+-------------+-------------+
| Completed Interviews per  | 19.11       | 44.1        | 95.2        |
| 1,000                     |             |             |             |
+---------------------------+-------------+-------------+-------------+

The final estimate was for an RDD list to be between 2 percent and 10
percent effective.

[]{#__RefHeading___Toc114975687 .anchor}Table 3.2 Completed List
Interviews per 1,000 Telephone Numbers (Est.)

+----------------------------+-------------+-------------+-------------+
|                            | ###         | **MOR**     | **Best      |
|                            |  Worst case |             | case**      |
+----------------------------+-------------+-------------+-------------+
| Prevalence                 | 40%         | 60%         | 80%         |
+----------------------------+-------------+-------------+-------------+
| Response rate              | 70%         | 70%         | 70%         |
+----------------------------+-------------+-------------+-------------+
| Residential number         | 85%         | 90%         | 95%         |
+----------------------------+-------------+-------------+-------------+
| Screening response rate    | 65%         | 75%         | 85%         |
+----------------------------+-------------+-------------+-------------+
| Completed Interviews per   | 154.7       | 283.5       | 452.2       |
| 1,000                      |             |             |             |
+----------------------------+-------------+-------------+-------------+

A similar assessment for the list sample (table 3.2) determined that we
could expect between 15 percent and 45 percent overall effectiveness. In
comparing the two possibilities, we found that the worst-case scenario
for the list sample was 62.5 percent more efficient than the best-case
scenario for RDD data collection, while, at the other extreme, the
best-case scenario for the list sample estimate was 24 times as
efficient as the worst-case scenario for RDD.

Based on these assessments, we developed a dual-frame model and
determined that 400 RDD responses would provide enough data to establish
prevalence. An additional 1,000 list-based responses could be collected
without exceeding the resources available. The total of 1,400 would
provide enough data to make accurate analyses of relational hypotheses,
and the RDD sample would be used, if necessary, to weigh the responses
in the list sample.

#### Questionnaire 

After a series of meetings and written exchanges between staff members
of NIDRR, RESNA and researchers from the Survey Research Center \[SRC\]
of the University of Michigan's Institute for Social Research, the
initial version of the instrument was completed in November 2000.

#### Screening

The screener was constructed to ensure that survey respondents would
meet strict criteria for inclusion and therefore represent the universe
of persons with mostly moderate to severe disabilities.

After a residence[^3] had been contacted,[^4] interviewers took a roster
of all household members and selected one eligible respondent. If more
than one household member was eligible, one was selected at random.
Eligibility was established if a member of the household met any one of
the following criteria:

-   Used a wheelchair, special bed, special telephone, cane, crutches,
    walker, or the assistance of another person or any other assistive
    device, to perform daily tasks and activities in the home, at
    school, at work or in the community;

-   Had a condition which prevents or greatly limited working at a job,
    walking/lifting/carrying, dressing/bathing/getting around inside the
    home, going outside, learning/remembering/concentrating; or

-   Was blind, deaf or had a serious impairment of vision or hearing.

#### Pretest

A pretest was conducted on a list sample of 50 respondents. The pretest
instrument was a paper-and-pencil instrument administered by experienced
research technicians at SRC in December 2000. The pretest established
that the instrument was user-friendly (as was evidenced by a high
cooperation rate among eligible respondents), without employing
extensive refusal conversion techniques. There were no break-offs or
interviews which were incomplete because respondents had refused to
finish. However, we made two changes in the questionnaire based on the
results of the pretest.

First, interviewers noted that persons with disabilities objected to the
use of the word "need" in the questionnaire. As a result, the word need
was removed. Need was assessed by asking respondents to report the
extent to which a device would be useful.

The second change was the inclusion of open-ended responses so
respondents could list the devices they used and the conditions which
limit their abilities, rather than present closed-ended checklists, as
had been done during the pretest.

#### Final Questionnaire

The complete questionnaire is contained in the Appendix. The
questionnaire was organized into 11 sections.

Section A consisted of two questions. First, the respondent was asked to
indicate whether she is employed, able to work but unemployed, unable to
work because of her disability, retired, in school, or a homemaker. Up
to three responses per respondent were allowed \[e.g., in school,
homemaker, unable to work\]. Second, the respondent was asked, "What
condition of limitation do you have that impairs your functioning?" as
an open-ended item.

The next four sections (B, C, D and E) asked the same questions about
the use, need for, and general issues concerning learning about,
obtaining, satisfaction with, and paying for assistive devices. The
respondent was asked Section B only if she indicated she was a student,
and Section C if she was gainfully employed away from the home. All
respondents were asked Section D, about AT in the home, and all those
who had ventured out of the home in the two weeks prior to the interview
were asked about AT in the community (Section E).

The respondent's experience with AT use, need, selection and acquisition
was assessed with the following probing questions:

**Current Use**

-   What kind of AT/IT devices do you use?

-   How did you learn about this device?

-   Where did you get the device?

-   How was the device paid for?

-   Were you satisfied with the device?

-   Did you receive help from an agency during the selection and
    purchase of the device?

**Current Need**

-   What kind of AT/IT device do you need?

-   How will you learn more about this device?

-   What, if any, agency or organization do you plan to contact for
    help?

-   If you do not plan to seek help from an agency, what are your
    reasons?

If the respondent was using an assistive device in any context, the
protocol in figure 3.1 was implemented.

[]{#__RefHeading___Toc114975402 .anchor}Figure 3.1 Assistive Technology
Use: Probing Pattern

The questions in this section were asked wherever appropriate. Thus, if
a respondent was in school and gainfully employed, she was asked the
entire battery concerning use going to school, at school, going to work,
and at work. The same was true of the following protocols: other
assistive technology (AT), information technology (IT), and access.

If the respondent did not currently use an assistive device in some
context, the protocol in figure 3.2 was implemented.

[]{#__RefHeading___Toc114975403 .anchor}Figure 3.2 Assistive Technology
Need: Probing Pattern

The next four sections assessed telephone and computer (IT) use.
Sections F, G and H concerned telephone use at school, work and in the
community, while Section J covered computer use at school, work and
home.[^5]

After the assistive devices questions, the protocol covering IT
(telephone and computer) use was implemented, as shown in figure 3.3.

[]{#__RefHeading___Toc114975404 .anchor}Figure 3.3 Telephone and
Computer Use: Probing Pattern

Sections K, L, M and N covered access to buildings and facilities and
equipment at school, work, at home and in the community.

The community activity and access protocol is outlined in figure 3.4.
Respondents were first asked "About how many days in the last two weeks
did you participate in social activities outside the home?" Those who
responded "none" were not asked community activity questions.

[]{#__RefHeading___Toc114975405 .anchor}Figure 3.4 Access to the
Environment: Probing Pattern

Section P consisted of a set of questions probing the respondents'
overall views of the availability of and information about AT, the
benefits of AT, and how their existence had changed over the past
decade. The purpose of these questions was to learn about how
respondents viewed disability and assistive device use in a broader
social and political context. The questions were also posed to give
respondents an opportunity to comment on specific experiences and
evaluate changes over time. The personal views and opinions questions
were:

