DOT HS 811 468A February 2012

Taxonomy of Older Driver 

Behaviors and Crash Risk
DISCLAIMER 

This publication is distributed by the U.S. Department of 

Transportation, National Highway Traffic Safety Administration, in 

the interest of information exchange. The opinions, findings, and 

conclusions expressed in this publication are those of the authors 

and not necessarily those of the Department of Transportation or the 

National Highway Traffic Safety Administration. The United States 

Government assumes no liability for its contents or use thereof. 

If trade names, manufacturers’ names, or specific products are 

mentioned, it is because they are considered essential to the object 

of the publication and should not be construed as an endorsement. 

The United States Government does not endorse products or 

manufacturers. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 Reproduction of completed page authorized
	

Technical Report Documentation Page 

1. Report No. 

DOT HS 811 468A

2. Government Accession No. 3. Recipient's Catalog No. 

4. Title and Subtitle 

Taxonomy of Older Driver Behaviors and Crash Risk 

5. Report Date 

February 2012

6. Performing Organization Code 

7. Authors 

Loren Staplin, Kathy H. Lococo, Carol Martell, and Jane Stutts 

8. Performing Organization Report No. 

9. Performing Organization Name and Address

 TransAnalytics, LLC 

 336 West Broad Street 

Quakertown, PA 18951 

 Highway Safety Research Center, University

 730 Martin Luther King, Jr. Blvd. 

Chapel Hill, NC 27599-3430 

of North Carolina 

10. Work Unit No. (TRAIS) 

11. Contract or Grant No. 

Contract No. DTNH22-05-D-05043, 

Task Order No. 08 

12. Sponsoring Agency Name and Address 

Office of Behavioral Safety Research 

National Highway Traffic Safety Administration 

U.S. Department of Transportation 

1200 New Jersey Avenue SE 

Washington, DC 20590 

13. Type of Report and Period Covered 

Final Report 

14. Sponsoring Agency Code 

15. Supplementary Notes

 Dr. Kathy Sifrit was the NHTSA Task Order Manager on this project. 

16. Abstract 

This project’s objectives were to identify risky behaviors, driving habits, and exposure patterns that have been shown 

to increase the likelihood of crash involvement among older drivers; and to classify these crash-contributing factors 

according to a set of underlying functional deficits specific to, or more prevalent among, the older driver population. 

Such deficits may result from normal aging, age-related medical conditions, or medication use. A further goal was to 

identify and critically examine behavioral countermeasures with the potential to mitigate functional loss and/or 

diminish the occurrence of risky behaviors—and thus ameliorate crashes among older drivers. 

The first task was an analysis of older driver injuries and fatalities using national databases (FARS, GES), to identify 

driving patterns, driving tasks, and contributing factors associated with crashes by older drivers; more details are 

available in a separate document, Report No. DOT HS 811 093, “Identifying Behaviors and Situations Associated 

With Increased Crash Risk for Older Drivers.” Additional project tasks included a review of the literature describing 

age-related functional changes, and evaluations of existing behavioral countermeasures to reduce older drivers’ crash 

risk; an expert panel meeting to supplement the information from the database analyses and literature review; and 

unstructured interviews with older drivers who have had crashes within the previous three years, and an age-matched 

group who have not had crashes within that period, to determine whether these groups differ in factors such as 

exposure or use of countermeasures. 

The outcomes of these project activities were used to develop and refine a taxonomy table that captures critical 

relationships between topics and subtopics highlighted in the literature review and crash database analyses. This table 

identifies critical performance errors that underlie crash types where older drivers are most strongly overrepresented; 

the functional deficits that are implicated in causing such performance errors; and the countermeasure strategies that 

presently appear to hold the greatest promise to ameliorate or to accommodate those (age-related) deficits. 

The taxonomy table is a resource that provides at-a-glance, state-of-the-knowledge information to assist researchers, 

health care practitioners, and others concerned about older driver safety to identify particular risk factors, and what can 

be done to reduce the risk. A hard copy version and an expanded, electronic version of this resource were developed. 

17. Key Words 

Safety, older drivers, functional abilities, crash analysis, 

countermeasure, driver performance, driving errors, 

rehabilitation, remediation, accommodation, compensation. 

18. Distribution Statement 

Document is available to the public from 

National Technical Information Service 

www.ntis.gov 

the 

19. Security Classif. (of

 Unclassified 

this report) 20. Security Classif. (of

 Unclassified 

this page) 21. No. of Pages 

107

22. Price 

Form DOT F 1700.7 (8-72) 

i
	
ACKNOWLEDGEMENTS 

The authors wish to thank the following people for their thoughtful and substantive 

contributions to the expert panel discussion in this project (in alphabetical order): Keli Braitman, 

Ph.D.; David Carr, M.D.; Elin Schold Davis, OTR/L, CDRS; Richard Marottoli, M.D., M.P.H.; 

Dennis McCarthy, Ph.D., M.ED., OTR/L; Gerald McGwin, Ph.D.; Lisa Molnar, MHSA; George 

Rebok, Ph.D., M.A.; Nina Silverstein, Ph.D.; Jane Stutts, Ph.D.; Janet Szlyk, Ph.D.; Carol 

Wheatley, M.S., OTR/L, CPCRI, CDRS. We also sincerely appreciate the efforts of Gayla 

Cissell, M.A., for carrying out the older driver interviews; Mary Ellen Tucker, M.L.S., for library 

research support; and John Joyce, for Maryland crash data extraction and analysis. 

ii
	
iii
	

TABLE OF CONTENTS
	

EXECUTIVE SUMMARY .............................................................................................................1 

INTRODUCTION AND BACKGROUND ....................................................................................3 

BACKGROUND AND UNDERSTANDING OF THE PROBLEM..................................3 

PROJECT OBJECTIVE ......................................................................................................3 

PROJECT SCOPE ...............................................................................................................4
	

METHODS ......................................................................................................................................5 

DATABASE ANALYSES ..................................................................................................5 

LITERATURE REVIEW ..................................................................................................10 

TAXONOMY TABLE DEVELOPMENT ........................................................................11 

EXPERT PANEL...............................................................................................................16 

INTERVIEWS WITH OLDER DRIVERS .......................................................................25 

FINDINGS.....................................................................................................................................34
 

ACUITY ............................................................................................................................36
 

CONTRAST SENSITIVITY .............................................................................................38
 

VISUAL FIELDS ..............................................................................................................40
 

DEPTH AND MOTION PERCEPTION ...........................................................................41 

DARK ADAPTATION AND GLARE RECOVERY .......................................................42
 

SPEED OF PROCESSING ................................................................................................42 

SELECTIVE ATTENTION ...............................................................................................44 

DIVIDED ATTENTION ...................................................................................................45 

WORKING MEMORY .....................................................................................................46 

EXECUTIVE FUNCTION (JUDGMENT AND DECISION-MAKING)........................47 

SPATIAL ABILITIES .......................................................................................................47 

KNOWLEDGE..................................................................................................................48
	

HEAD/NECK/TRUNK RANGE OF MOTION ................................................................49 

ARM STRENGTH/RANGE OF MOTION/SPEED OF MOVEMENT AND 

LEG STRENGTH/RANGE OF MOTION/SPEED OF MOVEMENT ............................50 

DISCUSSION AND CONCLUSIONS .........................................................................................52 

REFERENCES ..............................................................................................................................55 

APPENDICES 

APPENDIX A: Expert Panel Composition and Commentary for Countermeasures .... A-1 

APPENDIX B: Unstructured Interviews of Older Drivers .............................................B-1 

APPENDIX C: Taxonomy Table Detail (Published online at DOT HS 811 468B) 

 APPENDIX D: Literature Review (Published separately as DOT HS 811 468C) 
 

LIST OF TABLES
	

Table Number 

1. Eligible Single- and Two-Vehicle Crashes for FARS and GES Study Files. ......................7 

2. Sample Induced Exposure Table for a Specified Two-Vehicle Crash Situation. ................8 

3. Recommended Changes by Panelists to Countermeasures Listed in the Preliminary 

Taxonomy Table. ...............................................................................................................18 

4. Changes to Critical Driver Performance Errors Based on Panel Input ..............................20 

5. Mean Age for the Total Sample, Crash-Involved Drivers and Crash-Free Drivers. .........26 

6. Race and Sex by Crash Status............................................................................................26 

7. Driving Exposure for Continuous Variables Overall and by Crash Status. .......................27 

8. Driving Exposure for Categorical Variables Overall and by Crash Status. .......................28 

9. Frequency and Percentage of Drivers Reporting Difficulties by Crash Status..................30 

10. Frequency and Percentage of Changes in Driving Habits by Crash Status .......................31 

11. Frequency of Driver Education and Professional Evaluations by Crash Status ................32 

12. Frequency of Regular Physical and Mental Exercise and Eye Exams by Crash Status ....32 

13. Crash Types, Performance Errors, Functional Deficits, and Behavioral 

Countermeasures Included in the Taxonomy Table. .........................................................34
 

iv
	
LIST OF FIGURES 

Figure Number 

1. Preliminary Taxonomy Table Detail Pages for Crash Type 1 and 

Visual Acuity Deficit. ........................................................................................................13 

2. Critical Driver Performance Errors by Functional Deficits. ..............................................21 

3. Countermeasures by Functional Deficits. ..........................................................................22 

4. Number of Panelists in Agreement With Countermeasure-by-Deficit Association, 

and Mean Likelihood of Effectiveness Ratings. ................................................................24 

5. Annual Miles Driven by Driver Crash Status. ...................................................................28 

6.		 Taxonomy Table. ...............................................................................................................35
 

v
	
LIST OF ACRONYMS AND ABBREVIATIONS 

AMA ................................................................................................ American Medical Association 

BTW ...................................................................................................................... Behind the Wheel 

CDRS ............................................................................... Certified Driver Rehabilitation Specialist
	

CDS ....................................................................................................Crashworthiness Data System 

CIR ............................................................................................................ Crash Involvement Ratio 

DRS ................................................................................................. Driver Rehabilitation Specialist 

FARS.........................................................................................Fatality Analysis Reporting System
	

GES ..........................................................................................................General Estimates System 

GIS ................................................................................................. Geographic Information System 

GPS ......................................................................................................... Global Positioning System 

MLE ............................................................................................ Mean Likelihood of Effectiveness 

NASS .................................................................................. National Automotive Sampling System 

NHTSA ................................................................National Highway Traffic Safety Administration 

OT ................................................................................................................ Occupational Therapist 

PDI ....................................................................................................... Potentially Driver Impairing
	

vi
	
 

 

 

EXECUTIVE SUMMARY 

This study updates and extends our understanding of how age-related functional deficits 

can influence driver performance, and in turn crash risk for older drivers. It also examines the 

potential for behavioral countermeasures targeted to the remediation or accommodation of such 

deficits to attenuate critical errors in performance, and thus to reduce crash risk. A taxonomy 

table displaying the demonstrated and inferred links between these variables was developed as 

the central product of this research. 

An analysis of national crash databases (FARS and GES) initially prioritized five crash 

types where older drivers were most strongly overrepresented in the 5-year period 2002-2006: 

(1)		 The driver turned left at an intersection with stop-sign control, where cross traffic does not 

stop. 

(2)		 The driver turned left at an intersection with signal control, where the permissive (not 

protected) green phase was displayed during the driver’s approach. 

(3) The driver turned right at an intersection controlled by a yield sign, in a channelized rightturn lane, merging with traffic approaching from the left on a principal arterial with 

operating speeds of 40-45 mph. 

(4)		 The driver merged onto a limited access highway, in a ramp/acceleration lane controlled by 

a yield sign. 

(5)		 The driver changed lanes on a multilane roadway (4+ lanes). 

A review of technical literature provided a detailed summary of the current state of the 

knowledge regarding age-related functional impairment, driving performance, and safety; 

medical conditions and medications that can affect driving performance—with a separate chapter 

addressing dementia and diminished driving skills; plus descriptions and (where available) 

evaluations of behavioral countermeasures to help older people drive safely longer. 

The results of the crash analysis and literature review supported development of the 

taxonomy table. This resource presents key interrelationships between priority crash types for 

older drivers and critical driver performance errors implicated as pre-crash events, with 

additional links to specific sensory/perceptual (primarily visual), cognitive, and 

physical/psychomotor deficits that can contribute to these errors, and to countermeasures 

advanced as interventions for particular errors or deficits. 

