Internet Use among Low-Income Longitudinal Survey Respondents as 

they Update Contact Information 

Bryan B. Rhodes and Ellen L. Marks 

RTI International 

6110 Executive Blvd., Suite 902 

Rockville, MD 20852 

brhodes@rti.org / emarks@rti.org 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Achieving maximum participation from study participants is a primary goal of virtually all surveys. Researchers review the 

literature, extract lessons from experience, and invest substantial resources to design survey methods that remove as many 

barriers as possible so sample members can and will respond to efforts to obtain their participation. Over the past decades as 

survey research has become more sophisticated and as new technologies surface, survey designs have kept pace. Computerassisted telephone and personal interviewing, use of handheld devices, and access to geospatial databases are examples of 

some recent developments in survey research. 

The growth of the Internet and emerging use of Web-based data collection are particularly interesting to survey researchers. 

This mode of data collection offers several benefits, among them the potential for lower costs, wider participation, fewer 

errors, and faster turnaround. As with any new approach, the opportunity for Web-based information collection has produced 

many questions about its use, including the representativeness of the sample, especially in regard to populations that may not 

have ready access to the Internet. 

To date, many studies conducted on Internet usage in survey research focus on technical and statistical concerns associated 

with Web-based data collection.1 In this paper, we take advantage of an ongoing study that asks lower-income sample 

members to confirm or update contact information in various ways. They may respond by mail, phone, or Web. Although the 

study was not designed for this purpose, we are able to compare characteristics of Web vs. non-Web responders, thus helping 

advance understanding about potential benefits and disadvantages of using the Web in survey research. 

Background of the Study 

Saving for Education, Entrepreneurship, and Downpayment (SEED) is a multiyear national effort to help children and youth 

open savings accounts that can eventually be used for expenses associated with education, opening a business, or making a 

down payment on a house purchase. The basic principle underlying SEED is that asset development is a way to help families 

achieve economic stability and improve chances for young people to succeed. SEED is targeted primarily at low-income 

families. At present, SEED is operating 12 programs with community partners across the United States.2 

This paper reports on data from one SEED experiment known as the Pre-School Demonstration and Impact Assessment, 

being conducted in conjunction with the Oakland Livingston Human Service Agency (OLHSA), a community-based 

organization in Pontiac, Michigan, that provides services to low-income families. 

The overarching research question focuses on the effect of having a savings account that can eventually be used for a child’s 

education. In the experiment,3 14 Head Start centers were identified and matched on the basis of various enrollment and 

1 See, for example, D.A. Dillman, Mail and Internet Surveys: The Tailored Design Method, John Wiley & Sons, New York, 

2000; H.C. Contrino, S. Echevarria-Cruz, and J. Shleymovich, “Potential Utility of Web Based Data Collection Options,” 

presented at the 2005 FCSM Conference, November 14, 2005, Arlington, VA; D. Andrews, B. Nonnecke, and J. Preece, 

“Electronic Survey Methodology,” International Journal of Human-Computer Interaction, Vol. 16, No. 2, 2003, pp. 185-

210; and J.A. Benfield and W.J. Szlemko, “Internet-based Data Collection: Promises and Realities,” Journal of Research 

Practice, Vol. 2, No. 2, Article D1, retrieved September 4, 2007, from http://jrp.icaap.org/index.php/jrp/article/view/30/51. 

2 Funding for SEED comes primarily from The Ford Foundation and other philanthropic organizations. CFED (formerly the 

Corporation for Enterprise Development) runs SEED operations and provides technical assistance. Other partners include the 

Center for Social Development at Washington University, the University of Kansas, and the New America Foundation. 

3 Researchers at the University of Kansas and the Center for Social Development designed the SEED Impact Assessment in 

cooperation with colleagues at the University of Michigan, CFED, and OLHSA. SEED researchers are guided in their work 

by a Research Advisory Council, a group of social scientists with expertise in child welfare, youth development, asset policy, 

and economics. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

demographic characteristics,4 then the centers were randomly assigned to treatment and comparison groups. Parents at the 14 

centers were invited to participate and complete a baseline survey. After completing the baseline survey, respondents whose 

child was at a Head Start treatment site were informed they had been selected to receive $800 deposited in an account in the 

state’s 529 plan (a college savings plan) and the opportunity to earn up to $1,400, which would be used to match funds the 

respondent (or others) deposited in the 529 account. The child is named as the beneficiary. 