1.  Overall, how much information and advice have you received about
    assistive technology---would you say a lot, some, a little, or none?

```{=html}
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```
2.  Overall, how much information and advice have you received about how
    to obtain it---would you say a lot, some, a little, or none?

3.  Overall, how much difference would you say that the information and
    advice about assistive technology and how to obtain it has made in
    increasing your level of learning, independence, productivity and
    community integration?

4.  Overall, how much has information and advice about assistive
    technology and how to obtain it helped you to become more aware of
    your rights?

5.  How much has your use of assistive technology devices and services
    decreased your need for help from another person?

6.  To what extent have better-designed products and environmental
    access features or universal design products reduced your need for
    assistive technology devices and services?

7.  Compared to 10 years ago, people are more aware of the need for
    assistive technology devices and services for persons with
    disabilities. Would you say that you strongly agree, agree,
    disagree, or strongly disagree?

8.  Compared to 10 years ago, laws or program policies have been changed
    to help persons with disabilities to get assistive technology. Would
    you say that you strongly agree, agree, disagree, or strongly
    disagree?

9.  Compared to 10 years ago, more people are aware of assistive
    technology and understand how it can benefit persons with
    disabilities. Would you say that you strongly agree, agree,
    disagree, or strongly disagree?

10. Compared to 10 years ago, it is easier to find assistance for
    purchasing assistive technology devices and services. Would you say
    that you strongly agree, agree, disagree, or strongly disagree?

The questionnaire concluded with the following demographic questions:

-   Age range. This served as an internal check, since the exact age of
    the respondent was established in the household screener

-   Sex \[Not asked: interviewer determined.\]

-   Are you of Spanish or Latino origin?

-   Which of the following racial or ethic groups best describes you?

-   Highest grade of school or year of college completed

-   Household income category

-   Personal income category

#### Interviewer Training 

The University of Michigan Institute for Social Research had the
technology and expertise to conduct the interviews, but had limited
experience interviewing persons with disabilities. Interviewers received
16 hours of instruction, including practice calls and a training manual
containing information about NIDRR, RESNA, persons with disabilities,
and assistive technology. The screener and the core questionnaire were
thoroughly explained, and a full section on how to use the CATI program
"Blaise" was included in the manual (Survey Services Laboratory, 2001).

#### Survey Administration

The survey was conducted using computer-assisted telephone interview
(CATI) software that administered all skips and directions automatically
and with programmed internal consistency checks. All closed-ended
responses and verbatim typescripts of responses to open-ended questions
were automatically recorded in an electronic data file. The data were
downloaded into SPSS and Microsoft Excel applications.

The study and the questionnaire were approved by the University of
Michigan Institutional Review Board. All respondents were told that
their participation in the survey was strictly voluntary and
confidential. If respondents were not comfortable answering a particular
question, they were allowed to skip that question and complete the
survey (typically, education and income questions are most likely to be
skipped). All respondent identification was housed separately from the
main data set; respondents were assigned a project ID number, and
analysts and other study personnel, including the principal
investigators, never saw the names or addresses of the respondents.

#### Respondent Incentive

Respondents were offered an incentive of \$20 as a token of appreciation
for completing the questionnaire. Completion was defined as reaching the
final set of questions on demographic characteristics. When a respondent
had completed the interview, the interviewer requested the respondent's
name and mailing address where the check could be sent.

#### Coding

A total of 119 different respondent conditions were coded according to
the categories published in NIDRR Disability Statistics Report 7, table
A-1, NHIS Impairment and ICD-9 Codes (LaPlante and Carlson, 1996). Up to
three conditions per respondent were coded and judged to be the most
severe. All open-end coding was 100 percent verified. If more than three
were mentioned, the least serious were excluded. All cases in which the
respondent mentioned an injury were also coded as to the type of
limitation or condition that resulted.

The definition of disability adhered to the definitions of disability
upon which the 2000 Census and the National Health Interview Survey
based their estimates. These definitions include self-reported or
proxy-reported physical, cognitive, and emotional impairments and
limitations, activity limitations, and assistive device use. In
addition, any person who used or needed help from another person because
of her impairments and limitations was also included in our definition
of disability.

AT services help persons with disabilities select, acquire or use
adaptive devices. Such services also include functional evaluations,
training on or demonstration of devices, and purchasing or leasing
devices.

Information technology refers to electronic products, devices or
equipment that are used to produce, exchange, send or receive
information (or otherwise facilitate communication), such as computers,
telephones, teletypewriters (TTYs), augmentative communication devices,
or fax machines.

For purposes of this study, each respondent was asked what sort of AT
she used in each of four domains (where appropriate): 1) at or getting
to school; 2) at or getting to work; 3) at home; and 4) in the
community. Coding was based on the document entitled AT/IT Device and
Service Categories (see Appendix). As with the respondent conditions, we
coded up to three AT devices per respondent.

#### Call Volume, Negative Codes and Response Rates

Previously we described how we arrived at the dual-frame sample, largely
as a response to an anticipated large-cost differential. The prediction
turned out to be true, as the data will illustrate. While a precise
accounting is not possible, we estimated that each RDD interview was
between 15 and 20 times the cost of each list interview. The overall
call statistics for the survey are shown in table 3.3.

[]{#__RefHeading___Toc114975688 .anchor}Table 3.3 Call Statistics

+------------------------------------------+-------------+-------------+
|                                          | ### List    | **RDD**     |
+------------------------------------------+-------------+-------------+
| Total dials                              | 17,247      | 52,235      |
+------------------------------------------+-------------+-------------+
| Mean \[calls per completed interview\]   | 17.2        | 126.8       |
+------------------------------------------+-------------+-------------+
| Median                                   | 20          | 24          |
+------------------------------------------+-------------+-------------+
| Mode                                     | 2           | 2           |
+------------------------------------------+-------------+-------------+

These statistics show the efficiency of obtaining data from the list was
roughly seven times greater than the efficiency of obtaining interviews
via RDD.

One reason for the discrepancy was the quality of the samples. Figure
3.5 shows how many more nonsample numbers were in the RDD list.
Nonworking numbers, nonresidential and other nonsamples, including all
problem numbers and other non-households, accounted for 35 percent of
the RDD numbers as compared to 10 percent of the numbers from the list.
That is, the amount of time spent in identifying non-usable numbers was
roughly 3.5 times as great compared to working with a random-digit dial
list.

[]{#__RefHeading___Toc114975406
.anchor}![](media/image1.wmf){width="4.0in"
height="2.8777777777777778in"}Figure 3.5 Disposition of Sample Telephone
Numbers

The results from the calls in the RDD sample were as follows:

-   3,305 households reached

-   2,556 screened

-   421 eligible respondents identified as a result of screening

-   412 interviewed

-   Five final refusals

In comparison, the results from the calls in the targeted list sample
were as follows:

-   2,322 households reached

-   1,932 screened

-   1,014 eligible respondents identified as a result of screening

-   1,002 interviewed

-   Five final refusals

The negative codes shown in figure 3.6 demonstrate that the list sample
was far more economical than the RDD method. We required a sample of
2,750 to complete the list calls (1,002) versus a sample of 5,103 to
complete the RDD calls (412).

[]{#__RefHeading___Toc114975407
.anchor}![](media/image2.wmf){width="4.0in"
height="1.9465277777777779in"}Figure 3.6 Negative Codes

#### Response Rates

The American Association of Public Opinion Research (AAPOR) standard
definitions for outcome rates for surveys specifies four different
calculations. RR1 is the minimal response rate, defined as the number of
completed interviews divided by the total of interviews and
non-interviews; RR3 is the rate which estimates the proportion of
eligibles among the non-interviews (the estimate is based on the
screening rate); COOP is the cooperation rate, or the percent of
eligible respondents who were interviewed; and the Overall Response rate
is RR3 multiplied by COOP.

[]{#__RefHeading___Toc114975689 .anchor}Table 3.4 Response Rates

+---------------------------+-------------+-------------+-------------+
|                           | ### RDD     | **List**    | *           |
|                           |             |             | *Combined** |
+---------------------------+-------------+-------------+-------------+
| RR1                       | 77%         | 83%         | 80%         |
+---------------------------+-------------+-------------+-------------+
| RR3                       | 95%         | 91%         | 92%         |
+---------------------------+-------------+-------------+-------------+
| COOP                      | 98%         | 99%         | 99%         |
+---------------------------+-------------+-------------+-------------+
| Overall                   | 93%         | 90%         | 91%         |
+---------------------------+-------------+-------------+-------------+

Although there are no universally accepted criteria for the goodness of
response rates, as there are for statistical significance, RDD surveys
surpassing 70 percent are relatively rare, and 60 percent is considered
by many to be an adequate response rate. The response rate obtained in
this study was the result of exhaustive and effective calling
strategies.

#### Interviewer Notes and Observations

An informal e-mail survey of interviewers established a baseline of
information on the specific characteristics of surveying the population
of persons with disabilities. The following were the interviewers'
impressions:

-   Interviewers found that persons with disabilities were no different
    to deal with than the general population. If there was a difference,
    persons with disabilities were more compliant, more willing to
    contribute their opinions, and were quite open and forthcoming in
    discussing their conditions.

-   The most difficult task was achieving household listings.

-   The repetitive questioning over all the domains---school, work, home
    and community---was the only aspect of the protocol that drew
    objection from the respondents. The interviewers heard "I've already
    answered that question" from a number of respondents.

-   There were no apparent differences between the respondents from the
    two sample frames.

#### Section Summary

This section provided a detailed background of the methods and
techniques applied to this survey of AT use and need among persons with
disabilities. Financial constraints and the characteristics of the
target population led us to a dual-frame approach that included a
certain degree of representativeness provided by the RDD part and the
robustness provided by the targeted list component of the sample. By
including persons with more severe disabilities through the list
component, we were able to focus more clearly on a wider variety of
aspects about assistive technology use and need as stated in the purpose
of the study. However, the relatively small sample (n=1,412) raised
questions about the extent to which the findings from this survey can be
used to generalize about persons with disabilities using or needing AT.
Therefore, a closer examination of the validity and representativeness
of this study is presented in the next section.

### Data Validity, Consistency and Limitations

Respondents were carefully screened with regard to any chronic illness,
functional limitation, impairment or disability that would make them
likely users of AT and recipients of personal care services. Our RDD
sample of 412 cases (with a 93 percent response rate) was selected from
2,556 household interviews before given an in-depth interview, and
represented the population of persons with disabilities in the United
States at that point in time at a rate of 18.6 percent. This estimate
was slightly lower than the 2000 Census estimate of about 20 percent of
adults, and the 21.5 percent prevalence estimate obtained from the
1994--95 National Health Interview Survey.

The survey findings indicated that the sample contained a greater
percentage of persons with moderate or severe disabilities, compared to
the abovementioned surveys. Similarly, the targeted list sample included
a relatively large number of wheelchair users and persons whose reported
health condition also indicated more severe levels of disability. All of
these persons were screened with the same instrument to ensure a certain
degree on homogeneity. A series of split-half sample reliability tests
was performed to test for differences in response patterns between the
two samples. No statistically significant differences were detected, and
the robustness of the sample was ensured.

By choosing the same disability assessment questions as the Census (U.S.
Census Bureau, 2001; Adler, Clark, DeMaio, Miller, & Saluter,1999); and
the NHIS-D (National Center for Health Statistics, 1999a, 1999b), we
were able to compare our findings with those from the other two major
disability surveys and determine the validity of our findings. With
these quality controls in mind, we are confident that the findings
presented in this paper are valid and accurately represent the
experiences of persons with disabilities who use or need AT, and how
they went about obtaining and paying for it.

While conducting detailed analyses, we found that a number of items had
very low frequency counts. Such events commonly occur in health and
disability surveys. Low frequency items or responses are generally
marked as "not reliable," and rules as to the size of the relative
standard error indicate the magnitude below which an estimate is deemed
"not reliable." We caution the reader not to interpret ratio estimates
based on low-frequency counts as reliable. Whenever possible and
meaningful, we grouped similar items into larger categories and based
our interpretations on these larger estimates.

#### Sampling Bias

This section presents an overview of the sample analyzed with a focus on
gender, race and level of education.

##### [Gender]{.smallcaps}

In the total sample, the sex of the respondent was determined by the
interviewer by observation at the conclusion of the interview; 826 (58.4
percent) of the respondents were women, 588 (41.6 percent) were men. The
difference was highly significant; the likelihood of such an occurrence,
given equal likelihood of including both men and women in the sample, is
less than one in one million \[chi-square value with one degree of
freedom = 40.059\].

-   The difference between men and women in percent of AT use was
    negligible.

-   Women were more likely than men to be unemployed because of their
    disability---50 percent versus 43 percent \[t = -2.67, p\<.01\].

-   Men were more likely than women to be gainfully employed or running
    a business---23 percent versus 19 percent \[t = 2.18, p\<.025\].

-   Women were eight times as likely to be classified as homemakers than
    men---8 percent versus 1 percent, \[t = -7.21, p\~0\].

-   Men were almost twice as likely as women to be retired---23 percent
    versus 12 percent \[t = 5.35, p\~0\].

-   Men and women answered each of the public opinion questions in
    virtually the same manner.

-   There was no difference in average age between men and women.

-   There were no differences in education levels across gender.

-   The family income reported by women was significantly higher than
    that reported by male respondents. Fifty-four percent of women and
    43 percent of men reported higher than median family incomes \[χ^2^
    = 10.88, *df=*1, p\~0\].

-   The finding for personal income was reversed from what it was with
    family income. Fifty-four percent of men and 34 percent of female
    respondents reported higher-than-median personal incomes \[χ^2^ =
    46.5, *df=*1, p\~0\].

-   There was no difference in the size of states holding male and
    female respondents.

##### [Race]{.smallcaps} 

Each respondent was asked to provide a primary racial identification,
i.e. to name the racial or ethnic group that "best describes you." The
first group mentioned was coded into one of six categories: American
Indian or Alaska Native; Asian; black or African-American; Native
Hawaiian or other Pacific Islander; White or caucasian, or Anything
Else.[^6] Primary racial identification was established, with
respondents who identified themselves as White/Caucasian totaling 1,204
and nonwhites totaling 203.

-   The percent of white and nonwhite respondents who reported using AT
    was virtually identical.

-   The level of education achieved by black respondents was
    significantly lower than that achieved by white respondents (t=
    -2.03, p\<.025[^7]). Split along the median level of education, 50
    percent of whites and 42 percent of blacks were above the median
    level of education.

-   Half of the white respondents and 35 percent of black respondents
    reported family income above the median level. The difference was
    statistically significant (t= -2.74, p \<.005). When we examined
    family income for whites versus nonwhites along the entire
    dimension, the distinction became quite clear: the greatest
    discrepancy was found among the lowest two income categories, where
    17 percent of the nonwhites and 7 percent of whites were located.
    Above \$70,000/year, we found a nearly equal distribution of wealth
    across races (nonwhites at 14.5 percent, versus 14.3 percent for
    whites).

-   The difference in personal income between blacks and whites was not
    quite as significant (t= -1.7, p\<.05). Thirty-six percent of black
    respondents and 46 percent of white respondents, reported having
    personal incomes higher than the median.

-   White respondents averaged just over four years older than nonwhite
    respondents; the difference was statistically significant \[t=
    -2.93, p\<.005\].

-   There were consistently more nonwhites in the younger age categories
    and consistently more whites in the older age categories.

-   The proportion of women among the black respondents was 71 percent,
    which was significantly higher than the 57.5 percent among white
    respondents, or the female proportion of all nonwhites (63.8
    percent). \[t= 2.82, p\<.005\].

-   Although there was a slight tendency for black respondents to come
    from states with a higher population, the trend was not
    statistically significant.

-   The relative frequency of blacks and whites who were currently
    gainfully employed or running a business was virtually identical.

-   More than twice as many whites were retired compared to blacks (17
    percent versus 7 percent) \[t= -3.83, p\<.001\].

-   There were 10 public opinion questions. There were no significant
    differences in the responses of black or white respondents to these
    questions.

##### [Education]{.smallcaps} 

Each respondent was asked about the highest level of education achieved.
Responses were classified as follows: 1- Kindergarten; 2- Elementary
School; 3- High School Graduate; 4- Some College; 5- College Graduate;
and 6- Postgraduate Study. The median level was high-school graduate.
Fifty percent of the respondents had at least some college experience.
Levels of education were associated with the following characteristics:

-   AT use among the respondents with higher levels of education was
    significantly above that among the less educated respondents \[t=
    2.93, p\<.01\].

-   Fifty-five percent of the less educated respondents were unemployed
    as a result of their disability, as compared to 40 percent of those
    with more education \[t = -5.79, p\~0\].

-   Twenty-eight percent of the highly educated respondents were
    working, as compared to 13 percent of the less educated \[t = 6.98,
    p\~0\].

-   The level of education achieved by black respondents was
    significantly lower than that achieved by white respondents (t=
    -2.03, p\<.025[^8]). Split along the median level of education, 50
    percent of whites and 42 percent of blacks were above the median
    level of education.

-   Both family and personal income were related to education. Income
    levels were significantly higher for respondents with higher levels
    of education \[t values for both were greater than 9.57, p\~0\].

-   Respondents with more education were slightly younger \[average 55
    versus 58 years\] of age. The difference was statistically
    significant.

-   Equal proportions of high- and low-education respondents came from
    high and low populated states.

-   No differences in education levels by gender were detected.

-   Respondents with higher education levels reported positive
    experiences with technical assistance agencies to a significantly
    greater extent than those with lower education levels.

#### State-By-State Analysis

The survey drew respondents from all 50 states and the District of
Columbia. There was an overall correlation of +.85 \[coefficient of
determination = 72 percent\], which means that the more populous states
contributed larger numbers of respondents than did the less populous
states. However, the smaller states generally had greater numbers of
respondents than might have been expected from their populations, while
the larger states were generally underrepresented.

About one-third of the respondents were located through random-digit
dialing and the rest were selected at random from a list supplied from
the sampling organization. The respondent by state and state population
correlation coefficient increased from +.84 in the total population to
+.92 in the RDD sample, and the correlation between representativeness
and population was reduced from -.34 to -.11. Since the coefficient of
determination for the respondent-by-population relationship accounted
for 85 percent of the covariance, and the
representativeness-by-population relationship accounted for only 1
percent of the covariance, we can assert that there was no under- or
over-representativeness of persons with disability in the data on a
state-by-state basis. The slight, non-significant correlation was
largely a function of the very small numbers of respondents in the
states with low populations.

Having established that there is no evidence for a bias in selection of
persons with disabilities, we may look at the ways, if any, in which the
respondents within the various states differ from one another. An
exhaustive comparison of the responses given by persons living in the
states with larger-than-average population versus those living in the
smaller states revealed no significant differences in behavioral,
opinion or demographic responses with the exception of income. The
respondents from the larger states were significantly higher in both
personal and family incomes. Both differences were significant, but the
differences in personal income were more significant than in family
income (Ehrlich, 2003).

### Summary and Conclusions

The survey employed a dual-frame design to collect at least 400 cases
via random-digit dial from all 50 states to provide normative data on
prevalence, etiology and demographics, and at least 1,000 cases via a
targeted list to provide greater detail with a lower expenditure of
resources. We determined a priori that we would perform statistical
analyses comparing the results from the two subsamples and combine them
only if the results were statistically comparable.

We found that the RDD sample appeared to have a slightly lower level of
disability than the list sample. Evidence for the difference is in the
proportions in each sample who are working or in school versus not
working because of a disability, and in rates of use of AT devices and
services. In terms of demographics, the RDD sample was more racially
diverse and reported a slightly higher personal income than the list
sample. However, the differences in severity of disability and
demographic characteristics were not echoed by differences between the
two samples in the patterns of use of assistive technology---the devices
used, and the way in which the respondents learned about, paid for,
obtained and were satisfied by the devices. Nor were there any
meaningful, qualitative differences in respondents' opinions as a
function of whether they came from the RDD or the list sample.

We conclude that the use of the dual-frame design allowed us to collect
enough data via RDD to make statements about prevalence that are
generally in line with previous studies, and the combined data from the
RDD and list provided a robust sample from which to draw reliable
conclusions about the persons with disabilities population and their use
of assistive devices.

# Part II: Descriptive and Bivariate Analyses

## 4. Respondent Characteristics and Patterns of Assistive Technology Use

The purpose of this is to provide a detailed account of the findings
from survey participants---persons with disabilities who used or needed
AT. We will present these details in the form of a comparison between
respondents who were selected with the random digit dial (RDD) method
and persons who were selected from a targeted list. The previous
explained why we used this dual-frame design. The analyses in this will
show the extent to which the respondents from the two samples were
similar or different in terms of their personal characteristics and in
terms of their respective patterns of AT use. The purpose of these
analyses also is to show that there was no significant response bias due
to sample selection.

The evidence presented in this is contained in cross tabulations and bar
charts, and discussed in a short narrative. Whenever we detected
differences between list respondents and RDD respondents, we tested the
finding for statistical significance and reported the relevant
statistics.

### Respondent Characteristics

#### Gender

The interviewers established the sex of the respondents without
specifically asking. There were no respondents who were not easily
identifiable as male or female. As table 4.1 shows, the samples were
well matched on this variable.

[]{#__RefHeading___Toc114975690 .anchor}Table 4.1 Gender, by Type of
Sample

  -------------- -------------- -------------- -------------- --------------
                 RDD                           **List**       

                 *Number*       *Percent*      *Number*       *Percent*

  Male           167            41             421            42

  Female         245            59             581            58
  -------------- -------------- -------------- -------------- --------------

#### Age

We established age by asking the respondent to choose a category in
which her age fell. The mean ages in the two samples, calculated by
using the midpoints, were 57.9 for the RDD sample and 57.1 for the list
sample. Using the actual ages as listed in the household rosters, the
averages were 57.4 for the RDD respondents and 57.0 for the list sample,
indicating good reliability of the use of the age categories. Although
the means were virtually identical, the distributional correspondence of
age across the two samples was less than what one would expect by chance
(Chi square = 30.4, df = 7, p \< 0.0001).

[]{#__RefHeading___Toc114975408
.anchor}![](media/image3.wmf){width="4.0in"
height="2.8243055555555556in"}Figure 4.1 Age Category of Respondents, by
Sample

As figure 4.1 shows, the RDD distribution was flatter than the list
sample, with a greater proportion of responses in the extremes, and a
greater standard deviation. The list sample was less representative of
the population as a whole, since it was a self-selected group of people
who included themselves as respondents to a mail survey from Survey
Sampling, Inc. While equal diligence was exerted in reaching respondents
from both samples, as evidenced by the response and cooperation rates
noted in the discussion of call statistics, 68 percent of the list
sample was contained in the 46--75 age range, compared with 56 percent
of the RDD sample.

#### Race and Ethnicity

We followed the protocol of first asking whether the respondent was of
Spanish or Latino origin, and determined that 16 RDD respondents (3.9
percent) and 15 list respondents (1.5 percent) answered in the
affirmative. We then asked for the respondent's race. Table 4.2
demonstrates the greater racial diversity of the RDD sample. The
apparent diversity is statistically significant (Chi square = 41.5, df =
6, p \< 0.0001). This is another indication that the RDD sample was more
representative of the population as a whole.

[]{#__RefHeading___Toc114975691 .anchor}Table 4.2 Race and Ethnicity, by
Type of Sample

  -------------- -------------- -------------- -------------- --------------
                 **RDD**                       **List**       

                 *Number*       *Percent*      *Number*       *Percent*

  Asian          2              1              3              0

  Black          49             12             51             5

  Hawaiian/PI    1              0              1              0

  Hispanic       16             4              15             1

  Native Amer.   10             2              41             4

  White          320            78             884            88

  Other          20             5              20             2
  -------------- -------------- -------------- -------------- --------------

#### Education

We asked respondents to indicate, by category, the highest level of
education attained. Computing by midpoint, we found a slight difference
in mean years: 12.0 for the RDD sample, 12.4 for the list sample. This
difference was not significant, especially when the ranges were unequal
in size (i.e., the scale used was only ordinal, not interval, and the
use of means was inappropriate). The difference in distribution was not
statistically significant. The preponderance of cases in both samples
laid in the 9--15 year range: 76 percent in the RDD sample and 79
percent in the list sample. The modal level of education was 9--12 years
(high school graduate).

[]{#__RefHeading___Toc114975693 .anchor}Table 4.3 Level of Education, by
Type of Sample

  --------------------- ------------ ------------ ------------ ------------
                        **RDD**                   **List**     

                        *Number*     *Percent*    *Number*     *Percent*

  None, Kindergarten    3            1            7            1

  1--8 (Elementary)     29           7            41           4

  9--12 (High school)   203          50           426          43

  1--3 Years of college 106          26           362          36

  College graduate      31           8            102          10

  Postgraduate          38           9            61           6
  --------------------- ------------ ------------ ------------ ------------

#### Income

We asked respondents to indicate their household and personal income
levels for the year 2000. However, only 61 percent of the RDD sample and
65 percent of the list sample answered these questions. The remaining 35
percent chose not to respond. Since we do not know the reasons why
anyone refused to answer, we cannot correct the data for any consistent
bias, and the results cannot be given the same credence as the rest of
the study.

[]{#__RefHeading___Toc114975409
.anchor}![](media/image4.wmf){width="5.75in"
height="3.7090277777777776in"}Figure 4.2 Household Income, Year 2000

The mean household income, when calculated by midpoint, was \$45,700 for
RDD respondents, significantly higher than the mean household list
income of \$39,750. However, when the average category was computed, the
difference was nonsignificant. The distributions did vary in the same
way that age varied, (i.e. there are proportionally more cases in the
extremes in the RDD sample than in the list sample, as shown in figure
4.2), and the RDD sample median was one category higher than the list
sample median. Figure 4.3 shows the comparison of household to personal
incomes for all respondents.

[]{#__RefHeading___Toc114975410
.anchor}![](media/image5.wmf){width="6.5in"
height="3.4472222222222224in"}Figure 4.3 Personal Income and Household
Income for 2000

As might be expected, household income greatly exceeded the personal
income reported for these individuals. As shown in figure 4.4, the
personal median for both samples was in Category 3: \$10,000 to
\$14,999. The RDD group was significantly higher on average, computed on
categories; more importantly, however, the list sample was again more
clustered around the central tendency---the RDD sample more
variable---with greater representation in the extremes.

[]{#__RefHeading___Toc114975411
.anchor}![](media/image6.wmf){width="5.0in"
height="3.3930555555555557in"}Figure 4.4 Personal Income, Year 2000

#### Type of Impairment

The Census 2000 and National Health Interview Survey both asked about
visual and hearing impairments. We included this question in our survey
to ensure that the respondents' impairments were assessed in the same
way. With that purpose in mind, the screening question asked: "Does
anyone in your household who is over age 18 have any of the following
conditions:

-   Blindness;

-   Severe vision impairment;

-   A hearing impairment that is not as severe as deafness; or

-   Deafness?"

Figure 4.5 shows that the respondents in both samples reported virtually
the same rates for all four types of sensory impairment.

[]{#__RefHeading___Toc114975412
.anchor}![](media/image7.wmf){width="3.5in"
height="2.354861111111111in"}Figure 4.5 Households With a Person With
Impairment, by Type: RDD vs. List

#### [Type of Functional Limitation]{.smallcaps}

In keeping with our intent to make our sample comparable to that of the
2000 Census and NHIS, we included the question about functional
limitations in the screener. The question was: "Does anyone in your
household who is over age 18 have a condition that prevents or greatly
limits such basic physical activities as:

-   Working at a job or business;

-   Walking, lifting or carrying;

-   Dressing, bathing or getting around inside the home;

-   Going outside the home alone to shop or visit a doctor's office; or

-   Learning, remembering or concentrating?"

Figure 4.6 shows that the order and distribution of responses obtained
from the two samples was the same, but that the proportion of persons
reporting functional limitations was substantially higher in the list
sample. This finding suggests that this screening question proved to be
quite sensitive and specific. The higher rates of functional and
activity limitations observed among respondents in the list sample were
a direct result of how they were selected (i.e., based on
characteristics such as heart problems, multiple sclerosis or wheelchair
use).

[]{#__RefHeading___Toc114975413
.anchor}![](media/image8.wmf){width="4.5in"
height="2.421527777777778in"}Figure 4.6 Percent of Households With a
Person With Functional Limitation, by Type:\
RDD vs. List

To determine respondent status (i.e., being in school, working, able to
work but unemployed, unable to work because of his disability, a
homemaker or retired), respondents were given the opportunity to choose
all that applied. Results are shown in figure 4.7. Here, the modal
category chosen as the first response was "unable to work because of a
disability." The second most populated category was "working," followed
by "retired," "unemployed," "homemaker," and "enrolled in school."

[]{#__RefHeading___Toc114975414
.anchor}![](media/image9.wmf){width="4.75in" height="3.11875in"}Figure
4.7 Respondent Status, by Type of Sample

### Assistive Technology Device Use in the Two Samples

Assistive device use was assessed in the screener and in the
questionnaire. The questions on the screener asked: "Is there anyone in
the household who uses \... ," and then followed up by "Who would that
be?" Figure 4.8 shows that in virtually every category asked during the
screener, the proportion of households screening in was substantially
higher for the list sample.

[]{#__RefHeading___Toc114975415
.anchor}![](media/image10.wmf){width="4.500694444444444in"
height="2.6034722222222224in"}Figure 4.8 Percent of Households Reporting
AT Device Use

Although not shown in the figure, 42 percent of the list sample, as
compared to 18 percent of the RDD sample, used the assistance of another
person in their daily lives. AT use among Asians, blacks and whites
across both samples showed virtually no differences in the percentage of
respondents using AT.

A further comparison of AT device use reported by respondents in the RDD
and list samples in the questionnaire itself showed that six of the top
seven devices used were mobility devices. The list in table 4.4 contains
the 11 most frequently mentioned AT devices for respondents from both
samples. (Eleven devices were listed because crutches and back braces
each received equal mentions from the RDD group.)

[]{#__RefHeading___Toc114975694 .anchor}Table 4.4 Most Mentioned AT
Devices Used

  ----------------------------------- -----------------------------------
  **RDD**                             **List**

  Cane or walking stick               Wheelchair

  Wheelchair                          Cane or walking stick

  Hearing aid                         Walker

  Walker                              Hearing aid

  Scooter                             Scooter

  Other personal-use AT               Crutch

  Oxygen tank                         Electric wheelchair

  Other brace                         Oxygen tank

  Forceps, "grabbers"                 Other personal-use AT

  Crutch                              Shower seat

  Back brace                          Back brace
  ----------------------------------- -----------------------------------

As a check on the distribution of devices, we examined the devices used
at home---the one location used by all respondents. The same four