An expert panel of researchers and clinicians distinguished in the area of older driver 

safety and mobility reviewed a preliminary version of the taxonomy table, the crash analysis 

report, and literature review. The panel gathered for a day-and-a-half meeting and recommended 

corrections and refinements. The meeting culminated in an exercise to rate the likely 

effectiveness of all countermeasures discussed by the panel that continued, iteratively, until 

consensus was reached among the panel members. This input was essential in finalizing the 

content and format of the taxonomy table, as presented in this report. 

Interviews with a sample of 50 older Maryland drivers provided another perspective on 

the efficacy of behavioral countermeasures. Half of this sample had experienced crashes in the 

past three years and the other half was crash-free. Participants in each group provided self1
	
 

reported measures of exposure, of driving situations that present difficulty, and of strategies to 

avoid or compensate for such difficulties. No clear differences emerged that would suggest more 

awareness of difficulties associated with functional aging, nor a greater reliance on 

countermeasures for safe driving, by the crash-free group. 

Like the taxonomy table, the conclusions drawn from this work represent a synthesis of 

the project tasks outlined above. These are presented below. 

	 All but two of nine critical driver performance errors identified in this study—which in 

turn manifest age-related functional deficits—could result in any of the major crash types 

for older drivers. Thus, effective countermeasures for the remediation of functional 

deficits have broad potential for crash reduction; they are not specific to any particular 

crash type. 

	 The driver interview data, though reflecting a small sample, reveal that when older 

drivers are aware of a functional impairment, they will make an effort to compensate or 

correct it, but are likely to drive anyway under some circumstances. 

	 The older drivers were often unaware of the consequences of functional aging on driving 

task performance, which suggests a significant opportunity to improve safety through 

appropriate educational interventions. 

	 Self-awareness drives the application of any strategy or countermeasure unless it is 

absolutely passive to the client’s will (e.g., intelligent cruise control). As a corollary, if 

an individual must remember to employ an intervention or believe that it is needed, a 

rehabilitation professional should be involved in determining if the intervention is 

appropriate. 

	 Attempts to keep impaired drivers on the road longer with devices or strategies that 

improve competence in very specific areas carry significant risk. Research is needed to 

define the boundaries of what can be responsibly prescribed or advocated as a 

countermeasure for age-related diminished capabilities outside of a formal rehabilitation 

context, and what interventions should only be administered with the supervision of a 

driving rehabilitation professional. 

	 If cognition is not intact, then vision countermeasures must be supplemented by other 

strategies that address the cognitive deficit. Any vision countermeasure requires intact 

cognition, to realize the desired safety and performance gains. Similarly, judgment and 

self-awareness are critical to the effectiveness of any countermeasure involving legal 

restrictions on driving. 

Finally, this study has provided important insights about the operating conditions and 

traffic situations where crashes involving older drivers are most likely. But it is unknown how 

often older drivers are exposed to the most risky situations, either relative to the exposure of all 

drivers or to their own exposure at younger ages. The mounting evidence that functional deficits 

underlie (at-fault) crashes by older drivers similarly requires at least some knowledge of the 

driving contexts in which performance errors reflecting those deficits are manifested. An 

integration of function, exposure, and safety data is needed to describe a true taxonomy of older 

driver problems, and to permit evaluations of countermeasure effectiveness that are free of the 

most serious confounds in work performed to date. 

2
	
 

 

INTRODUCTION AND BACKGROUND 

This section describes the rationale behind the project, highlights the objectives, and 

provides the reader with a brief overview of the technical approach. 

BACKGROUND AND UNDERSTANDING OF THE PROBLEM 

A substantial body of research has documented declines in older drivers’ functional 

abilities that support driving safely, and has associated these declines with specific errors and 

with a significantly higher risk of at-fault crash involvement. Countermeasures to mitigate crash 

risk for older drivers have included improvements in the design and operation of highways; 

vehicle modifications to improve control, provide warnings of hazards, and enhance occupant 

protection; and changes in drivers’ behavior aimed at reducing exposure to specific risks and/or 

to equip individuals with strategies and tactics to help them safely negotiate problem situations. 

A previous NHTSA report, Intersection Negotiation Problems of Older Drivers, Volume 

II: Background Synthesis on Age and Intersection Driving Difficulties (Staplin, Lococo, 

McKnight, McKnight, & Odenheimer, 1998) provided a description of specific functional 

declines associated with increased crash risk. A publication from NHTSA and the AMA, 

Physician’s Guide to Assessing and Counseling Older Drivers (Wang, Kosinski, Schwartzberg, 

& Shanklin, 2003), focused on medical conditions that may impair driving, and identified 

changes in driving habits that older people could adopt to help keep driving safely as functional 

abilities decline with advancing age. More recent work sponsored by NHTSA – Identifying 

Strategies to Study Drug Usage and Driving Functioning Among Older Drivers (Lococo & 

Staplin, 2006) – has improved understanding of the relationship between medication use and 

driving safety. 

The expanding older driver population dictates a need to revisit, update and enhance the 

base of knowledge manifested in these resources. Continuing investigations into factors that 

contribute to older driver crashes, coupled with a review of research describing how age-related 

functional changes can translate into specific driving errors, complement evaluations of the 

effectiveness of existing behavioral countermeasures while supporting development of innovative 

strategies to improve older driver safety and mobility in the future. 

PROJECT OBJECTIVE 

The project’s objectives were to identify risky behaviors, driving habits, and exposure 

patterns that have been shown to increase the likelihood of crash involvement among older 

drivers, and to classify these crash contributing factors according to a set of underlying 

functional deficits prevalent among the elderly. Such deficits may result from normal aging, 

age-related medical conditions, or medication use. A further goal was to identify and critically 

examine behavioral countermeasures with the potential to mitigate functional loss and/or 

diminish risky behavior(s), and thus ameliorate crash problems among older drivers. 

3
	
 

 

PROJECT SCOPE 

The scope of work in this project is described by the following five major tasks: 

	 Analyze data on older driver injuries and fatalities from the Fatality Analysis Reporting 

System (FARS) and National Automotive Sampling System/General Estimates System 

(NASS/GES) databases to identify driving behaviors and combinations of driver, vehicle, 

roadway, and environmental characteristics associated with increased crash involvement 

in older drivers. 

	 Review the literature to update the information regarding age-related functional changes 

in Intersection Negotiation Problems of Older Drivers, Volume II: Background Synthesis 

on Age and Intersection Driving Difficulties (Staplin et al., 1998a). The goals of this 

review were to: 

o	 Extend the scope of the 1998 report beyond negotiating intersections to include 

issues identified in the database analyses. 

o	 Identify evaluations of existing behavioral countermeasures to reduce older 

drivers’ crash risk. 

o	 Classify risky driving behaviors according to potentially underlying functional 

declines. 

	 Create a taxonomy table that captures critical relationships between topics and subtopics 

highlighted in the literature review and crash analysis, including: 

o	 Risky driving behaviors/driving errors associated with older driver crash 

involvement. 

o	 Operational factors and conditions under which driving errors are most likely to 

occur. 

o	 General and specific functional deficits that have been identified as underlying 

causes of driving errors and crash risk. 

o	 Behavioral countermeasures that have been developed to address specific 

functional deficits and/or associated risky behaviors. 

o	 Countermeasure evaluations, where they exist, and their methodological 

soundness. 

	 Conduct an expert panel meeting to supplement the information from the database 

analyses and literature review, and provide critical review of the taxonomy table. 

	 Conduct unstructured interviews with two sets of older drivers: those who were involved 

in a crash within the previous three years, and an age-matched group who were crash free 

within that period to determine whether these groups differ in factors such as driving 

exposure or use of countermeasures. 

4
	
METHODS 

This section provides a description of how each of the main tasks in this project was 

conducted. 

DATABASE ANALYSES 

The methods and results of the FARS and GES database analyses performed as the initial 

task in this project are summarized below. More details are available in a stand-alone report, 

entitled Identifying Behaviors and Situations Associated With Increased Crash Risk for Older 

Drivers (Stutts, Martell, & Staplin, 2009), available on NHTSA’s Web site at 

Two analytic approaches were undertaken. The first was to carry out separate descriptive 

analyses of single-vehicle and two-vehicle crashes, looking for situations where older drivers 

were overrepresented compared to middle-aged drivers. This relied on crosstabulations of FARS 

and GES data for the 5-year period 2002-2006. A more in-depth, “induced exposure” analysis 

was undertaken for the two-vehicle crashes. This technique compared the ratios of at-fault to 

not-at-fault drivers within age groups, producing a crash involvement ratio (CIR) that signifies 

the degree of over- or under-involvement of each age group with respect to particular risk 

factors. While feasible only with large data sets, this approach is notable in that it uses each 

group as its own control, thus taking into account differences in driving exposure across age 

groups with respect to a particular factor, such as driving at nighttime or on Interstate highways. 

Development of Data Files 

The examination of factors contributing to older driver crashes used 2002-2006 FARS 

and GES crash data. Consideration was given to using Crashworthiness Data System (CDS) 

data; however, the CDS is based on a much smaller number of actual crashes (fewer than 5,000 

per year, compared to some 56,000 for the GES). A preliminary analysis of 2006 CDS data 

revealed only three reported crashes involving an older driver merging in traffic. Although the 

raw CDS data are weighted to reflect national crash numbers, such small counts can lead to 

unstable estimates if used in the sort of finely stratified analyses required for the current project. 

The FARS and GES data analysis files developed for use in the project were restricted to 

single- and two-vehicle crashes involving the following vehicle types: 

 Passenger cars; 

 Sport utility vehicles; 

 Light vans; 

 Pickup trucks; and 

 Other light trucks (GVWR <10,000 lbs). 

For a two-vehicle crash to be included in the database, both vehicles needed to be one of these 

body types. This analysis excluded crashes involving large trucks, motorcycles, pedestrians and 

bicyclists, as well as crashes involving more than two vehicles. 

5
	
 

 

 

A second step in the preparation of the study files was the assignment of fault or 

responsibility for the crash. Neither the FARS nor the GES data contains a variable indicating 

driver fault. In a prior crash analysis using FARS and GES crash data, fault status was 

determined based on contributing factors and/or violations cited by the investigating officer 

(Reinfurt, Stewart, Stutts, & Rodgman, 2000). In two-vehicle crashes, if one driver was cited for 

one or more contributing factors or moving violations and the other driver was not cited for any 

contributing factors or moving violations, the first driver was deemed at-fault. Crashes in which 

both drivers had contributing factors, or in which neither driver was identified with a 

contributing factor, were excluded from the analysis. This same approach was followed in the 

current study for assigning fault to drivers involved in fatal two-vehicle crashes, using the FARS 

variables Related Factors – Driver Level (P22) and Violations Charged (P21). As before, nonperformance-related factors or violations – such as “driving with a suspended or revoked 

license,” “obscured vision,” and “defective vehicle equipment” – were not considered in 

determining a driver’s fault. Following this approach, 88.5% of the two-vehicle crashes 

involving eligible vehicle types in the FARS data were coded as having one at-fault and one notat-fault driver. 

Applying this approach to the GES data was less successful. While the GES data still 

include a similar variable (Critical Event, Precrash 2) describing contributing pre-crash events, 

this variable has been revised considerably since Reinfurt et al. (2000) used it. Documentation 

for data collectors states that culpability should not be considered a factor in determining precrash vehicle events. Indeed, when crosstabulating a potential grouping of the Critical Event, 

Precrash 2 variable by violation charged, there was substantial disagreement between this 

variable and the violation charged. 

Consequently, fault status in the GES datafile was assigned based purely on the violation 

variable (Violation Charged, D02). The following variable levels were considered indicative of 

fault: alcohol, drugs, speeding, reckless driving, failure to yield right-of-way, running a traffic 

signal or stop sign, violation charged-no details, and other violation. Note that neither “driving 

with a suspended or revoked license” nor “hit-and-run” were used to assign fault, nor were 

“unknown if charged” or “not reported.” Anecdotal reports suggest that driver violations more 

often go unreported than contributing factors, and a possible bias in which officers decline to cite 

a (older) driver for a violation may be acknowledged. Notwithstanding these limitations, the 

present approach allowed 52% of eligible two-vehicle crashes to be coded as one driver at fault 

and one not-at-fault for use in the induced exposure analyses in GES. However, when 

generating descriptive two-vehicle crash statistics, the substantial restrictions on determining 

fault for crashes in the GES datafile led to a decision to include all crashes involving eligible 

vehicle types, without regard to fault status. 