The Sample 

To recruit sample members, OLHSA mailed letters to all families enrolled in the 14 Head Start centers. Letters were sent in 

summer 2004 and explained the study, outlined incentives ($30 for a completed baseline interview in fall 2004, $10 for each 

time contact information was updated, and $60 for a completed follow-up interview in fall 2008), and asked sample members 

to indicate their willingness to participate by signing and returning a consent form. After two mailings, responses were 

sparse. As Head Start centers opened for the school year in September 2004, OLHSA staff attended open houses and parent 

orientation sessions during which they explained the study and encouraged participation, but enrollment into the study 

remained low. To increase enrollment, RTI (which had been awarded the grant to conduct data collection) posted staff at 

Head Start centers during dropoff and pickup times, where they approached adults, explained the study, and invited them to 

participate.5 

Although enrollment in the sample improved, the numbers remained below targets set by the research team and funders, so 

the enrollment period was extended (and, in fact, continued throughout the data collection period) and additional steps were 

taken, including: 

 allowing verbal consent (previously, written consent was necessary to be enrolled in the sample); 

 increasing the incentive to $40; 

 attempting to contact remaining eligible parents by telephone to encourage their participation; and 

 preparing attractive information packets and sending them home with Head Start children. 

At the conclusion of these efforts, 871 parents were enrolled in the study.6 

Survey Administration 

The baseline survey was administered via a computer-assisted telephone interviewing (CATI) system from RTI’s call center 

in Greenville, North Carolina. The survey was conducted between September 21 and December 1, 2004.7 A total of 732 

interviews were completed. Most participants were reached through telephone calls to their homes, although a substantial 

portion—143 respondents—called the project’s toll-free number in response to messages left on an answering machine or 

with someone at their home. Surveys conducted in English and Spanish lasted 45 minutes on average. Because a number of 

respondents wanted to conduct the survey in Arabic, RTI trained a translator and a three-way call was conducted with the 

4 Head Start is a federally funded early childhood program that offers education, nutrition, and health services to children 

between the ages of 3 and 5. Eligibility is determined by household income relative to family size. In 2004, the income 

ceiling was $18,850 for a family of four (Head Start Family Income Guidelines for 2004, ACYF-IM-HS-04-03; 

http://eclkc.ohs.acf.hhs.gov/hslc, accessed September 3, 2007). 

5 Several Head Start centers transport children by bus. Because there would have been no opportunity to present the study to 

parents, we did not post staff at those locations. 

6 Program designers had initially hoped to have 1,200 respondents complete the baseline survey. 

7 Initially, survey operations were to be completed on or about October 20. Because the process of obtaining signed consent 

did not produce the expected number of study participants, new plans had to be implemented to increase sample size and the 

period of survey operations was extended. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

respondent, the interviewer, and the translator. After RTI had made at least 10 attempts to reach a respondent by telephone, 

cases were assigned to trained field representatives who visited the sample members’ homes to encourage participation. Field 

representatives offered to phone RTI’s call center using a cellular telephone in case lack of access to a phone had hindered 

participation in the study. Of the study’s 732 respondents, 588 either answered RTI’s call or called RTI after receiving a 

message, 105 called RTI after having been contacted by a field representative at their homes, and 39 used a field 

representative’s cellular telephone to call RTI and complete the interview (see Exhibit 1). The response rate was 

89.97 percent. 

Exhibit 1. Phone Use in Baseline Survey 

5% 

14% 

81% 

Own Telephone after RTI 

Outbound Call 

Own Telephone after Field 

Representative Contact 

Field Representative Cell 

Phone 

After reviewing the numbers, SEED program planners were still disappointed with the number of parents who agreed to 

participate in the initiative. In response, the invitation to enroll in SEED was extended, the evaluation was correspondingly 

expanded, and RTI was asked to locate and interview parents who agreed to open SEED accounts but had not completed the 

baseline survey (most entered Head Start after the period for conducting the baseline survey had ended). We completed 

surveys with an additional 58 respondents, thus bringing the total sample size to 790. 