devices (canes, wheelchairs, hearing aids and walkers) remained the most
prevalent, used by a total of 62 percent of the respondents. Scooters
(the majority of which are used at stores that provide them, like
Wal-Mart), crutches and electric wheelchairs fell out of the top-10
devices used at home, but there was excellent agreement between the
samples as to which devices were most used, and the use pattern at home
was a good, general index.

Overall, 690 of 1,003 list respondents (69 percent) and 211 of 412 RDD
respondents (51 percent) said that they used an assistive device in one
or more of the contexts asked: either going to or at school or work; at
home; or in the community. The higher levels of AT use among list
respondents gave the impression that impairment levels were higher in
this group as compared to the RDD sample.

Where did the respondents learn about the devices? Figure 4.9 summarizes
all of the information sources in all contexts.

[]{#__RefHeading___Toc114975416
.anchor}![](media/image11.wmf){width="5.5in"
height="3.5479166666666666in"}Figure 4.9 Sources of Information About AT

While there were some minor discrepancies, the trend was clear: most
respondents learned about AT devices from their doctors.

The next item asked was: "Where did the respondent obtain the AT
device?" Figure 4.10 shows the overall results in all contexts. The
modal source of assistive technology was the same for both samples: the
medical or orthopedic supply store.

[]{#__RefHeading___Toc114975417
.anchor}![](media/image12.wmf){width="6.0in" height="2.95625in"}Figure
4.10 Source of Supply of AT

The next item was: "Who paid for the device?" Figure 4.11 shows the
distribution of payment sources. In both samples, 37 percent of devices
were paid for by the respondent or someone in the respondent's family.
However, 38 percent were covered under the combined categories of
private health insurance, Medicare and Medicaid. We also note that 6
percent said their AT devices were free.

[]{#__RefHeading___Toc114975418
.anchor}![](media/image13.wmf){width="5.0in"
height="3.186111111111111in"}Figure 4.11 Source of Payment for AT

As shown in figure 4.12, satisfaction with the device was uniformly
high:

[]{#__RefHeading___Toc114975419
.anchor}![](media/image14.wmf){width="5.25in"
height="2.845833333333333in"}Figure 4.12 Level of Satisfaction With AT

As to the question of getting help in the selection and purchase of
their devices, 92 respondents from the RDD sample (19 percent) and 344
respondents from the list sample (21 percent) reported receiving such
help. The difference between the samples was not statistically
significant. (Chi square with Yates' correction for continuity = 1.48,
df = 1, p = 0.22 \> 0.05).

As to the propensity for seeking help, we encountered the first
meaningful difference in response between the two samples: 9 percent of
the respondents in the RDD sample sought help, compared to 25 percent of
the respondents in the list sample. The RDD respondents were
significantly less likely to have sought help than the list respondents.
(Chi square with Yates' correction for continuity = 13.24, df = 1, p =
0.0002 \< 0.001). Note that only respondents who reported no help were
asked whether they had sought help. Perhaps there was no advantage to
seeking help, since there was no significant difference in the
likelihood of receiving it between the two groups.

Finally, all respondents were asked, in each section, whether they
planned to contact an agency for help or advice in the future. Seventeen
percent of the RDD sample respondents and 20 percent of the list sample
respondents answered that they would contact an agency for help or
advice in the future. The difference between the two groups was not
significant (Chi square with Yates' correction for continuity = 3.66, df
= 1, p = \> 0.05).

#### Telephone Use

We asked all respondents about the availability of telephones for their
use in the community, as well as their ability to use a standard phone
without assistance. Where appropriate (with the student and working
populations), we asked about telephone availability and ability to use
without assistance at school or at work. We found that 94 percent of the
respondents from the RDD sample and 97 percent of the respondents from
the list sample had access to telephones in school, at work and in the
community. The differences between the samples were not significant.
Similarly, 85 percent of the respondents from the RDD sample and 82
percent of the respondents from the list sample were able to use the
telephone without assistance. Again, the between group difference was
not statistically significant.

Since there was no significant difference between the groups, we can
examine where telephones were most and least available across the entire
sample. Figure 4.13 shows, somewhat surprisingly, that availability at
work far exceeded availability in school or in the community. The
difference was statistically significant (Chi square=30.48, df=2, p
\<.001). Since the interview was conducted via telephone, the
availability of telephones in the home was assumed to be 100 percent.

[]{#__RefHeading___Toc114975420
.anchor}![](media/image15.wmf){width="4.5in"
height="2.488888888888889in"}Figure 4.13 Telephone Availability Outside
the Home

Only six respondents---one in the RDD sample and five in the
list---reported needing special modifications, such as TTY or relay
services, to make a telephone call, and only three respondents---two RDD
and one list---reported having received advice or help using the
telephone.

#### Computer Use

We asked all respondents about the availability of computers for their
use in the community and in the home. In addition, where appropriate
(i.e., with the student and working populations, we asked about computer
availability at school or at work). Overall, 67 percent of the
respondents in the RDD sample and 69 percent of the respondents in the
list sample had access to a computer. There was no significant
difference between the samples. The locations at which computers were
available are shown in figure 4.14.

[]{#__RefHeading___Toc114975421
.anchor}![](media/image16.wmf){width="5.0in"
height="2.473611111111111in"}Figure 4.14 Computer Availability

As might be expected, schools were more likely to have computers than
any of the other locations. The distribution was significantly different
from what could be expected by chance (Chi-square = 81.46, df = 3, p \<
0.0001).

In addition, respondents reported that 91 percent of the computers they
can use were connected to the Internet, 36 percent required the
assistance of another person, and 14 percent required special
modifications to use a computer. Twenty-one percent had received advice
in using the computer.

### Access to Buildings and Equipment at Home, School, Work and the Community

We asked six questions about access: 1) did the respondent need the help
of another person; 2) did the respondent need special modifications to
gain access to facilities, buildings or equipment; 3) were special
modifications provided; 4) did the respondent have access; 5) did the
respondent try to get help in getting special modifications or
accommodations; and 6) did the respondent plan to contact anyone to get
help.

All respondents were questioned about home. Those who were not homebound
were asked about access in the community at large outside the home;
students and workers were asked about access at school and at work.

The first question in all locales was: "Do you need the help or
assistance of another person to access or use buildings, rooms or
equipment at \[school/work/home/community\]. Nineteen percent of the RDD
sample respondents and 29 percent of the list sample respondents
answered that they needed the assistance of another person to gain
access to, or use buildings, rooms and equipment. The inter-sample
difference was statistically significant (Chi square with Yates'
correction = 33.27, df = 1, p \< 0.0001), pointing once again to the
greater level of mobility impairment in the list sample compared to the
RDD sample. The locations where assistance was needed are shown in
figure 4.15. The home and community differences were statistically
significant but the school difference was not, due to the small number
of respondents who were in school. Once again, the list respondents were
more impaired than RDD respondents.

[]{#__RefHeading___Toc114975422
.anchor}![](media/image17.wmf){width="4.25in" height="3.09375in"}Figure
4.15 Need for Assistance to Access the Environment

We also asked if respondents needed special modifications, adaptations
or accommodations to enter or use buildings and facilities, rooms, and
equipment at school, work, home or in the community. Overall, 13 percent
of the RDD sample respondents and 29 percent of the list sample
respondents needed special modifications to access such locations. As
was true in the assistance category, the inter-sample difference was
statistically significant \[Chi-square with Yates' correction for
continuity = 86.6, df = 1, p \< 0.0001\]. Figure 4.16 shows how the need
for modifications was distributed over the four locations. The home and
community differences were statistically significant. Also note that the
percentages of school modifications needed represented responses
totaling only 15 responses.

[]{#__RefHeading___Toc114975423
.anchor}![](media/image18.wmf){width="3.75in"
height="2.8930555555555557in"}Figure 4.16 Need for Environmental
Modifications

We asked if the needed modifications at work had been provided by the
respondents' employers. In 38 cases, the answer was positive; in 40
cases, their employers had not provided the needed modifications. There
was no significant difference between the samples in this respect.

Similarly, we asked if access was available at school, at work, at home
and in the community. Accessibility was evenly distributed at 95--96
percent across all locations. The inter-sample differences were not
statistically significant.

Next, we asked if the respondent had tried to obtain help in getting
special modifications, and whether the respondent planned to contact any
agency or organization to get the needed modifications. Over all
locations, only 17 (13 percent) mentions were made of attempts to obtain
help, and there were only 10 (9 percent) positive intentions to contact
an agency.

### Open-Ended Questions

#### Respondent Conditions

The first question asked of each respondent, after establishing the
respondent's current status, was worded: "What condition or limitation
do you have that impairs your functioning?" The verbatim responses were
coded according to the categories published in NIDRR Disability
Statistics Report 7, table A-1, NHIS Impairment and ICD Codes
corresponding to conditions listed in text table B and detailed tables
6--8. Up to three impairments were coded for each respondent; if more
than three items were coded, the less severe impairments were omitted.
For example, if a respondent reported having had a stroke, congestive
heart failure, an amputated limb and carpal tunnel syndrome, carpal
tunnel syndrome was not scored. The coded impairments were distributed
across the two samples as shown in table 4.5.

[]{#__RefHeading___Toc114975695 .anchor}Table 4.5 Number of Conditions
Coded, by Type of Sample

  ------------- -------------- -------------- -------------- --------------
                **RDD**                       **List**       

                *Number*       *Percent*      *Number*       *Percent*

  **One**       412            100            1,002          100

  **Two**       155            38             271            27

  **Three**     42             10             97             10
  ------------- -------------- -------------- -------------- --------------

We coded a total of 119 different conditions. Table 4.6 lists the 10
most frequently listed conditions for each sample.

[]{#__RefHeading___Toc114975696 .anchor}Table 4.6 List of Frequently
Mentioned Health Conditions

  ----------------------------------- -----------------------------------
  **RDD**                             **List**

  Hearing loss, both ears             Osteoarthritis

  Osteoarthritis                      Injury, chronic or late effects

  *Unspecified mobility disorder*     Hearing loss, both ears

  Injury, chronic or late effects     *Unknown, unspecified other*

  Back disorders, other               Multiple sclerosis

  Diabetes                            Heart disease, other

  *Orthopedic impairment,             Diabetes
  lower extremity*                    

  Heart disease, other                Back disorders, other

  *Visual impairment, both eyes*      *Stroke*

  Multiple sclerosis                  *Nervous system, unspecified*
  ----------------------------------- -----------------------------------

Conditions in italics were unique to the sample listed. It should be
noted that the category "Injury, Chronic or Late Effects" was high on
both lists; all such cases were combined with a secondary diagnosis.

#### Assistive Devices Used

We asked each respondent what sort of AT she used in all locations where
appropriate: at or getting to school or work; at home; and in the
community. A total of 75 different AT devices were coded. Averaged over
all mentions, the RDD sample provided 1.0 devices per respondent, while
the list group accounted for 1.6 devices per respondent. The
distribution of responses was very markedly skewed for both groups, as
shown in table 4.7. In this table, sorted by responses given across both
samples, six of the top seven devices are mobility devices. The column
at the far right indicates the ratio of percentage use in the two
samples. For example, list respondents were five times as likely to use
unclassified home-use AT devices than were RDD respondents, while RDD
respondents were four times more likely to use personal-use AT than list
respondents. However, the main point here was that there was excellent
agreement between the samples as to which devices were most used.

[]{#__RefHeading___Toc114975719 .anchor}Table 4.7 Type of AT Device Used
at Home, School, Work and in the Community

  ------------------- ----------- ----------- ---------- ----------- ---------- ----------- ----------
                      **TOTAL**               **RDD**                **List**               **RDD to
                                                                                            List**

  **Device Type**     *Number*    *Percent*   *Number*   *Percent*   *Number*   *Percent*   **Ratio 1
                                                                                            : x**

  Cane or walking     466         22.7        116        27.4        350        21.5        0.78
  stick                                                                                     

  Wheelchair          461         22.5        55         13.0        406        25.0        1.92

  Walker              201         9.8         44         10.4        157        9.6         0.93

  Hearing aid         161         7.9         51         12.1        110        6.8         0.56

  Scooter             122         6.0         21         5.0         101        6.2         1.25

  Crutch              55          2.7         7          1.7         48         3.0         1.78

  Electric wheelchair 48          2.3         4          0.9         44         2.7         2.86

  Other AT at home    41          2.0         2          0.5         39         2.4         5.07

  Other personal-use  40          2.0         21         5.0         19         1.2         0.24
  AT                                                                                        

  Oxygen tank         39          1.9         10         2.4         29         1.8         0.75

  Bathroom            26          1.3         2          0.5         24         1.5         3.12
  modifications                                                                             

  Shower seat         23          1.1         4          0.9         19         1.2         1.23

  Nebulizer           20          1.0         3          0.7         17         1.0         1.47

  Leg brace           20          1.0         2          0.5         18         1.1         2.34

  Other brace         19          0.9         9          2.1         10         0.6         0.29

  Back brace          18          0.9         7          1.7         11         0.7         0.41
  ------------------- ----------- ----------- ---------- ----------- ---------- ----------- ----------

As a check on the distribution of devices, we examined the devices used
at home, the one location used by all respondents. Table 4.8 shows the
same four devices as most prevalent, used by a total of 62 percent of
the respondents. Scooters (the majority of which were used at stores
that provide them, like Wal-Mart), crutches and electric wheelchairs
fell out of the top-10 devices used at home, but we concluded that the
overall use pattern at home was a good, general index.

[]{#__RefHeading___Toc114975720 .anchor}Table 4.8 AT Use in the Home

  ---------------------------------------- ------------------------------
  **Type of AT**                           *Percent of Respondents Using*

  Cane or walking stick                    23

  Wheelchair                               19

  Walker                                   13

  Hearing aid                              7

  Other personal-use AT                    4

  Bathroom modifications                   3

  Walker                                   3

  Other personal-use AT                    2

  Shower seat                              2

  Oxygen tank                              2
  ---------------------------------------- ------------------------------

#### Reasons for Not Contacting an Agency for Technical Assistance

Whenever a respondent reported that she didn't plan to contact an agency
for help, we asked: "Why not?" We recorded 817 verbatim responses from
the RDD respondents. The initial impression we had was that the
respondent did not consider herself to be in need of assistance. To
confirm that, we performed a search that located 400 uses of the word
"need," and another 17 uses of wording indicating a lack of need, such
as "get along" and "ok." A word search of the word "insurance" revealed
18 uses, "money" was used six times, and "know" was used 92 times. A
similar overview was made of the verbatim responses from the list
respondents. The general conclusion was that the primary reason persons
with disabilities did not plan to contact an agency for help was that
they did not feel the need to do so; the secondary reason was that they
did not know whom to contact.

We also asked each respondent who did not contact an agency, "What were
the reasons that you did not contact an organization or agency?" and
found a similar set of responses.

### Unmet Need for Assistive Technology

We divided the total respondent population into three categories: 1)
those who did not need modifications; 2) those who needed them and had
those needs met; and 3) those who expressed unmet needs. To be
considered a person needing modifications, a respondent would have had
to express that need in at least one, but possibly as many as four,
different domains. To be a person in Category 2 ("Needs Expressed and
Met"), a respondent would have given the answer that modifications are
available in at least one domain, and to be a person in Category 3,
("Expressed Needs Unmet"), a respondent would have given a "No" answer
that modifications are available. Thus, it might have been possible for
a person to have expressed a need for modifications in all four domains
and found them available in one, and be counted in the "Needs Met"
category (i.e., the "Needs Unmet" category was a minimalist estimate,
but with so small a sample, further differentiation of level of meeting
needs was not feasible).

Given the limitation stated above, we compared the three groups on all
independent and dependent variables, and arrived at the following
conclusions.

#### Level of Education

To illustrate the effects of the independent variables, we arbitrarily
set the mean value for those not in need of modification ("No Need") as
the comparative standard, then normalized the scores for those needing
and having available the modifications ("Need/Has AT") and those who had
unmet needs ("Need/Does Not Have AT") relative to the group not in need.
Figure 4.17[^9] shows how the three groups compared in the level of
education attained.

[]{#__RefHeading___Toc114975424
.anchor}![](media/image19.wmf){width="4.25in"
height="2.214583333333333in"}Figure 4.17 Unmet Need for AT and Level of
Education

The finding corroborates the overall finding that education level was
related to acquiring AT, or, in this case, a lower education level was
associated with not acquiring needed modifications.

#### Attitude and Opinions About Assistive Technology

Each respondent answered six attitude questions about the knowledge to
acquire AT, the availability of such knowledge, and the utility of AT in
improving life, as well as four questions that compared the respondents'
perceptions of their situations at the time versus 10 years ago. Figure
4.18 shows the attitudes of the respondents on the two topics. Note that
those in need of modifications were generally more negative in assessing
how their current situations compared to what they were 10 years ago,
and those who did not have the modifications were considerably more
negative than those who had them. It is also important to note that
those who had modifications available to them in some domain were more
positive than the respondents who did not need modifications.

[]{#__RefHeading___Toc114975425
.anchor}![](media/image20.wmf){width="5.0in" height="2.125in"}Figure
4.18 Unmet Need for AT and Attitudes and Opinions About AT

#### Race

Among nonwhite respondents, 60 percent expressed no need for
modifications; among whites the proportion was also 60 percent.
Therefore, we focused attention on those who expressed some need. Among
whites, 13.8 percent of those needing some modification failed to obtain
it in any domain, compared with 22 percent of nonwhites whose needs were
similarly unsatisfied. This means that nonwhites with a need for
modifications were 59 percent more likely to experience unmet need.

#### Age

Respondents who needed modifications were, on average, slightly younger
than those who did not. Figure 4.19 illustrates the distributions of the
three groups (not needing, needing and having, and not having) in terms
of their underrepresentation or overrepresentation relative to the total
sample.

[]{#__RefHeading___Toc114975426
.anchor}![](media/image21.wmf){width="5.5in"
height="2.765277777777778in"}Figure 4.19 Unmet Need for AT and Age

It is evident that, for the youngest two cohorts (under 40 years old),
those who needed modifications were overrepresented, and for the highest
two cohorts (over 55), they were underrepresented. A possible
interpretation for this is that persons in need of modifications needed
them at younger ages and were less likely to survive to older ages,
especially if they did not receive them.

#### Income

We measured personal and family income. As shown in figure 4.20, all
persons in need fell below the income levels attained by those who did
not need modifications. The family income level was far lower for those
who needed modifications and did not receive them, while the personal
income level was roughly equal for both groups.

[]{#__RefHeading___Toc114975427
.anchor}![](media/image22.wmf){width="4.75in"
height="2.282638888888889in"}Figure 4.20 Unmet Need for AT and Personal
and Family Income

#### Gender

Male respondents were coded as "1," and females as "2;" thus, in figure
4.21, positive values indicated a higher level of females in the group.

[]{#__RefHeading___Toc114975428
.anchor}![](media/image23.wmf){width="4.5in"
height="2.7256944444444446in"}Figure 4.21 Gender and Unmet Need for AT

As we moved from those not in need of modification, and those needing
and having modifications available and to those with unmet needs, we
found an increasing proportion of females in each successive group.

### Summary

Respondents from the RDD sample were found to have experienced somewhat
lower levels of disability than those from the list sample. They were
about one-third less likely to describe themselves as unable to work
because of their disabilities, and about one-third more likely to
describe themselves as able to work. When all status statements were
combined, a total of 729 respondents (52 percent) reported being unable
to work because of their disabilities.

The respondents cited more than 100 different conditions as causing
their limitations. Major contributors included osteoarthritis, hearing
loss, chronic or late effects of injury, multiple sclerosis, heart
disease and diabetes.

Almost two-thirds (64 percent) of all respondents reported using AT in
one or more of the six contexts asked: either going to or at school or
work, at home or in the community. This question was asked at the
beginning of the survey. When asked later in the questionnaire whether
their use of assistive technology had reduced their dependence on help
from another person, only 13 percent said they did not use AT or the
assistance of another person.

More than any other source, doctors and other health care professionals
were named as the source of information about AT 51 percent of the time.
The next highest category was family and friends, at 13 percent; *Tech
Act* agencies comprised less than 1 percent of the responses.

AT was most likely obtained from a medical or orthopedic supply store,
as cited by 44 percent of the respondents; an additional 19 percent got
AT from hospitals and clinics, of which 74 percent were non-VA and 26
percent were VA, and 12 percent obtained their AT directly from a
doctor's office.

Persons with disabilities paid for their devices primarily through
insurance (38 percent, including the combined categories of private
health insurance, Medicare and Medicaid) and by themselves or through
family members (37 percent). Six percent of AT devices were free to the
respondents.

The respondents were quite well satisfied with their AT; 90 percent were
very satisfied or satisfied with the AT that they used.

Nineteen of the respondents received an agency's or organization's
assistance in the process of selecting and purchasing their AT. However,
only 23 percent of the respondents had sought such help. Similarly, 24
percent of the respondents indicated that they intended to seek out help
in the future. Of those who did not intend to seek help, the majority
gave responses that indicated that they did not feel that help was
necessary.

Fewer than 1 percent of the respondents reported a need for special
modifications to use the telephone. We also found that the overall
availability of telephones was about 85 percent (this was exclusive of
the home; since the questionnaires were administered over the telephone,
home availability was *de facto* 100 percent). Telephones were almost
universally available at work, and somewhat less available in schools
and in the community.

More than two-thirds of the respondents reported that they had a
computer available for their use. As to where the computers were
located, schools were more likely to have had computers (about 85
percent) than any of the other locations, followed by places in the
community, the workplace, and the home (just over 50 percent). In
addition, respondents reported that: 91 percent of the computers they
could use were connected to the Internet; 36 percent of the respondents
required the assistance of another person to use a computer; 14 percent
of the respondents required special modifications to use a computer; and
21 percent had received advice in using computers.

Just over one-quarter (26 percent) of the answers given by respondents
to the question "Do you need the help or assistance of another person to
access or use buildings, rooms or equipment at \[school /work/ home/
community\]" were in the affirmative, over all locations. The place
where the fewest individuals needed help was work, a finding which is
most likely attributable to the fact that the working population was
operationally defined as less impaired than the nonworking population.

For each location where it was appropriate, we asked if the respondent
did, in fact, have access: 95 percent answered "Yes."

Our study showed that the unmet need for modification correlated with
low levels of education, personal and family income, nonwhite racial
category, nonworking status, younger age, and a more negative attitude.

In all, we found that persons with disabilities used assistive
technology devices and environmental access features to a very large
extent. Compared to the surveys discussed in 2, our respondents had
higher rates of access to computers and the Internet.

## 5. Assistive Technology Use at Home, in School, at Work and in the Community

The previous contained a section on assistive technology use that
provided a general overview of how AT users learned about AT, where they
got it, how AT was paid for, and how satisfied they were with the
devices and the services they obtained in the process of selecting and
purchasing the needed equipment or technology. We found high rates of
overall use of AT (64 percent) and high rates of satisfaction with
technology related assistance. In addition, we found that medical and
rehabilitation professionals were not only the key source of AT-related
information and assistance, but also frequent suppliers of AT devices
and services.

In this chapter, we take a closer look at how AT was acquired for use in
the various domains of daily living (i.e., home, school, work and
community). Making these analytical distinctions is helpful for the
identification of potential gaps in the availability of assistive
technology for tasks specific to home, school or place of work. An
improved understanding of AT use and need in these domains will also
assist in the development of better technical solutions for increased
access to these environments.

### Assistive Technology Use in the Home

We asked each respondent: "Do you use an AT device or service to help or
assist you with doing daily tasks and chores at home?" In the RDD
sample, 149 respondents (36.2 percent) reported using AT in the home,
whereas 542 list sample respondents (54.1 percent) reported using AT in
the home. The difference is obvious. A greater percentage of persons
from the list sample used AT. We then asked how the respondents learned
about the device. Their responses are shown in table 5.1.

[]{#__RefHeading___Toc114975721 .anchor}Table 5.1 Sources of Information
(AT at Home)

  ------------------------------------------------------------------------
                                  **RDD**             **List**   
  ------------------------------- --------- --------- ---------- ---------
  Doctor, health care             332       62%       325        43%
  professional                                                   

  Vocational rehab center         67        13%       61         8%

  Family/friends/neighbors        83        16%       77         10%

  Pamphlets, magazines            34        6%        32         4%

  Center for independent living   2         0%        2          0%

  Tech assistance center          0         0%        4          1%

  *Tech Act*/other state          1         0%        7          1%
  organization                                                   

  TV/Radio                        0         0%        9          1%

  Yellow pages                    0         0%        2          0%

  Internet                        1         0%        104        14%

  Other                           13        2%        120        16%
  ------------------------------------------------------------------------

We noticed that while respondents from both samples get more information
from the medical profession, a higher percentage of list sample
respondents get their information from the Internet or other sources.

The next question asked respondents where they got their AT devices.
Table 5.2 shows that the RDD sample respondents were twice as likely to
obtain their devices from a doctor's office than were the list sample
respondents. The main source for all respondents, however, was the
medical or orthopedic supply store. The next question asked who paid for
it.

[]{#__RefHeading___Toc114975722 .anchor}Table 5.2 Sources of Supply (AT
at Home)

  ------------------------------------------------------------------------------
                                            **RDD**           **List**   
  ----------------------------------------- --------- ------- ---------- -------
  Doctor's office                           31        20%     62         10%

  Hospital/clinic \[not VA\]                28        18%     83         13%

  VA Hospital/clinic                        4         3%      35         5%

  Vocational rehab center                   9         6%      39         6%

  Nursing home                              0         0%      4          1%

  Medical/orthopedic supply store           55        36%     292        46%

  Prescription from drugstore, including    6         4%      22         3%
  Wal-Mart                                                               

  OTC from drugstore, including Wal-Mart    2         1%      7          1%

  Mail order                                2         1%      8          1%

  Other                                     15        10%     85         13%
  ------------------------------------------------------------------------------

Table 5.3 shows that the distribution pattern for the two subsamples of
AT users at home was virtually identical.

[]{#__RefHeading___Toc114975723 .anchor}Table 5.3 Sources of Payment (AT
at Home)

  -----------------------------------------------------------------------------------
                                         **RDD**         **List**            
  -------------------------------------- --------- ----- ---------- -------- --------
  Self, family member                    76        44%              257      37%

  Private health insurance               24        14%              113      16%

  Medicare                               33        19%              116      17%

  Medicaid                               11        6%               41       6%

  Rehab program                          4         2%               7        1%

  Employer                               5         3%               22       3%

  School system                          0         0%               1        0%

  VA program                             4         2%               35       5%

  Free                                   11        6%               43       6%

  Other                                  9         5%               53       8%
  -----------------------------------------------------------------------------------

Next, we asked the respondent's satisfaction with the AT device. The
responses to this question are shown in table 5.4.

[]{#__RefHeading___Toc114975724 .anchor}Table 5.4 Level of Satisfaction
With AT (AT at Home)

  ------------------------------------------------------------------------------
                                            **RDD**           **List**   
  ----------------------------------------- --------- ------- ---------- -------
  Very satisfied                            80        54%     320        59%

  Somewhat satisfied                        52        35%     178        33%

  Somewhat dissatisfied                     10        7%      27         5%

  Very dissatisfied                         7         5%      16         3%
  ------------------------------------------------------------------------------

The results in this section showed that the respondents' primary source
of information for AT in the home was the medical profession; however
most obtained AT from a medical supply house. Most paid for the device
by themselves, or through insurance, and most were very satisfied with
the device they obtained.

The next section of the questionnaire asked about help received during
the selection and purchase of the home AT device. Of the list
respondents who used a device at home, 383 of 543 (71 percent) said they
did not receive help from an agency or organization during the selection
and purchase of the services. In the list sample, 108 of 149 (73
percent) did not receive help.

We asked about satisfaction with the help received, with the following
results:

[]{#__RefHeading___Toc114975725 .anchor}Table 5.5 Level of Satisfaction
With Advice (AT at Home)

  -----------------------------------------------------------------------------
                                         **RDD**            **List**   
  -------------------------------------- --------- -------- ---------- --------
  Very satisfied                         29        62%      116        73%

  Somewhat satisfied                     16        34%      34         21%

  Somewhat dissatisfied                  1         2%       5          3%

  Very dissatisfied                      1         2%       4          3%
  -----------------------------------------------------------------------------

Of those who did not receive help, only 51 of 383 (13 percent) from the
list sample, and four of the 108 from the RDD sample (4 percent)
actually sought help.

We then asked whether there are additional AT devices that respondents
would use at home; 193 of 530 (36 percent) from the list sample and 43
of 104 respondents in the RDD sample said they believed there are such
devices.

We asked all respondents whether they had ever tried and failed to
obtain an assistive device for use in the home. Of the 1,002 list
respondents, 163 (16 percent) list sample said yes, as did 29 of 411 (7
percent) RDD respondents. Of the 163 in the list sample, 104 came from
the 542 (19 percent) in the home who use devices at home, 59 from the
460 (13 percent) who do not. Of the 29 respondents in the RDD sample who
failed to obtain assistive devices for use in the home, 16 (11 percent)
came from the 149 respondents who use devices, 13 (5 percent) from the
non-AT using group.

Next, we found that 464 (47 percent) of the 995 list respondents and 192
of 408 RDD respondents (also 47 percent) said they were aware that they
could get help to obtain AT. They said they would seek that help
learning about the devices from the agencies tabulated below.
Forty-eight percent (225 of 464) of list respondents and 40 percent of
RDD respondents (77 of 192) who were aware that they could get help
planned to contact an agency. None specified an agency that they planned
to contact. Table 5.6 shows the distribution of possible sources of
information across the two samples. Doctors and health care
professionals were mentioned most frequently as a source of information.

[]{#__RefHeading___Toc114975726 .anchor}Table 5.6 Sources of Help (AT at
Home)

  --------------------------------------- --------- ------- ---------- -------
                                          **RDD**           **List**   

  Doctor, health care professional        104       47%     188        34%

  Vocational rehab center                 12        5%      40         7%

  Family/friends/neighbors                11        5%      28         5%

  Pamphlets, magazines                    6         3%      18         3%

  Center for independent living           10        4%      12         2%

  Tech assistance center                  7         3%      15         3%

  *Tech Act*/other state organization     7         3%      21         4%