There were 109,937 crashes (72,847 single-vehicle plus 37,090 two-vehicle where one 

driver was identified at fault), used in the FARS data analysis. The raw number of crashes 

available for the GES analysis was 181,698 (69,689 single- vehicle and 112,009 two-vehicle 

crashes, without regard to fault status), which translated into 23.5 million weighted crashes. 

Table 1 shows the distribution of single- and two-vehicle crashes involving eligible study 

vehicles, and their at-fault status, for both the FARS and GES datafiles. 

6
	
 

 

 

Table 1. Eligible Single- and Two-Vehicle Crashes for FARS and GES Study Files. 

Crash Type and Fault Status 2002-2006 

FARS 

2002-2006 GES 

Unweighted Weighted 

Single-vehicle 72,847 69,689 7,860,000 

Two-vehicle, only one driver at-fault 37,090 62,090 8,112,000 

Two-vehicle, neither driver at fault 1,624 45,062 6,975,000 

Two-vehicle, both drivers at fault 3,195 4,857 567,000 

Two-vehicle, without regard to fault 41,909 112,009 15,654,000 

Data Analysis 

As noted, separate analyses were carried out on single-vehicle and two-vehicle crashes, to 

identify the factors that most strongly characterize older driver crashes. The crosstabulations 

involving age and other crash descriptors focused on identifying specific vehicle maneuvers and 

crash types or situations where older drivers were over-represented compared to middle-aged 

drivers, or where there was a pattern of increased involvement with age. Driver sex was 

examined as a potential mediating variable, along with other situational variables such as light 

condition, number of travel lanes, and speed limit. These descriptive analyses identify crash 

scenarios that comprise the biggest proportion of the older driver crashes. The age groups 

included in these analyses were: 60-69, 70-79, and 80+. 

For two-vehicle crashes, an additional set of analyses compared at-fault versus not-atfault crash involvement ratios across driver age categories, for a particular crash type or crash 

situation. As previously described, this approach, based on the concept of induced exposure, 

takes into account potentially different exposure levels across different age groups, and is 

therefore especially useful for pinpointing situations that pose the greatest risks to older drivers. 

The relative involvement of drivers in at-fault, versus not-at-fault, crashes is expressed as a 

“crash involvement ratio” (CIR). 

The following eight categories of driver age were used in the induced exposure analyses: 

<20, 20-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80+. Mid-decade groupings were eschewed, 

as a relatively small number of drivers in the 85+ category could hinder valid comparisons in 

some of the less common crash situations (e.g., changing lanes or merging on freeways). 

Table 2 shows the typical table layout for the induced exposure analyses, where D1a is 

the number of drivers under age 20 who were identified at-fault in the particular two-vehicle 

crash situation, and D2a the number of identified not-at-fault drivers under age 20. The at-fault 

crash involvement ratio (CIR) for drivers under age 20 is then D1a / D2a. Similar ratios can be 

calculated for the other age groups, using row and column totals to indicate which groups are 

over- (or under-) represented in the particular crash situation under study. 

Analysis results include full data tables (see template below), which were generated to 

check for adequate sample sizes. Graphs showing the calculated CIR values illustrate which 

situations and (combinations of) factors were most problematic for drivers of different ages. 

7
	
 

 

 

 

 

 

 

 

 

 

Note that significance testing on the observed differences was not performed, as these descriptive 

analyses were not initiated with any particular set of hypotheses in mind. 

Table 2. Sample Induced Exposure Table for a Specified Two-Vehicle Crash Situation. 

Driver1 Age 

(at fault) 

Driver2 Age (not-at-fault) 

<20 20-29 30-39 40-49 50-59 60-69 70-79 80+ Total 

<20 D1a 

20-29 D1b 

30-39 D1c 

40-49 D1d 

50-59 D1e 

60-69 D1f 

70-79 D1g 

80+ D1h 

Total D2a D2b D2c D2d D2e D2f D2g D2h Total 

Summary of Findings 

First, across this entire set of analyses there was little evidence of elevated risk for drivers 

60 to 69, the “young-old.” Most often, the data only began to demonstrate a substantial upturn in 

crash experience for drivers 70 to79, with over-representation for many crash types then 

accelerating more sharply for drivers 80 and older. Another notable pattern in these data were 

crash involvement ratios for older age groups that did not bear out conventional wisdom about 

certain situations being especially risky for these drivers, such as merging, changing lanes, 

driving on Interstate highways, and driving in bad weather. 

The situations that appeared most problematic for older drivers reinforce and extend 

relationships that are well established in the technical literature. Left turns were highlighted in 

this regard, as were movements at stop-sign-controlled intersections. Starting at age 70, older 

drivers in two-vehicle crashes were especially likely to crash at intersections, with the likelihood 

of an intersection crash strongly associated with increasing age. Over half of all fatal twovehicle crashes involving drivers 70 and older occurred at intersections. While drivers 70 and 

older were somewhat overrepresented in two-vehicle crashes at traffic signal locations, they were 

more strongly overrepresented in two-vehicle crashes at stop sign locations. In an analysis of 

maneuver (going straight versus turning left) and traffic control at intersections (signalized 

versus stop-controlled), the most dangerous situation for drivers 70 and older was turning left at 

a signal-controlled intersection, while the least dangerous was going straight at a signalcontrolled intersection. Turning left or going straight at a stop sign posed intermediate and 

approximately equal levels of risk. 

Over a third of fatal two-vehicle crashes involving drivers 80 and older occurred at stop 

sign locations—twice the percentage as at signal locations. With regard to drivers 80 and older 

and maneuvers at yield-sign- or stop-sign-controlled intersections, going straight at a yield sign 

8
	
 

 

 

emerged as the most dangerous maneuver. This might occur when merging onto a limited access 

roadway and having to check behind for traffic. 

Although older drivers were under-represented in crashes occurring at non-junction 

locations and those categorized as intersection-related, the category of “other non-interchange,” 

appeared most prominently for drivers 80 and older. This category refers to crashes that 

occurred at same-grade lane channels; for example, when there was a left or right turn lane that 

was not a through lane (often marked by a traffic island). 

Older people were increasingly less likely to be driving the striking vehicle in a twovehicle crash, and more likely to be driving the struck vehicle. Once a critical event had 

occurred, older drivers were less likely to brake, steer, or otherwise maneuver their vehicle to 

avoid the crash. However, in the absence of objective signs such as tire skid marks, this 

information was typically unreported. 

High-speed, two-lane roadways and multi-lane roads with speed limits of 40-45 mph 

(e.g., suburban arterials) were associated with heightened older driver crash involvement. For 

fatal crashes, both “young-old” and “old-old” drivers were more likely to make errors at 

intersections controlled by flashing signals. An error negotiating a yield-sign-controlled 

intersection was the reason for the crash in 26 of 27 such incidents for drivers 80 and older. 

With respect to two-vehicle crashes, failure to yield was the most frequently cited factor 

among older drivers. Overall, 27% of drivers failed to yield, but this percentage increased to 39% 

for drivers 60 to 69, 51% for drivers 70 to 79, and 62% for drivers 80 and older. As a group, 

older drivers were underrepresented in citations for failure to keep in proper lane (e.g., crossing 

the centerline, going straight in a turn lane), driving too fast, alcohol or drug use, and careless or 

reckless driving, all of which were important contributors to two-vehicle crashes overall. 

With respect to single-vehicle crashes, older drivers were somewhat more likely to be 

identified as ill or blacking out, drowsy or asleep, using medications or drugs (other than 

alcohol), and having some other physical impairment (missing limb, hearing loss, etc.). They 

were less likely to be identified as driving too fast, and somewhat less likely to have 

overcorrected. Otherwise, their related factor profile did not differ greatly from that of the 

general driving population. 

Situations that were risky for older drivers often included complex visual searches and 

information from multiple sources that must be processed rapidly under divided attention 

conditions. These are conditions where context-appropriate driver behavior often depends less 

upon conformity to formal or informal rules than to judgment or “executive function.” This 

converges substantially with the cluster of cognitive abilities validated as significant predictors 

of at-fault crashes by older drivers in previous NHTSA research (see Staplin, Gish, & Wagner, 

2003). 

9
	
 

Findings Informing Taxonomy Table Development 

Based on the findings of the FARS and GES database analyses describing driver, vehicle, 

roadway, and environmental characteristics of crashes in which older drivers were overrepresented, five driving situations were chosen for inclusion in the taxonomy table: 

 Left turn at an intersection with stop-sign control for the older driver’s approach. Cross 

traffic does not stop. 

 Left turn at an intersection with signal control; permissive phase for older driver’s 

approach. 

	 Right turn at an intersection controlled by a yield sign in a channelized right-turn lane, 

merging with traffic approaching from the left on a principal arterial (with speeds of 40-

45 mph). 

 Merge at a yield sign onto a limited access highway. 

 Lane change on a multilane (4+ lanes) roadway. 

These five priority crash types were the starting point for an in-depth examination of how 

crashes may result from age-related functional changes, mediated through specific driver 

performance errors. Findings from the literature review, described in the next section, enabled a 

better understanding of these relationships while identifying potential countermeasures for 

lowering older driver crash risk. 

LITERATURE REVIEW 

The literature review updated the material from “Age Differences in Functional 

Capabilities” reported by Staplin et al. (1998a). This review maintains the structure of the earlier 

report and expands the scope to include potential effects of age-related functional changes on 

driving situations highlighted through the crash database analyses described above. The present 

review was also expanded to include the documented or potential effects on driving capability of 

(1) medical conditions common in older adults and (2) medications commonly used by this 

population; plus, (3) evaluations of existing behavioral countermeasures that may affect older 

drivers’ safety. 

The literature review, included in its entirety as Appendix D, is a 212-page discourse that 

was prepared to support the expert panel discussion in this project, as well as the development of 

the taxonomy table. The panelists deemed it sufficiently useful as a reference for researchers and 

practitioners interested in older driver safety to recommend its inclusion in the final technical 

report. The literature review contains 7 chapters, as follows: 

 Diminished Sensory/Perceptual Capabilities; 

 Diminished Cognitive Capabilities; 

 Diminished Physical/Psychomotor Response Capabilities; 

 Medical Conditions and Driver Safety; 

 Medication Use in the Older Driver Population and Effects on Driving; 

 Dementia and Diminished Driving Skills; and
	

 Behavioral Countermeasures to Reduce Crash Risk. 

10
	
 

 

 

 

 

A search for relevant literature published between 1997 and 2008 was conducted in the 

TRIS, PsychINFO, and AgeLine databases. Keywords were: older drivers, driver age, physical 

ability, cognitive ability, visual ability, functional ability, attention, vision, strength, flexibility, 

and range of motion. The searches excluded the keywords alcohol and DUI. This strategy was 

augmented with a literature search in MedLine in two areas, Alzheimer’s Disease/Dementia and 

Medical Conditions. Dr. David Carr and Dr. Nina Silverstein, respectively, contributed 

additional references and original writings on these topics. The chapter on medication use was 

extracted from a recently completed literature review for a curriculum developed for NHTSA by 

TransAnalytics, to educate pharmacists and pharmacy technicians about medication-impaired 

driving (Lococo & Tyree, 2008). 

The results of the searches for literature addressing the relationships between (deficits in) 

functional abilities and driving outcomes also described behavioral countermeasures. A 

supplemental search using terms such as older driver retraining, education, interventions, and 

self-regulation helped to pinpoint those citations that deserved further review in this regard. 

A total of 142 reports were retrieved and reviewed to update the state of the knowledge in 

the seven areas covered by the literature review (see Appendix D, published separately as DOT 

HS 811 468C). 

TAXONOMY TABLE DEVELOPMENT 

The taxonomy table represents the key deliverable in this project. Its development built 

on the five specific situations/maneuver types emerging from the earlier crash analyses where 

older drivers are most strongly overrepresented in crashes (see page 10). 