Sample Maintenance 

In anticipation of achieving a high response rate for the follow-up survey planned for fall 2008 (with a target of 85 percent 

retention), RTI conducts semi-annual sample maintenance, namely verifying sample members’ current addresses and 

telephone numbers. Information is also gathered to determine whether the focal child from the baseline study is still living 

with the original sample member. If the focal child has moved, RTI attempts to obtain contact information for an adult 

member in the household where the focal child is living. 

The first two rounds of sample maintenance activities were conducted 6 and 12 months after the baseline survey. We 

implemented the following techniques, which we call “full-scale locating:” 

 A letter was mailed to the survey respondent, asking him/her to confirm or update contact information by return 

mail, a phone call to RTI’s toll-free project telephone number, or entering information on the project’s secure Web 

site. 

 After 2 weeks, nonrespondents were mailed a follow-up letter making the same request. 

 After 2 more weeks, RTI made telephone calls to remaining nonrespondents. 

 After 4 weeks, RTI sent field representatives to remaining nonrespondents’ homes. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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A $10 incentive was mailed to every individual who confirmed or updated contact information. 

Results from the first two rounds of sample maintenance were extremely positive: RTI heard from 97 percent and 95 percent 

of respondents, respectively, who confirmed or updated their contact information. Still, we sensed that sample members were 

becoming a bit numb to our outreach, so we instituted a new procedure for subsequent rounds of sample maintenance. The 

procedure began with dividing the sample into half according to the birth date of the baseline survey respondent. 

 Respondents born between January and June receive a birthday card in the month of their birth with a request to 

confirm or update their contact information by telephone, mail, or Web. Sample members who respond receive $10. 

 During that same period, sample members with birthdays between July and December receive full-scale locating, 

described above. To encourage sample members to respond early, people who respond within 10 days of the initial 

letter receive $20; people who respond later receive $10. 

 The process is switched for the two samples during the second half of the year. 

Thus, each sample member receives one birthday card and one attempt at full-scale locating during the course of each 12-

month period. 

Note that in each round of sample maintenance, respondents can update contact information in one of three ways: completing 

a form and returning it through the mail, calling the study’s toll-free number, or visiting a study Web site.8 Sample members 

who choose to update their contact information via the study Web site are asked to enter their unique case identification 

number (printed on all correspondence with the respondent) and the month and date of their birth date (see Exhibit 2). The 

Web site checks this information against a master database, provides the respondent with contact information on record, then 

asks the respondent to confirm or update that information. Visitors to the Web site can choose between English or Spanish. 

Exhibit 2. The SEED Sample Maintenance Web Site 

During full-scale tracing, respondents contacted in person were able to give updated information to the field representative. 8 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sample Maintenance Results 

Sample maintenance efforts to date have been extremely successful. At 2-1/2 years after baseline, overall retention is above 

90 percent. Two other figures reinforce the point: (1) only 1.2 percent of baseline survey respondents have never confirmed 

or updated their contact information; and (2) when using full-scale locating, we have heard from at least 94 percent of 

respondents in each round of sample maintenance. 

Five rounds of sample maintenance have been completed since the baseline survey, the most recent during the first half of 

2007 (30 months after the baseline survey). Exhibit 3 presents the methods respondents have used at each round to confirm or 

update their contact information. In all instances of full-scale locating, the most common method is reply by phone (which 

includes incoming calls from respondents and outgoing calls RTI places to the respondent). When only a birthday card was 

sent, however, more respondents reply via mail. 

Exhibit 3. Method of Response, Each Round of Sample Maintenance (in percents) 

Method of 

Reply 

Round 1 

Spring 2005 

Round 2 

Fall 2005 

Round 3 

Spring 2006 

Round 4 

Fall 2006 

Round 5 

Spring 2007 

Full Locating 

(n=732) 

Full Locating 

(n=732) 

Full 

(n=364) 

B-day 

(n=367) 

Full 

(n=367) 

B-day 

(n=364) 

Full 

(n=364) 

B-day 

(n=367) 

Web 3 5 9 5 5 4 9 7 

Mail 37 29 38 25 35 24 35 24 

Phone 47 54 41 9 44 10 36 6 

In-person 9 8 6 n/a 9 n/a 16 n/a 

Refusal 1 0 0 0 1 0 0 0 

No response 2 5 6 62 6 62 3 63 

Web vs. Non-Web Responders 

The ability to locate and re-interview baseline survey participants at the time of a follow-up survey is critical in longitudinal 

studies, so researchers often use a variety of methods to keep accurate contact information on sample members between 

survey administrations. Researchers, however, must balance the costs of each method with the expected outcome. Although 

some methods may be effective in allowing some sample members to easily update their information, the number who use a 

given method must be sufficiently large to be cost effective. Since lower-income populations are less likely to have Internet 

access in the home,9 the use of the Web may be less than optimal for studies of these populations. RTI’s SEED study, 

however, found the Web to be a useful option for lower-income families. Over the five rounds of sample maintenance 

conducted so far, 18 percent of respondents have used the Web option at some point to update their contact information. 