  TV/Radio                                5         2%      11         2%

  Yellow pages                            2         1%      5          1%

  Internet                                6         3%      41         7%

  Other                                   53        24%     168        31%
  --------------------------------------- --------- ------- ---------- -------

### Detailed Findings of the Student Population

We asked: "Do you use an assistive technology device or service to help
you with getting to or from school, or while you are at school?"
Clearly, the two samples were different. The respondents from the list
sample were more likely to use assistive devices than were those from
the RDD sample, as shown in figure 5.1.

[]{#__RefHeading___Toc114975429
.anchor}![](media/image24.wmf){width="3.5in"
height="2.5236111111111112in"}Figure 5.1 Use of AT by Enrolled Students

We then asked how the respondents learned about the device. Their
answers are tabulated in table 5.7. Doctors and health care
professionals were the primary source of information about assistive
devices for the students in the sample.

[]{#__RefHeading___Toc114975727 .anchor}Table 5.7 Source of Information
(AT in School)

  -------------------------------------- --------- -------- ---------- --------
                                         **RDD**            **List**   

  Doctor, health care professional       1         33%      7          47%

  Vocational rehab center                1         33%      3          20%

  Family/friends                         0         0%       1          7%

  Tech assistance center                 0         0%       1          7%

  *Tech Act*/other state organization    0         0%       1          7%

  TV/Radio                               0         0%       1          7%

  Internet                               0         0%       1          7%

  Other                                  1         33%      0          0%
  -------------------------------------- --------- -------- ---------- --------

The next question asked where the student respondents got their AT
devices.

[]{#__RefHeading___Toc114975728 .anchor}Table 5.8 Source of Supply (AT
in School)

  ----------------------------------- --------- -------- ---------- --------
                                      **RDD**            **List**   

  Doctor's office                     2         67%      5          42%

  Medical supply store                1         33%      7          58%
  ----------------------------------- --------- -------- ---------- --------

Then the next question asked who paid for it.

[]{#__RefHeading___Toc114975729 .anchor}Table 5.9 Source of Payment (AT
in School)

  ----------------------------------- --------- -------- ---------- --------
                                      **RDD**            **List**   

  Self, household member              2         67%      6          43%

  Private health insurance            0         0%       2          14%

  Medicare                            0         0%       1          7%

  Medicaid                            0         0%       1          7%

  Rehab program                       1         33%      2          14%

  Employer                            0         0%       1          7%

  Free                                0         0%       1          7%
  ----------------------------------- --------- -------- ---------- --------

This was followed by the respondents' satisfaction with the AT devices.

[]{#__RefHeading___Toc114975730 .anchor}Table 5.10 Level of Satisfaction
With AT (AT in School)

  ----------------------------------- --------- -------- ---------- --------
                                      **RDD**            **List**   

  Very satisfied                      1         33%      10         63%

  Somewhat satisfied                  2         67%      4          25%

  Somewhat dissatisfied               0         0%       2          13%

  Very dissatisfied                   0         0%       0          0%
  ----------------------------------- --------- -------- ---------- --------

The student respondents' primary source of information and supply was
the medical profession. Most paid for the devices by themselves, or
through insurance, and most were very satisfied with the devices they
obtained.

The next section of the questionnaire asked about help received during
the selection and purchase of the AT devices. In the list sample, 12 of
the 16 respondents who had a device said they received no help from an
agency or organization during the selection and purchase of the
services; none of the RDD respondents received help.

We then asked whether there were additional devices that the respondents
would use: 1) to get to or from school; or 2) while at school. Four of
the 16 users from the list, and none from the RDD sample, said there
were additional devices to get to or from school. Eight of the 16 users
from the list sample, and one from the RDD sample, said there were
additional devices to use while at school. We also asked the students
who did not use a device to get to school or while at school whether
there were devices available that might help. None said that there were
any.

We asked all students whether they had ever tried and failed to obtain
an assistive device. In the list sample, 10 of the 29 (34 percent) said
yes, they had experienced failure. Of these 10, six came from the 16 (38
percent) who used devices and four from the 13 (31 percent) who did not.
In the RDD sample, there were three who had tried without success to
obtain devices; all three are individuals who did not use AT.

Next, we found that 14 (48 percent) of the students from the list sample
and 12 (57 percent) from the RDD sample said they were aware that they
could get help to obtain AT. Those who were aware were asked where they
would go to learn more about the devices or services. Their responses
were shown in table 5.11. Other organizations included agencies such as
insurance companies, hospitals or social workers.

[]{#__RefHeading___Toc114975731 .anchor}Table 5.11 Sources of Help (AT
in School)

  ----------------------------------- --------- -------- ---------- --------
                                      **RDD**            **List**   

  Doctor, health care professional    4         36%      5          33%

  Vocational rehab center             2         18%      1          7%

  Tech assistance center              0         0%       1          7%

  *Tech Act*/Other state organization 1         9%       1          7%

  Yellow pages                        0         0%       1          7%

  Other                               4         36%      6          40%
  ----------------------------------- --------- -------- ---------- --------

In the list sample, 13 of 14 of those who were aware that they could get
help planned to contact an agency. In contrast, five of the 12 RDD
respondents planned to contact an agency. No one from either sample
specified an agency that she planned to contact.

In summary, the results from the student population showed some
measurable differences between the respondents in the two samples. Most
obviously, the RDD sample was less severely impaired as defined by their
self-assigned status, and as confirmed by their lower use of AT in their
lives as students.

### Detailed Findings of the Working Population

The results from the question: "Do you use an assistive technology
device or service to help you with getting to or from work, or while you
are at work?" were similar to those found in the student population. As
shown in figure 5.2, the list sample respondents were more likely to use
AT than those from the RDD sample.

[]{#__RefHeading___Toc114975430 .anchor}Figure 5.2 Use of AT by Employed
Respondents

![](media/image25.wmf){width="4.0in" height="2.5125in"}Table 5.12 shows
how the respondents learned about the device. Most of the respondents
from both samples learned about the device from doctors or a health care
professional.

[]{#__RefHeading___Toc114975732 .anchor}Table 5.12 Source of Information
(AT at Work)

  ----------------------------------------------------------------------------
                                          **RDD**           **List**   
  --------------------------------------- --------- ------- ---------- -------
  Doctor, health care professional        26        60%     45         44%

  Vocational rehab center                 0         0%      7          7%

  Family/Friends/Neighbors                3         7%      11         11%

  Pamphlets, magazines, etc.              0         0%      6          6%

  Tech assistance center                  1         2%      1          1%

  Center for independent living           0         0%      2          2%

  *Tech Act*/Other state organization     1         2%      1          1%

  TV/Radio                                1         2%      1          1%

  Other                                   11        26%     29         28%
  ----------------------------------------------------------------------------

The next question asked where the respondents obtained their AT devices.
Table 5.13 summarizes the source of AT at work.

[]{#__RefHeading___Toc114975733 .anchor}Table 5.13 Source of Supply (AT
at Work)

  ----------------------------------------------------------------------------
                                               RDD           **List**   
  -------------------------------------------- ------ ------ ---------- ------
  Doctor's office                              10     24%    15         22%

  Hospital/clinic \[not VA\]                   6      14%    7          10%

  VA Hospital/clinic                           1      2%     2          3%

  Vocational rehab center                      2      5%     3          4%

  Medical/orthopedic supply store              11     26%    35         51%

  Prescription from drugstore, including       4      10%    3          4%
  Wal-Mart                                                              

  OTC from drugstore, including, Wal-Mart      3      7%     1          1%

  Mail order                                   0      0%     2          3%

  Other                                        5      12%    0          0%
  ----------------------------------------------------------------------------

Table 5.14 shows the source of payment for the AT.

[]{#__RefHeading___Toc114975734 .anchor}Table 5.14 Source of Payment (AT
at Work)

  --------------------------------------------------------------------------
                                      **RDD**            **List**   
  ----------------------------------- --------- -------- ---------- --------
  Self, household member              30        68%      49         55%

  Private health insurance            7         16%      18         20%

  Medicare                            1         2%       5          6%

  Medicaid                            0         0%       1          1%

  Rehab program                       0         0%       3          3%

  Employer                            4         9%       7          8%

  VA program                          1         2%       3          3%

  Free                                1         2%       3          3%
  --------------------------------------------------------------------------

The final question assessed the respondents' satisfaction with the AT
devices. Table 5.15 shows that the satisfaction levels were similar
between RDD and list respondents, with most being somewhat or very
satisfied with AT at work.

[]{#__RefHeading___Toc114975735 .anchor}Table 5.15 Level of Satisfaction
with AT (AT at Work)

  ----------------------------------- --------- -------- ---------- --------
                                      **RDD**            **List**   

  Very satisfied                      23        53%      50         50%

  Somewhat satisfied                  13        30%      47         47%

  Somewhat dissatisfied               7         16%      1          1%

  Very dissatisfied                   0         0%       2          2%
  ----------------------------------- --------- -------- ---------- --------

The next section of the questionnaire asked about help received during
the selection and the purchase of the AT device. In the list sample, 58
of 81 (72 percent) working respondents who had a device said they
received no help from an agency or organization during the selection and
purchase of the services. In the RDD sample, 35 of 43 (81 percent) said
they had not received help.

Of those who did not receive help, 20 of the 23 list sample respondents
were very satisfied, and three were somewhat satisfied with the help
they received. Seven of the eight RDD respondents were very satisfied,
while the other was somewhat satisfied.

Of those who did not receive help, only seven (12 percent) in the list
sample and one (3 percent) in the RDD sample sought help.

When asked whether there were additional AT devices that respondents
would use to get to or from work, 10 of 80 (13 percent) list sample
workers and two of 40 (5 percent) of RDD workers said there were. Asked
about additional devices they would use while at work, 17 of 81 (21
percent) from the list sample and 10 of 42 (24 percent) from the RDD
sample said there were.

We also asked the working respondents who did not use a device to get to
work or while at work whether there were devices available that might
help getting to or from work. Only five of 104 (5 percent) from the list
sample and eight of 67 (2 percent) of the RDD sample said that there
were any. Over both samples, nine said AT would help "A lot," two each
said AT would help "Somewhat" or "A little." When asked about AT that
would help them at work, 13 (13 percent) from the list sample and 19 (28
percent) from the RDD sample said there were, with 18 saying that it
would help "A lot," 11 "Somewhat" and two "A little."

We asked all workers whether they had ever tried and failed to obtain an
assistive device. In the list sample, 23 of 189 (12 percent) said yes,
they had experienced failure. Of these 23, 12 came from the 82 (15
percent) who used devices, and 11 from the 107 (10 percent) who did not.
In the RDD sample, 10 of 102 (10 percent) had failed to get a device;
five of these were from persons who used devices.

Next, 89 (47 percent) of the list sample workers and 55 (49 percent) of
workers from the RDD sample said that they were aware that they could
get help to obtain AT. Those who were aware were asked where they would
go to learn more about the devices or services. The responses are shown
in table 5.16.

[]{#__RefHeading___Toc114975736 .anchor}Table 5.16 Source of Help (AT at
Work)

  ----------------------------------------------------------------------------
                                          **RDD**           **List**   
  --------------------------------------- --------- ------- ---------- -------
  Doctor, health care professional        26        47%     31         26%

  Vocational rehab center                 3         5%      9          8%

  Family/Friends/Neighbors                1         2%      8          7%

  Pamphlets, magazines                    1         2%      4          3%

  Center for independent living           0         0%      5          4%

  Tech assistance center                  1         2%      3          3%

  *Tech Act*/Other state organization     2         4%      7          6%

  TV/Radio                                0         0%      1          1%

  Yellow pages                            3         5%      1          1%

  Internet                                3         5%      16         14%

  Other                                   15        27%     32         27%
  ----------------------------------------------------------------------------

Thirty-eight percent (34 of 89) of the list sample workers and 21
percent (23 of 111) of the RDD workers who were aware that they could
get help planned to contact an agency.

In summary, the workers from the RDD sample were less frequent users of
AT. The working respondents' primary source of information was the
medical profession, and most obtained AT from a medical supply house.
The majority of respondents paid for the devices themselves, or through
insurance, and most were very satisfied with the devices they obtained.

### Detailed Findings on Assistive Technology Use in the Community

Respondents were asked about the use of AT outside the home. Fourteen of
the respondents in the list sample and five in the RDD were homebound,
and consequently were not asked this set of questions. We asked each
respondent: "Do you use an AT device or service to help or assist you
with activities outside the home such as shopping or visiting friends
and family?" Of the 983 list respondents, 548 (56 percent) answered
"Yes," as did 153 of the 407 RDD respondents (38 percent). The
difference between proportions was significant at the .01 level. We then
asked how the respondents learned about the device. The distribution of
their responses is shown in table 5.17. There was good correspondence
about the source of information between the two groups.

[]{#__RefHeading___Toc114975737 .anchor}Table 5.17 Source of Information
(AT in the Community)

  ----------------------------------------------------------------------------
                                          **RDD**           **List**   
  --------------------------------------- --------- ------- ---------- -------
  Doctor, health care professional        84        51%     288        48%

  Vocational rehab center                 10        6%      43         7%

  Family/Friends/Neighbors                26        16%     82         14%

  Pamphlets, magazines                    2         1%      20         3%

  Center for independent living           1         1%      6          1%

  Tech assistance center                  1         1%      8          1%

  *Tech Act*/Other state organization     4         2%      5          1%

  TV/Radio                                1         1%      15         2%

  Yellow pages                            1         1%      5          1%

  Internet                                0         0%      4          1%

  Other                                   36        22%     129        21%
  ----------------------------------------------------------------------------

The next question asked where the respondents got their AT devices.
Table 5.18 shows that the sources for obtaining the devices were very
similar across the two samples.

[]{#__RefHeading___Toc114975738 .anchor}Table 5.18 Source of Supply (AT
in the Community)

  -------------------------------------------------------------------------------
                                               **RDD**          **List**   
  -------------------------------------------- --------- ------ ---------- ------
  Doctor's office                              29        19%    79         11%

  Hospital/Clinic \[not VA\]                   21        14%    68         10%

  VA Hospital/Clinic                           7         5%     26         4%

  Vocational rehab center                      11        7%     27         4%

  Nursing home                                 0         0%     3          0%

  Medical/Orthopedic supply store              50        33%    257        37%

  Prescription from drugstore, including       6         4%     11         2%
  Wal-Mart                                                                 

  OTC from drugstore, including Wal-Mart       5         3%     12         2%

  Mail order                                   1         1%     2          0%

  Other                                        23        15%    103        15%
  -------------------------------------------------------------------------------

We then asked who paid for the community AT device, and obtained the
following results shown in table 5.19. There were no significant
differences between the two samples regarding the sources of payment for
the AT devices and the services used outside of the home.

[]{#__RefHeading___Toc114975739 .anchor}Table 5.19 Source of Payment (AT
in the Community)

  ----------------------------------------- --------- ------- ---------- -------
                                            **RDD**           **List**   

  Self, family member                       67        37%     281        36%

  Private health insurance                  22        12%     138        18%

  Medicare                                  27        15%     118        15%

  Medicaid                                  9         5%      54         7%

  Rehab program                             3         2%      13         2%

  Employer                                  6         3%      12         2%

  School system                             0         0%      1          0%

  VA program                                9         5%      38         5%

  Free                                      18        10%     61         8%

  Other                                     11        6%      69         9%
  ----------------------------------------- --------- ------- ---------- -------

The questionnaire next assessed the respondents' satisfaction with the
AT devices used outside the home. Table 5.20 shows a significant
difference in the amount of satisfaction between the samples. While the
difference between the ratings of positive satisfaction (i.e., very
satisfied versus somewhat satisfied) was statistically significant,
there was no indication of dissatisfaction among the majority of the
respondent population.

[]{#__RefHeading___Toc114975740 .anchor}Table 5.20 Level of Satisfaction
(AT in the Community)

  ----------------------------------- --------- -------- ---------- --------
                                      **RDD**            **List**   

  Very satisfied                      85        29%      339        62%

  Somewhat satisfied                  173       59%      173        32%

  Somewhat dissatisfied               23        8%       23         4%

  Very dissatisfied                   10        3%       10         2%
  ----------------------------------- --------- -------- ---------- --------

The next section of the questionnaire asked about help received during
the selection and purchase of the community AT device. Of the
respondents who used a device outside the home, 400 of 545 (73 percent)
list respondents and 116 of 153 (76 percent) RDD respondents said they
received no help from an agency or organization during the selection and
purchase of the services. Table 5.21 shows the frequencies and
percentages for satisfaction with advice received during the selection
and purchase of AT for use outside the home. As in previous examples,
there was a good correspondence between list and RDD samples.

[]{#__RefHeading___Toc114975741 .anchor}Table 5.21 Satisfaction With
Advice (AT in the Community)

  ----------------------------------- --------- -------- ---------- --------
                                      **RDD**            **List**   

  Very satisfied                      26        67%      110        76%

  Somewhat satisfied                  8         21%      26         18%

  Somewhat dissatisfied               3         8%       6          4%

  Very dissatisfied                   0         0%       3          2%
  ----------------------------------- --------- -------- ---------- --------

We asked whether there were additional AT devices that respondents would
use outside the home; 171 of 540 AT users in the list sample (32
percent) and 44 of 153 RDD AT users (29 percent) said there were. When
asked how much help additional AT outside the home would be, the
proportion of list sample respondents who answered "A lot" was about the
same as in the RDD sample (73 percent versus 76 percent).

We asked all respondents whether they had ever tried and failed to
obtain an assistive device. In the list sample, 137 of 980 (14 percent)
said "Yes." Of these 137, 87 came from the 548 (16 percent) who used
devices, and 50 came from the 454 (11 percent)\] who did not. In the RDD
sample, 31 of 406 (8 percent) had tried without success---18 from the
153 (12 percent) who used devices, and 13 (5 percent) from the 259 who
did not.

Next, we found that 477 (49 percent) of 980 list respondents and 184 (46
percent) of 402 RDD respondents said they were aware that they could get
help to obtain AT. They said they might seek help about the devices from
the agencies shown in table 5.22.

[]{#__RefHeading___Toc114975742 .anchor}Table 5.22 Sources of Help (AT
in the Community)

  --------------------------------------- --------- ------- ---------- -------
                                          **RDD**           **List**   

  Doctor, health care professional        115       52%     229        35%

  Vocational rehab center                 8         4%      44         7%

  Family/Friends/Neighbors                10        5%      48         7%

  Pamphlets, magazines                    9         4%      37         6%

  Center for independent living           10        5%      15         2%

  Tech assistance center                  5         2%      13         2%

  *Tech Act*/Other state organization     7         3%      17         3%

  TV/Radio                                0         0%      11         2%

  Yellow pages                            5         2%      18         3%

  Internet                                7         3%      51         8%

  Other                                   45        20%     164        25%
  --------------------------------------- --------- ------- ---------- -------

Thirty-eight percent (179 of 477) of list respondents and 35 percent of
RDD respondents (64 of 184) who were aware that they could get help
planned to contact an agency. None specified an agency that they planned
to contact.

### Summary

Analysis of AT use at home, in school, at work and in the community
showed that the community was the domain where most devices and
accommodations were used. There, 56 percent of the list sample
respondents and 38 percent of the RDD sample respondents reported using
some type of AT. The home was the second site of use by 54 percent of
the list sample respondents, and by 36 percent of the RDD sample. School
was reported as a place of use by 52 percent of the list respondents
(versus 15 percent of RDD respondents), and work by 38 percent of list
sample respondents (versus 34 percent of RDD sample respondents).

List sample respondents used AT at a significantly higher rate than RDD
sample respondents. For all four domains, information about AT was
obtained from medical and rehabilitation professionals in 50 to 75
percent of the cases. The doctor's office or the medical supply store
were the most frequently mentioned sources of supply, and self and
family were the most frequently mentioned sources of payment.

Satisfaction with the devices and with the help in obtaining AT
frequently exceeded 90 percent, with list respondents expressing higher
levels of satisfaction than RDD respondents. Persons in the RDD sample
who used or needed AT at work expressed the lowest levels of
satisfaction with AT, but were otherwise very satisfied with the help
they received selecting or buying AT. Failure to obtain AT-related help
or advice, depending on sample membership, was observed in 13 percent or
less of the cases.

There was also a strong reliance on conventional professional sources of
advice about, and supply of, AT. Altogether, centers of independent
living, *Tech Act* organizations and state-based technical assistance
agencies were mentioned as a source of information, help or advice in
less than 10 percent of the cases. In comparison, the Internet was
mentioned as a source of information in as many as 14 percent of the
cases, again depending on sample membership. Generally, however, list
respondents were more likely to use a wider variety of sources of
information, advice and help about AT than RDD respondents.

The differing patterns of use of AT in the two samples resulted from the
inclusion criteria that determined the composition of the list sample.
Compared to the general population represented in the RDD sample, higher
levels of AT use observed in the list sample appeared to have had a
substantial effect on such items as knowledge and awareness of AT. List
respondents were more informed about AT and interacted with AT-related
service providers to a greater extent. In the next chapter, we will
examine the effects that different patterns of AT knowledge and use had
on attitudes and opinions about AT-related services, policies and
legislation.

##  {#section .unnumbered}

## 6. Attitudes and Opinions About Assistive Technology-Related Services, Policies and Legislation

The purpose of this is to present the trends and developments since the
enactment of the *Tech Act*. General as well as specific questions about
the likely impact of this law and other related legislation were posed.
The purpose of the questions was to assess the extent to which the
various provisions of the *Tech Act*---raising awareness, aiding in the
selection and purchase of AT, and providing technology related
assistance---have influenced public attitudes and opinions about
AT-related services and policies. In the case of assistive
technology-related legislation, we expected that persons with
disabilities would have some knowledge about how lawmakers address their
needs for AT-related information and assistance. While we did not expect
the majority of respondents to know about specific laws, we nevertheless
expected that respondents would be able to identify sources of
information and help in case they needed technology-related assistance.
This presents the results of the 10 opinion questions.

Question 1: "Overall, how much information and advice have you received
about assistive technology? Would you say a lot, some, a little, or
none?"

As shown in figure 6.1, the two groups differed significantly in their
responses to this question. The modal response of the RDD sample was
"None," and the modal response for the list sample was "A little." The
least-used response for both samples was "A lot." In general, we could
characterize the response to this question as essentially negative
(i.e., that whatever information and advice they received was perceived
as minimal).

[]{#__RefHeading___Toc114975431
.anchor}![](media/image26.wmf){width="4.5in"
height="2.2847222222222223in"}Figure 6.1 Amount of Information Received
About AT

### 

Question 2: "Overall, how much information and advice have you received
about how to obtain it? Would you say a lot, some, a little, or none?"

For this question, there was no significant difference between the two
samples. The modal response was "None," and the median was "A little."
Figure 6.2 shows that compared to the response given to question 1, the
population was even more negative. The implication here is that, while
there was a general lack of information about assistive technology,
there was less information available about how to obtain it than there
was about assistive technology in general.

[]{#__RefHeading___Toc114975432
.anchor}![](media/image27.wmf){width="4.75in"
height="2.2847222222222223in"}Figure 6.2 Amount of Information About How
to Obtain AT

Question 3: "Overall, how much difference would you say that the
information and advice about assistive technology and how to obtain it
has made in increasing your level of learning, independence,
productivity and community integration?"

This result was much more positive. There was no significant difference
between the two samples, although the trend has been established that
the respondents in the RDD sample were somewhat more negative than those
in the list sample. The modal and median response was "Some," indicating
that the central tendency was closer to "A lot" than "None."

[]{#__RefHeading___Toc114975433
.anchor}![](media/image28.wmf){width="4.0in"
height="2.167361111111111in"}Figure 6.3 Impact of Information About AT

Considered in the light of the previous two responses, we have an
indication that the perception of the respondents was that the
information and advice they *did* receive about assistive devices and
how to obtain them was worthwhile. However, we must be cautious in our
interpretation: it could well be that the respondents were getting some
information and advice that they judged to be inadequate, and hence not,
in the literal sense, information at all.

The fact is, we have determined that all respondents who used AT gave
some answer to the question: "Where did you learn about the device?" If
the respondents learned about the device, it could be argued that they
received information about it, and in that case, the answer "None" to
either of the first two questions would be invalid. A more reasonable
interpretation is, as stated above, that the respondents were judging
the utility of the information and advice that they had received over
and above some putative baseline.

Question 4: "Overall, how much has information and advice about
assistive technology and how to obtain it helped you to become more
aware of your rights?"

The results here were very similar to those for the previous question,
with the mode and median again residing the in response "Some." There
was no significant difference in the responses given by the two samples.
The only unusual aspect of the responses to this question, compared to
the preceding three, was that the two samples were almost equally
positive, and for the first time, a proportionally smaller group of
respondents from the RDD sample answered "None" as compared to the
respondents from the list sample.

[]{#__RefHeading___Toc114975434
.anchor}![](media/image29.wmf){width="4.0in"
height="2.198611111111111in"}Figure 6.4 Awareness Raised Through
Information About AT

Question 5: "How much has your use of AT devices and services decreased
your need for help from another person?"

One-hundred twenty-two respondents (12 percent) from the list sample and
68 (17 percent) from the RDD sample reported that they used no AT device
or service. Almost as many said "None" as the modal response of "A lot."
It is unclear from these results whether those who answered "None" meant
that they did not need assistance from another person even without the
device, or that at least part of their disability was not ameliorated by
AT (which could be the case for the respondents who do not use AT as
well).

[]{#__RefHeading___Toc114975435
.anchor}![](media/image30.wmf){width="4.0in"
height="2.232638888888889in"}Figure 6.5 AT Use and Decreased Need for
Personal Assistance

Question 6: "To what extent have better-designed products and
environmental access features or universal design products reduced your
need for AT devices and services?"

Respondents here stated clearly that improved design was a factor that
reduced their reliance on assistive technology devices and services. The
significant difference here---again, the RDD respondents were more
negative in their responses to this question---can be interpreted as a
reflection of the fact that RDD respondents, as a group, appeared to be
less severely impaired than those from the list; and consequently, they
perceived themselves as less "needy" than the others. Thus, the
"reduction in need" is likely to be smaller for them than for the
respondents from the list sample.

[]{#__RefHeading___Toc114975436
.anchor}![](media/image31.wmf){width="4.5in"
height="2.2180555555555554in"}Figure 6.6 Impact of Better Designed
Environmental Access Features

Question 7: "Compared to 10 years ago, people are more aware of the need
for assistive technology devices and services for persons with
disabilities. Would you say that you strongly agree, agree, disagree, or
strongly disagree?"

The response to this question leaves little doubt that public awareness
of the need for AT is greater now than 10 years ago. The difference
between the two samples occurred in the level of agreement, but both
groups were overwhelmingly positive in their response to this question.

[]{#__RefHeading___Toc114975437
.anchor}![](media/image32.wmf){width="4.5in"
height="2.3409722222222222in"}Figure 6.7 Increased Awareness of Need for
AT

Question 8: "Compared to 10 years ago, laws or program policies have
been changed to help persons with disabilities to get assistive
technology. Would you say that you strongly agree, agree, disagree, or
strongly disagree?"

Similar to question 7, the mode and median response was an overwhelming
agreement. The difference between the two samples did not reach
statistical significance.

[]{#__RefHeading___Toc114975438
.anchor}![](media/image33.wmf){width="4.75in"
height="2.432638888888889in"}Figure 6.8 Systems' Changes Helped to Get
AT

Question 9: "Compared to 10 years ago, more people are aware of
assistive technology and understand how it can benefit persons with
disabilities. Would you say that you strongly agree, agree, disagree, or
strongly disagree?"

Question nine had virtually the same result as the previous two
questions. The respondents asserted that the public is more aware of how
AT can help them. The difference between the two samples in the
respondents' responses here was similar to what occurred in question 7
(i.e., the response of both samples was positive, but there were more
extreme positives, proportionally, among the list respondents than the
RDD respondents).

[]{#__RefHeading___Toc114975439
.anchor}![](media/image34.wmf){width="4.5in"
height="2.3916666666666666in"}Figure 6.9 Increased Awareness About AT

Question 10: "Compared to 10 years ago, it is easier to find assistance
for purchasing assistive technology devices and services. Would you say
that you strongly agree, agree, disagree, or strongly disagree?"

This question received a less positive result than the three preceding
questions. The level of disagreement was higher here. We note the
similarity of this item to question 2. Given the general level of
agreement to questions 7, 8 and 9, the more negative response here was
consistent with the opinion expressed in question 2 that there was
little information and advice available about purchasing AT.

[]{#__RefHeading___Toc114975440
.anchor}![](media/image35.wmf){width="4.5in" height="2.41875in"}Figure
6.10 Availability of Technical Assistance

### Summary 

The respondents generally felt that there was little or no information
given to them about AT and less about how to obtain it, but that the
information that they did receive was generally helpful and made them
more aware of their rights.

Respondents also stated that their use of AT did not generally reduce
their independence on help from another person, but that improved design
in products and improved environmental access had reduced their reliance
on AT.

Compared to 10 years ago, the respondents were very largely in agreement
with the statements that people are more aware of the need for AT, that
they understand AT, that laws have changed, and that it is easier to get
assistance in obtaining AT. In all cases, the responses of the persons
who were using AT were more positive than those of the non-AT users.

Overall, the differences between the two samples on the opinion
questions were more a matter of degree than direction. The mean
difference---where the two samples were significantly different---was
one-tenth of a scale point, and did not meet the level of power
necessary for meaningful distinction.

## 7. Assistive Technology Use and Personal Assistance Services

Until recently, research in the area of assistive technology and
personal assistance services (PAS) had been largely clinically oriented,