With these five crash types as the top level organizing principle for the taxonomy table, 

the contents of the literature review chapters were examined to identify specific functional 

deficits that could be implicated as a contributing factor in each crash scenario. Applying the 

evidence from available research within the framework of driving task analysis (cf. Staplin et al., 

1998a), each specific deficit was then associated with one or more driver performance errors that 

could logically result from the deficit, and in turn lead to a crash. Countermeasures revealed 

through the present search, which have been suggested or applied to address specific deficits, 

were then identified. 

To summarize and integrate this information, Preliminary Taxonomy Table Detail Pages 

were developed at the level of general and specific areas of functional deficit for each of the five 

priority crash types. The specific functional abilities addressed in the Preliminary Taxonomy 

Table Detail Pages are listed below. 

Functional Deficits Relating to Crashes: 

 Sensory/Perceptual (Vision) 

 Acuity 

 Contrast sensitivity 

 Visual fields 

 Depth and motion perception 

 Dark adaptation and glare recovery 

11
	
 

 Attention/Cognition 

 Speed of processing 

 Selective attention 

 Divided attention 

 Working memory 

 Executive function (judgment/decision-making) 

 Spatial abilities 

 Knowledge 

 Physical/Psychomotor 

 Head/neck/trunk range of motion 

 Arm strength/range of motion 

 Leg strength/range of motion 

In developing detail pages for each of the five crash types, associated critical driver 

performance errors and behavioral countermeasures were entered for each included specific 

functional deficit. An example is presented here pertaining to specific deficits in visual acuity 

(in the general area of sensory-perceptual capabilities) for Crash Type #1: Left turn at an 

intersection with stop-sign control for the older driver’s approach. Cross traffic does not stop. 

Figure 1 displays the format in which this information was presented in the Preliminary 

Taxonomy Table Detail Pages. 

Finally, a preliminary draft of the taxonomy table was developed. The goal was to 

capture the key inter-relationships among each of the priority crash types and the critical driver 

performance errors implicated through task analysis as pre-crash events. Additional links were 

provided to the specific functional deficits that can contribute to these errors, as well as the 

countermeasures that have been advanced to address a given performance error or functional 

deficit. An expert panel (in a subsequent project task) critically evaluated the Preliminary 

Taxonomy Table. Critical driver performance errors, functional deficits, and behavioral 

countermeasures were modified based on the panelists’ recommendations. 

12
	
13
	

CRASH TYPE #1: LEFT TURN AT INTERSECTION WITH STOP SIGN CONTROL F

APPROACH 

(CROSS TRAFFIC DOES NOT STOP). 

General Deficit Specific Deficit Associated Driver Performance Errors Behavioral Countermeasure Countermeasur

Evaluations? 

Sensory/ 

Perceptual 

(Vision) 

Acuity 

Could contribute to a failure to visually detect a potential threat. Marottoli et al. (1998) acuity poorer than 20/40 independently associated with self-reported crashes, moving violations, being stopped by police in prior 5-year period. McKnight and McKnight (1999): Acuity (score and response time) related to unsafe driving incidents; correlations higher for time to respond to acuity stimuli than acuity errors. Acuity response time rather than acuity score related to driving exam score (Staplin et al., 1998). Acuity slightly worse than 20/30 independently associated with self-reported difficulty driving on interstates, at night, in the rain, on hightraffic roads, during rush hour, alone, and 

Refractive correction Cataract surgery 

No before-after studies refraction correction (upprescription for correctiglasses) and driving safuncovered. McGwin, Scilley, BrowOwsley (2003) found improvements in acuity cataract surgery, and thimprovement in visual ahad a significant, indepassociation with the chaactivities of daily vision (that includes daytime a

making left turns (McGwin, Chapman, & Owsley, 2000). Poorer dynamic acuity related to crash involvement in prior 2-year period (Shinar, Mayer, & Treat, 1975). Dynamic acuity included in model predictive of closed course driving performance (Wood, 2002). Shinar, McDonald, and Treat (1978): significant relationship between acuity and improper lookout. (Cont'd) 

nighttime driving). WooCarberry (2006) found timprovement in acuity taccompanied cataract suwas related to improvemoverall driving score. 

Figure 1. Preliminary Taxonomy Table Detail Pages for Crash Type 1 and Visual Acuity D
14
	

Functional Deficits 

That Influence 

Crash Risk 

CRASH TYPE #1: LEFT TURN AT INTERSECTION WITH STOP SIGN CONTROL FOR 

(CROSS TRAFFIC DOES NOT STOP). 

OLDER D

General Deficit Specific Deficit Associated Driver Performance Errors Behavioral Countermeasure Countermeasu

Evaluations? 

Sensory/ 

Perceptual 

(Vision) 

(Cont’d) 

Acuity 

(Cont’d) 

• McGwin, Chapman, and Owsley (2000): visual impairment worse than 20/30 in the better eye was independently associated with self-reported difficulty making left turns in sample of 384 drivers 55-85. Refractive error most frequent cause of impairment for the subsample with acuity worse than 20/40 but better than 20/60; cataract next most frequent cause (both conditions are correctable). • Decina and Staplin (1993): combined criterion using acuity, CS, and horizontal visual fields significantly related to prior crash involvement in drivers 66+, but no visual measure alone was significantly associated. 

Avoid challenging 

driving situations 

• Gallo, Rebok, & Les(1999). Self-reported impairment was relateavoidance of challengdriving situations, but self-reported citations crashes in prior 2 yearAuthors conclude that impaired drivers who restricted were less likcrash. Vision impairmcategories: no trouble a little trouble, a lot of (i.e., may not be speciacuity). • Ball, Owsley, StalveRoenker, Sloane, & G(1998): No relationshibetween avoidance sccrashes in subsequent period. • De Raedt & PonjaerKristoffersen (2000): pperformers on a road twere free of (self-repofault crashes (prior 12 used significantly morstrategic compensation (avoidance of challengsituations) than poorperforming drivers wihistory of at-fault cras

Figure 1 (Cont’d). Preliminary Taxonomy Table Detail Pages for Crash Type 1 and Visual Acu
15
	

Functional Deficits 

That Influence 

Crash Risk 

CRASH TYPE #1: LEFT TURN AT INTERSECTION WITH STOP SIGN CONTROL FOR 

(CROSS TRAFFIC DOES NOT STOP). 

OLDER D

General Deficit Specific Deficit Associated Driver Performance Errors Behavioral Countermeasure Countermeasu

Evaluations? 

Sensory/ 

Perceptual 

(Vision) 

(Cont’d) Acuity 

(Cont’d) 

Driver Safety 

Education 

(Theory) 

• Owsley, McGwin, PMcNeal, and Stalvey (found no difference in rate during 2 year follperiod for drivers with more reduction in UFOvisual acuity deficit (220/60) in an educationintervention group ("Knowledge EnhanceSafety") who reduced overall exposure and adriving at night, in the rush hour, and made rturns around the block avoid left turns across Avoidance and exposuself-reported, so sociadesirability may have operative; or restrictionot frequent enough to protective. Also, crash was not restricted to athe study. 

Figure 1 (Cont’d). Preliminary Taxonomy Table Detail Pages for Crash Type 1 and Visual Acu
 

 

 

EXPERT PANEL 

Purpose of the Panel 

An expert panel examined and supplemented the information compiled in earlier tasks 

about functional status, crash risk, and countermeasure strategies to aid older drivers. Panelists 

included key researchers and clinicians working in this area. The panel sought first to identify 

topics that were not covered adequately in the literature review, then to reach consensus (or at 

least broad agreement) about which functional losses best explain the performance errors 

highlighted in the FARS and GES analyses, as well as the feasibility of addressing them with 

behavioral countermeasures. 

The project team modified the preliminary taxonomy table based on the panel’s guidance 

to produce a resource that captures the state of the knowledge about how crash types may result 

from age-related functional changes, mediated through specific driver performance errors; while 

highlighting the most promising countermeasure strategies and priorities for continuing research. 

Planning and Logistics 

Panelists included physicians, geriatricians, and vision specialists with expertise in aging, 

functional change, and mobility outcomes; occupational therapists/rehabilitation professionals 

who routinely seek behavioral countermeasures to assist their clients; and epidemiologists who 

supplemented the project team’s understanding of the statistical and operational significance of 

crash contributing factors. 

The expert panel was convened at the Conference Center at the Maritime Institute, in 

Linthicum, Maryland. The meeting began at 1 pm and continued through 5 p.m. that day, then 

resumed at 9 a.m. the next morning and ended at 3 p.m. The meeting was professionally 

recorded (audio only) and transcribed. 

Two weeks prior to the meeting, panelists were provided with the crash analyses and 

literature review completed earlier, as background for the meeting. One week before the 

meeting, they were provided with taxonomy table worksheets that provided bullet point 

summaries of key research findings in each general area (e.g., vision) and specific sub-area (e.g., 

contrast sensitivity), describing the impact of a deficit in function on driver performance or 

safety. This information was included as preface to a table addressing “Associated Behavioral 

Countermeasures.” 

A central mission in this project was to document the state-of-the-knowledge about the 

existence of such countermeasures and evaluations (if any) of their effectiveness. A related goal 

was to generate ideas about potential new interventions to ameliorate crash risk for older drivers, 

and/or develop sound research designs to evaluate promising but untested approaches. 

Prior to their arrival at the meeting, participants were asked to add countermeasures to 

those listed for each sub-area of driver function in the worksheets. They came to the meeting 

16
	
prepared to discuss what has been tried, what has worked and has not worked, and what deserves 

either further research or application for clinical practice. 

Meeting Proceedings 

The discussion of countermeasures and their relationship to different deficits and subdeficits (taxonomy table worksheets) was scheduled for the last two hours on Day 1. However, 

that discussion lasted well into Day 2, as the assembled experts continued to discuss links 

between countermeasures and functional deficits. Since this was the part of the taxonomy table 

for which the research team was most dependent upon the contributions of these professionals, 

the discussion was encouraged. Panelists discussed at length a variety of countermeasures that 

clinicians often use in practice, but that lack evidence-based research. Identifying 

countermeasures that clinicians commonly use, but which have not been evaluated, is important 

for setting research agendas to clarify which countermeasures are effective in improving older 

adults’ driving performance and safety. 

Reflecting panelists’ comments, the phrase “Speed of Movement” was added to the 

deficits originally listed as “Arm Strength/Range of Motion” and “Leg Strength/Range of 

Motion” in the Preliminary Taxonomy Table. In addition, panelists recommended: (1) changes 

to the wording of eight of the countermeasures; (2) eliminating three countermeasures; and (3) 

adding six countermeasures. The changes to countermeasure descriptions resulting from the 

expert panel discussion are shown in Table 3. 

The three countermeasures that panelists recommended eliminating were: perceptual 

training in collision detection, peripheral movement detection practice, and passengers as copilots. The rationale for these changes is as follows. 

Perceptual training in collision detection. This countermeasure was suggested by 

Andersen and Enriquez (2006), but no evaluations were found in the literature. Panelists stated 

that this is not a trainable ability because it is dependent on the sensation of “optical flow.” This 

cannot be trained; however, a driver could be educated to recognize the deficit (using executive 

function) and compensate for it. 

Peripheral movement detection practice. Johnson and Leibowitz (1974) conducted a 

laboratory study with four psychology students experienced in visual psychophysics, and found 

that practice improved motion detection in the periphery at eccentricities greater than 20 degrees 

(20 to 80 degrees). However, the overall panel was highly skeptical that this is a trainable 

ability; it is specifically related to flicker rate. 

Passengers as copilots. Hing, Stamatiadis, and Aultman-Hall (2003) found that in multivehicle crashes, the presence of 2 or more passengers was the riskiest for drivers 75 and older 

(RR=1.8), but even 1 passenger increased the risk slightly compared to driving alone (RR = 1.6 

versus 1.5). The study included a general population sample (not dementia). Bédard and Myers 

(2004) found that for drivers 65 to 79, the presence of passengers overall was protective 

compared to driving alone. As per the FARS analysis in this project, it appears that the presence 

of passengers is protective for some actions but detrimental for others; for example, passengers 

17
	
 

 

 

 

increase the risk of unsafe actions related to obeying signs/warnings/right of way, for young-old 

and old-old drivers. 