9 About one-fourth of all households with incomes of less than $15,000 report having Internet access in the home in October 

2003. See The 2007 Statistical Abstract, Households With Computers and Internet Access by Selected Characteristic: 2003 

(http://www.census.gov/compendia/statab/information_communications/internet_access_and_usage, accessed September 6, 

2007). 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

When they are given multiple methods for response, we assume that sample members will generally choose to reply using 

whatever method is easiest for them at that time. If a particular option is not available, some sample members may not reply 

and thus be lost to follow-up. If those members are lost and/or are sufficiently different from those who are retained in the 

sample, follow-up information could be affected by nonresponse bias. To help understand characteristics of low-income 

respondents who use the Web for sample maintenance, we examine characteristics of the SEED sample below. 

Demographics 

We analyzed six major demographic categories (defined from self-reports on the baseline survey)—race, ethnicity, education, 

age, employment status, and household income—to look for differences between Web and other types of responders. 

Comparing Web responders (defined as those who ever used the Web to update their contact information) and non-Web 

responders, Exhibit 4 shows that Web responders are more likely than nonresponders to be white, have at least some college 

education, range in age from 25–34, and have an annual household income over $15,000. 

Exhibit 4. Demographic Characteristics of Web vs. Non-Web Sample Maintenance Responders (in percents) 

Characteristic Web Responders Non-Web Responders 

Race* White 55 44 

African-American 33 46 

Other 12 10 

Ethnicity Hispanic 10 12 

Non-Hispanic 90 88 

Education 

level* 

Less than high school 19 32 

High school diploma/GED 28 33 

Some college or more 53 36 

Age at 

baseline* 

18–24 19 27 

25–34 61 47 

34 and above 19 26 

Employment Respondent works < 30 hours/week 67 66 

Respondent works  30 hours/week 33 34 

Income level* < $15,000 46 56 

$15,000 and above 54 44 

* p < .05 

Notes: Household median income for the sample is $15,000 annually; median income in 2004 for Oakland County, 

Michigan is $64, 293.10 

Trends 

Except for the fourth round of sample maintenance, the trend is a steady increase in the number of respondents who use the 

Web to confirm or update their contact information (see Exhibit 5). The upward trend in absolute numbers is even more 

10 U.S. Bureau of the Census. “State and County Quickfacts.” U.S. Census. 

http://quickfacts.census.gov/qfd/states/26/26125.html (accessed August 2, 2007). 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

meaningful because half of the sample was contacted only through a birthday card during rounds 3, 4, and 5. (Typically, the 

birthday-card-only results in responses from only about one-third of the sample.) 

We expected that most who used the Web to respond would do so each time. Instead, we found that 69 percent of 

respondents who ever used the Web for sample maintenance did so only one time and only 10 percent used the Web more

than two times (see Exhibit 6). Additionally, the percentage of Web respondents who were first-time Web respondents 

remained above 50 percent for every round of sample maintenance. 

Exhibit 5. Total Number of Web Responders, by Round of Sample Maintenance 

0 

10 

20 

30 

40 

50 

60 

70 

Round 1 Round 2 Round 3 Round 4 Round 5 

Birthday Card Recipients 

Full Locating 

Exhibit 6. Repeat Web Repliers 

Number of Times Replied by Web Percent of All Web Respondents 

1 69 

2 22 

3 4 

4 6 

5 0 

We examined the demographic characteristics of Web responders and non-Web responders at each round of sample 

maintenance (see Exhibit 7). The analysis shows no particularly interesting differences except one, and it is important. Web 

responders who received full locating efforts in rounds 3 and 4 were significantly more likely to be in the higher-income 

bracket (i.e., household income over $15,000 at baseline). This changed dramatically in round 5. Although the same 

respondents (those with birthdays in the second half of the year) received full locating efforts in both rounds 3 and 5, the 

percent of Web responders in the lower-income bracket increased from 36 percent to 62 percent (see Exhibit 8). This change 

is shown in Exhibit 9. For the first four rounds of sample maintenance, most Web responders had baseline incomes of over 

$15,000. In the fifth and most recent round, where Web response was the highest, Web respondents with baseline incomes 

less than $15,000 outnumbered those with incomes greater than $15,000. 