pertaining to specific devices and assessments of their ability to meet
physiological long-term care needs (Agree, 1994; Batavia & DeJong,
1990). However, assistive technologies---especially those that could
substitute for human assistance---have also been recognized for their
potential to reduce the costs of personal assistance services (Mann,
Hurren, Tomita, & Charvat, 1995a, 1995b; Agree, 2000; Hoenig, Taylor, &
Sloan, 2003). They hold out the promise of making persons with
disabilities more independent by reducing their reliance on other
persons.

Kennedy, LaPlante, & Kaye (1997) studied data from the 1991--92 Survey
of Income Program Participation (SIPP) and found that 3.7 million
persons aged 15 and over, or about 1.9 percent of the U. S. population
needed assistance with at least one ADL---in most cases bathing. Most of
these services were provided by family members. Paid help was used in
less than 10 percent of the cases. McNeil (2001) estimated that at the
end of the decade, the number of persons in need for personal assistance
services had grown to 10.1 million persons, or 3.8 percent of the U.S.
population, with 4.1 million of this figure being represented by persons
aged 65 and over. With the rapid aging of the population, this figure is
expected to grow rapidly, and so is the demand for personal care
services and the cost of care.

Ken Manton and his colleagues at Duke University explored the question
of substitutability of technology for human help. Their findings
indicated that the use of assistive technology was growing and that some
substitution of technology for human assistance had been taking place
(Manton et al., 1993). Agree (1994) suggests that the use of assistive
technology by older persons tends more often to supplement, rather than
substitute, human assistance. However, while there can be some
substitution, PAS and assistive technology are complementary and needed.
Consumers need access to assistive technology and flexibility in
combining AT with PAS. In this chapter, we will explore the extent to
which persons with disabilities consider AT a complement or a substitute
to personal assistance services, and how personal characteristics and
needs may have shaped these views.

### Findings

In the survey, potential respondents were screened to determine who
among the residents of a household used a personal assistant. The
screener began with the general question: "Does anyone in your household
who is over age 18 use or need any of the following special equipment to
perform daily tasks and activities in the home, at school, at work or in
the community?" After asking about the use of a wheelchair, a special
bed or telephone, the informant was given the alternative "... The
assistance of another person?" and "Who is that?"

Over the entire sample, 34.9 percent (494 of 1414) said that they used a
personal assistant to perform daily tasks. However, this screening
question produced different results from the list and RDD samples. Only
18.4 percent of the RDD sample used a personal assistant, compared with
41.7 percent of the list sample. In this chapter, we will report the
results separately for both samples. The chart below shows the
relationship between use of PAS and use of AT.

[]{#__RefHeading___Toc114975441
.anchor}![](media/image36.wmf){width="4.5in"
height="2.8979166666666667in"}Figure 7.1 Use of AT and Personal
Assistance Services

In figure 7.1, the x-axis has four categories: those who used AT and
those who did not from the two samples. For both samples, respondents
who used AT were about twice as likely to use PAS as those who did not
(i.e., that the relative use of AT for the two samples shows the same
pattern, although a higher percentage of respondents in the list sample
use PAS).

A similar pattern emerged when we considered the severity of the
impairment. As might be expected, the use of PAS increased as the
severity of the impairment increased in each sample.

![](media/image37.wmf){width="4.75in"
height="2.651388888888889in"}**Figure 7.2 Use of Personal Assistance and
Severity of Impairment**

Again, the pattern within the two samples was similar with regard to the
race of the respondents: in both RDD and list samples, slightly more PAS
users were nonwhite than white.

[]{#__RefHeading___Toc114975442
.anchor}![](media/image38.wmf){width="4.5in"
height="2.6527777777777777in"}Figure 7.3 Use of Personal Assistance and
Race

The nonwhite to white ratio for the RDD sample was 1.16:1, versus 1.20:1
for the list sample. The difference between whites and nonwhites was not
significant in both samples.

The level of education showed only a very slight relationship to the use
of PAS among the respondents. The direction of the effect was that the
higher the level of education, the lower the incidence of PAS use.

[]{#__RefHeading___Toc114975443
.anchor}![](media/image39.wmf){width="4.5in"
height="2.6972222222222224in"}Figure 7.4 Use of Personal Assistance and
Education

Taken together with the strong relationship between level of education
and AT use, a relationship that occurred in the opposite direction, we
can say that the use of a personal assistant was indicative of a
particular combination of impairments different from those associated
with respondents who used AT.

An exhaustive compilation of respondent conditions revealed that there
were some significant differences in the impairments of those who did
and did not use the help of another person. PAS users listed four
conditions---stroke, nervous system disorders, soft-tissue disorders and
rheumatoid arthritis---among the 10 most frequent conditions that did
not appear in the top 10 for nonusers. Nonusers reported hearing loss,
back disorders, orthopedic impairments of the lower extremities and
unspecified mobility problems that did not appear in the users' top 10
conditions. Six conditions---osteoarthritis, multiple sclerosis, chronic
injuries, heart disease and diabetes, and unknown, unspecified
conditions---were among the most frequent impairments for both users and
nonusers of PAS.

Further, PAS users were more than twice as likely to have had multiple
sclerosis or stroke as nonusers; all but one of the 16 quadriplegics in
the sample required a personal assistant; at the other end of the
spectrum, only about 10 percent of persons with some hearing loss less
than deafness used a personal assistant.

[]{#__RefHeading___Toc114975444
.anchor}![](media/image40.wmf){width="4.5in"
height="2.623611111111111in"}Figure 7.5 Use of Personal Assistance and
Family Income

With regard to income, there was a slight tendency for more use of a PAS
with lower family income, but a very pronounced tendency, in the same
direction, for personal income---most likely an indication that
respondents who needed PAS were generally too disabled to work.

The data support this hypothesis (see figure 7.6). Respondents who did
not need a personal assistant were more than twice as likely to be
employed as those who did (26.2 percent versus 10.3 percent), and were
more likely to count themselves able to work but unemployed (7.6 percent
versus 4.3 percent). But the most dramatic statistic was that almost
two-thirds of persons who needed to have the assistance of another
person (64.4 percent) said they were so disabled that they were unable
to work, versus 38.3 percent of the respondents who did not need the
assistance of another person.

[]{#__RefHeading___Toc114975445
.anchor}![](media/image41.wmf){width="4.5in"
height="2.3881944444444443in"}Figure 7.6 Use of Personal Assistance and
Personal Income Level

Figure 7.7 illustrates the distribution of persons who used the
assistance of another person within age categories.

[]{#__RefHeading___Toc114975446
.anchor}![](media/image42.wmf){width="5.5in"
height="3.134027777777778in"}Figure 7.7 Percent Within Age Groups Using
Personal Assistance\
RDD vs. List Sample Respondents

The linear trend lines show that, in the list sample, use of PAS
decreased with increasing age, while the trend was in the opposite
direction for the RDD sample. Among the youngest RDD respondents, only
about one in 10 used PAS, compared to more than half of the youngest
list respondents. As stated earlier, personal assistance was the one
variable in which there was a systematic difference between the two
samples.

[]{#__RefHeading___Toc114975447
.anchor}![](media/image43.wmf){width="5.5in"
height="3.170138888888889in"}Figure 7.8 Percent Within Age Groups, All
Respondents\
RDD vs. List Sample Respondents

It is instructive to note the distribution of all respondents plotted as
an identical chart in figure 7.8. Note that the R^2^ figures for the
overall distribution are close to zero, indicating no linearity to speak
of, and are virtually identical.

### Summary

For purposes of this study, persons who used the assistance of another
person to conduct daily activities were considered a subset of the
population of persons with a disability. They differed from other
persons with a disability in the following ways:

-   They were more likely to use some form of assistive technology;

-   They were more severely impaired;

-   Their level of personal income was much lower; and

-   They were much less likely to be employed.

There were no significant differences in race, level of education or
age, with the exception that the RDD sample respondents were slightly
more likely to use PAS with increasing age. The type of impairment
(e.g., paralysis resulting from stroke, central nervous system disorders
and rheumatoid arthritis) was associated with a higher likelihood of
using PAS. With reference to our discussion of the substitutability of
assistive technology for personal assistance services, we were not able
to provide conclusive evidence that AT can substantially reduce the need
for PAS; persons with severe disabilities need both.

## 8. Assistive Technology Use and Community Integration

In the context of this study, community integration refers to a person's
active involvement in all aspects of daily living. This includes social
contacts with family, friends or strangers; the ability to move around
(e.g., to go shopping, to go to school, work or the doctor's office; and
in other ways independently, spontaneously and with the least
constraints participate in activities and events). Community integration
means that the person does not live in an institution, that the freedom
to choose is not unnecessarily restricted, and that with technological
or personal assistance the person would be able to live as independently
as circumstances permit.

Over the past decades, a significant number of community-based
organizations and independent living centers (ILCs) emerged that, with
funds authorized in the *Rehabilitation Act*, help persons with
disabilities with housing, schooling, work, technology and legal
questions (National Council on Independent Living, 2003). However, large
parts of the country remain underserved, and persons with disabilities
continue to face problems with unemployment, lack of adequate education
and training opportunities, lack of access to technology, and inadequate
housing and transportation. As a result, persons with disabilities
participate less in social events and feel less integrated into the
community than persons without disabilities.

### Participation in Social Activities Outside the Home

The survey contained one diagnostic item to characterize the degree to
which the respondent was likely to be involved in community activities.
We asked each respondent, "How many days in the last two weeks did you
participate in social activities outside your home such as visiting
friends and family, going to a restaurant or movie, or going to church?"
The respondent's answers were coded from 1 to 6, with one being zero
days out of the house, and 6 being out every day in the past two weeks.
Figure 8.1 shows how respondents answered.

[]{#__RefHeading___Toc114975448
.anchor}![](media/image44.wmf){width="5.5in"
height="2.904861111111111in"}Figure 8.1 Days Out of the Home 14 Days
Prior to Interview

Overall, 86 percent of respondents spent every other day at home.
Fifty-seven percent of the respondents spent at least 10 days out of the
14 without leaving their homes, 16.5 percent were completely homebound,
and 10 percent were out every day. While comparable figures for the
nondisabled population are not available, we can assume that what we
found was a barrier to community integration among persons with
disabilities. The relationship between AT use and being homebound is
shown in figure 8.2.

[]{#__RefHeading___Toc114975449
.anchor}![](media/image45.wmf){width="6.0in"
height="2.535416666666667in"}Figure 8.2 AT Use and Number of Days Spent
Out of the Home

The linear regression between AT use and days out of the home is -.87;
that is, the more days that the respondent ventured out of the home, the
less likely she used AT. Figure 8.3 illustrates how the AT users differ
from nonusers with respect to venturing outside the home.

[]{#__RefHeading___Toc114975450
.anchor}![](media/image46.wmf){width="5.25in"
height="2.854861111111111in"}Figure 8.3 Days Out of the Home and AT Use

The trend lines illustrate that AT users were less integrated into the
community than those who did not use AT. For the three lowest categories
that relate to going out of the home, there was a greater likelihood
that the respondent would be an AT user than not; the reverse was true
for those who got out of the home more than four days out of 14.

Figure 8.4 illustrates the relationship between the severity of the
condition, the use of AT, and the propensity of persons with
disabilities to leave the home.

[]{#__RefHeading___Toc114975451
.anchor}![](media/image47.wmf){width="5.75in" height="2.95625in"}Figure
8.4 Leaving Home, Level of Impairment and AT Use

The respondents who did not use AT were, across the board, more mobile.
If we compare the levels of extra-home mobility (i.e., the average
number of days a person spent out of the home) within severity levels
for those using AT with those who did not use AT at all, we see that
severely impaired AT users were highly mobile, but nonusers were among
the least severely impaired. It seems counterintuitive---we expect that
AT will be most helpful to those with the most severe conditions. This
could be an artifact of the way the respondent conditions were assigned
levels of severity. But perhaps it is more heuristically valuable to
consider that persons with mild impairments that do not hinder mobility
are far less likely to use AT.

An examination of the issue of race and being homebound, by dividing the
sample into whites versus nonwhites, showed that race in and of itself
is not a meaningful factor in community integration. Figure 8.5 shows
considerable overlap between the races and the pattern is essentially
the same.

[]{#__RefHeading___Toc114975452
.anchor}![](media/image48.wmf){width="4.25in" height="2.73125in"}Figure
8.5 Race and Days Out of the Home

However, the data supported an interaction effect among age, race and
disability in the respondent population. As shown in table 8.1\*, the
likelihood of finding a nonwhite person with a disability decreased with
each increasing age category. The Pearson Correlation Coefficient of
White Percentage and Age is +.92, R^2^ = .85, which was a statistically
significant result \[t= 5.9, p\<.01\].

[]{#__RefHeading___Toc114975743 .anchor}Table 8.1 Race, Age and
Disability

  -------------- -------------- -------------- -------------- --------------
  Age Range      Total          White          Nonwhite       White %

  18-25          42             30             12             71

  26-35          85             68             17             80

  36-45          189            160            29             85

  46-55          334            283            51             85

  56-65          308            263            45             85

  66-75          269            240            29             89

  76-85          124            107            17             86

  \>85           55             53             2              96

  Total          1,406          1,204          202            

  *\*Eight                                                    
  respondents                                                 
  did not                                                     
  identify                                                    
  themselves by                                               
  race.*                                                      
  -------------- -------------- -------------- -------------- --------------

Application of the age and race breakdown to the number of days out of
the home showed an interesting pattern. Figure 8.6 illustrates the
three-way interaction by computing the percentage of whites and
nonwhites in each age category who were below the median in number of
days that they left the home.

[]{#__RefHeading___Toc114975453
.anchor}![](media/image49.wmf){width="5.5in"
height="2.5618055555555554in"}Figure 8.6 Proportion of Respondents Below
Median in Number of Days Out of the Home, by Race and Age

Note that for all but the 36--45 year-old age range, nonwhites were more
likely to be below the median for extra-home mobility than whites.
However, the overall average number of days out of the home was not
significantly different for nonwhites (scale value of 3.2) as compared
to whites (scale value of 3.3).

Men were slightly, but significantly, more mobile than women, and as
figure 8.7 shows, the difference was consistent over age groups.

[]{#__RefHeading___Toc114975454
.anchor}![](media/image50.wmf){width="5.75in"
height="2.2395833333333335in"}Figure 8.7 Proportion of Respondents Below
Median in Number of Days Out of the Home, by Gender and Age

Only in the 76--85 year-old group were women who were more able to get
out of the house than were men. Personal income was also a significant
factor.

[]{#__RefHeading___Toc114975455
.anchor}![](media/image51.wmf){width="5.5in"
height="3.0194444444444444in"}Figure 8.8 Respondent Level of Personal
Income and Days Out of the Home

Figure 8.8 shows the divergent pattern for high- and low-income
respondents (high- and low-income being relative terms, defined as above
and below the median personal incomes for the sample). For those below
the median in personal income, there was a clear tendency toward
decreased frequency of leaving the home, versus a slightly reversed
trend for those above the median in personal income. Note that the
linear trendline for the low-income group is steeper than the line for
the high income group (as well as pointing in the opposite direction).
Simply stated, under-average earners were more than twice as likely to
be homebound than those whose income was above average.

#### Mobility and Opinions About Assistive Technology

There was no relationship between an individual's history of leaving the
home and any of the 10 opinion questions posed in the survey. This was
almost certainly a direct function of the extremely high response
concordance to the opinion questions.

#### Education

As shown in figure 8.9, the level of education, again split on the
median, had virtually no effect on community integration. That is, there
was virtually no difference between the two plotted trend lines.
Education was evidently not a factor in leaving the home.

[]{#__RefHeading___Toc114975456
.anchor}![](media/image52.wmf){width="6.0in"
height="2.970138888888889in"}Figure 8.9 Respondent Level of Education
and Days Out of the Home

#### Barriers to Access

While the frequency of leaving one's home provided a partial insight
into a person's level of community integration, for persons with
disabilities, one must assess the impact of the barriers to use and
access once the person has ventured out. To address this issue, we asked
a series of questions about access and modifications to the environments
of all respondents.

-   To the question---"People who have physical impairments or health
    problems sometimes need assistance in obtaining access to all the
    places they need to go and to facilities and equipment they need to
    use. Do you need the help of another person to access or use public
    buildings and facilities such as libraries, government buildings,
    public transportation, restaurants, theaters, stores and shopping
    malls?"---444 respondents (31.5 percent) answered "Yes," and 964
    respondents (68.5 percent) answered "No."

-   435 respondents (30.9 percent) needed special modifications,
    adaptations or accommodations to enter or use public buildings and
    facilities, while 975 respondents (69.1 percent) did not.

-   When asked if there are special modifications, adaptations or
    accommodations to enable persons with disabilities to enter and use
    public buildings and facilities, 870 respondents (62.9 percent)
    answered "Yes," and 513 persons (37.1 percent) answered "No."

-   To the question---"Do you have access to public buildings and
    facilities?"---1,358 respondents (96.3 percent) answered "Yes," and
    52 respondents (3.7 percent) answered "No."

The overall picture indicated that persons with disabilities generally
did have access to public buildings and facilities, albeit with the
assistance of others or with special modifications in many cases. The
stated need for assistance or modifications had only a minor effect on
accessibility.

The findings presented on page 113 applied only to those individuals who
were not homebound and applied only to access to public buildings and
facilities. Similar questions were posed to all respondents regarding
school, work and home environments.

[]{#__RefHeading___Toc114975744 .anchor}Table 8.2 Need for Personal
Assistance and Environment Modifications

  --------- ---------------- --------------- --------------- ---------------
            **Assistance**   Modifications   **Mods          Have Access
                                             Available**     

  School    22.6%            17.0%           66.7%           95.7%

  Work      12.2%            11.3%           69.1%           96.2%

  Home      23.6%            20.6%           23.6%           95.4%

  Public    31.5%            30.9%           62.9%           96.3%
  --------- ---------------- --------------- --------------- ---------------

As might be expected, respondents who were gainfully employed or running
a business were significantly lower in their need for assistance and
modifications. Also note that in answer to the question, "Are there
special modifications ... available at home?" 23.6 percent answered
"Yes," the lowest percentage by far of any of the four domains, as shown
in table 8.2. It should be noted that of the respondents who needed
modifications in the home, 66 percent say they were available; in other
words, of the 23.6 percent of respondents who said their homes had
special modifications, 58 percent were respondents who said they needed
such modifications.

Table 8.3 shows the need for modifications and the availability of those
modifications for those who stated a need, broken down by occupational
status.

[]{#__RefHeading___Toc114975745 .anchor}Table 8.3 Need for Environmental
Modifications and Major Activity

  ---------------------- ----------------- ----------------- ------------ ------------
                         **Need            **Modifications   **Total**    **Percent of
                         Modifications**   Available If                   Total**
                                           Needed**                       

  **Overall**            **40%**           **85%**           **1,415**    **100**

  In School              38%               84%               50           4

  Working                24%               83%               292          21

  Able to work,          23%               90%               91           6
  unemployed                                                              

  Unable to work         53%               85%               671          47

  Homemaker              23%               81%               69           5

  Retired                32%               88%               229          16

  Other                  38%               80%               13           1
  ---------------------- ----------------- ----------------- ------------ ------------

An individual who expressed a need for modifications in any of the four
domains was counted as a positive instance. For example, 24 percent of
working respondents expressed a need for modifications in general, while
the previous table showed 12 percent of respondents expressing a need
for modifications in the workplace*.*

By far, the highest need for modifications to improve accessibility is
in the group who were unable to work because of their disability, while
the lowest percentage occurred in the working and homemaker groups.
Overall, 85 percent of persons needing modifications had them available,
while 15 percent did not have them.

### Summary

Analyses showed that persons with disabilities experienced varying
levels of community integration and access to places in the community.
The type of health condition, level of impairment and disability, as
well as factors such as age, use of technology and personal assistance,
can determine a person's likelihood to leave the home and participate in
social and community events. For instance, while we observed a general
tendency among AT users to go out less often, those with severe mobility
impairments using mobility technology were able to leave the house at
frequent intervals.

We also found that persons with lower incomes and women were less likely
to leave the home. However, levels of education had no effect on one's
propensity to participate in activities outside the home.

We explored the extent to which a lack of environmental access features
and environmental accommodations prevent persons with disabilities to go
out into the community. We found that substantially more access features
and environmental accommodations were available in the community than in
the home. This confirms earlier observations that the need for AT in the
home was greatest among the severely disabled and the unemployed.

# Part III: In-Depth Analyses

## 9. Severity of Impairment and Assistive Technology Use and Need

The research presented in this draws some tentative conclusions about
the relation between the severity of the impairment and AT use and need,
based on a person's self-reported health conditions. The proposed rating
method can be employed to show why and where AT is likely to be used or
needed, and how AT can improve a person's ability to perform daily tasks
and activities.

The level of impairment is an important correlate and predictor of
disability and is significantly related to levels of education, income,
independence and quality of life (Barbotte, Guillemin, & Chau, 2001).
High levels of impairment are frequently associated with lower levels of
education and income (Russell et al., 1997; Kaye, Kang, & LaPlante,
2000), and increased dependence on the help of others (Carlson, Ehrlich,
Berland, & Bailey, 2002a, 2002b, 2002c). While there are numerous
examples of severely impaired persons who pursued successful careers or
reported relatively high levels of quality of life (Albrecht &
Devlieger, 1999), in a large number of cases, basic functioning is
maintained only with mechanical or personal assistance (LaPlante,
Hendershot, & Moss, 1992).

Most of our current disability assessment, disability measurement and
disability survey research is based on models that associate physical
and emotional illnesses, injuries or disorders with a person's reduced
ability to perform a range of daily tasks and activities that are
frequently grouped under activities of daily living (ADLs) such as
dressing, walking or self-care, and instrumental activities of daily
living (IADLs) that include shopping or money management (LaPlante &
Carlson, 1996; Pope & Tarlov, 1991; Brandt & Pope, 1997).

The severity of the disease or disorder is related to the level of
impairment primarily by the presence of disease-specific symptoms or
characteristics. Co-morbidities, or secondary conditions, often add to
levels of impairment. Furthermore, certain types of injuries, illnesses
and disorders are frequently associated with higher levels of impairment
than others (Social Security Administration, 2002). For example, the
loss of a leg may be associated with higher levels of impairment than
the loss of a finger or a toe; multiple sclerosis may be considered more
severely impairing than chronic back pain; or schizophrenia may be
viewed to be more disabling than mild anxiety. While these ranking
methods may not be as specific as clinical diagnoses and
assessments---and while there may be differences in judgment and opinion
between clinicians and non-clinicians---these ordering preferences
indicate probabilities that can be used for descriptive purposes,
formulation of hypotheses and statistical analyses.

Depending on the purpose of a study, disability and rehabilitation
researchers can draw from a variety of models and definitions for the
measurement of severity of impairment and disability (Murray, 1994;
Albrecht, Seelman, & Bury, 2001; World Health Organization; 2001). While
this is not an exhaustive list, the most common approaches for
determining levels of impairment and disability are based on:

1.  The clinical model;

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```
11. The bio-psycho-social and ecological model;

12. The public health or epidemiological model;

13. The disability services and benefits entitlement model; and

14. The statistical or probabilistic model.

The clinical or medical model rests on the premise that the evaluation
of impairments requires a complete medical examination that includes an
accurate and objective measure of function. Such evaluations play a key
role in the treatment and rehabilitation process, but they frequently
are narrow in scope. Medical diagnoses and assessments provide important
information to persons with disabilities, their families and caregivers
as well as researchers and practitioners, and have led to such
impairment measures as the Functional Independence Measure or FIM
(Deutsch, Braun, & Granger, 1997).

The bio-psycho-social and ecological model, sometimes referred to as the
new model for the enabling process or the new paradigm of disability,
takes into account the complete person and his or her environment
(Brandt & Pope, 1997). According to this model, adverse manifestations
of injury, illness or impairment can be mitigated by psychosocial,
environmental or technological interventions. As a result of such
interventions, levels of impairment can be reduced or accommodated in
ways that are perceived as less restricting. Because of the complexity
of this model, it is difficult to determine what interventions are most
appropriate, given limited financial resources. It is also difficult to
assess the multiplicity of factors associated with impairment and
disability and their interaction in research.

The public health or epidemiological model is used for surveillance
purposes and to study the impact of disability incidence and prevalence
on broad societal indices such as health care costs, lost productivity,
or burden of disease measures (Murray & Lopez, 1996; Nord, 1992).
Severity of illness and impairment are major indicators for estimating
unemployment, health service use, or other adverse effects of reduced
participation due to disability on economy and society.

The disability services and benefits entitlement model defines levels of
impairment in a context of benefits providers and payers of services
determining eligibility and the disbursement of benefits based on
stringent medical and administrative criteria of severity (Wunderlich,
Rice, & Amado, 2002). For instance, in case of the Social Security
Administration, a listing of impairments, also known as "the Blue Book"
contains a description of severe health conditions and guidelines for
clinicians to diagnose and evaluate them (Social Security
Administration, 2002). In essence, this model is the strict application
of medical principles and practices followed by an administrative
review.

The statistical or probabilistic model is analogous to the public health
model in that it is concerned with measuring levels of impairment in
population samples, but it expands the public health model by using more
advanced statistical concepts[^10]. Typically, one begins with an
ordinal scale of severity of impairment, then imputes rank-order
relationships, and finally uses statistical models to validate them. The
statistical model is most useful when there is limited information about
the level of impairment among self-reported health conditions, and other
indicators of impairment, such as the reported inability to walk or
work, have to be considered in the rating process.

As this brief discussion has shown, all of the models have limitations.
Since our study did not include independent clinical diagnoses and
evaluations, and only a few systematic questions about levels of
functioning and impairment had been asked primarily for screening
purposes, we employed the statistical model to evaluate the level of
impairment of each respondent, thereby allowing us to quantify severity
of impairment at the ordinal level of scaling, taking into account both
the nature of specific conditions and co-morbidities. The construction
of even a simple scale of severity of impairment permitted us to
identify factors that are significantly related, but the extent to which
each relationship can be quantified is limited.

### Findings

Level of impairment was coded on a three-point scale of severity of
disability. The three levels were labeled mild, moderate and severe
disability. The coding was accomplished in the following manner: each
respondent was asked this open-ended question early on: "What condition
or limitation do you have that impairs your functioning?" We recorded up
to three conditions for each respondent. The final classification was a
simple addition of all respondent conditions, yielding a distribution of
862 respondents classified as mildly disabled (total disability score
\<3), 227 moderate (total disability score = 3) and 327 classified as
severe (total disability score \>3). The use of an arithmetic ranking
system, rather than an intuitive case-by-case analysis, is in line with
the research of Dawes (1988) and Meehl (1954), who have established
that, over a period of almost 50 years, there has yet to be a study
which has shown a superiority of clinical over statistical validity in
classification or predictive schemes.

Our first calculations showed that the more severely impaired
respondents used more AT (figure 9.1).

[]{#__RefHeading___Toc114975457
.anchor}![](media/image53.wmf){width="4.25in" height="2.55in"}Figure 9.1
AT Used by Respondents, by Severity of Impairment

We asked respondents about their use of AT in four domains: at school
and at work---getting to and at both locations---at home and in the
community. The only domain which all respondents identified was the
home. There, 49 percent of all respondents used assistive technology.
Within the group of mildly impaired respondents, 44 percent were likely
to use AT, followed by moderately impaired respondents who used AT in 54
percent of the cases. Within the group of severely impaired persons, AT
was used in 59 percent of the cases.

The influence of severity on the perceived need for additional AT was
more complicated. The greatest unmet needs occurred among the moderately
impaired in the home, while the smallest unmet need for AT occurred
among the severely impaired expressed in the workplace (see figure 9.2).

[]{#__RefHeading___Toc114975458
.anchor}![](media/image54.wmf){width="5.25in"
height="3.5854166666666667in"}Figure 9.2 Unmet Need for AT, by Severity
of Impairment and Domain of Living

A likely explanation is that respondents who were severely impaired were
not only less likely to be gainfully employed, but also, when they were
working, were more likely to already employ AT than the other, less
severely impaired respondents. However, when we multiplied the
percentage of respondents having each level of severity in the workplace
by the percent of each using AT in the workplace, we found that the
joint probability of AT use and workplace participation was lowest for
the severely impaired, and highest for those with mild levels of
impairment. This suggests that the bulk of AT use in the workplace
occurred among the less severely impaired. The severely disabled who
would benefit most from AT at work were least likely to be employed, or
if employed, least likely to obtain needed AT. This can also be
confirmed by our general observation that the more severely impaired
respondents were more likely to express a need for more AT (see figure
9.3).

[]{#__RefHeading___Toc114975459
.anchor}![](media/image55.wmf){width="3.35in"
height="1.9048611111111111in"}Figure 9.3 Expressed Need for More AT

Table 9.1 illustrates the use of AT in the home by level of severity.
Persons with the highest levels of mobility impairment, for instance,
were most likely to use a wheelchair, whereas persons with moderate
mobility impairments were most likely to use canes, walking sticks or
walkers. Persons using hearing aids were likely to be rated mildly
impaired.

[]{#__RefHeading___Toc114975746 .anchor}Table 9.1 Type of Devices Used,
by Level of Impairment

  ----------------------------------- ------------ -------------- ---------- -------------
  **Device**                          **Severe**   **Moderate**   **Mild**   **Overall**

  Cane or walking stick               19%          29%            13%        17%

  Manual Wheelchair                   23%          15%            10%        13%

  Walker                              10%          11%            8%         9%

  Hearing aid                         4%           2%             6%         5%

  Bathroom modifications              4%           4%             1%         2%

  Other in-home devices               5%           3%             2%         2%

  Stool, seat or chair for bathing or 5%           3%             1%         2%
  showering                                                                  

  Other personal use                  1%           3%             2%         2%

  Crutch                              1%           2%             2%         1%

  Oxygen tank                         2%           0%             2%         1%
  ----------------------------------- ------------ -------------- ---------- -------------

Severity ratios were an alternative method of conceptualizing the
relationship between the level of disability and various other factors,
because in cases where there were many levels of the independent
variable, the use of the severity ratio was graphically more compelling
than would be similar data presented in traditional form.

[]{#__RefHeading___Toc114975460
.anchor}![](media/image56.wmf){width="5.5in"
height="2.8291666666666666in"}Figure 9.4 Level of Educational Attainment
and Severity of Impairment

As an example, consider the question of level of disability and highest
level of education attained by the respondent. Figure 9.4 is a
traditional bar chart showing the education level as a function of the
level of disability. Figure 9.5 shows the same data displayed as a
severity ratio.

[]{#__RefHeading___Toc114975461
.anchor}![](media/image57.wmf){width="4.5in"
height="2.2916666666666665in"}Figure 9.5 Severity of Impairment and
Level of Educational Attainment

Using the simpler chart (figure 9.5), we can see that while the effect
is roughly monotonic, only the least educated had a severity ratio of
greater than one, which accounted for most of the covariance between the