The consensus of the expert panel was that this was not an appropriate countermeasure. 

Although several commented that a copilot may be appropriate for someone who is cognitively 

intact who only needs help with navigation, panelists were concerned about potential application 

to drivers with progressive diseases and that copilots would be used for other driving tasks, such 

as telling drivers when to stop or go in response to signs, signals, and traffic conditions. 

Table 3. Recommended Changes by Panelists to Countermeasures Listed in the 

Preliminary Taxonomy Table. 

Original Description Revised Description 

Refractive Correction Refractive Correction (Including wavefront 

technology1) 

Avoidance of Challenging Driving Situations 

Avoidance of Challenging Driving Situations 

(includes license restriction, driver 

rehabilitation specialist initiated, or selfrestriction) 

Bioptic Telescopic Lenses Central Vision Enhancem 

telescopic lenses, implanta 

ent Systems (bioptic 

ble telescopes) 

Bioptic Amorphic Lenses Visual Field Expansion Systems (prisms, 

bioptic amorphic lenses, video feeds) 

Training in Compensatory Head/Eye Training in Compensatory Head/Eye 

Movements Movements, Scanning Strategies 

Physical Aerobic Activity Physical Aerobic Activity/Training 

Driver Education Theory Driver Education Theory/Classroom 

Flexibility Exercises Strength and Flexibility Exercises 

The six new countermeasures recommended by panelists for inclusion in the taxonomy 

table were: 

 Medical management (including pharmacy review). 

 Cognitive rehabilitation (including memory training) for normally aging drivers.
	

 Compensatory cognitive/memory training for the impaired/mild cognitive impairment 

(MCI) population. 

 Pre-trip planning. 

 Education about driving aids: CarFit, features/adaptive equipment, diabetic shoes, etc. 

 Driver safety education: interactive/computer-based technology. 

The final products of the expert panel discussion were changes in language that qualified 

six of the eight critical driver performance errors listed in the Preliminary Taxonomy Table. 

This was done to highlight assumptions (e.g., “assuming no sensory deficit”), exclusions (e.g., 

1 Wavefront technology diagnoses higher-order vision errors represented by the way the eye refracts or focuses 

light; such aberrations defocus images even with 20/40 acuity. Wavefront guided lenses can reduce certain higherorder aberrations, which potentially can improve low light image quality during activities such as driving at night. 

18
	
 

 

 

 

“not willful or aggressive driving”), or to avoid overlap between categories of performance 

errors. Also, a ninth critical driver performance error was added, and panelists provided input 

helpful in mapping deficits to the critical driver performance errors. 

The changes to descriptions of the critical driver performance errors are shown in Table 4. 

The additional critical driver performance error endorsed by the expert panel – “Inappropriate 

response selection (pedal errors)” – is included in Figure 2, which also reveals how panelists 

mapped functional deficits to critical driver performance errors. 

Finally, review of the meeting transcript by project staff led to a reconsideration of deficits 

associated with Critical Performance Error 1, “Failure to visually detect potential conflicts, 

hazards, or traffic control information,” and the subsequent qualification of this entry by adding 

“without regard to cognitive status.” This preserves a focus on purely sensory factors and the 

need to address deficits at the earliest stages of driver information processing—without in any 

way diminishing the panel’s emphasis on attentional and cognitive factors as more potent 

predictors of crash risk. 

Following discussions about the appropriateness of countermeasures for selected 

impairments and populations, countermeasures were mapped (through panel consensus) to 

functional deficits2

 as shown in Figure 3. Appendix A provides a description of each of the 21 

countermeasures; a summary of research evaluating countermeasure effectiveness (where 

available); a summary of the panelists’ comments about the countermeasure; and the functional 

deficits addressed by the countermeasure. The appendix includes a metric describing panelists’ 

opinions regarding the likelihood that the countermeasure will be effective in promoting safe 

driving when it is targeted to a particular deficit. The next report section describes this metric 

and the exercise used to obtain it. 

Follow-Up Exercise: Gauging the Likelihood of Countermeasure Effectiveness 

Two weeks following the meeting, panelists were emailed a request to review the 

countermeasure-by-deficits table (shown in Figure 3) in a two-step exercise. In Step 1, they 

indicated their agreement or disagreement that each “X” placed in the matrix was appropriate, 

i.e., that the indicated countermeasure has some potential value as an intervention to promote 

safe driving practices for the indicated deficit. In Step 2, they provided a subjective evaluation 

of the countermeasure’s level of effectiveness for the indicated deficit using a rating scale. 

Specific instructions for this exercise are included in Appendix A. 

2

 One potential new countermeasure suggested by panelists during the meeting – “backing aids” – is not included in 

this table, as it does not relate to any of the crash problems shown to be most problematic for older drivers in the 

FARS and GES analyses. One potentially new critical driver performance error – “Lack of Awareness” [of changes 

in functional abilities] – also was not included, in the interest of establishing associations between functional deficits 

per se and countermeasures. 

19
	
 

 

 

 

 

 

 

 

Table 4. Changes to Critical Driver Performance Errors Based on Panel Input. 

Original Description Revised Description 

CRITICAL DRIVER PERFORMANCE ERROR 2 CRITICAL DRIVER PERFORMANCE ERROR 2 

Gap judgment errors Gap judgment errors (assuming no sensory deficit) 

(inability to accurately estimate closing speed and (inability to accurately estimate closing speed and 

distance) distance) 

CRITICAL DRIVER PERFORMANCE ERROR 3 CRITICAL DRIVER PERFORMANCE ERROR 3 

Inability to predict the development of future conflicts Inability to predict the development of future conflicts 

from current traffic & contextual information from current traffic & contextual information (assuming 

no sensory deficit) 

CRITICAL DRIVER PERFORMANCE ERROR 4 

Slowed vehicle control response 

CRITICAL DRIVER PERFORMANCE ERROR 4 

Slowed vehicle control response (assuming appropriate 

response) 

CRITICAL DRIVER PERFORMANCE ERROR 5 CRITICAL DRIVER PERFORMANCE ERROR 5 

Inadequate visual search/improper lookout Inadequate visual search/improper lookout (assuming no 

sensory deficits) 

(attentional failure, includes "looked but didn't see") 

(attentional failure, includes "looked but didn't see") 

CRITICAL DRIVER PERFORMANCE ERROR 6 

Slowed decision making; traffic situation has changed 

by the time a maneuver is initiated, resulting in 

potential conflict 

CRITICAL DRIVER PERFORMANCE ERROR 6 

Slowed decision making (assuming no sensory deficit); 

traffic situation has changed by the time a maneuver is 

initiated, resulting in potential conflict 

CRITICAL DRIVER PERFORMANCE ERROR 8 CRITICAL DRIVER PERFORMANCE ERROR 8 

Lack of understanding of safe driving practices Lack of understanding (leading to failure to apply) safe 

(communication, use of and aiming of mirrors, etc). driving practices (e.g., aiming mirrors, positioning within 

intersection to increase sight distance). Not willful or 

aggressive driving. 

Eleven of the 12 panelists completed this exercise. In summarizing Step 1, project staff 

established a criterion for retaining the “X” in any given cell, vis-à-vis the version of the 

countermeasure-by-deficit matrix provided to the various panel members. To retain the “X” at 

least 8 of the 11 responding experts were required to show agreement. All entries shown in 

Figure 2 met this criterion; therefore, none of the “X’s” in this matrix was removed. 

Similarly, the criterion for adding an “X” in the countermeasure-by-deficit matrix was 

defined by a simple majority: if 6 or more experts among the 11 responding to this exercise 

added an “X” in a given cell, it would be retained. No new entries suggested by experts met this 

criterion. There was one case where 5 panelists added an “X” to the matrix. This was in the cell 

indicating that cognitive rehabilitation including memory training for the normally aging 

population was an appropriate countermeasure to address a speed of processing deficit. As per 

research findings for the ACTIVE trials, memory training did not improve speed of processing 

performance (Ball et al., 2002). It was also the opinion of a panelist who is an author of the 

ACTIVE report, and who was not among the 5 panelists that entered an ‘X” in this cell, that 

memory training should not be identified as an intervention for a speed of processing deficit. 

20
	
21
	

Deficits 

Critical Driver Performance Errors 

1 2 3 4 5 6 7 

Failure to 

visually detect 

potential 

conflicts, 

hazards, or 

traffic control 

information 

(without regard 

to cognitive 

status)

 Gap judgment 

errors (assuming 

no sensory 

deficit) 

(inability to 

accurately 

estimate closing 

speed and 

distance)

 Inability to 

predict the 

development of 

future conflicts 

from current 

traffic & 

contextual 

information 

(assuming no 

sensory deficit)

 Slowed 

vehicle 

control 

response 

(assuming 

appropriate 

response) 

Inadequate visual 

search/improper 

lookout (assuming 

no sensory 

deficits) 

Attentional failure 

(includes "looked 

but didn't see") 

Slowed decision 

making 

(assuming no 

sensory deficit); 

traffic situation 

has changed by 

the time a 

maneuver is 

initiated, 

resulting in 

potential conflict 

Lack 

underst

of rules 

roa

1. Acuity X 2. Contrast Sensitivity X 3. Visual Fields X 4. Depth & Motion Perception X X 5. Dark Adaptation &  Glare Recovery X 6. Speed of Processing X X X X X 

7. Selective Attention X X X X X 8. Divided Attention X X X X X 9. Working Memory X X 10. Executive Function (Judgment/Decision- Making) X X X X X 11. Spatial Abiliies X X X X 

12. Knowledge X X 

13. Head/Neck/Trunk 

Range of Motion X X 

14. Arm Strength/ Range of Motion/ Speed of Movement 

X 

15. Leg Strength/ 

Range of Motion/ 

Speed of Movement 

X 

Figure 2. Critical Driver Performance Errors by Functional Deficits.
22
	

Functional Deficits 

COUNTERMEASURES 1. Acuity 2. Contrast Sensitivity 3. Visual Fields 4. Depth & Motion Perception 5. Dark Adaptation & Glare Recovery 6. Speed of Processing 7. Selective Attention 8. Divided Attention 9. Working Memory 10. Executive Function (Judgment/ Decision- Making) 11. Spatial Abiliies 12. Knowle

A. Refractive Correction 

 (incl. Wavefront technology) X X 

B. Cataract Surgery X X X 

C. Avoidance of Challenging

 Situations (license restriction, 

or DRS initiated, or self) 

X X X X X X X X 

D. Conformal Vision 

Enhancement System X X 

E. Central Vision Enhancement

 Systems (Bioptic Telescopic

 Lenses; Implantable Telescopes) 

X X X 

F. Visual Field Expansion Systems

 (Prism, Bioptic Amorphic Lenses, Video Feeds) 

X 

G. Training in Compensatory

 Head/Eye Movements, Scanning

 Strategies 

X 

H. Speed of Processing Training X X X 

I. Physical Aerobic Activity/Training X X X X 

J. Strength & Flexibiliy Exercises K. Visual Perceptual Therapy X L. Driver Safety Education: 

Theory/classroom only X X X X X X X X X X X X 

M. Driver Safety Education: 

Theory + Behind the Wheel (BTW) X X X X X X X X X X X X 

N. Driver Education: 

Interactive/Computer-Based 

Technology 

X X X X X X X X X X X X 

O. Education about Driving Aids 

(Car Fit, Features/Adaptive Equip, Shoes, etc.) 

X X X X 

P. Collision Warning Systems X X X X X 

Q. After-Market Non-Planar

 Driver-Side Mirror 

R. Medical Management 

(incl Pharmacy Review) X X X X X X X X X X X X 

S. Cognitive Rehab (incl Memory 

Training) for Normally Aging X X X X 

T. Compensatory Cognitive/

 Memory Training for Impaired/ 

 MCI Population 

X X X X 

U. Pre-Trip Planning X X X 

Figure 3. Countermeasures by Functional Deficits. 
 

Mean “Likelihood of Effectiveness” (MLE) ratings were calculated to summarize 

panelists’ judgments of countermeasure effectiveness in Step 2 of this exercise. A “1” to “5” 

scale was anchored by “extremely unlikely” and “extremely likely” effectiveness ratings, 

respectively. Mean ratings were grouped into three categories: 

 Top third on the rating scale (mean ratings of 3.68 to 5.0). 