The number in the lower income bracket who use the Web to reply tends to increase over time, paralleling the upward trend 

in the overall sample. They show a decrease in round 4, which mirrored the decrease in the total sample, and then a large 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

increase during the fifth round—so large that during the fifth round those with incomes less than $15,000 constitute 

55 percent of all Web respondents (see Exhibit 10).11 

Exhibit 7. Demographic Characteristics of Web Responders and Non-Web Responders at Each Round of Sample 

Maintenance 

Characteristic 

Round 1 Round 2 Round 3 Round 4 Round 5 

Full 

Locating 

(n=732) 

Full 

Locating 

(n=732) 

Full 

(n=364) 

B-day 

(n=367) 

Full 

(n=367) 

B-day 

(n=364) 

Full 

(n=364) 

B-day 

(n=367) 

Web Not Web Not Web Not Web Not Web Not Web Not Web Not Web Not 

Race 

White 48 46 55 46 30 42 50 51 72 50 64 40 48 40 54 51 

Afr.-Amer. 33 44 36 44 55 45 31 39 28 39 21 51 33 51 29 39 

Other 19 10 13 10 15 9 19 10 0 11 14 9 18 9 17 10 

Ethnicity 

Hispanic 6 12 12 12 6 12 12 12 0 13 0 12 6 12 0 13 

Non-Hisp. 94 88 88 88 94 88 88 88 100 87 87 88 94 88 100 87 

Education 

Less than HS 17 30 21 30 9 31 24 30 6 31 21 29 15 30 21 30 

HS Diploma/ 

GED 

26 32 24 32 27 32 29 33 44 32 29 31 26 32 38 32 

Some college 

or more 

57 38 56 38 64 37 47 38 50 38 50 39 53 38 42 38 

Age 

18–24 13 46 18 26 12 26 24 27 22 27 14 26 15 26 17 27 

25–34 74 29 62 49 55 51 59 48 67 47 71 50 65 50 50 48 

35 + 13 25 21 25 33 23 18 26 11 26 14 24 21 24 33 25 

Employment 

< 30 hrs/wk 74 66 66 66 69 66 65 66 72 65 54 67 76 66 63 66 

30 hrs/week 26 34 34 34 31 34 35 34 28 35 46 33 24 34 38 34 

Exhibit 8. Income of Web Responders and Non-Web Responders at Each Round of Sample Maintenance 

Round 1 Round 2 Round 3 Round 4 Round 5 

Full Full 

Tracing Tracing Full B-day Full B-day Full B-day 

(n=732) (n=732) (n=364)* (n=367) (n=367)* (n=364) (n=364) (n=367) 

Income % Web Not Web Not Web Not Web Not Web Not Web Not Web Not Web Not 

<$15,000 39 55 50 55 36 59 41 52 28 53 43 58 62 57 46 52 

$15,000+ 61 45 50 45 64 41 59 48 72 47 57 42 38 43 54 48 

* = p < .05 

11 Interestingly, 55 percent of the baseline sample have incomes of less than $15,000. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exhibit 9. Percent of Web Responders by Income at Each Round of Sample Maintenance 

0 

10 

20 

30 

40 

50 

60 

70 

1st Round 2nd Round 3rd Round 4th Round 5th Round 

<$15,000 

$15,000 + 

Exhibit 10. Number of Web Responders with Income Less Than $15,000 per Year (at baseline) 

0 

5 

10 

15 

20 

25 

30 

35 

Birthday Card Recipients 

Full Tracing Recipients 

1st Round 2nd Round 3rd Round 4th Round 5th Round 

Internet Access at Home 

Among this low-income population, 38 percent of baseline respondents did not have a computer in the home; 54 percent 

reported not having Internet access in the home. As would be expected, Web responders during sample maintenance were 

significantly more likely to have Internet access in the home (p <= .05). Interestingly, however, among those who did not 

have Internet at baseline, 12 percent used the Web to update their contact information at some point during sample 

maintenance. 