two independent variables.

[]{#__RefHeading___Toc114975462
.anchor}![](media/image58.wmf){width="4.5in"
height="2.263888888888889in"}Figure 9.6 Severity of Impairment and Major
Activity Status

Similarly, the severity ratio for occupational status revealed some
subtleties that would have been difficult to discern from a more complex
chart. For example, in figure 9.6, we see that the persons who
classified themselves as able to work but were currently unemployed
were, in fact, more severely disabled than the working population. Even
considering the sexes of the respondents, differences which might
otherwise have been overlooked were clarified by the technique of
computing the severity ratio, as shown in table 9.2. A three-percentage
point difference in mild and moderate scores is seen as a more
compelling seven-point difference, amounting to a ratio of 5:6,
demonstrating that in this population, men were more severely impaired
than women.

[]{#__RefHeading___Toc114975747 .anchor}Table 9.2 Severity of
Impairment, by Gender

  ---------- --------------- --------------- --------------- ---------------
             Mild            **Moderate**    **Severe**      **Severity
                                                             Ratio**

  Male       59%             16%             25%             0.42

  Female     62%             16%             22%             0.35
  ---------- --------------- --------------- --------------- ---------------

The overall severity index for the entire survey population was 327
divided by 862, or 0.38. The severity ratio for respondents using AT was
1.36. Thus, the respondents who used AT were more than 3.5 times more
disabled than the total survey population. Finally, the respondent who
did not use AT had a severity ratio of 0.27, one-fifth of the 1.36 ratio
for those respondents who used AT. Thus, we can say AT was used in
direct relation to the severity of the impairment.

In the course of our analyses, we noted that the SR (Severity Ratio) was
higher for blacks than for whites (.45 versus .38), and lower family
incomes were associated with higher levels of severity of impairment,
with an R^2^ (Coefficient of Determination) that indicates that 31
percent of the covariance was explained. The results of the self-income
were much weaker than the family income trend. The R^2^ value of 0.01
indicates that the amount of covariance predicted by the linear
regression was about 1 percent, meaning that individual income and
severity were unrelated.

Next, we looked at the ages of the respondents. While we might have
expected the severity of their impairments to be a factor that increases
with increasing age, the results, while weak, show exactly the opposite.
The R^2^ indicated that about 15 percent of the covariance is accounted
for, meaning that the oldest respondents are less impaired.

Last, we found the SR for the lower echelon of family income respondents
was .38, and for the younger group, the SR was .42; however, for the
younger and poorer taken together, the SR rose to .48. And, if we add in
sex, and look only at the younger, poorer men, the SR reaches .86. We
could add additional respondent characteristics and obtain even higher
values, but the point is that for our purposes the scaling of severity
has both predictive validity and heuristic utility. By using this
method, we were able to show that respondents whose conditions were more
severe had the following characteristics, compared to less impaired
respondents:

-   Greater use of AT, both in the likelihood of use and in the number
    of devices used;

-   More likely to have had their AT paid for by Medicare or the
    Veterans Administration, and less likely to have had it paid by self
    or private medical insurance;

-   Lower education levels;

-   Greater likelihood of being unable to work because of their
    conditions;

-   Lower family incomes;

-   More likely to be males than females;

-   More likely to be black than white; and

-   More likely to have a broader base of information about AT.

We also found that persons who were more severely impaired were more
positive in their responses about the information they had received, the
use of that information, and the help they received from improved
products and AT in general, but more negative in judging improvements
over the past decade.

Looking at severity ratios among AT users (the proportion of severely
impaired respondents using AT divided by the proportion of mildly
impaired respondents using AT), we found a clear monotonic relationship
between the severity of their impairments and AT-related knowledge,
attitudes and opinions. We asked the following 10 questions:

1.  Overall, how much information and advice have you received about
    assistive technology? Would you say a lot, some, a little, or none?

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15. Overall, how much information and advice have you received about how
    to obtain it? Would you say a lot, some, a little, or none?

16. Overall, how much difference would you say that the information and
    advice about assistive technology and how to obtain it has made in
    increasing your level of learning, independence, productivity and
    community integration? Would you say a lot, some, a little, or none?

17. Overall, how much has information and advice about assistive
    technology and how to obtain it helped you to become more aware of
    your rights? Would you say a lot, some, a little, or none?

18. How much has your use of assistive technology devices and services
    decreased your need for help from another person? Would you say a
    lot, some, a little, or none?

19. To what extent have better designed products and environmental
    access features or universal design products reduced your need for
    assistive technology devices and services? Would you say a lot,
    some, a little, or none?

20. Compared to 10 years ago, people are more aware of the need for
    assistive technology devices and services for persons with
    disabilities. Would you say you strongly disagree, disagree, agree,
    or strongly agree?

21. Compared to 10 years ago, laws or program policies have been changed
    to help persons with disabilities to get assistive technology. Would
    you say you strongly disagree, disagree, agree, or strongly agree?

22. Compared to 10 years ago, more people are aware of assistive
    technology and understand how it can benefit persons with
    disabilities. Would you say you strongly disagree, disagree, agree,
    or strongly agree?

23. Compared to 10 years ago, it is easier to find assistance for
    purchasing assistive technology devices and services. Would you say
    you strongly disagree, disagree, agree, or strongly agree?

The most extreme answers in the positive direction for the first six
questions on information and utility of AT, and the most extreme
disagreement as to improvement over the past 10 years, were expressed by
the more seriously impaired respondents. The first questions showed that
the more severely disabled persons received the greatest amount of
information and the most information about obtaining assistive devices.

The third question asked how much all of the information and advice,
both on the devices and how to obtain them, had increased the
respondents' levels of learning, independence, productivity and
community integration. The greatest help was obtained by the more
severely impaired. Question 4, how the information had helped the
respondents' awareness of their rights, showed the same pattern of
response as Question 3, but the severity curve once again was completely
monotonic. Taken together, these two questions on the utility of
information about AT and how to obtain it showed that, in general,
information was seen as more useful by the more severely impaired
individuals. Recall that they asserted, in the first two questions, that
the amount of information they received was greater. If we can make the
assumption that the more severe a person's disability, the more
information about AT and how to obtain it is needed, then we could
assert that the information was getting to the proper customers, and
they were making good use of it.

Questions 5 and 6 concerned how the use of AT reduced the respondents'
reliance on the assistance of other persons and the extent to which
product designs reduce the need for AT, establishing a hierarchy of
assistance. Once again, the most positive responses were characteristic
of the more severely impaired. Universal product design was, once again,
seen as most salutary by the more severely impaired respondents.

When asked about how things had changed in the past 10 years, more
people were aware now of the need for AT. But while there was strong
agreement to this set of questions, strong disagreement was associated
with the severest levels of impairment. Thus, we might conclude that
those individuals who were most severely disabled were less likely to
have noted improvement in their situations over the past decade. The few
respondents who disagreed strongly were more severely impaired. Taken
together with the findings from the first six opinion questions, the
indication is that, for the more severely impaired among the disabled,
there was a great deal of helpful information about AT and how to obtain
it, and AT use had improved their lives in many ways; however, the
general social context---people's awareness of the need for AT, their
understanding of the benefits of AT, the ease of getting help purchasing
AT, and the help coming from laws and program policies---had not
improved over the past 10 years.

### Summary and Conclusion

This showed that there was a strong association between level of
impairment and AT use and need among our study participants. This
finding is not surprising, given the overwhelming evidence from this
survey and ones similar to it, and it provided an indication that the
scaling of severity had a degree of contextual validity. We found that
the more severely disabled were:

-   More likely to have had greater needs for AT and environmental
    accommodations;

-   Less likely to work and participate in social activities;

-   Least likely to report that AT has made them less dependent on the
    help of other persons; and

-   Least likely to conclude that disability-related legislation has
    helped them to improve their lives.

The study gives substantial support to the thesis that disabilities in
general, and severe disabilities in particular, systematically deny
opportunities to millions of citizens. Persons with disabilities cannot
participate fully in activities in school, at work or in the community
without assistance. Such assistance, whether provided by technology or
human beings, is necessary in proportion to the severity of the
impairments.

In spite of our efforts to better understand the need for AT by persons
with disabilities, gaps in knowledge about the costs and benefits
associated with the use of AT remain. We therefore conclude that a
careful study---with special emphasis on persons with more severe
impairments---of the costs and benefits of investing into AT should be
conducted. This should include a better assessment of the severity of
the impairments and a better classification of AT. If we have that, we
will obtain a better understanding of how much persons with disabilities
and their families are able to invest in AT on their own, how much
private entities can contribute, and what share of the cost the public
should bear.

## 10. Education As a Predictor of Assistive Technology Use and Need

Assistive technology and education are major factors in the process of
enabling persons with disabilities to participate to a greater extent at
home, school, work and in the community (Flippo, Inge, & Barcus, 1995).
Education plays a pivotal role in this process. Technology can assist in
the process of learning (Cavanaugh, 2002; Gitlow, 2000). Such
technologies include: talking software; scan and screen readers; word
prediction programs; portable word processors; touch screens; graphic
organizers; alternative keyboards; track balls; multimedia programs; and
e-books (White, Wepner, & Wetzel, 2003). Schools throughout the country
now use technologies to ensure that students with disabilities can
obtain a free and appropriate education in an integrated school
environment, as provided by the *Individuals with Disabilities Education
Act*. Educational technology-related assistance is available through
numerous agencies and organizations such as the Assistive Technology
Educational Network (2003), Disability Resources (2003) or the American
Speech-Language-Hearing Association (2003).

Assistive technology use by younger persons with disabilities plays a
crucial role in the transition from school to work (Goodman, 1998). For
many students with disabilities, this transition can be facilitated
through continued and improved provision of assistive technology,
vocational rehabilitation services, and support in the workplace (Inge,
Strobel, & Shepherd, 1999). Adequate preparation, planning and
assistance from teachers and parents also contribute to a successful
transition from school to work (Canfield & Reed, 2001).

There is now a growing body of evidence that suggests that assistive
technology use, workplace accommodations and level of education result
in better employment outcomes for persons with disabilities. Hendershot
(2001) found that assistive technology use is positively associated with
employment. McNeil (1994) found that persons with disabilities who used
wheelchairs and were employed had similar earning levels than persons
without disabilities. Carlson (2002) showed that levels of employment
and income of persons with disabilities were significantly related to
levels of education and assistive technology use. These survey-based
findings, supported by anecdotal accounts (National Council on
Disability, 1993) and legislative findings (United States Senate, 1998)
strongly suggest that education and assistive technology use can improve
levels of independence, participation and overall quality of life of
persons with disabilities.

Training and education regarding assistive technology, particularly
high-tech AT, leads to a growing number of persons who are "technology
savvy" and understand how AT can help them to better perform their tasks
at home, in school and at work. An informed understanding of the power
inherent in technology fosters the demand for AT devices, programs and
services. We would therefore expect that persons with higher levels of
education and familiarity with technological issues use AT with greater
frequency and demand better products. We therefore examined if and how
levels of education affect a person's propensity to use or need
assistive technology.

### Findings

The first step in this analysis was to investigate the percentage of the
population who use AT in any of the four domains as a function of the
highest level of education that they had attained. This variable proved
to be the most influential of all variables examined, as shown in Table
10.1[^11].

[]{#__RefHeading___Toc114975748 .anchor}Table 10.1 AT Use and Level of
Education, by Severity of Impairment

  ---------------------------- ----------- -------------- ---------- -------------
                               **Percent                             
                               Using AT**                            

  **Education Level**          Severe      **Moderate**   **Mild**   **Overall**

  Postgraduate                 84%         78%            59%        66%

  College graduate             71%         74%            67%        69%

  Some college                 75%         69%            64%        67%

  High-school graduate         69%         62%            57%        60%

  Elementary                   53%         47%            56%        53%

  Kindergarten                                                       

                                                                     

  Correlation coefficient      **0.90**    **0.96**       **0.54**   **0.85**

  Coefficient of determination **80%**     **92%**        **29%**    **72%**
  ---------------------------- ----------- -------------- ---------- -------------

All of the correlation coefficients, computed on the rank of education
level and percent of AT use within each level, are statistically
significant. The coefficients of determination, reported as percentages,
indicate the amount of covariance accounted for by the individual
correlations.

Overall, then, 72 percent of the variance within the amount of AT use
can be attributed to the amount of education attained by the respondent.
Figure 10.1 demonstrates that there was no discernible pattern relating
severity of impairment to education level, thereby eliminating one
possible source of confounding.

[]{#__RefHeading___Toc114975463
.anchor}![](media/image59.wmf){width="5.5in"
height="3.457638888888889in"}Figure 10.1 Distribution of Respondents, by
Severity and Educational Level

Further, there was no statistically significant relationship between the
age of the respondents and their education levels. The highest reported
age was associated with respondents who had attained elementary school
education (up to the 8th grade), followed by high school, postgraduates,
college graduates, and then respondents with some college---in short, a
non-monotonic pattern.

### Level of Education and Learning About AT

Each respondent who used AT in any location was asked: "Where did you
learn about the device that you now use?" Although the original intent
of the question was to determine the particular sources of information
accessed by the respondents, we summed all mentions of all sources of
learning and compared the totals, for each level of education, that said
the respondents got their information from any number of sources with
the totals of each level of education extant in the population.

The result of the comparison, splitting the data at the median level of
education, was a chi-square of association of 27.61, *df*=1[^12],
p\<0.000007[^13]; in short, those who were more educated accessed more
sources of information than those who were less educated. While this may
seem to be an obvious conclusion, it lends support to the finding that
the relationship between education and the use of AT is a causal one.

In a similar vein, we asked respondents whether they planned to contact
any person or agency to get advice. There was a clear indication that
the more educated the person, the more likely they were to say that they
planned to contact someone. (Spearman-Brown rank-order correlation
\[rho\] = +.83, coefficient of determination = 69 percent of covariance
explained by the relationship.)

There was an even more pronounced effect of education when we asked the
respondents if they were aware that they could get help or advice in
obtaining AT. Here the rho reached +.89; the coefficient of
determination was 78 percent.

There was also a tendency for the better-educated respondents to be more
satisfied with the AT they use and with the assistance they got in
selecting and obtaining AT, but the small numbers of respondents render
these findings inconclusive.

In contrast, when we asked the question, "Have you ever tried to obtain
AT without success?," we found no relationship between education and the
likelihood of failure to obtain AT. (rho= -.08, coefficient of
determination \<1 percent.) Nor did we find any relationship between the
level of education and the perceived need for additional AT (rho= -.03,
coefficient of determination \<1 percent).

It is also important to note that level of education was unrelated to
severity of impairment (chi-square = 16.77, *df*=10, p\>0.05, ns), and
similarly, education was unrelated to the sex of the respondent
(chi-square = 10.2, *df*=5, p\>.05, ns), or to the respondent's
race[^14] (chi-square = 6.1, *df*=5, p\>.05, ns). On the other hand,
there was a strong relationship between education and family income
(rho= +.66, coefficient of determination 43 percent), and an even
stronger relationship between education and personal income (rho= +.94,
coefficient of determination 89 percent).

Given that both personal and family income were related to education,
and level of education was related to AT use, it would seem reasonable
to assume that income level is also related positively to AT use.

However, there was no relationship between family income and AT use, and
a strong negative relationship between personal income and AT use (rho=
-.77, coefficient of determination 60 percent). And while AT users were,
on average, more educated than nonusers, they were slightly lower in
both family and personal income. So, education emerged as the
controlling variable.

### Learning About Assistive Technology As a Function of Severity of Disability

Table 10.2 relates the severity of one's disabling condition to the
source respondents used to learn about assistive technology. The
percentages are the percent of total mentions per severity category. The
table shows that, once again, severity of disability made a difference.
The severely disabled individuals were roughly twice as likely to get
information from alternative sources. Since this item was not probed,
there were only four mentions of what these other sources might have
been (American Arthritis Association, VA, high school and a conversation
with a family member).

[]{#__RefHeading___Toc114975749 .anchor}Table 10.2 Source of
Information, by Level of Impairment

  ----------------------------------- -------------- -------------- -----------
                                      **Level of                    
                                      Impairment**                  

  **Source of Information**           **Severe**     **Moderate**   **Mild**

  Doctor/Other health care prov.      53%            61%            64%

  Vocational rehab counselor          9%             6%             6%

  Family/Friends/Neighbors            10%            11%            12%

  Pamphlets, magazines                2%             4%             2%

  Centers for independent living      0%             0%             1%

  Tech assistance centers             0%             2%             0%

  *Tech Act*/Other state orgs.        2%             0%             1%

  TV/Radio                            1%             2%             1%

  Yellow pages                        0%             0%             1%

  Internet                            1%             2%             0%

  Other                               23%            12%            13%
  ----------------------------------- -------------- -------------- -----------

Indeed, the number of devices used per person increased with severity,
as shown in table 10.3.

[]{#__RefHeading___Toc114975750 .anchor}Table 10.3 Number of AT Devices
Used, by Level of Impairment

  ----------------------------------- -------------- -------------- -----------
                                      **Level of                    
                                      Impairment**                  

  **AT Device Use**                   **Severe**     **Moderate**   **Mild**

  Total number of devices             322            192            536

  Number of respondents               327            227            862

  Devices per respondent              0.98           0.85           0.62
  ----------------------------------- -------------- -------------- -----------

Referring again to Severity Ratio, the SR for respondents using one
device was 0.78; for those respondents using two devices, 1.03, and for
those using three or more AT devices, 2.04.

### Income and Employment Status

As might be expected, both personal and family incomes were positively
related to education levels (correlations of +.94 and +.66, education
with personal and family income, respectively), a fact that might lead
one to believe that income and AT use were also positively related.
However, the relationship between personal income and AT use was
negative---minus .77---and there was no relationship between family
income and AT use. The reason that the two positives produced a negative
can be explained with reference to figure 10.2.

[]{#__RefHeading___Toc114975464
.anchor}![](media/image60.wmf){width="5.0in"
height="3.6354166666666665in"}Figure 10.2 AT Use as a Joint Function of
Education and Personal Income

The AT use by income negative correlation was strongest for the
least-educated, who were the largest group (totaling almost as many
respondents as in the medium and highly educated groups combined) and
the group which was clearly lower in percent of respondents using AT
than either of the others.

The percentage of respondents using AT was virtually constant for the
highly educated, declining from 69.2 percent for the low income to 68
percent for the highest income category; for the respondents with median
education levels, the decline was steeper---from 70.8 percent to 63.1
percent as one moves from low to high income. For the least-educated,
who comprised the largest group, the decline was equally steep, from a
lower base, which translated into a larger percentage loss---from 58.1
percent to 50.5 percent.

Finally, if we ignore the interaction between education and income and
look only at the percentage of respondents above and below the median in
both variables who used AT, the better-educated respondents exceeded
their less-educated counterparts by 9 percent, 68 percent for the
higher-educated, 59 percent for the lower-educated, while the
lower-than-median earners exceeded their better-paid counterparts 65
percent to 60 percent. Comparing the two main effects, education was
almost twice as powerful as income.

In addition, we found that:

-   Respondent age, race, sex, severity of respondent condition, or
    perceived need for more assistance, were unrelated to the level of
    education achieved (thereby eliminating these variables as sources
    of confounding);

-   Persons with higher levels of education made use of more sources of
    information to obtain AT, were more likely to contact another person
    or agency to obtain more help, were more aware that help is
    available in obtaining AT, and were more satisfied with their AT and
    the assistance they got in obtaining it;

-   There was no effect of educational level on the likelihood of having
    tried, and failed, to obtain AT;

-   Age, sex and race were uncorrelated with AT use; and

-   Although Asian respondents were more educated than any other race,
    there were so few Asians in the sample that the result did not reach
    statistical significance.

### Summary and Conclusion

For many persons with moderate and severe disabilities, education,
income and assistive technology are key determinants for independence
and higher levels of participation in community and society. Whereas
education provides the intellectual prerequisite for greater levels of
engagement in school, work and beyond, AT and environmental
accommodations provide the engineered means for participation.

We found that persons with higher levels of education were more aware of
the benefits they obtained from using AT, and subsequently appeared more
savvy about what AT to get, how to get it, and from where to get it. Our
analysis showed clearly that the more educated respondents:

-   Had more sources of information about how to obtain AT;

-   Were more aware that help to obtain AT is available; and

-   Were more likely to contact someone about getting help.

In addition, the more educated respondents were more likely to be
satisfied with the AT they had and with the assistance they received,
but they were also more likely to express a need for more AT.

Our findings provide evidence for what has been suggested
elsewhere---namely that awareness and knowledge of assistive technology
(AT) are key factors in supporting the empowerment of people with
disabilities (Andrich & Besio, 2002). Awareness and knowledge of AT
contribute greatly to the success of AT solutions, and above all, enable
persons with disabilities to fully enjoy the rights granted in the
*Americans with Disabilities Act* (Button & Wobschall, 1994).

This study shows that education plays a key role in the acquisition and
use of AT. Education, if defined as the ability to acquire and use
knowledge and information, enables persons with disabilities to select
and use the most appropriate technologies and devices necessary to
enhance physical and cognitive functions, provided that knowledge and
information about assistive technology are made available and accessible
to the greatest extent possible. Knowing about AT and its benefits leads
to a reassessment of one's need and the recognition that particular
devices and technologies provide venues for new opportunities, as well
as new and better things to do.

Getting the right AT largely depends on access to information and help.
While such help is increasingly more available, there are segments of
the population that do not get this information quickly or easily.

## 11. Sources of Information About Assistive Technology

Accessible information about assistive technology devices and
technology-related assistance services play a major role in the
successful rehabilitation and integration of persons with disabilities
into school, work and the community (United States Senate, 1998; United
States House of Representatives, 1998). Based on data from this survey,
we estimate that as many as 25 million adults with disabilities in the
United States in 2001 used AT in one form or another (Carlson, Ehrlich,
Berland, & Bailey, 2001). A substantial number of AT users reported that
the overall benefits of AT use and environmental accommodations at work,
for instance, included a higher likelihood of being employed while
having a work disability, and earning higher levels of income (Carlson,
2002).

Careful matching of AT products with personal needs is essential for
optimal use (Scherer, 2001). Poorly designed or poorly fitted products
may cause serious health problems (Nelson, 1997; Taylor, 1987).
Dissatisfied users are likely to abandon poorly fitted products and are
forced to look for better ones elsewhere (Riemer-Reiss & Wacher, 2000;
Phillips & Zhao, 1993).

Matching persons with disabilities with the appropriate technology can
be a difficult process. For example, Abledata's database contains over
19,000 currently available products from over 2,000 different companies
(Abledata, 2003). While each product record contains a detailed
description of the product as well as the price, and the manufacturer
and distributor information, the sheer volume of items available for
review is daunting. To answer the question of what products and services
are available and how and where persons with disabilities can learn more
about these products and services and possibly test them or try them
out, requires information and assistance provided by trained
professionals and organizations who are committed to offering the best
possible services to current and potential AT users.

Persons with disabilities using or needing AT can turn to several
sources of information. The most common ones are medical professionals
and rehabilitation specialists, vocational and occupational
rehabilitation counselors, AT practitioners, and family and friends.
There are also several comprehensive directories (Grey House Publishing,
2003), Internet sites, trade association meetings and trade shows that
inform persons with disabilities and practitioners alike about their
latest products and services.

For example, the Assistive Technology Industry Association (ATIA) (2003)
serves as the collective voice of the AT industry to ensure that the
best products and services are delivered to people with disabilities.
ATIA and other trade organizations organize large meetings and fairs to
introduce new and improved AT products and services as well as equipment
trial and training opportunities. Professional organizations such as the
Rehabilitation Engineering and Assistive Technology Society of North
America (RESNA, 2003a) promote technology development and application
and train AT practitioners, but also disseminate useful and important
information to persons with disabilities. In addition, a wide network of
state-based technical assistance projects reach out to persons with
disabilities by organizing awareness campaigns, distributing pamphlets
and flyers, and using radio broadcasts and other information
dissemination techniques (RESNA, 2003b). There are also hundreds of Web
sites available on the Internet, many of them put up by NIDRR grantees,
that provide excellent information about assistive technology (Ehrlich,
Carlson, & Bailey, 2003).

However, there remains a limited understanding about the sources of
information on assistive technology that are available and accessible to
persons with disabilities, how useful the information is, and how the
information helps with the selection and acquisition of suitable devices
and technologies. The debates surrounding the *Technology-Related
Assistance for Individuals with Disabilities Act of 1988*, amended in
1994, and the *Assistive Technology Act of 1998* revealed that
information about how to obtain AT plays a crucial role in the
rehabilitation process of persons with disabilities (Carlson & Ehrlich,
2002; National Council on Disability, 2000).

This presents findings on how persons with disabilities obtain
information on selecting and acquiring AT.

### Sources of Information About Assistive Technology

Figure 11.1 shows the relative frequency with which each information
source was reported. The most often-mentioned information source (53
percent of all sources) was a physician or other health care
professional, followed by family or a friend (15 percent) and vocational
rehabilitation counselor (13 percent).

[]{#__RefHeading___Toc114975465
.anchor}![](media/image61.wmf){width="6.0in"
height="2.8069444444444445in"}Figure 11.1 Sources of Information About
AT

To demonstrate the effects of each source of information on the
attitudes and opinions of persons with disabilities who use or need AT,
we performed a series of discriminant function analyses (DFA), a
precursor of logistic regression (Fisher & Van Belle, 1993). We used
this technique to accommodate a range of variables of different scale
properties, from true nominal scale dichotomies (working/not working,
white/nonwhite) to ordinal scales (level of education, scaled from
1--kindergarten to 6--postgraduate degree), to interval (equal-interval
categories of income) and ratio scales (age of respondent at the time of
the interview). For all scales above the nominal level, the data were
split at the median so that the two groups, for example older and
younger, would have approximately equal representation.

The variable producing the greatest overall discriminant factor (DF) was
the dichotomy constructed from the opinion questions, named here "AT
Opinion." There were six questions that respondents answered about their
opinions about the helpfulness or the amount of information they
received about AT, the usefulness of AT, and the like. For each of these
questions, the answers ranged from "A lot" to "None." The scores for
each individual were averaged across the six items and divided at the
median for all AT users. Figure 11.2 illustrates how this method was
employed to show these effects.

[]{#__RefHeading___Toc114975466
.anchor}![](media/image62.wmf){width="6.0in"
height="2.8930555555555557in"}Figure 11.2 Opinions About the Usefulness
of Information About AT As a Discriminant Factor Across Information
Sources

Accordingly, AT users who received their information from family and
friends were less positive in their assessments of that information than
those who received their information from all others, but especially
those who received their information from vocational rehabilitation
counselors (total difference = .91 σ) or from physicians or other health
care professionals (total difference = .81 σ). This result would seem to
be intuitively obvious (i.e., that information from professionals would
be more helpful than that received from well-meaning but untrained
acquaintances and relatives).

#### Occupational Status

We dichotomized the AT users into those who reported themselves to be
gainfully employed as one group, and all other AT users. Respondents who
used AT and were not working at the time of the interview were more
likely to obtain their information from vocational rehabilitation
counselors or family and friends, and less likely to get information
from printed material than those who were employed.

#### Race

The variable "race" was dichotomized as white versus nonwhite. The only
trend revealed is that nonwhites were less likely to receive information
from vocational rehabilitation counselors than whites.

#### Severity of Impairment

Each respondent was asked to describe the conditions that caused her
disability, and up to three independent conditions were recorded and
scored for the level of disability on a four-point scale. We added the
scores across all mentions to arrive at a summary level of disability.
The variable was dichotomized according to the nearest sum to the
median. The results indicated that the more severely impaired
respondents were more likely to receive information from family and
friends than those less severely impaired.

#### Age

We found that there was a slight tendency for the older population to
receive more information from family and friends and less from
vocational rehabilitation counselors.

*Impact of AT related legislation*

Respondents answered four questions comparing conditions at the time of
the survey with how things were 10 years ago. Again, the scores were
averaged over those four questions and then split at the median. Our
findings suggest that neither positive opinions nor negative opinions
about improvement and change over the past 10 years were associated with
any particular source of information about AT.

*Income*

Respondents gave figures within ranges on an 11-point scale for both
family and personal income in the year previous to the survey. Splits
were made at the median for both sets of responses. Neither personal nor
family income was found to be a reliable discriminant factor.

#### Education

Each respondent provided the highest level of education attained, and
the results were coded into six ordinal categories. Data were split at
the median. The data provided some indication that the more educated
individuals were more likely to get information from vocational
rehabilitation counselors than those with lower levels of education. The
result is supported by the fact that working AT users were significantly
higher in educational attainment levels than nonworking AT users, and
would therefore have been more likely to visit vocational rehabilitation
counselors.

#### Personal Assistance Services 

When respondents using personal assistance services (PAS) were asked the
10 opinion questions, we found that the greatest difference was that
personal assistance users were less positive about AT decreasing their
need for personal assistance. This is illustrated figure 11.3.

[]{#__RefHeading___Toc114975467
.anchor}![](media/image63.wmf){width="6.0in"
height="2.3541666666666665in"}Figure 11.3 Attitudes and Opinions About
AT, by Persons With Disabilities Using Personal Assistance (PAS) vs.
Non-PAS Users

The obvious interpretation is that a large segment of personal
assistance is outside of the range of activities that AT can address.
And this in turn suggests that the greatest need in the AT field is not
for technological advancement in existing AT, but extending the range of