 Middle third on the rating scale (mean ratings of 2.34 to 3.67). 

 Bottom third on the rating scale (mean ratings of 1.0 to 2.33). 

MLE ratings in the top third of the range were interpreted to mean that panelists had a relatively 

high level of confidence that a given countermeasure would be effective as an intervention for a 

targeted deficit. MLE ratings in the middle third were interpreted to mean that panelists regarded 

an approach as credible, but that more information/research is needed before they could endorse 

an intervention for a targeted deficit. MLE scores in the bottom third of the countermeasures 

rated by the panel signified interventions they considered unlikely to be effective (at least, not in 

isolation), given the present state of the knowledge in this area. 

Figure 4 presents the results of the countermeasure effectiveness rating exercise. It 

shows the number of panelists indicating agreement for each countermeasure-by-deficit 

association, and the mean MLE ratings. MLE ratings are color coded in this figure indicating 

values in the top (green), middle (yellow), and bottom (red) third of the range on the rating scale. 

While the majority of the countermeasure-by-deficit associations received MLE ratings in 

the middle third of the scale indicating a need for more research, the following countermeasure 

applications (showing the targeted deficits in italics) received the highest ratings: 

 Refractive Correction (including Wavefront technology): Acuity; Contrast Sensitivity. 

 Cataract Surgery: Acuity, Contrast Sensitivity; Dark Adaptation and Glare Recovery. 

 Training in Compensatory Head/Eye Movements, Scanning Strategies: Visual Fields; 

Head/Neck/Trunk Range of Motion. 

 Physical Aerobic Activity/Training: Arm Strength/Range of Motion/Speed of Movement; 

Leg Strength/Range of Motion/Speed of Movement. 

 Strength and Flexibility Exercises: Head/Neck Trunk Range of Motion; Arm Strength/ 

Range of Motion/Speed of Movement; Leg Strength/Range of Motion/Speed of Movement. 

 All three Driver Education Modes: Knowledge. 

 After-Market Non-Planar Driver-Side Mirror: Head/Neck/Trunk Range of Motion. 

 Pre-Trip Planning: Knowledge. 

At the other end of the range, the following countermeasure applications (showing the 

targeted deficits in italics) received the lowest ratings: 

 Driver Safety Education/Theory Classroom Only: All deficits with the exception of 

Knowledge. 

 Driver Safety Education/Theory + BTW: Acuity. 

 Driver Safety Education/Interactive Computer-Based: Acuity. 

 Education About Driving Aids: Depth and Motion Perception; Dark Adaptation/Glare 

Recovery. 

23
	
24 

Functional Deficits 

10. 

5. 

4. Executive 

2. 3. Dark 6. 7. 8. 9. 11. 

COUNTERMEASURES 1. Depth & Function 12

Contrast Visual Adaptation & Speed of Selective Divided Working Spatial 

Acuity Motion (Judgment/ Knowl

Sensitivity Fields Glare Processing Attention Attention Memory Abiliies 

Perception Decision- 

Recovery 

Making) 

A. Refractive Correction 

(incl. Wavefront technology) 

B. Cataract Surgery C. Avoidance of Challenging 

Situations (license restriction, 11 (2.91) 11 (3.18) 11 (2.91) 11 (3.09) 11 (3.45) 11 (2.82) 11 (2.70) 11 (2.70) or DRS initiated, or self) 

D. Conformal Vision 11 (3.14) 10 (2.83) Enhancement System 

E. Central Vision Enhancement 

Systems (Bioptic Telescopic 11 (3.33) 11 (2.78) 11 (3.00) 

Lenses; Implantable Telescopes) 

F. Visual Field Expansion Systems 

(Prism, Bioptic Amorphic Lenses, 11 (3.40) 

Video Feeds) 

G. Training in Compensatory 

Head/Eye Movements, Scanning 

Strategies 

H. Speed of Processing Training 11 (3.64) 10 (3.40) 10 (3.40) I. Physical Aerobic Activity/Training 11 (2.91) 11 (2.73) 10 (2.50) 10 (2.50) J. Strength & Flexibiliy Exercises K. Visual Perceptual Therapy 11 (3.33) L. Driver Safety Education: 

Theory/classroom only 

M. Driver Safety Education: 11 (2.55) 11 (2.36) 10 (2.40) 11 (2.73) 11 (2.45) 11 (2.64) 9 (2.67) 11 (3.00) 10 (2.50) 11 (4

Theory + Behind the Wheel (BTW) 

N. Driver Education: 

Interactive/Computer-Based 11 (2.73) 11 (2.55) 11 (2.36) 11 (3.27) 11 (3.27) 11 (3.45) 10 (3.40) 11 (2.91) 11 (2.91) 11 (3

Technology 

O. Education about Driving Aids 

(Car Fit, Features/Adaptive Equip, 11 (4

Shoes, etc.) 

P. Collision Warning Systems 11 (3.36) 11 (3.45) 11 (3.45) 11 (3.40) 11 (3.30) Q. After-Market Non-Planar 

Driver-Side Mirror 

R. Medical Management 11 (3.50) 10 (3.00) 10 (3.0) 10 (2.67) 10 (3.00) 11 (3.18) 11 (3.30) 11 (3.09) 11 (3.20) 11 (3.27) 11 (2.40) 11 (3

(incl Pharmacy Review) 

S. Cognitive Rehab (incl Memory 11 (2.89) 11 (2.80) 11 (2.80) 11 (2.80) Training) for Normally Aging 

T. Compensatory Cognitive/ 

Memory Training for Impaired/ 11 (2.89) 11 (2.80) 11 (2.90) 11 (2.80)

 MCI Population 

U. Pre-Trip Planning 11 (3.09) 11 (3.09) 8 (3.

Key to Middle Third Bottom Third 

color code 2.34 to 3.67 1 to 2.33 

11 (4.0) 11 (3.89) 

11 (4.60) 11 (4.56) 

Top Third 

3.68 to 5.0 

11 (4.13) 

11 (3.82) 

11 (1.64) 11 (1.82) 11 (1.82) 10 (1.50) 10 (1.80) 10 (2.00) 10 (1.80) 10 (1.80) 10 (1.70) 11 (2.18) 10 (1.80) 11 (3

10 (2.10) 11 (2.56) 10 (2.20) 11 (2.64) 

11 (2.55) 10 (1.89) 10 (2.40) 

Figure 4. Number of Panelists in Agreement with Countermeasure-by-Deficit Association, and Mea

Effectiveness Ratings. 
 

 

INTERVIEWS WITH OLDER DRIVERS 

A group of 50 older drivers participated in unstructured telephone interviews. Half of 

these drivers were involved in crashes between 2006 and 2008. The objective of the interviews 

was to determine whether crash-involved and crash-free drivers differed in factors such as (selfreported) exposure or use of countermeasures. The unstructured interview, as shown in Appendix 

B, included questions related to (1) current driving status; (2) current driving exposure; (3) 

difficulties with driving over the past 5 to 10 years; (4) changes in driving habits over the past 5 

to 10 years; (5) driver education and professional evaluations over the past 5 years; (6) physical, 

mental and visual fitness; and (7) driving after alcohol consumption. Participant recruitment 

methods and a summary of the findings comparing the crash-involved and the crash-free groups 

are presented below. 

Participants 

Individuals were recruited by telephone from the sample of 1,722 older drivers who 

previously consented to telephone interviews during the Maryland Older Driver Pilot Study 

(Ross et al., 2009; Staplin, Lococo, Gish & Decina, 2003). The crash-involved sample was 

nearly exhaustive, given attrition from the dates of first recruitment almost a decade earlier. 

After these 25 phone interviews were completed, a calling list of crash-free participants was 

generated. After restricting the sample to include active drivers with birth years between 1924 

and 1944 (based on driver license information) to match the age range for the crash-involved 

interviewees, a prospective sample of 592 remained. After sorting by date of birth, every 15th 

person was selected to create an initial call list (n=39). Two attempts were made to contact those 

on the list. Two additional call lists were generated selecting every 16th and every 17th person, 

respectively, until interviews with 25 age-matched, crash-free participants were completed. 

The average age of the participants was 76 (range: 62-85). The age difference between 

the crash-involved sample (mean age=75.4) and the crash-free sample (mean age=76.7) was not 

significant. Age information for the total sample, crash-involved group, and crash-free group is 

presented in Table 5. 

Participants were primarily white (n=44) and male (n=32). While race was distributed 

approximately equally across the two samples, gender was not. As shown in Table 6, the crashfree sample included a greater proportion of males (19 males, 6 females) than the crash-involved 

sample (13 males, 12 females). 

Correction for Current Driving Status 

Although 50 individuals were interviewed, four of these participants were not currently 

driving. While all four had been involved in a crash, only one attributed the crash as the reason 

for driving cessation; the other three indicated they had stopped driving due to stroke or falling. 

Three participants reported that they stopped driving in 2008; the fourth participant’s driving 

status had changed within three weeks of the interview due to stroke. Thus, the following 

summary is based upon 46 individuals, with 21 participants represented in the crash-involved 

group. 

25
	
 

Table 5. Mean Age for the Total Sample, Crash-Involved Drivers, and Crash-Free Drivers.
	

Crash Status Mean Age SD Range N 

Crash 75.38 5.49 62.26 - 84.83 25 

No Crash 76.68 4.99 67.15 - 85.15 25 

Total 76.03 5.23 62.26 - 85.15 50 

Table 6. Race and Sex by Crash Status. 

Prior Crash? Race 

Sex 

Female Male Total

African American 1 2 3 

No 

White 4 17 21 

Asian 1 0 1 

Total 6 19 25 

African American 1 0 1 

Yes 

White 10 13 23 

Asian 1 0 1 

Total 12 13 25 

Driving Exposure 

Participants responded to the following questions regarding driving exposure: 

 How many days per week do you normally drive? 

 On a typical day, how many trips do you make? 

 How many total miles do you drive in a normal week? 

 In a normal week, about what percentage of your overall travel (miles driven) occurs at 

night? 

 Is most of your nighttime travel on lit or unlit roads? 

 About how many miles per year do you drive? 

 What kind of area do you live in (city, suburban, rural)? 

 Do you do most or all of your driving close to home? 

26
	
 

 During the past year, have you driven to places that take more than 1/2 hour to get to or 

are more than 10 miles away? 

 During the past year, have you driven to places that take more than 1 hour to get to or are 

more than 50 miles away? 

The categorical variables were interviewees’ estimates of miles driven annually (range: 

1=less than 1,000 to 12=30,001 or more), estimates of nighttime travel on lit or unlit roads, home 

area type (city, suburban, rural), and distance driven from home in the past year. The results for 

the continuous variables, with the exception of miles driven annually, are presented in Table 7 

and the results for the categorical variables are presented in Table 8. Summary statistics for 

annual miles driven are presented in Table 7 both by the category that represents the range of 

miles driven (i.e., 1 - 12) and by miles, calculated using the midpoint of the mileages listed for 

each category. Figure 5 presents a histogram of annual miles driven by driver crash status. 

The average interviewee reported driving 5 days per week, making 2 trips per day, 

driving 161 miles per week, and driving between 5,000 to 10,000 miles per year (see Table 7). 

Regular nighttime driving was reported by 31 (67.4%) interviewees; comprising 11% of their 

weekly driving. The majority of those that reported driving at night (74.2%) drove on lit roads. 

The crash-involved reported driving on lit roads 91.7% of the time and the crash-free reported 

driving on lit roads 63.2% of the time. The majority of the participants reported living in the 

suburbs (54.3%) and doing most or all of their driving close to home (87%); but most reported 

driving to places more than 10 miles away (93.5%) and 50 miles away (73.9%) during the past 

year (see Table 8). 

Table 7. Driving Exposure for Variables Overall and by Crash Status. 

Exposure Question 

Total 

(N=46) 

Crash 

(n=21) 

No Crash 

(n=25) 

M SD M SD M SD 

How many days per week do you 

normally drive? 5.04 2.00 4.76 2.17 5.28 1.86 

On a typical day, how many trips 

do you make? 2.13 1.33 2.05 1.28 2.20 1.38 

How many total miles do you 

drive in a normal week? 160.91a 229.68 183.38 307.11 141.25b 134.33 

In a normal week, about what 

percentage of your overall travel 

(miles driven) occurs at night? 