Those who did not have Internet access at home at baseline made up one-third of the total number who have used the Web to 

update their contact information. Even at the first round of sample maintenance—only 6 months after the baseline survey— 

13 percent of those who used the Web to update contact information did not have the Internet in their home at the time of the 

baseline survey. Exhibit 11 shows an upward trend over time, with the exception of a slight decrease during the most recent 

round. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

- -

-

-

- -

-

-

- -

- -

Exhibit 11. Percent of Web Responders Without Internet Access in the Home at Baseline 

40 

35 

30 

25 

20 

15 

10 

5 

0 

6 12 18 24 30 

Months from baseline 

Used web to update information 

Summary and Conclusions 

This paper has investigated characteristics of survey respondents who responded via Web and other methods to requests for 

updated contact information, focusing on low-income sample members. Our analysis is based on a sample that is not 

representative of the general population (e.g., 92 percent of the sample is female and the average age of sample members is 

30), but provides important information about Web vs. non-Web responders among low-income households. 

We begin by concluding that offering a Web option is cost efficient and worthwhile. Establishing a secure Web site for 

sample members to use costs a relatively small amount of money, especially when compared to the costs of repeated 

mailings, telephone calls, and visits to sample member homes. Although the number who reply by Web has not yet exceeded 

more than a few dozen, we judge the method to be a good way to enable participation. 

Perhaps because the sample is relatively homogeneous to begin with (all parents of Head Start children, all living within a 

general geographic area), an examination of demographic characteristics among sample maintenance responders shows some 

differences between those who use the Web and those who respond through mail, phone, or in-person options. Web 

responders are more likely to be white, have at least some college education, range in age from 25–34, and have an annual 

household income over $15,000. 

The follow-up survey scheduled for fall 2008 will allow us to pose questions to expand our understanding of Web 

responders. Based on findings from analyses reported in this paper, we intend to further examine the following items. 

We are intrigued that the proportion of first-time Web respondents remained above 50 percent for every round of sample 

maintenance, showing a large turnover in Web respondent at each time. Several possible reasons could account for this 

figure: (1) respondents do not like their Web experience when they update their contact information, (2) the novelty of using 

the Web to update information may wear off rather quickly, and (3) the respondent may simply choose the most convenient 

method. Further study is needed to determine if one of these factors accounts for this phenomenon. 

We are also interested in the finding that the lack of Internet access in the home at baseline did not preclude respondents from 

using the Internet to update their contact information. These respondents may have recently arranged to have Internet access 

at home or can access it at work, someone else’s home, the library, or some other location. 

One of the more interesting findings is the increase in lower-income respondents’ use of the Web; they now use the Web 

more than higher-income respondents. We speculate more such respondents may have Internet access at home (especially 

since their focal children are now school-aged) or more may be working at jobs with Internet access (again, now that at least 

some children are in full-day schooling). 
 

 

 

 

 

 

 

 

 

 

 

References 

Andrews, D., B. Nonnecke, and J. Preece, “Electronic Survey Methodology,” International Journal of Human-Computer 

Interaction, Vol. 16, No. 2, 2003, pp. 185-210. 

Benfield, J.A. and W.J. Szlemko, “Internet-based Data Collection: Promises and Realities,” Journal of Research Practice, 

Vol. 2, No. 2, Article D1, retrieved September 4, 2007, from http://jrp.icaap.org/index.php/jrp/article/view/30/51. 

Contrino, H.C., S. Echevarria-Cruz, and J. Shleymovich, “Potential Utility of Web Based Data Collection Options,” 

presented at the 2005 FCSM Conference, November 14, 2005, Arlington, VA. 

Dillman, D.A., Mail and Internet Surveys: The Tailored Design Method, John Wiley & Sons, New York, 2000. 

The 2007 Statistical Abstract, Households With Computers and Internet Access by Selected Characteristic: 2003 

http://www.census.gov/compendia/statab/information_communications/internet_access_and_usage, (accessed September 6, 

2007). 

U.S. Bureau of the Census. “State and County Quickfacts.” U.S. Census. 

http://quickfacts.census.gov/qfd/states/26/26125.html (accessed August 2, 2007).