AT to areas that are now addressed only by the assistance of another
person.

#### State of Residence

The *AT Act* placed emphasis on states to provide technology-related
assistance to persons with disabilities, and granted a large degree of
freedom in how this assistance was to be provided. We were particularly
interested in finding out if any differences at the state level between
modes of information delivery or effectiveness of information
dissemination could be detected. However, the small sample of the survey
raised concerns about whether or not we could detect valid and
meaningful differences. We therefore chose total state population and
state population density instead of state-by-state comparisons because
the total sample size was not sufficient to allow a full state-by-state
comparison.

Frequency estimates of use were based on the sum of all mentions of each
source of information about AT. In the course of administering the
questionnaire, the question "Where did you learn about the AT that you
use?" could have been asked up to nine times; each respondent mentioned
all possible sources, and the interviewer noted each mention of the 10
source categories included in the questionnaire.

In our analysis, the states were grouped according to population into
"High" (average population of \~14.6 million) "Medium" (average
population of \~5.7 million) and "Low" (average of \~2.1 million). There
were 11 states with a population greater than 8.0 million, 10 with a
population between 4.5 and 8.0 million. The remaining 39 states and the
District of Columbia comprised the low population group. The data are
summarized in table 11.1. The overall figures show good consistency
across the population categories, with a slight decline in the use of
the primary source (physician or other health care professional) with
decreasing population, and a corresponding increase in the use of the
vocational rehabilitation counselor. Print media diminishes as a source
of information in the less populous states.

[]{#__RefHeading___Toc114975751 .anchor}Table 11.1 Sources of
Information About AT, by State Population Characteristics

+---------------------+-------+-------+-------+-------+-------+-------+
|                     | **H   |       | **Med |       | **    |       |
|                     | igh** |       | ium** |       | Low** |       |
+---------------------+-------+-------+-------+-------+-------+-------+
| **Source of         | ###   | *Per  | ###   | *Per  | ###   | *Per  |
| Information**       | # Sum | cent* | # Sum | cent* | # Sum | cent* |
+---------------------+-------+-------+-------+-------+-------+-------+
| MD/Other health     | 256   | 56    | 122   | 56    | 130   | 50    |
| care prov.          |       |       |       |       |       |       |
+---------------------+-------+-------+-------+-------+-------+-------+
| Voc rehab counselor | 47    | 10    | 24    | 11    | 41    | 16    |
+---------------------+-------+-------+-------+-------+-------+-------+
| Family/Friends      | 72    | 16    | 44    | 20    | 43    | 17    |
+---------------------+-------+-------+-------+-------+-------+-------+
| Pamp                | 38    | 8     | 12    | 6     | 17    | 7     |
| hlet/Magazine/Print |       |       |       |       |       |       |
+---------------------+-------+-------+-------+-------+-------+-------+
| CIL                 | 4     | 1     | 3     | 1     | 4     | 2     |
+---------------------+-------+-------+-------+-------+-------+-------+
| Disability Tech     | 8     | 2     | 2     | 1     | 5     | 2     |
| Center              |       |       |       |       |       |       |
+---------------------+-------+-------+-------+-------+-------+-------+
| *Tech Act*/Other    | 7     | 2     | 2     | 1     | 7     | 3     |
| state orgs          |       |       |       |       |       |       |
+---------------------+-------+-------+-------+-------+-------+-------+
| Yellow pages        | 4     | 1     | 0     | 0     | 2     | 1     |
+---------------------+-------+-------+-------+-------+-------+-------+
| TV/Radio            | 13    | 3     | 7     | 3     | 9     | 3     |
+---------------------+-------+-------+-------+-------+-------+-------+
| Internet            | 5     | 1     | 1     | 0     | 1     | 0     |
+---------------------+-------+-------+-------+-------+-------+-------+
| **TOTAL**           | **    | **    | **    | **    | **    | **    |
|                     | 454** | 100** | 217** | 100** | 259** | 100** |
+---------------------+-------+-------+-------+-------+-------+-------+

### Summary and Conclusion

Each respondent was asked about the sources of AT information that they
used. More than half of all respondents mentioned receiving some or all
of their information from physicians or other health care professionals,
followed by family and friends, and vocational rehabilitation
counselors.

We examined 10 sources of information and nine demographic factors, and
found that physicians and health care professionals provided information
to all groups without significant variance. With regard to the users of
assistive technology who got information from family and friends we
found:

-   Strong evidence that they were less positive in their attitudes
    toward the information they received and the utility of assistive
    technology;

-   These respondents were likely to be more severely impaired and older
    than those who did not receive information from family and friends;
    and

-   There was a lesser tendency for these individuals to be in the
    nonworking group, to have a less positive view of changes over the
    previous decade, have lower family and personal incomes and to be
    nonwhite.

Users of AT who mentioned receiving information from vocational
rehabilitation counselors were likely to be nonwhite, unemployed and
have a higher level of education.

Our overall conclusion is that the source of information had a major
effect on one's attitudes about the utility of that information and of
AT. The information respondents got from family and friends was seen
less positively than that received from other sources in general, and
vocational rehabilitation counselors in particular. The demographic
characteristics that defined this group---older, more severely impaired
(recall that severity of impairment and age are uncorrelated), tending
to be unemployed and coming from poorer, minority backgrounds---indicate
where information from knowledgeable sources should be directed. This
group was accessing information from the most convenient, rather than
the most knowledgeable, source.

The relatively small sample size of this national survey (n = 1,412),
and the low number of responses indicating a state-based agency as the
source of information, prevented us from detecting significant
differences between states clustered by total population and population
density.

Two final observations also needing further study point out that
state-based agencies providing technical assistance to persons with
disabilities using or needing AT appear to have raised awareness about
themselves in a relatively small number of respondents (about 3 to 5
percent). This proportion may be higher, assuming that a large
proportion of pamphlets and publications mentioned by 7 percent of the
respondents originated in state-based technical assistance agencies.
Second, centers for independent living and the Internet as a source of
information about AT were mentioned each by 1 percent of respondents.
These findings suggest that two rich sources of information about AT may
be underutilized.

## 12. Sources of Payment for Assistive Technology

Estimates from the Survey of Income Program Participation showed that 54
million persons, or about 20 percent of the U.S. population, have
activity limitations or disabilities (McNeil, 1997). About half of them
used assistive devices and technologies or special equipment (canes,
wheelchairs, special beds or special telephones) as well as medical
devices (prosthetics, orthotics, respirators or diabetic equipment), and
rely on home modifications, school or workplace accommodations, or
modified cars or vans to perform daily tasks and activities (Carlson et
al., 2002). These estimates indicate that a rather large segment of the
population utilize AT devices and services. However, little is known
about how much is paid for these products and who pays for it. It was in
part because of the lack of quantitative knowledge on this subject that
the 2001 AT survey was conducted.

A review of the literature revealed three payment studies that showed
that when asked how respondents pay for their assistive technology, 48
percent said that they or their families paid for the devices with no
assistance from third parties (LaPlante et al., 1992). According to the
same source, more than 75 percent of persons with home accessibility
features said they were paid for entirely by themselves or by their
families. The Agency for Healthcare Research and Quality (2000), based
on findings from the Medical Expenditure Panel Survey of 1996, reported
that in 54 percent of all "Other Medical Expenses" (this includes
medically necessary equipment and supplies), payments were made
out-of-pocket. This is the highest ratio of out-of-pocket expenses for
any type of medical service-related payments. In a similar vein,
Connell, Turner and Gruber (1996) found in a study of 49 North
Carolinians who modified their homes that 67 percent of the
modifications were paid for by family and friends, and much of the labor
was donated.

The shifting of the burden of paying for AT onto the consumer and
limiting the involvement of third party payers in the payment for AT was
observed a decade ago as being inherent in "programs that help people in
poverty and those over 65 to acquire assistive technology devices, but a
third or more are purchased by poor individuals and their families
without contributions from other parties" (LaPlante et al., 1992). The
ability to pay for much-needed AT continues to constitute a barrier to
equal participation and inclusion in work and community that the *Tech
Act* aimed at reducing (National Council on Disability, 2000). As
LaPlante et al. further pointed out, "Despite financial problems in
acquiring assistive technology devices, use of devices has increased
dramatically over the past decade" (1992). At that time, over 13 million
people used AT. Now, after another decade has passed, we estimate that
about 25 million people use some form of AT to help them perform their
daily tasks and activities (Carlson et al., 2002b). Because the
population of AT users has nearly doubled, new and better estimates are
needed to understand how AT is paid for today.

Our review of the literature revealed that payment for AT by oneself or
others often depends on the type of device or adaptation, and anecdotal
evidence suggests that expenses for many items used as AT, such as tub
mats to prevent slipping and falling (and thus preventing injuries and
disabilities) are not considered reimbursable by third parties. At a
more general level, there are no good estimates of the proportion of
payments made by whom, and for what. Third-party payers such as private
insurance companies, Medicare, Medicaid or the vocational rehabilitation
system have no consistent or compatible payment formulas across
geographic regions, by types of impairment or disability, or by
eligibility criteria (Arcarese, 2002). Personal, social and economic
characteristics of persons with disabilities using or needing AT greatly
affect the modes of acquisition of AT. In addition, the multifaceted
nature of AT, especially when multiple devices are used, further confuse
the understanding of who pays for what, and under what circumstances.
Finally, the legislative framework surrounding the provision of AT,
public assistance, and the role of third-party payers complicate the
modes of payment for AT even more.

For example, in the case of the *Individuals with Disabilities Education
Act* (IDEA), a child's need for assistive technology must be determined
on a case-by-case basis, made part of the individualized education plan
(IEP), and paid for by the public school system to ensure that the child
gets a free, appropriate public education. To learn about how many
respondents got their AT through IDEA was not part of our study design,
as the primary focus was to study the AT needs of adults with
disabilities. For adults, laws such as the *Rehabilitation Act of 1973*
as amended, (particularly Sections 504 and 508), the *Workforce
Investment Act of 1998*, the *Americans with Disabilities Act*, the
*Telecommunications Act of 1996*, and the *AT Act* guide the provision
of assistive technology and technology-related services. With regard to
the effects of these laws on payment for AT, vocational rehabilitation
agencies provide "rehabilitation technology services" to a relatively
small number of their clients. The bulk of payments for AT authorized by
these laws goes into making the built environment and the means of
public transportation and communication accessible to persons with
disabilities.

Frequently mentioned sources of payment for AT---Medicare and
Medicaid---require a certificate of medical necessity issued by a
physician or otherwise qualified health care professional to a person
seeking payment for AT. The type of device and the amount paid for a
device by Medicare and Medicaid is determined by administrative panels
that issue National Coverage Decisions (NCDs). The *Coverage Issues
Manual* contains a list of these devices (termed durable medical
equipment). In the durable medical equipment (DME) category, the Centers
for Medicare and Medicaid Services (CMS) includes outpatient
prescription drugs, other nondurable medical supplies, and durable
medical equipment based on CMS' healthcare common procedure coding
system (HCPCS) designations. In 2001, CMS spent about \$7.7 billion on
durable medical equipment. Payments for two items, oxygen and capped
rentals, constituted nearly half of this sum (\$3.5 billion). CMS'
reporting practices, however, do not make it possible to identify what
type of AT device was paid for and to whom the payment was made, unless
one occasionally comes across a press release on a particular issue,
such as the power wheelchair program in Medicare. According to one such
release, CMS spent \$845 million on 159,000 claims for a power
wheelchair in 2002 (Centers for Medicare and Medicaid Services, 2003).
However, obtaining national estimates on AT payment by CMS and other
payers would have gone far beyond the scope of this survey. The
Department of Veterans Affairs pays for AT, particularly for
service-connected disabilities, although some degree of determination of
what is needed and how it is paid for is made on a case-by-case basis.

The AT Survey did not attempt to estimate how much money is spent for AT
in the United States. At present, there is no information on this
subject. To obtain such information, a number of data sources would have
to be explored, including proprietary data from AT suppliers and
third-party payers.

To briefly sum up the findings relevant for our study of payment for AT:

-   Low-tech devices, adaptations and accommodations made up the bulk of
    AT used by persons with disabilities;

-   Regardless of type or level of technology, out-of-pocket expenses by
    persons with disabilities were mentioned as the most frequent source
    of payment;

-   AT that enhances physical functioning and mobility was most likely
    to be paid by third parties, and environmental adaptations and
    universal design products were least likely to be paid for by third
    parties; and

-   Inadequate funding of AT continued to be a barrier to the more equal
    inclusion of persons with disabilities in the community and in
    society.

The findings presented in this provide a summary of who paid for what
types of AT. Factors that affect a person's ability to pay for AT were
also explored.

### Findings

Respondents were asked about their use of assistive technology to get to
school and work, in school or at work, in the home, and in the
community. Of all respondents, 901 (64 percent) used some assistive
technology. Use at school and at work was 36 percent; use at home was 49
percent; and use in the community was 50 percent. Most of the assistive
devices used were designed to enhance mobility: canes, crutches,
walkers, scooters and wheelchairs. Hearing aids, oxygen tanks and other
personal-use devices were also among the most frequently used devices.

After the respondents were asked what type of AT they used at home, work
or in the community, they were asked who paid for it. Many devices
mentioned in the course of the interviews were used by a few respondents
only, and therefore were grouped into larger categories. Figure 12.1
provides an overview of these categories.

[]{#__RefHeading___Toc114975468
.anchor}![](media/image64.wmf){width="5.5in"
height="3.1493055555555554in"}Figure 12.1 Types of AT Used

The largest AT component was made up of mobility devices (over 68
percent), followed by hearing devices (9.4 percent) and personal or
medical use AT such as respirators, nebulizers, oxygen tanks or diabetic
equipment (7 percent). The next category included AT devices used in the
home but that were not part of the "built" structure of the home, such
as modified kitchen appliances or special kitchen or bathroom utensils.
These devices accounted for 5.4 percent of the devices for which a
source of payment was reported. Home AT use was followed by the
anatomical devices category that included prosthetics and orthotics, and
the assistive transportation technology that included modified vans or
portable ramps. Finally, the smallest AT categories contained structural
home modifications (2 percent), visual AT (1 percent), and other AT,
primarily for persons with sensory or speech impairments (also 1
percent).

We asked the respondents: "Who paid for the device or service?" and
interviewers checked all that applied from the following list: self; a
family or household member; private health insurance; Medicare;
Medicaid; the vocational rehabilitation system; the employer; the
Veterans Administration; free; or other. Figure 12.2 contains a
breakdown of these payment sources. Out-of-pocket expenses by the direct
beneficiaries constituted the largest share of all payments (37
percent), followed by Medicare, private health insurance, and free
items. Medicaid payments accounted for a relatively small share (5
percent), about equal in size to payments by the Veterans Administration
and other sources. The smallest shares consisted of payments made by
employers (3 percent), the vocational rehabilitation system (2 percent),
and a family or household member (also 2 percent).

[]{#__RefHeading___Toc114975469
.anchor}![](media/image65.wmf){width="5.0in"
height="3.1666666666666665in"}Figure 12.2 Sources of Payment for AT

Tables 12.1 and 12.2 contain the counts and proportions of payment
source cross-tabulated by type of AT category. A total of 737 AT
devices, adaptations or environmental accommodations were reported that
had an identifiable source of payment. In terms of absolute numbers,
persons with mobility impairments used most AT devices. Hearing devices
constituted the second largest component. Table 12.1 also shows that
respondents themselves most often paid for mobility devices, hearing
devices and home AT. In absolute numbers, Medicare was the second
largest source of payment for mobility devices, followed by private
insurance and "free" mobility devices (mostly canes and a few manual
wheelchairs).

[]{#__RefHeading___Toc114975753 .anchor}Table 12.1 Sources of Payment,
by Type of Device\*

  ------------------ --------- --------- --------- --------- --------- -------- -------- --------- -------- -------- ---------
  **Device**         **% of    **SEL**   **F/H**   **PHI**   **MC**    **MA**   **VR**   **EMP**   **VA**   **FR**   **OTH**
                     Total**                                                                                         

  All anatomical     32        9         0         8         4         1        0        3         5        0        2
  devices                                                                                                            

  All mobility       502       174       8         82        104       24       10       11        22       43       24
  devices                                                                                                            

  All hearing        69        47        1         4         4         3        1        1         5        1        2
  devices                                                                                                            

  All vision devices 10        7         0         1         0         0        1        0         0        0        1

  All asst.          16        7         0         3         3         1        1        0         1        0        0
  transportation                                                                                                     
  tech.                                                                                                              

  All                51        7         0         15        11        5        0        3         2        3        5
  personal/medical                                                                                                   
  use AT                                                                                                             

  All struct. home   13        6         1         0         2         3        0        0         0        0        1
  modifications                                                                                                      

  All AT/IT in the   40        21        1         5         3         1        1        4         1        3        0
  home                                                                                                               

  All other AT       4         3         0         1         0         0        0        0         0        0        0

  **All**            **737**   **281**   **11**    **119**   **131**   **38**   **14**   **22**    **36**   **50**   **35**

  **\*Legend:** SEL                                                                                                  
  = Self; F/H =                                                                                                      
  Family or                                                                                                          
  Household Member;                                                                                                  
  PHI = Private                                                                                                      
  Health Insurance;                                                                                                  
  MC = Medicare;                                                                                                     
  MA = Medicaid; VR                                                                                                  
  = Voc. Rehab; EMP                                                                                                  
  = Employer; VA =                                                                                                   
  Veterans                                                                                                           
  Administration; FR                                                                                                 
  = Free; OTH =                                                                                                      
  Other                                                                                                              
  ------------------ --------- --------- --------- --------- --------- -------- -------- --------- -------- -------- ---------

In terms of relative numbers, table 12.2 shows that whereas mobility
devices made up the bulk of AT (68.1 percent), about 35 percent of these
devices were paid for by respondents, and hearing devices that made up a
much smaller part of the "AT market" in terms of numbers were paid for
by the respondents in 68 percent of the cases.

[]{#__RefHeading___Toc114975754 .anchor}Table 12.2 Sources of Payment,
by Type of Assistive Device in Percent\*

<table style="width:100%;">
<colgroup>
<col style="width: 23%" />
<col style="width: 9%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
</colgroup>
<tbody>
<tr class="odd">
<td></td>
<td colspan="11"><em>Proportion of Payment by Payer in
Percent.</em></td>
</tr>
<tr class="even">
<td><strong>Device</strong></td>
<td><strong>% of Total</strong></td>
<td><h5 id="self"><strong>SELF</strong></h5></td>
<td><strong>F/H</strong></td>
<td><strong>PHI</strong></td>
<td><strong>MC</strong></td>
<td><strong>MA</strong></td>
<td><strong>VR</strong></td>
<td><strong>EMP</strong></td>
<td><strong>VA</strong></td>
<td><strong>FR</strong></td>
<td><strong>OTH</strong></td>
</tr>
<tr class="odd">
<td>All anatomical devices</td>
<td><strong>4.3</strong></td>
<td>28.1</td>
<td>0.0</td>
<td>25.0</td>
<td>12.5</td>
<td>3.1</td>
<td>0.0</td>
<td>9.4</td>
<td>15.6</td>
<td>0.0</td>
<td>6.3</td>
</tr>
<tr class="even">
<td>All mobility devices</td>
<td><strong>68.1</strong></td>
<td>37.7</td>
<td>1.6</td>
<td>16.3</td>
<td>20.7</td>
<td>4.8</td>
<td>2.0</td>
<td>2.2</td>
<td>4.4</td>
<td>8.6</td>
<td>4.8</td>
</tr>
<tr class="odd">
<td>All hearing devices</td>
<td><strong>9.4</strong></td>
<td>68.1</td>
<td>1.4</td>
<td>5.8</td>
<td>5.8.</td>
<td>4.3</td>
<td>1.4</td>
<td>1.4</td>
<td>7.2</td>
<td>1.4</td>
<td>2.9</td>
</tr>
<tr class="even">
<td>All vision devices</td>
<td><strong>1.4</strong></td>
<td>70.0</td>
<td>0.0</td>
<td>10.0</td>
<td>0.0</td>
<td>0.0</td>
<td>10.0</td>
<td>0.0</td>
<td>0.0</td>
<td>0.0</td>
<td>10.0</td>
</tr>
<tr class="odd">
<td>All asst. transportation tech.</td>
<td><strong>2.2</strong></td>
<td>43.8</td>
<td>0.0</td>
<td>18.8</td>
<td>18.8</td>
<td>6.3</td>
<td>6.3</td>
<td>0.0</td>
<td>6.3</td>
<td>0.0</td>
<td>0.0</td>
</tr>
<tr class="even">
<td>All personal/medical use AT</td>
<td><strong>6.9</strong></td>
<td>13.7</td>
<td>0.0</td>
<td>29.4</td>
<td>21.6</td>
<td>9.8</td>
<td>0.0</td>
<td>5.9</td>
<td>3.9</td>
<td>5.9</td>
<td>9.8</td>
</tr>
<tr class="odd">
<td>All struct. home modifications</td>
<td><strong>1.8</strong></td>
<td>46.2</td>
<td>7.7</td>
<td>0.0</td>
<td>15.4</td>
<td>23.1</td>
<td>0.0</td>
<td>0.0</td>
<td>0.0</td>
<td>0.0</td>
<td>7.7</td>
</tr>
<tr class="even">
<td>All AT/IT in the home</td>
<td><strong>5.4</strong></td>
<td>52.5</td>
<td>2.5</td>
<td>12.5</td>
<td>7.5</td>
<td>2.5</td>
<td>2.5</td>
<td>10.0</td>
<td>2.5</td>
<td>7.5</td>
<td>0.0</td>
</tr>
<tr class="odd">
<td>All other AT</td>
<td><strong>0.5</strong></td>
<td>75.0</td>
<td>0.0</td>
<td>25.0</td>
<td>0.0</td>
<td>0.0</td>
<td>0.0</td>
<td>0.0</td>
<td>0.0</td>
<td>0.0</td>
<td>0.0</td>
</tr>
<tr class="even">
<td><strong>All</strong></td>
<td><strong>100.0</strong></td>
<td>38.1</td>
<td>1.5</td>
<td>16.1</td>
<td>17.8</td>
<td>5.2</td>
<td>1.9</td>
<td>3.0</td>
<td>4.9</td>
<td>6.8</td>
<td>4.7</td>
</tr>
<tr class="odd">
<td colspan="12"><strong>*Legend:</strong> SEL = Self; F/H = Family or
Household Member; PHI = Private Health Insurance; MC = Medicare;
MA = Medicaid; VR = Voc. Rehab; EMP = Employer; VA = Veterans
Administration; FR = Free; OTH = Other</td>
</tr>
</tbody>
</table>

The smallest share of out-of-pocket expenses for AT went toward
"medically needed or necessary" devices such as respirators or oxygen
tanks (about 14 percent), as third parties such as private health
insurance, Medicare or Medicaid paid over 60 percent of these expenses.
These same agencies also paid for anatomical devices or assistive
transportation technologies in about half of the cases, but paid very
little for hearing, vision or communication AT.

Technologies that foster independence and community integration (home AT
and communication devices) were paid for in large part by the
respondents themselves. Figure 12.3 shows this pattern in more detail.

[]{#__RefHeading___Toc114975470
.anchor}![](media/image66.wmf){width="6.0in"
height="3.1756944444444444in"}Figure 12.3 Share of Out--of--Pocket
Expenses, by Type of AT

A glance at out-of-pocket expenditures for AT illustrates the impact of
third parties who paid for AT that enhances mobility and personal
functioning. In this domain, out-of-pocket expenses were the lowest. The
middle range of third party involvement limited payments to about half
of transportation and home AT/home modification expenses. Although most
important for functioning in public environments such as work, school
and the community, sensory and communication enhancing technologies were
least likely to be paid for by third parties (i.e., they had to be paid
for by persons with disabilities who often did not have the means to pay
for these sometimes very expensive technologies).

In the following section, the results of a variable-by-variable
discriminant function analysis of the relationship between respondent
characteristics and sources of payment for AT is presented in both table
and graphic form. The purpose of these analyses is to show what factors
associated with disability influence the way AT was paid for. Table 12.3
below shows the values for the discriminant function analysis in a
variable-by-pay source matrix. Numbers in bold type indicate a value
well within the top quartile of absolute values. As mentioned earlier,
the most often mentioned payment source was self or a family member
living in the household, followed by private health insurance and
Medicare.

[]{#__RefHeading___Toc114975755 .anchor}Table 12.3 Respondent
Characteristics and Sources of Payment\*

<table style="width:100%;">
<colgroup>
<col style="width: 23%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
</colgroup>
<tbody>
<tr class="odd">
<td><strong>Characteristic / Source</strong></td>
<td><strong>SELF</strong></td>
<td><h5 id="foth"><strong>F/OTH</strong></h5></td>
<td><strong>PHI</strong></td>
<td><strong>MC</strong></td>
<td><strong>MA</strong></td>
<td><strong>VR</strong></td>
<td><strong>EMP</strong></td>
<td><strong>School</strong> <em><sup>a</sup></em></td>
<td><strong>VA</strong></td>
<td><strong>FR</strong></td>
<td><strong>OTH</strong></td>
</tr>
<tr class="even">
<td>Working, Not Working</td>
<td><strong>0.34</strong></td>
<td>0.18</td>
<td>-0.02</td>
<td><strong>-1.17</strong></td>
<td>-0.23</td>
<td><strong>0.33</strong></td>
<td><strong>0.48</strong></td>
<td>0.23</td>
<td>0.04</td>
<td><strong>-0.27</strong></td>
<td>0.09</td>
</tr>
<tr class="odd">
<td>Education: High, Low</td>
<td>0.24</td>
<td>0.01</td>
<td>0.23</td>
<td><strong>-0.82</strong></td>
<td><strong>-0.31</strong></td>
<td>0.13</td>
<td>0.12</td>
<td>0.08</td>
<td><strong>0.26</strong></td>
<td>-0.12</td>
<td>0.19</td>
</tr>
<tr class="even">
<td>Impairment: Severe, Mild</td>
<td><strong>-0.32</strong></td>
<td>-0.22</td>
<td>-0.03</td>
<td><strong>0.59</strong></td>
<td>-0.01</td>
<td>0.01</td>
<td>-0.15</td>
<td><strong>-0.26</strong></td>
<td>0.10</td>
<td>-0.10</td>
<td><strong>0.40</strong></td>
</tr>
<tr class="odd">
<td>AT Opinion: High, Low<sup>b</sup></td>
<td>-0.18</td>
<td><strong>-0.29</strong></td>
<td><strong>0.52</strong></td>
<td>0.10</td>
<td>-0.10</td>
<td>-0.01</td>
<td>-0.14</td>
<td>-0.06</td>
<td>0.12</td>
<td>-0.21</td>
<td><strong>0.43</strong></td>
</tr>
<tr class="even">
<td>Personal Income: High, Low</td>
<td>0.14</td>
<td>0.12</td>
<td>-0.01</td>
<td><strong>-0.32</strong></td>
<td><strong>-0.38</strong></td>
<td>0.10</td>
<td><strong>0.29</strong></td>
<td>0.13</td>
<td><strong>0.29</strong></td>
<td>-0.17</td>
<td>-0.19</td>
</tr>
<tr class="odd">
<td>Age: High, Low</td>
<td>-0.07</td>
<td>0.17</td>
<td>-0.22</td>
<td><strong>0.52</strong></td>
<td>-0.23</td>
<td>-0.04</td>
<td>-0.08</td>
<td>0.09</td>
<td>0.16</td>
<td>-0.12</td>
<td>-0.19</td>
</tr>
<tr class="even">
<td>Family Income: High, Low<sup>c</sup></td>
<td>0.10</td>
<td>0.14</td>
<td>0.05</td>
<td>-0.23</td>
<td><strong>-0.29</strong></td>
<td>0.09</td>
<td>0.08</td>
<td>0.10</td>
<td>0.22</td>
<td>-0.14</td>
<td>-0.13</td>
</tr>
<tr class="odd">
<td>AT Opinion: High, Low</td>
<td>-0.05</td>
<td>0.04</td>
<td>-0.04</td>
<td>0.24</td>
<td>-0.06</td>
<td>0.00</td>
<td>0.03</td>
<td>0.01</td>
<td>-0.04</td>
<td>-0.18</td>
<td>0.05</td>
</tr>
<tr class="even">
<td>Race: White, Nonwhite</td>
<td>0.01</td>
<td>0.10</td>
<td>0.02</td>
<td>0.13</td>
<td>-0.16</td>
<td>-0.01</td>
<td>-0.03</td>
<td>0.03</td>
<td>0.07</td>
<td>-0.03</td>
<td>-0.11</td>
</tr>
<tr class="odd">
<td colspan="12"><strong>*Legend:</strong> SEL = Self; F = Family; PHI =
Private Health Insurance; MC = Medicare; MA = Medicaid; VR = Voc. Rehab;
EMP = Employer; VA = Veterans Administration; FR = Free; OTH =
Other</td>
</tr>
<tr class="even">
<td colspan="12"><p><em><sup>a</sup> This category had so few
respondents that the percentage registered as zero in most cases. As a
result, this category has not been included in subsequent
tables.</em></p>
<p><em><sup>b</sup> These percentages reflect responses to questions 1–6
on the survey (see p. 189).</em></p>
<p><em><sup>c</sup> These percentages reflect responses to questions
7–10 on the survey (see p. 189).</em></p></td>
</tr>
</tbody>
</table>

Figure 12.4 compares the frequency of mention with the discriminant
power of the various payment sources. The values for the discriminating
factors "DF" and "Percent Mention" have been normalized. The payment
sources are displayed from top to bottom in descending order of DF. The
figure indicates that Medicare played the major role as a discriminating
source of payment.

[]{#__RefHeading___Toc114975471
.anchor}![](media/image67.wmf){width="6.0in"
height="3.5854166666666667in"}Figure 12.4 Source of Payment for AT,
Normalized Mention vs. DF

#### Occupational Status

The variable producing the greatest overall DF was the dichotomy
"Working, Not Working."

[]{#__RefHeading___Toc114975472
.anchor}![](media/image68.wmf){width="6.5in"
height="3.2805555555555554in"}Figure 12.5 Discriminant Function
Analysis: Working, Not Working

Those persons using AT who were working were much less likely to receive
payment from Medicare than those who were not working. The situation is
about the same when the comparison was made between those working and
those unable to work because of disability, as shown in figure 12.6.

[]{#__RefHeading___Toc114975473
.anchor}![](media/image69.wmf){width="6.5in"
height="3.176388888888889in"}Figure 12.6 Discriminant Function Analysis:
Working, Unable to Work

#### Education

Education emerged as the single most influential factor in determining
AT use. Among those who used AT, the same variable produced a pattern
similar to that produced by the working/not working and working/unable
to work dichotomies.

[]{#__RefHeading___Toc114975474
.anchor}![](media/image70.wmf){width="6.5in" height="3.45in"}Figure 12.7
Discriminant Function Analysis: High Education, Low Education

Respondents who used AT and who were above the median in educational
level attained were significantly less likely to mention Medicare as a
payment source than those whose level of education was below the median.

#### Severity of Impairment

Severity of impairment for AT users was dichotomized by using only those
categorized as mild or severe in level of impairment.

[]{#__RefHeading___Toc114975475
.anchor}![](media/image71.wmf){width="6.5in"
height="2.902083333333333in"}Figure 12.8 Discriminant Function Analysis:
Impairment, Severe--Mild

Here, the pattern shown in the previous two variables, work status and
education, was reversed. The more severely impaired respondents were
more likely to use Medicare than the mildly impaired.

*AT Attitudes and Opinions*

The questionnaire contained six questions about the respondents'
attitudes on the benefits of AT and on receiving information about AT
and how to obtain it. A total opinion score was created, averaging the
scores across all items answered for each respondent, and the
respondents were scored as positive in attitude for scores below the
median (strong agreement with the positive statement earned a score of
1; strong disagreement was scored as 4) and negative in attitude for
scores above the median.

[]{#__RefHeading___Toc114975476
.anchor}![](media/image72.wmf){width="6.0in"
height="2.8055555555555554in"}Figure 12.9 Discriminant Function
Analysis: AT Opinion, Positive--Negative

Figure 12.9 indicates that those individuals who used private health
insurance were more positive in attitude compared to those using any of
the other assigned categories of payment.

*Personal Income*

Each respondent was asked the amount of income earned in the previous
year. The question was answered by 1,243 (88 percent) of respondents
overall, and 778 (87 percent) of respondents who used AT. While there
was some indication that those with lower personal incomes were more
likely to employ Medicare and Medicaid and less likely to have had their
AT provided by a VA program or an employer, the values shown in figure
12.10 are not compelling, and should not be given great weight in
evaluating the strength of the variable. Recall that the median personal
income was in the \$10,000--\$14,999 range; a significant proportion of
those above the median range in personal income still fell below the
poverty line.

[]{#__RefHeading___Toc114975477
.anchor}![](media/image73.wmf){width="6.5in"
height="2.8819444444444446in"}Figure 12.10 Discriminant Function
Analysis: Personal Income, High--Low

*Age*

Figure 12.11 indicates that the older respondents were more likely to
use Medicare. No other values exceed what might be expected by chance.
Furthermore, family income, race and opinions about changes in policies
over the last 10 years had little or no influence on how AT was paid
for.

[]{#__RefHeading___Toc114975478
.anchor}![](media/image74.wmf){width="6.5in"
height="2.848611111111111in"}Figure 12.11 Discriminant Function
Analysis: Age, Older--Younger

### Summary and Conclusion

This study revealed an important overall trend in payment practices for
AT. About 10 years ago, "medically necessary" AT to enhance physical
functioning and mobility was paid in part or in full by third parties.
This pattern of use and payment did not appear to have changed
significantly. Low-tech devices, adaptations and accommodations used by
persons with disabilities for purposes of improved mobility remained the
bulk of AT and were paid by third parties in more than half of the
cases. In 9 percent of the cases, mobility devices were provided free.

About 10 years ago, home AT and other environmental accommodations were
paid, according to some estimates, by persons with disabilities and
their families in 67 to 75 percent of the cases, whereas in 2001 this
share of the burden to persons with disabilities dropped to less than 60
percent. In some cases, Medicaid or Medicare paid for railings and other
structural adaptations, and in almost 8 percent of the cases, smaller
home AT items were obtained at no cost.

With advances in modern technology, however, a third type of AT---mostly
high-tech and high-cost---demanded the largest share of payment from
personal funds (about 70 percent and more). These items included
technologically advanced wheelchairs and scooters, hearing devices,
vision technology and high-tech communication devices. The latter were
particularly important for persons with disabilities who want to