11.09 14.90 7.67 12.62 13.96 16.28 

About how many miles per year 

do you drive? (categorical 

response) 

4.47c,e 2.79 4.57 3.47 4.38d 2.08 

About how many miles per year 

do you drive? (estimate derived 

using midpoint of each category) 

8,016 7,915 8,678 10,030 7,437 5,623 

a,cN=45 b,dn=24 e

4=5,001 to 7500, 5=7,501 to 10,000 

27 
 

 

 

0% 

5% 

10% 

15% 

20% 

25% 

30% 

35% 

Percent of Group 

No Crash 

Crash 

<1,000 1,001 - 2,501 - 5,001 - 7,501 - 10,001 - 12,501 - 15,001 - 17,501 - 20,001 - 25,001 - 30,001 or 

2,500 5,000 7,500 10,000 12,500 15,000 17,500 20,000 25,000 30,000 more 

Annual Mileage Category 

Figure 5. Annual Miles Driven by Driver Crash Status. 

Table 8. Driving Exposure for Categorical Variables Overall and by Crash Status. 

Exposure Question Total 

(N=46) 

Crash 

(n=21) 

No Crash 

(n=25) 

Is most of your nighttime travel on lit or 

unlit roads? (% lit) 74.2a 91.7b 63.2c 

What kind of area do you live in? 

(% suburbs) 54.3 57.1 52 

Do you do most or all of your driving close 

to home? (% yes) 87 90.5 84 

During the past year, have you driven to 

places that take more than 1/2 hour to get 

to or are more than 10 miles away? (% yes) 

93.5 90.5 96 

During the past year, have you driven to 

places that take more than 1 hour to get to 

or are more than 50 miles away? (% yes) 

73.9 71.4 76 

a

n=31 bn=12 cn=19 

A MANOVA revealed no significant differences between crash-involved and crash-free groups 

for the continuous variables described above. Similarly, there were no differences between these 

groups indicated by chi-square and Fisher’s Exact tests, for responses on the categorical items. 

28
	
Driving Challenges 

This section summarizes the responses to the 19 questions about driving challenges. 

These questions were structured so that if a participant responded that a given situation had 

become more challenging over the past 5 or 10 years, the researcher asked whether they 

continued to drive under those conditions in spite of the difficulty, and if so, how often. 

Of the 19 driving situations queried, the top 5 questions for which participants responded 

that driving situations had become more challenging were: 

 Seeing at night (n=21, 45.7%). 

 Dealing with bad weather (n=15, 32.6%). 

 Turning the head/neck (n=10, 21.7%). 

 Judging actions of others/hazard anticipation (n=9, 19.6%). 

 Changing lanes/merging (n=6, 13.0%). 

For these five situations, only judging the actions of others (hazard anticipation) suggested a 

potential difference between the crash-involved (n=7) and the crash-free (n=2). Despite 

difficulty with these driving situations, the majority reported driving anyway. For each of these 

five situations, the percentage for those who drive anyway despite reporting difficulty follows: 

 Seeing at night (14/21, or 67%). 

 Dealing with bad weather (9/15, or 60%). 

 Turning the head/neck (9/10, or 90%). 

 Judging the actions of others/hazard anticipation (8/9, or 89%). 

 Changing lanes/merging (5/6, or 83%). 

The five situations for which no one reported difficulty were understanding signs, staying 

in their lane, moving the foot between the brake and gas pedals, knowing which pedal was the 

brake and which was the gas, and steering when turning. For the remaining 9 situations, the 

number of participants reporting difficulty ranged from 1 to 4. No other potential trends were 

observed. These data are summarized in Table 9. 

Changes in Driving Habits 

Participants were asked whether their driving habits had changed over the past 5 or 10 

years for each of 20 driving behaviors including driving fewer miles, making fewer trips, 

avoiding specific driving situations, or employing strategies such as trip planning or using invehicle technologies to make the driving task easier (see Table 10). 

29
	
 

Table 9. Frequency and Percentage of Drivers Reporting Difficulties by Crash Status. 

Driving Situation 

No Crash 

N=25 

Crash 

N=21 

Number (%) Reporting 

Difficulty 

Number (%) 

Reporting Difficulty 

Seeing at Night 11 (44%) 10 (48%) 

Dealing With Bad Weather 7 (28%) 8 (38%) 

Judging Actions of Others 2 (8%) 7 (33%) 

Turning Head/Neck 4 (16%) 6 (29%) 

Changing Lanes / Merging 3 (12%) 3 (14%) 

Paying Attention to Everything 1 (4%) 3 (14%) 

Getting Tired Easily 1 (4%) 3 (14%) 

Judging Gaps 1 (4%) 2 (10%) 

Flowing With Traffic 1 (4%) 2 (10%) 

Knowing Right of Way 0 2 (10%) 

Reading Signs 3 (12%) 1 (5%) 

Detecting in Periphery 2 (8%) 1 (5%) 

Getting Lost/Disoriented Easily 0 1 (5%) 

Understanding Signs 0 0 

Staying in Lane 0 0 

Moving Foot Between Pedals 0 0 

Knowing Pedals 0 0 

Steering When Turning 0 0 

Other Difficulties 1 (4%) 1 (5%) 

As shown in Table 10, there were 14 changes in driving habits (in order of greatest 

reported change) that more than 25% of either the crash-involved or crash-free drivers reported: 

 Making fewer trips per week. 

 Driving fewer miles. 

 Avoiding or limiting night driving. 

 Avoiding or limiting driving at rush hour. 

 Avoiding or limiting driving in bad weather. 

 Increasing following distance. 

 Avoiding or limiting high traffic roads. 

 Planning the route before leaving. 

 Avoiding or limiting driving in unfamiliar areas. 

 Avoiding or limiting driving far from home. 

 Avoiding or limiting high speed roads. 

 Using in-vehicle technologies. 

 Avoiding freeways. 

 Limiting driving in other ways. 

A higher percentage of the crash-involved drivers reported making each of these changes. 

30
	
Table 10. Frequency and Percentage of Changes in Driving Habits by Crash Status. 

Changes in Driving Habits 

No Crash 

N=25 

Crash 

N=21 

Number (%) 

Reporting Changes 

Number (%) 

Reporting Changes 

Make Fewer Trips per Week 9 (36%) 15 (71%) 

Drive Fewer Miles 12 (48%) 14 (67%) 

Avoid Night Driving 8 (32%) 14 (67%) 

Avoid Driving at Rush Hour 7 (28%) 14 (67%) 

Avoid Driving in Bad Weather 10 (40%) 13 (62%) 

Increase Following Distance 7 (28%) 10 (48%) 

Avoid High Traffic Roads 7 (28%) 9 (43%) 

Plan Route Before Leave 4 (16%) 9 (43%) 

Avoid Driving Far From Home 6 (24%) 8 (38%) 

Avoid Unfamiliar Areas 5 (20%) 8 (38%) 

Avoid High Speed Roads 5 (20%) 8 (38%) 

Limit Driving in Other Ways 3 (12%) 8 (38%) 

Use In-Vehicle Technology 2 (8%) 8 (38%) 

Avoid Freeways 5 (20%) 6 (29%) 

Avoid Changing Lanes 4 (16%) 5 (24%) 

Use Adaptive Equipment 4 (16%) 3 (14%) 

Avoid Turning Left 3 (12%) 2 (10%) 

Drive Slower Than Speed Limit 2 (8%) 2 (10%) 

Drive Only With Passenger 0 1 (5%) 

Other Changes 3 (12%) 5 (24%) 

Responses for how participants limited driving in other ways included: not going on as 

many long trips, limiting driving in general, being more careful when changing lanes because of 

being surprised by a car, planning trips more carefully, preferring lights (versus stop signs) at 

intersections, driving only in familiar areas in the period before surgery for a cornea transplant, 

making a right turn if exiting and needing to cross four lanes (judging two gaps in traffic), 

avoiding busy areas during tourist season, and not driving on ice. 

Driver Education and Professional Evaluations 

Participants were asked whether, in the past 5 years, they had taken older driver 

education courses, had cataract surgery, had been counseled by a physician about safe driving, 

had their driving ability evaluated by an occupational therapist or other driver evaluator, or had 

been counseled by a pharmacist about the effects of their medications on driving. As shown in 

Table 11, the number of drivers responding positively to these questions ranged from 1 

(physician counseling) to 11 (cataract surgery). Equal percentages of crash-involved and crashfree drivers had undergone cataract surgery, but differences by crash status were seen for the 

other educational and counseling services. Only crash-free older drivers had taken a driver 

education course, with all three indicating that the course taken was through AARP. Only crashinvolved older drivers had received counseling by a physician (n=1) or undergone a professional 

31
	
 

driving evaluation (n=2). However, the two participants who had undergone professional driving 

evaluations completed those evaluations as part of their yearly job requirements (i.e., school bus 

driver, tour bus driver). Finally, a higher percentage of crash-involved older drivers had received 

counseling from their pharmacists about the effects of medications on their ability to drive 

safely. However, pharmacist counseling was not a frequently encountered service (only 5 of the 

46 drivers reported receiving such counseling). 

Table 11. Frequency of Driver Education and Professional Evaluations by Crash Status. 

Education or Professional Evaluation 

No Crash 

N=25 

Crash 

N=21 

Number (%) Receiving 

Education or 

Evaluation 

Number (%) 

Receiving Education 

or Evaluation 

Cataract Surgery 6 (24%) 5 (24%) 

Pharmacist Counseling 1 (4%) 4 (19%) 

Older Driver Education Courses 3 (12%) 0 

Professional Driving Evaluation 0 2 (10%) 

Physician Counseling 0 1 (5%) 

Physical, Mental and Visual Fitness 

Participants were asked whether they regularly do strength and flexibility exercises, 

aerobic exercises, computer exercises to keep mentally sharp, and receive eye exams/updated 

corrective lens prescriptions. Higher percentages of participants reported that they did not 

engage in regular physical (strength and flexibility, aerobic) or mental (computer program) 

exercise, than those who did. However, of those who regularly engaged in exercise (flexibility 

and strength, as well as aerobic), higher rates of participation were reported for crash-involved 

than for crash-free respondents (see Table 12). Approximately equal percentages of crashinvolved and crash-free interviewees reported participating in mental exercise programs on the 

computer. All but two drivers (1 crash-involved and 1 crash-free) reported getting regular eye 

exams/updated corrective lens prescriptions. 

Table 12. Frequency of Regular Physical and Mental Exercise and 

Eye Exams by Crash Status. 

No Crash 

N=25 

Crash 

N=21 

Exercise and Exams Number (%) 

Reporting Regular 

Participation 

Number (%) 

Reporting Regular 

Participation 

Eye Exams 24 (96%) 21 (100%) 

Strength and Flexibility Exercises 5 (20%) 13 (62%) 

Aerobic Exercises 5 (20%) 7 (33%) 

Computer Exercise Programs 5 (20%) 4 (19%) 

32
	
Driving After Alcohol Consumption 

Participants were asked if on occasion they drink alcohol and then drive, and if so, to 

estimate the extent of this behavior. The majority (29 of 46, or 63%) reported that they did not 

drink alcohol and then drive. Crash status did not differentiate those reporting having a drink 

and then driving from those who do not (67% of drivers with crashes did not drink alcohol and 

then drive, compared to 60% of the crash-free drivers who also did not drink alcohol and then 

drive). For the participants who reported driving after drinking alcohol (n=17), most reported 

engaging in this behavior one to two times per year (6 of 17, or 35%). Twenty-nine percent (5 of 

17) reported once per month, 12% (2 of 17) reported doing so three to four times per year, and 

another 12% indicated they did so once per week. One driver reported driving after drinking 

once every two months, and another driver reported doing so daily with dinner. 

33
	
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

FINDINGS 

The principal findings in this study include the interrelationships between functional 

deficits, driver performance errors and crashes described by the taxonomy table, with explicit 

links to behavioral countermeasures deemed most likely to be effective in reducing older driver 

crash risk. Key evidence in support of the taxonomy table is provided by the updated literature 

review, Taxonomy Table Detail pages, and expert panel discussion results. 