participate in school, at work, and in the community, and who are most
likely to depend on financial assistance or alternative financing
mechanisms to obtain the needed devices and technologies.

To answer the question of whether inadequate funding of AT continues to
be a barrier to the more equal inclusion of persons with disabilities in
society, this study found that while the absolute number of persons
paying for AT themselves continued to grow from over 6 million in 1990
to about 10 million in 2001, the proportion of persons with disabilities
who paid for AT appears to have decreased from about 48 percent in 1990
to under 40 percent in 2001. Whether or not this decrease was due at
least in part to the *AT Act* is difficult to ascertain. Findings from
this survey published elsewhere (Carlson et al., 2002) suggest that
technology-related legislation has had a positive impact on the lives of
persons with disabilities. We are therefore inclined to propose this as
a hypothesis to be tested by further research.

# Summary and Conclusion

Among the key components of the technology-related assistance
legislation was the nationwide effort to raise awareness about the
benefits of assistive technology and environmental
accommodations---namely that with the use of AT, persons with
disabilities could live more independent and productive lives. To help
with the selection and acquisition of appropriate AT, Congress included
a provision in the *Tech Act* that allowed state-based agencies and
organizations to provide direct support and assistance to persons with
disabilities and their families who needed such services.

We began our survey by asking respondents about their occupational
status. We found that the modal response for all (52 percent) was that
they are unable to work because of their disabilities. The next largest
category was respondents working; fewer than 10 percent were able to
work but were unemployed. When we asked respondents to explain in detail
what condition was responsible for their disabilities, osteoarthritis,
hearing loss, the lingering effects of injury, back disorders, multiple
sclerosis, diabetes and heart ailments were the most often mentioned
causes.

Respondents were asked about their need for and the use of assistive
technology in getting to school and to work, in school or at work, in
the home, and in the community. Of all respondents, 901 (64 percent)
used some assistive technology. Use at school and at work was 36
percent; use at home was 49 percent; and use in the community was 50
percent. Most of the assistive devices used were designed to enhance
mobility: canes, crutches, walkers, scooters and wheelchairs. Hearing
aids, oxygen tanks and other personal-use devices were also among the
most frequently used devices.

We then asked respondents about the process of acquiring such
technology: how they learned about it, whether they had help acquiring
it, how it was paid for, whether they had attempted to get help, and
their successes or failures in these attempts. The most mentioned
information source was a physician or other health care professional,
accounting for 53 percent of all sources mentioned. The only other
frequently mentioned sources were family and friends (15 percent) and
vocational rehabilitation counselors (13 percent). We found that
physicians and health care professionals provided information to all
groups without significant variance. Respondents who used family and
friends as a source of information tended to be older, poorer,
unemployed, more severely impaired and nonwhite; most significantly,
they rendered a more negative opinion of the amount and utility of
information they had received about AT, and about the helpfulness of AT
in general. Persons obtaining information from vocational rehabilitation
counselors tended to be better educated, nonwhite, and unemployed, and
had a more positive opinion about AT. In all, over 90 percent of the
respondents reported being satisfied or very satisfied with the help
that they received in the selection and purchase of AT.

More than one-third of the respondents had their devices paid for by
themselves or by family members; and a like number paid for them with
private insurance, Medicare and Medicaid. Only about one in five
respondents had help in the selection and purchase of their assistive
technology. Most of those who had asked for help received it, but the
prevailing sentiment was that the respondents did not feel the need to
ask for help.

We asked respondents about their use, need and ability regarding
information technology, such as telephones and computers. We found
virtually no difficulties encountered in using telephones, and
significantly more in the use of computers; however, the majority of
respondents were well served in both areas.

The analysis included respondents' reported behaviors in leaving the
home, the need for modifications to access buildings and facilities
outside the home, and the need for personal assistance, all measured
against the variables of severity of impairment, education, income, race
and age. The primary finding was that socioeconomic factors play the
larger role in determining who, among persons with disabilities, had the
ability to be integrated into the community. The poor, young,
undereducated, and nonwhite encountered more barriers to community
integration**.**

We asked respondents about access and accommodations in the buildings
and living spaces they encountered in schools, at work, at home and in
their communities. We found greater needs in the home than in the
community and at school, and the least need at work---most likely
because working persons with disabilities tended to be less impaired
than those unable to work because of their disability. We also learned
that one in six respondents could be classified as homebound, having not
left their homes once in the two weeks preceding the interview.

The attitude and opinion questions centered on: information about AT and
how to obtain it; and the effects of AT on the respondents' lives. The
respondents asserted that:

-   They had received little information about assistive technology and
    less on how to acquire it, but those who had received information
    said that it was helpful; and

-   AT had made them more productive and more aware of their rights, but
    had not substantially reduced their dependence on other people.

We also asked their views on how AT had changed compared to 10 years
ago. The findings suggest that since the passage of the *Tech Act*:

-   The availability of, funding for, access to, and provision of AT
    devices and services have increased;

-   Awareness of AT-related laws, regulations and policies has increased
    over the past 10 years;

-   Awareness and knowledge of benefits of AT devices and services have
    increased; and

-   Awareness of the needs of persons with disabilities age 18 and over
    has increased.

We asked a series of demographic questions. The primary finding was that
persons with disabilities were well below the norm in personal income.
Furthermore, we were able to document and quantify the extent to which
gender and race were distributed in the disabled population. In short,
it was more likely that persons with disabilities were female than male
when compared to national statistics, but race did not seem to be a
factor.

Another factor that was considered to be of great importance in
disability research was age. But there was in the data no statistical
relationship between age and severity of impairment or AT use, and the
relationship between age and race (Nonwhites were significantly younger
than Whites in the sample) merely mirrors the national norm.
Furthermore, while age is a factor worthy of consideration in discussing
ability, there was also a rationale for making a distinction between the
gradual lessening of abilities due to aging and the condition of
disability *per se* that is independent of aging. In the 2001 study, it
would seem that our respondents measured their levels of ability against
their age peers, rather than some ageless ideal of performance.

Persons who used the assistance of another person to conduct their daily
lives differed from other persons with a disability in the following
ways:

-   They were more likely to use some form of assistive technology;

-   They were more severely impaired;

-   Their levels of personal income were much lower; and

-   They were much less likely to be employed.

However, we found no significant differences in their races, levels of
education, or ages. When we compared the attitude statements of the
respondents who used personal assistance to those of the other persons
with disabilities, we found the greatest difference was that personal
assistance users were less positive about AT use decreasing the need for
personal assistance. The obvious interpretation is that a large segment
of personal assistance services was outside of the range of activities
that AT can address. This in turn points out that the greatest need in
the AT field is not for technological advancement in existing AT, but
the extension of the range of AT to areas that are now addressed only by
the assistance of another person.

In the case of severity of impairment, the research did document the
widely-held belief that the more severely impaired a person was, the
more likely that person needed or used assistive technology. The
measurement of severity was based on the independent assessment of the
level of severity of all respondent conditions reported, assigning
numerical weights to the conditions and then summing the weights for
individuals. This statistical evaluation was done in lieu of a
case-by-case analysis.

Open-ended questions provided much qualitative and quantitative detail.
While our analysis of these had centered on the quantitative---the
prevalence of predisposing conditions and the types of assistive
technologies employed by the respondents, one qualitative result is
worth noting. The population of persons with disabilities strongly
rejects the perception of themselves as being in need. Rather, the
quality of their responses shows considerable pride in their ability to
live full and productive lives regardless of the severity of their
impairments.

The survey revealed that the widely held belief among experts in the
field of assistive technology services that money is the key was
erroneous. Instead, we found that there is a strong, positive
relationship between level of education and both personal and family
income, but level of income and AT use were negatively correlated.

Education's role in the use of assistive technology was the major
unanticipated finding. We found that persons with disabilities who had
attained a higher level of education were more likely to use AT. In the
absence of more specific data, we cannot explain what drives this
relationship.

The relatively small sample size of this national survey (n = 1,414) and
the low number of responses indicating a state-based agency as the
source of information prevented us from detecting significant
differences between states clustered by total population and population
density.

Two related observations, also needing further study, point out that
state-based agencies providing technical assistance to persons with
disabilities using or needing AT appear to have raised awareness about
their existence in a relatively small number of respondents (about 3 to
5 percent). This proportion may be higher assuming that a large
proportion of pamphlets and publications mentioned as a source of
information by 7 percent of the respondents originated in state-based
technical assistance agencies. Second, centers for independent living
and the Internet as a source of information about AT were mentioned each
by 1 percent of respondents. These findings suggest that two rich
sources of information about AT may be underutilized.

The major shortfall of all studies about technical assistance on AT has
been the lack of state-based data on how well the technical assistance
programs have worked in the past, and if there are reasons to believe
that future investment in these programs will yield measurable benefits
for persons with disabilities. Such information is crucial for
understanding how the various state-based programs have worked,
considering that each state had a large amount of independence and
control over what services were provided, to whom, by whom, when, where
and how. States and territories provided different amounts of additional
funding in addition to federal funds, but more importantly, the
population size of the states and their political, economic and
geographic characteristics may have affected the quality and amount of
AT services provided differently to persons with disabilities as well.
There is no evidence today that can tell us how well the 56 programs
have worked as a whole or individually when compared to each other.

Finally, the effectiveness of a federal program to assist persons with
disabilities in the selection and purchase of AT should be measured in
terms of specific outcomes, such as employment and higher levels of
social integration. There is anecdotal evidence of how AT has helped
persons with disabilities and their families, but AT alone is not the
sole contributor to such success. Other factors such as adequate
education and job training of AT users play a major role as well. In
that regard, more research that measures the direct and indirect
benefits resulting from the purchase and use of AT in conjunction with
these other factors is needed.

# References

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http://quickfacts.census.gov/qfd/states/00000.html (accessed 7/13/05).

Uslan, M.M. (1992). Barriers to acquiring assistive technology: Cost and
lack of information. *Journal of Visual Impairment and Blindness, 86,*
402-407.

Watts, J.H., Erickson, A.E., Houde, L., Wilson, E., & Maynard, M.
(1996). Assistive device use among the elderly: A national data-based
study. *Physical and Occupational Therapy in Geriatrics, 14,* 1-18.

Wehmeyer, M.L. (1998). National survey of the use of assistive
technology by adults with mental retardation. *Mental Retardation*,
*36,* 44-51.

Wendt-Harris, W., Pollack, P., & Lassere, A. (2001). What SHHH members
say about hearing aids and audiological services. *Hearing Loss, 22,*
25-29*.*

White, E. A., Wepner, S.B., & Wetzel, D.C. (2003). Accessible education
through assistive technology. *Technical Horizons in Education, T.H.E.
Journal Online*. Available at
http://www.thejournal.com/magazine/vault/A4321.cfm (accessed 7/13/05).

World Health Organisation. (2001). *International classification of
functioning, disability and health.* Geneva: World Health Organisation.

Wunderlich, G.S., Rice, D.P., & Amado, N.L. (Eds.). (2002). *The
dynamics of disability. measuring and monitoring disability for social
security purposes*. Washington, D.C.: National Academy Press.

# Appendix A: Screening Instrument

Hello, my name is \_\_\_\_\_\_\_\_\_\_, and I am calling from the
University of Michigan Survey Research Center in Ann Arbor, Michigan.
We're doing a survey for the RESNA, the Rehabilitation Engineering
Society of North America, \[if asked to define, RESNA is a group of
people who design, engineer and build devices and technology to help
persons with disabilities\] about people who might use, need or want an
assistive device or assistive technology to help them in their daily
lives.

What we mean by an assistive device is any equipment that helps people
who have some limitations on their abilities to complete tasks with less
effort, or more efficiently. For instance, people with a condition that
limits their mobility might use crutches, a walker or a wheelchair, or
people with carpal tunnel syndrome might use a special computer; in
addition, people with some hearing loss might use a hearing aid, or a
special telephone.

Assistive technology is a much broader category: it includes such things
as software to help people with brain injuries to use computers and
automatic door openers**.**

Your telephone number was taken from a computer-generated list. If you
or anyone in your household qualifies for and chooses to participate in
the study, we will pay you \$20 as a token of our appreciation. Your
participation is completely voluntary, and your responses will be kept
strictly confidential.

In order to determine whether your household qualifies, I need first to
make a list of the members of your household, by obtaining only their
first names or their relationship to you---whichever you prefer---and
then ask a couple of brief questions. I am listing you first. \[Record
"informant" or informant's first name, in row 1 of "person" column.\]
Are there any other people 18 or older living there with you? \[Ask
informant for either relationship to him or her or first names of other
household members 18 or older and list them in subsequent rows in the
"Person" column.\]

> 1\. Does anyone in your household who is over age 18 use or need any
> of the following special equipment to perform daily tasks and
> activities in the home, at school or at work, or in the community:
>
> I-1 A wheelchair? (Who is that?) \[Mark next to person in column I-1\]
>
> I-2 A special bed? (Who is that?) \[Mark next to person in column
> I-2\]
>
> I-3 A special telephone? (Who is that?) \[Mark next to person in
> column I-3\]
>
> I-4 The assistance of another person? (Who is that?) \[Mark next to
> person in column I-4\]
>
> I-5 A cane, crutches or a walker? (Who is that?) \[Mark next to person
> in column I-5\]
>
> I-6 Any other type of assistive device? (Who is that?) \[Mark next to
> person in column I-6\]
>
> 2\. Does anyone in your household who is over age 18 have a condition
> that prevents or greatly limits such basic physical activities as:
>
> II-1 Working at a job or business? (Who is that?) \[Mark next to
> person in column II-1\]
>
> II-2 Walking, lifting or carrying? (Who is that?) \[Mark next to
> person in column II-2\]
>
> II-3 Dressing, bathing or getting around inside the home? (Who is
> that?) \[Mark next to person in column II-3\]
>
> II-4 Going outside the home alone to shop or visit a doctor's office?
> (Who is that?) \[Mark next to person in column II-4\]
>
> II-5 Learning, remembering or concentrating? (Who is that?) \[Mark
> next to person in column II-5\]
>
> 3\. Does anyone in your household who is over age 18 have any of the
> following conditions:

III-1 Blindness? (Who is that?) \[Mark next to person in column III-1\]

III-2 Severe vision impairment? (Who is that?) \[Mark next to person in
column III-2\]

> III-3 A hearing impairment that is not as severe as deafness? (Who is
> that?) \[Mark next to person in column III-3\]

III-4 Deafness? (Who is that?) \[Mark next to person in column
III-4\][^15]

  ---------- -- ---- ---- ---- ---- ---- ---- -- ----- ----- ----- ----- ----- -- ------ ------ ------ ------
  Person        I\   I\   I\   I\   I\   I\      II\   II\   II\   II\   II\      III\   III\   III\   III\
                1    2    3    4    5    6       1     2     3     4     5        1      2      3      4

                                                                                                       

                                                                                                       

                                                                                                       

                                                                                                       

                                                                                                       

                                                                                                       

                                                                                                       
  ---------- -- ---- ---- ---- ---- ---- ---- -- ----- ----- ----- ----- ----- -- ------ ------ ------ ------

Interviewer: Record the person with the highest priority condition
(lowest Roman and Arabic numbers) on the line if one or more adults in
the household have conditions. If no adult household member has any of
these conditions, thank the informant and terminate contact.

Person's name or relationship to informant

I would now like to speak with \[PERSON\]. Is he/she available? \[If
yes, go to questionnaire; if no, schedule a callback.\]

Interviewer: If Informant says that \[PERSON\] is unable to do the
interview over the phone *at all* (because of a disability such as
hearing impairment or because he/she does not speak English), ask: "Are
you or is someone else in the household able to answer some questions
about \[PERSON'S\] use of technology and services or his/her need for
technology and services?"

  ----------------------- ----------- ----------------------- -----------
  Yes                                 No                      

  ----------------------- ----------- ----------------------- -----------

Proxy name or relationship to \[PERSON\]

Are you (or this other person) available to answer the questions now?
\[If yes, go to proxy questionnaire; if no, schedule a call back. If no
one in the household can serve as proxy, explain in call notes on page 4
of the coversheet.

#  {#section-2 .unnumbered}

# Appendix B: Simplified Questionnaire---Content Only

This version presents the instrument in minimal complete version,
without repetition for designated subsamples.

######### Section A: Employment And Disability Status

**Status**

A1. Are you currently: *Choose all that apply.*

> Enrolled in school or any other educational program (college or
> university)? 1
>
> Gainfully employed or running a business? 2
>
> Able to work, but currently not working? 3
>
> Unable to work because of your disability? 4
>
> A homemaker? 5
>
> Retired? 6
>
> Anything else (specify) (vol) 7

A1b. *If respondent answered retired, probe for reason.*

> Did you:
>
> Retire, and then become disabled? 1
>
> Take an early retirement because of disability? 2
>
> Go on disability without becoming eligible for retirement benefits? 3
>
> Never worked because of disability? 4

A2. What condition or limitation do you have that impairs your
functioning? \[OE\]

######### Sections B, C, D and E: Assistive Devices 

These questions were asked of respondents at school or work (if
appropriate), and of all respondents about assistive devices at home and
in the community.

Questions here show the word "school;" content was repeated for work,
home and community.

*Interviewer reads*: As I mentioned earlier, an assistive device is any
equipment that helps people who have some limitations on their abilities
to function more efficiently, while an assistive service is any service
that directly helps someone select and get or buy any assistive device.

1\. Do you use an assistive technology device or service to help you
with getting to or from school? Y/N

> 2\. Do you use an assistive technology device or service to help you
> while you are at school? Y/N
>
> 3\. What is the assistive device or service that you are now using?
> (Any others?)

4\. How did you learn about the device(s) or service(s)?

######### *Choose all that apply; do not read list.*

> Doctor or Other Health Care Professional 1
>
> Vocational Rehabilitation Counselor 2
>
> Family, Friends and Neighbors 3
>
> Pamphlets, Magazines and Announcements 4
>
> Centers for Independent Living 5
>
> Disability Business Technical Assistance Centers 6
>
> *Tech Act* Organizations or Other State Organizations 7
>
> Yellow Pages 8
>
> Television/Radio 9
>
> Internet 10
>
> Anything Else (Specify) (Vol) 11
>
> 5\. Where did you get the device(s) or service(s)?
>
> ***If respondent mentions a drugstore, pharmacy or department store
> such as Wal-Mart or K-Mart, please probe:***
>
> Doctor's Office 1
>
> Hospital or Clinic (Not VA) 2
>
> VA Hospital 3
>
> Vocational Rehabilitation Facility 4
>
> Nursing Home 5
>
> Medical or Orthopedic Supply Store 6
>
> Prescription from Drugstore or Pharmacy, Including Wal-Mart, K-Mart or
> Other Dept. Store Pharmacy.. ......7
>
> Over-the-Counter from Drugstore or Department Store, Including
> Wal-Mart or K-Mart 8
>
> Mail Order Catalogue 9
>
> Anything Else (Specify) (Vol) 10

6.  Who paid for the device or service?

> Self or Family in Household 1
>
> Family Not in Household 2
>
> Private Health Insurance 3
>
> Medicare 4
>
> Medicaid 5
>
> Rehabilitation Program 6
>
> Employer 7
>
> School System 8
>
> VA Program 9
>
> Free 10
>
> Anything Else (Specify) (Vol) 11
>
> 7\. Overall, how satisfied are you with the device(s) or
> service(s)---would you say very satisfied, somewhat satisfied,
> somewhat dissatisfied, or very dissatisfied?
>
> 8\. Did you receive help from an agency or organization during the
> selection and purchase of the device(s) or service(s)? \[Y/N\]
>
> 9\. Overall, how satisfied were you with the help you received---would
> you say very satisfied, somewhat satisfied, somewhat dissatisfied, or
> very dissatisfied?

10\. Did you seek help from an organization or agency with the selection
and purchase of the device(s) or service(s)? \[Y/N\]

> 11\. From which agency or organization did you seek help? (Any
> others?)
>
> 12\. What were your reasons for not contacting an organization or
> agency? (Any other reasons?)
>
> 13\. In addition to the devices that you are using now, are there any
> additional assistive technology devices or services that would help
> you with getting to or from school? \[Y/N\]
>
> 14\. In addition to the devices that you are using now, are there any
> additional assistive technology devices or services that would help
> you while you are at school? \[Y/N\]
>
> 15\. What assistive devices or services would you use? (Any others?)

16. Is there an assistive technology device or service that would help
    you with getting to or from school? \[Y/N\]

> 16b. What assistive devices or services would you use? (Any others?)
>
> 16c. To what extent would these additional devices or services help?
> Would you say a lot, somewhat, or a little?
>
> 17a. Is there an assistive technology device or service that would
> help you while you are at school? \[Y/N\]
>
> 17b. What assistive devices or services would you use? (Any others?)
>
> 17c. To what extent would these additional devices or services help?
> Would you say a lot, somewhat, or a little?
>
> 18a. Have you ever tried to get a device or service without any
> success? \[Y/N\]
>
> 18b. What was the reason you were turned down? \[OE\]
>
> 18c. Are you aware you can get help to obtain the device or service?
> \[Y/N\]
>
> 19\. Where will you go to learn more about the device(s) or
> service(s)?

####### *Choose all that apply; do not read list.*

> Doctor or Other Health Care Professional 1
>
> Vocational Rehabilitation Counselor 2
>
> Family, Friends and Neighbors 3
>
> Pamphlets, Magazines and Announcements 4
>
> Centers for Independent Living 5
>
> Disability Business Technical Assistance Centers 6
>
> *Tech Act* Organizations or Other State Organizations 7
>
> Yellow Pages 8
>
> Television/Radio 9
>
> Internet 10
>
> Anything Else (Specify) (Vol) 11

20\. Do you plan to contact any agency or organization for help or
advice? \[Y/N\]

21\. Which agency or organization do you plan to contact? (Any others?)

22\. What are your reasons for not contacting any agency or
organization? \[OE\]

### Sections F, G and H: Telephone Use At School/Work/In Community

Since the interview was conducted via home telephone, none of the
telephone questions asked about availability at home. Questions here
show the word "school;" content was repeated for work and the community.

> 1\. Is there a telephone available for you to use at school? \[Y/N\]
>
> 2\. (Please remind me) Can you use a standard telephone without any
> assistance? \[Y/N\]
>
> 3\. (Please remind me) Do you need the help of another person to use
> the telephone? \[Y/N\]
>
> 4\. (Please remind me) Do you need any special modifications, such as
> TTY or relay services, in order to make a telephone call? \[Y/N\]
>
> 5\. Has any person or agency given you advice or help in using the
> telephone at school? \[Y/N\]
>
> 6\. What person or agency helped you? \[OE\] (Any others?)
>
> 7\. How did you learn about this service?

####### *Choose all that apply; do not read list.*

> Doctor or Other Health Care Professional 1
>
> Vocational Rehabilitation Counselor 2
>
> Family, Friends and Neighbors 3
>
> Pamphlets, Magazines and Announcements 4
>
> Centers for Independent Living 5
>
> Disability Business Technical Assistance Centers 6
>
> *Tech Act* Organizations or Other State Organizations 7
>
> Yellow Pages 8
>
> Television/Radio 9
>
> Internet 10
>
> Anything Else (Specify) (Vol) 11
>
> 8\. Have you had any difficulties in obtaining this service? \[Y/N\]
>
> 9\. What kind of difficulties have you had? \[OE\] (Any others?)

### Section J: Computer Use

> 1\. Is there a computer available for you to use at school?
>
> Yes 1
>
> No 5
>
> Yes, but not needed for school (vol) 2
>
> Yes, but do not know how to use (vol) 3
>
> No, but not needed for school (vol) 6
>
> No, but do not know how to use (vol) 7
>
> 2\. Is there a computer available for you to use at work?
>
> Yes 1
>
> No 5
>
> Yes, but not needed for school (vol) 2
>
> Yes, but do not know how to use (vol) 3
>
> No, but not needed for school (vol) 6
>
> No, but do not know how to use (vol) 7
>
> 3\. Is there a computer available for you to use at home?
>
> Yes 1
>
> No 5
>
> Yes, but do not know how to use (vol) 3
>
> No, but do not know how to use (vol) 7
>
> 4\. Is there a computer available for you to use in the community?
>
> Yes 1
>
> No 5
>
> Yes, but do not know how to use (vol) 3
>
> No, but do not know how to use (vol) 7
>
> 5\. (Is the/are any of the) computer(s) available to you connected to
> the Internet? \[Y/N\]
>
> 6\. Do you need the help of another person to use a computer? \[Y/N\]
>
> 7\. Do you need special modifications or accommodations in order to
> use a computer such as a special monitor, keyboard or accessories?
> \[Y/N\]

8\. Has any person or agency helped or advised you in using a computer?

> 9\. What person or agency helped you? \[OE\] (Any others?)

10\. How did you learn about this service?

######### *Choose all that apply; do not read list.*

> Doctor or Other Health Care Professional 1
>
> Vocational Rehabilitation Counselor 2
>
> Family, Friends and Neighbors 3
>
> Pamphlets, Magazines and Announcements 4
>
> Centers for Independent Living 5
>
> Disability Business Technical Assistance Centers 6
>
> *Tech Act* Organizations or Other State Organizations 7
>
> Yellow Pages 8
>
> Television/Radio 9
>
> Internet 10
>
> Anything Else (Specify) (Vol) 11

11\. Have you had any difficulties in obtaining this service? \[Y/N\]

12\. What kind of difficulties have you had? \[OE\] (Any others?)

######### Sections K, L, M and N: Access to Community Facilities

Questions here show the word "community;" content was repeated for work,
home and school.

1.  How many days in the last two weeks did you participate in social
    activities outside your home such as visiting friends and family,
    going to a restaurant or movie, or going to church?

> NONE / 1 / 2--4 / 5--9 / 10--13 / 14

######## If respondent answered NONE, these questions were not asked about community access.

> 2\. People who have physical impairments or health problems sometimes
> need assistance in obtaining access to all the places they need to go
> and to facilities and equipment they need to use. Do you need the help
> of another person to access or use public buildings and facilities
> such as libraries, government buildings, or public transportation, or
> restaurants, theaters, stores and shopping malls? \[Y/N\]
>
> 3\. Do you need special modifications, adaptations or accommodations
> to enter or use public buildings and facilities? \[Y/N\]

4\. Are there special modifications, adaptations or accommodations to
enable you to enter and use public buildings and facilities? \[Y/N\]

> 5\. Do you have access to public buildings and facilities? \[Y/N\]
>
> 6\. Have you tried to obtain help in getting special modifications?
> \[Y/N\]
>
> 7\. What agency or organization did you contact to get help? \[OE\]
> (Any others?)
>
> 8\. Do you plan to contact any agency or organization to obtain help
> in getting these special modifications? \[Y/N\]
>
> 9\. What agency or organization do you plan to contact to get help?
> \[OE\] (Any others?)
>
> 10\. What are your reasons for not planning to seek help from any
> agency or organization? \[OE\] (Any other reasons?)

######### Section P: Impact of Information and Assistance

PA. Now I'd like to ask you some questions about information and advice
on assistive devices that you may have received.

P1. Overall, how much information and advice have you received about
assistive technology? Would you say a lot, some, a little, or none?

P2. Overall, how much information and advice have you received about how
to obtain it? Would you say a lot, some, a little, or none?

P3. Overall, how much difference would you say that the information and
advice about assistive technology and how to obtain it has made in
increasing your level of learning, independence, productivity and
community integration? Would you say a lot, some, a little, or none?

P4. Overall, how much has information and advice about assistive
technology and how to obtain it helped you to become more aware of your
rights? Would you say a lot, some, a little, or none?

P5. How much has your use of assistive technology devices and services
decreased your need for help from another person? Would you say a lot,
some, a little, or none?

P6. To what extent have better-designed products and environmental
access features or universal design products reduced your need for
assistive technology devices and services? Would you say a lot, some, a
little, or none?

P7. Compared to 10 years ago, people are more aware of the need for
assistive technology devices and services for persons with disabilities.
Would you say that you strongly agree, agree, disagree, or strongly
disagree?

P8. Compared to 10 years ago laws or program policies have been changed
to help persons with disabilities to get assistive technology. Would you
say that you strongly agree, agree, disagree, or strongly disagree?

P9. Compared to 10 years ago more people are aware of assistive
technology and understand how it can benefit persons with disabilities.
Would you say that you strongly agree, agree, disagree, or strongly
disagree?

P10. Compared to 10 years ago it is easier to find assistance for
purchasing assistive technology devices and services. Would you say that
you strongly agree, agree, disagree, or strongly disagree?

######### Section Q: Demographics

Q1. What is your age?

18--25 1

26--35 2

36--45 3

46--55 4

56--65 5

66--75 6

76--85 7

\>85 8

Q2. Are you of Spanish or Latino origin? \[Y/N\]

> Yes 1
>
> No 5

Q3. Which of the following racial or ethnic group(s) best describes you?

####### *Choose all that apply; do not read list.*

> American Indian or Alaska Native 1
>
> Asian 2
>
> Black or African-American 3
>
> Native Hawaiian or Other Pacific Islander 4
>
> White/Caucasian 5
>
> Anything Else (Vol) 6

Q4. What is the highest grade of school or year of college you have
completed?

> None; Kindergarten 1
>
> 1--8 (Elementary) 2
>
> 9--12 (High School Graduate) 3
>
> 1--3 Yrs. College 4
>
> 4 Yrs. College Graduate 5
>
> 5+ Yrs. College 6

Q5. I am going to read you a list of income categories. Please tell me
which category best describes the total income of all members of your
family living in your house in 2000 before taxes. This figure should
include salaries, wages, pensions, dividends, interest, and all other
income.

\< \$5,000 ..1

\$5,000--\$9,999 ..2

\$10,000--\$14,999 ..3

\$15,000--\$19,999 ..4

\$20,000--\$24,999 ..5

\$25,000--\$34,999 ..6

\$35,000--\$49,999 ..7

\$50,000--\$69,999 ..8

\$70,000--\$89,999 ..9

\$90,000--\$109,999 10

\$110,000 + 11

Q6. Now we are interested in the income that you yourself received in
2000. This does not include any of the income received by the rest of
your family. Please stop me when I get to your income category.

\< \$5,000 ..1

\$5,000--\$9,999 ..2

\$10,000--\$14,999 ..3

\$15,000--\$19,999 ..4

\$20,000--\$24,999 ..5

\$25,000--\$34,999 ..6

\$35,000--\$49,999 ..7

\$50,000--\$69,999 ..8

\$70,000--\$89,999 ..9

\$90,000--\$109,999 10

\$110,000+ 11

Thank you very much for your time and your help with our research. I
would like to get your name and mailing address in case my office should
wish to get in touch with you to verify this interview. And, as I
mentioned before, the University of Michigan would like to send you a
check for \$20 as a token of our appreciation for your help.

![](media/image75.wmf){width="1.242361111111111in" height="1.25in"}

[^1]: The term \"person with a disability\" means any individual of any
    age, race or ethnicity who has a disability and who is or would be
    enabled by an assistive technology device or an assistive technology
    service to minimize deterioration in functioning, to maintain a
    level of functioning, or to achieve a greater level of functioning,
    in any major life activity.

[^2]: Amounts provided in an unpublished report to the National
    Institute on Disability and Rehabilitation Research by the
    Rehabilitation Engineering and Assistive Technology Society of North
    America (RESNA*), Progress and Outcomes: A Report on the State of
    Assistive Technology Act Programs*. Arlington, Va., September 2004

[^3]: A residence was defined as containing no more than eight
    individuals, at least two of whom must be related.

[^4]: Provisions had been made to conduct the interview over TTY relay,
    if the TTY signal was established on dialing.

[^5]: There was no Section I used in order to avoid confusion with Roman
    numerals.

[^6]: Verbatim responses were not recorded.

[^7]: One-tailed hypothesis testing performed. With high degrees of
    freedom, a t-value of +/- 1.64 equates to a probability of less than
    5 percent that there is no significant difference between two
    independent groups; +/- 1.96 translates to a probability of less
    than 2.5 percent, and 2.54 to a probability of \< one-half percent.

[^8]: One-tailed hypothesis testing performed. With high degrees of
    freedom, a t-value of +/- 1.64 equates to a probability of less than
    5 percent that there is no significant difference between two
    independent groups; +/- 1.96 translates to a probability of less
    than 2.5 percent, and 2.54 to a probability of \< one-half percent.

[^9]: In this chart, and in similar charts following, the mean is set at
    zero, and one standard deviation is set to 100 (standard score
    method). Thus, on average, those with unmet needs \[far right
    column\] are about one-quarter of a standard deviation below the
    value for those who need no modifications.

[^10]: Concepts such as Bayes' theorem, Boolean expressions or genetic
    algorithms.

[^11]: There were only 10 respondents overall with a kindergarten
    education.

[^12]: Degrees of freedom calculated by the formula (r-1)(c-1), where
    r=rows and c=columns. Thus, a 2x2 matrix has one degree of freedom,
    and a 3x6 matrix has 10. The more degrees of freedom in the matrix,
    the higher the value of chi-square must be to achieve statistical
    significance.

[^13]: The chi-square test of association (i.e., the 2x2 matrix
    chi-square) is a nominal-scale statistic of extremely low power.
    Significant findings using a weak statistic are *ipso facto* high in
    validity.

[^14]: We had enough data to accurately compare black and white
    respondents only.

[^15]: Template not drawn to scale.