The taxonomy table is presented in Figure 6, and the Taxonomy Table Detail pages are 

included in Appendix C. The five Crash Types in which older drivers are most strongly 

overrepresented; the nine Critical Driver Performance Errors highlighted as mediators of these 

crash types; the 15 age-related functional Deficits that contribute to these performance errors, 

based on the literature review; and the 21 behavioral Countermeasures for which there are the 

strongest expectations of efficacy among the expert panelists, are listed below in Table 13. 

Table 13. Crash Types, Performance Errors, Functional Deficits, and Behavioral 

Countermeasures Included in the Taxonomy Table. 

Crash Types Critical Driver 

Performance Errors Deficits Countermeasures 

1. 

2. 

3. 

4. 

5. 

Left Turn at an 

intersection with 

stop-sign control for 

the older driver’s 

approach. Cross 

traffic does not stop. 

Left turn at an 

intersection with 

signal control. 

Permissive phase for 

the older driver’s 

approach. 

Right turn in a 

channelized rightturn lane, merging 

with traffic 

approaching from 

the left on a 

principal arterial 

(40-45 mph) 

Merge at a yield 

sign onto a limited 

access highway. 

Lane change on a 

multilane roadway 

(4+ lanes). 

1. 

2. 

3. 

4. 

5. 

6. 

7. 

8. 

9. 

Failure to visually 

detect potential 

conflicts, hazards, or 

traffic control 

information (without 

regard to cognitive 

status). 

Gap judgment errors 

(assuming no sensory 

deficit). 

Inability to predict the 

development of future 

conflicts from current 

traffic and contextual 

information (assuming 

no sensory deficit). 

Slowed vehicle control 

response (assuming 

appropriate response) 

Inadequate visual 

search/improper 

lookout (assuming no 

sensory deficits) 

Slowed decisionmaking (assuming no 

sensory deficit) 

Lack of understanding 

of rules of the road. 

Lack of understanding 

of safe driving 

practices. 

Inappropriate response 

selection. 

1. 

2. 

3. 

4. 

5. 

6. 

7. 

8. 

9. 

10. 

11. 

12. 

13. 

14. 

15. 

Acuity 

Contrast sensitivity 

Visual fields 

Depth & motion 

perception 

Dark adaptation and 

glare recovery 

Speed of processing 

Selective attention 

Divided attention 

Working memory 

Executive function 

(judgment/decisionmaking) 

Spatial abilities 

Knowledge 

Head/neck/trunk 

range of motion 

Arm strength/range 

of motion/speed of 

movement 

Leg strength/range 

of motion/speed of 

movement 

1. 

2. 

3. 

4. 

5. 

6. 

7. 

8. 

9. 

10. 

11. 

12. 

13. 

14. 

15. 

16. 

17. 

18. 

19. 

20. 

21. 

Refractive correction 

Cataract surgery 

Avoidance of challenging driving 

situations 

Conformal vision enhancement 

system 

Central vision enhancement systems 

Visual field expansion systems 

Training in compensatory head/eye 

movements, scanning strategies 

Speed of processing training 

Physical aerobic activity/training 

Strength and flexibility exercises 

Visual perceptual therapy 

Driver safety education – 

theory/classroom only 

Driver safety education – theory plus 

behind-the-wheel 

Driver safety education – 

interactive/computer-based 

technology 

Education about driving aids 

Collision warning systems 

After-market non-planar driver side 

mirror 

Medical management (incl. 

pharmacy review) 

Cognitive rehab (incl. memory 

training) for normally aging 

population 

Compensatory cognitive/memory 

training for impaired/MCI population 

Pre-trip planning 

34
	
35 

Figure 6. Taxonomy Table. 
 

The taxonomy table reflects our understanding of how changes in functional ability that 

occur with normal aging (plus the diseases that more frequently afflict older people and the 

medications used to treat them) can influence driver performance and crash risk, and ties the 

development and evaluation of behavioral countermeasures to these associations. At present, 

there is a dearth of empirical evidence on which to judge countermeasure effectiveness. 

Accordingly, the collective judgment of the project’s expert panel regarding the likely 

effectiveness of the included interventions to ameliorate the identified functional deficits (shown 

earlier in Figures 3 and 4), including qualifications and reservations based on their professional 

experience, represents an additional noteworthy finding in this research. 

This information is summarized in the following pages, organized around the 15 agerelated functional deficits associated with driver performance errors (shown earlier in Figure 2). 

Findings from the older driver interviews are also included in this discussion, as appropriate. As 

noted earlier, a more detailed summary of countermeasure evaluations and panelists’ opinions 

about countermeasure effectiveness for each deficit may be found in Appendix A. 

ACUITY 

An acuity deficit was associated with a failure to visually detect potential conflicts, 

hazards, or traffic control information (Critical Performance Error #1). This was the only 

Critical Performance Error that the expert panelists mapped to an acuity deficit. This could 

cause a driver to crash as a result of performing any of the first four driving tasks identified as 

high-risk for older drivers: 

1.		 Turning left at an intersection with stop control on the older driver’s approach and where 

cross traffic does not stop. 

2.		 Turning left at an intersection with permissive signal control for the older driver’s 

approach. 

3.		 Turning right at a yield-controlled intersection in a channelized turn lane and merging 

with traffic approaching from the left on a principal arterial. 

4.		 Merging at a yield sign upon entrance to a limited access highway. 

Nine countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of effectiveness in remediating an acuity deficit. Those rated by the 

panelists as most likely to be effective were: 

 Refractive correction (including wavefront technology), and 

 Cataract surgery. 

One panelist with expertise in the area stated that although the ophthalmology literature 

contains ample research on age and satisfaction for refractive error corrective surgery for 

improved performance in everyday tasks, it is unknown whether refractive error correction is 

related to improved driving performance. However, even without research on effectiveness, 

panelists agreed that refractive correction (lens prescriptions) should be advocated solely on the 

prevalence of the problem and the low cost of the intervention, particularly as there appears to be 

a decline in the number of older people who get annual eye exams. Annual eye exams, refractive 

36
	
 

 

 

 

 

 

 

correction, and early diagnosis of treatable conditions (e.g., cataracts) are inexpensive solutions. 

Panelists stressed the importance of vision specialists providing feedback to their patients 

regarding the driver licensing laws in their State, in relation to their level of impairment. They 

noted that this interaction is rare in practice. Increasing patients’ awareness of impairments may 

lead to appropriate self-restriction. 

Panelists rated four of the countermeasures for acuity deficits in the middle third of the 

effectiveness scale, indicating a need for more information/research before they could endorse 

the countermeasures: 

 Avoidance of challenging driving situations; 

 Central vision enhancement systems; 

 Collision warning systems; and 

 Medical management (including pharmacy review). 

The panel noted that avoiding challenging driving situations may be more effective if the 

driver chooses to adopt the strategy as opposed to a DRS or licensing agency imposing driving 

restrictions. The extent to which drivers comply with externally imposed restrictions is unknown. 

Judgment and self-awareness are critical to selecting and applying an appropriate 

restriction countermeasure; a client must remember to employ it and believe it is needed. 

Panelists noted that people try to self-regulate when there are alternative transportation options, 

but there are times when they feel they must drive even if they'd rather not. This point was 

underscored in the older driver interviews. However, making people aware of deficits is the first 

step in getting people to self restrict, if they will self restrict. Ophthalmologists and optometrists 

need to be included as targets of outreach. 

Panelists agreed that central vision enhancement systems3 have potential if they are 

accompanied by training, with driving safety assessed after training. Licensing should be 

recommended only after a driver participates in a low-vision driving rehabilitation program and 

shows effective and safe use of an apparatus. Drivers should be trained to use the lens only for 

spotting (5-10% of time). Panelists indicated that the training curriculum and design of lenses 

need to be validated and standardized. Panelists deemed this countermeasure appropriate only 

for drivers without cognitive deficits. 

With regard to collision warning systems, panelists indicated a need for forward as well 

as side-collision warning and noted that, in addition to providing a warning, the system should 

cause the vehicle to brake. A word of caution was provided by an occupational therapist who 

mentioned that although certain advanced technologies may enable older people to drive more 

safely for a longer period of time, they also may allow unsafe drivers to continue driving. 

Panelists voiced concern about drivers relying exclusively on the collision warning technology to 

3 Central vision enhancement systems include bioptic telescopic lenses, which are a lens system with a telescope 

attached to a pair of glasses, mounted above the normal line of sight. This allows a trained user to detect objects or 

movement within the driving scene using the wide field of view available through the regular spectacle lens (the 

“carrier” lens) and to resolve fine details such as road sign messages by glancing briefly and intermittently into and 

out of the miniature telescopic unit (by a downward tilt of the head). 

37
	
 

detect hazards, especially for backing up, where older drivers may perform the maneuver without 

doing head/shoulder checks. Also, older people may be more distracted than assisted by some of 

the advanced technologies. Panelists noted that training is a key element in advanced technology 

countermeasures, particularly for older drivers. A barrier to this training is that adapted cars at 

most rehabilitation centers do not include high-end/high tech equipment. In the driver interviews 

conducted in this project, only 10 of the 46 drivers indicated using in-vehicle technology. It is 

unknown what types of equipment these older drivers used (navigation, collision warning, vision 

enhancement, etc). 

Panelists indicated that medical management was an appropriate countermeasure for all 

15 listed functional deficits, including acuity deficits. They stated that medical management 

leads to early detection of impairments and remediation, and as such, it is important for 

researchers/sponsors of research to provide education to physicians, pharmacists, and eyecare 

specialists linking medical conditions to functional impairments and driving risk, so they can 

educate their patients. Patients rely on their healthcare providers to diagnose, treat, and counsel, 

so their physicians and pharmacists also need to be educated. Of the 46 older drivers 

interviewed in this project, only 1 reported receiving advice from a physician about driving, and 

only 5 had been counseled by their pharmacist about the effects of medication on their ability to 

drive safely. 

The three countermeasures rated as the least likely to effectively remediate an acuity 

deficit, given the present state-of-the-knowledge, were the three driver safety education 

countermeasures: 

 Theory/classroom only; 

 Theory plus behind-the-wheel training; and 

 Interactive/computer-based technology. 

CONTRAST SENSITIVITY 

A contrast sensitivity deficit was associated with a failure to visually detect potential 

conflicts, hazards, or traffic control information (Critical Performance Error #1). As with an 

acuity deficit, this was the only Critical Performance Error that the expert panelists mapped to a 

contrast sensitivity deficit. This driver performance error could cause an older driver to be 

involved in a crash in any of the five driving situations prioritized as high-risk for older drivers, 

including making a lane change on a multilane roadway. 

Ten countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate a contrast sensitivity deficit. Those rated by the 

panelists as most likely to be effective were the same as for an acuity deficit: 

 Refractive correction (including wavefront technology); and 

 Cataract surgery. 

Panelists agreed that cataract surgery is a relatively inexpensive treatment, and resulting 

visual improvements have been shown to result in crash reduction. Cataracts are often the only 

38
	
 

medical condition affecting driving performance. Even if the crash reduction benefit is small, 

cataract surgery may provide a large public health benefit because of the large number of people 

affected. Interestingly, of the 46 drivers interviewed in this project, 45 reported having a regular 

eye exam/updated corrective lens prescription, and 11 reported having cataract surgery. 

Seven of the 10 countermeasures were rated in the middle third of the effectiveness scale, 

indicating a need for more information/research before panelists could endorse them as likely to 

be effective for a contrast sensitivity deficit. These were: 

 Avoidance of challenging driving situations; 

 Conformal vision enhancement systems; 

 Central vision enhancement systems; 

 Driver education that incorporates theory plus behind-the-wheel training; 

 Driver education using interactive/computer-based technology; 

 Collision warning systems; and 

 Medical management (including pharmacy review). 

Regarding avoidance of challenging driving situations, driver awareness of visual 

impairments is a key to getting drivers to restrict their driving. This underscores the need to 

educate eyecare professionals about contrast sensitivity deficits and driver performance and 

include them as targets for outreach to their patients. Decina and Staplin (1993) found that older 

drivers who could pass the State acuity standard for driving but who suffered impairment in 

contrast sensitivity were at the highest risk of crashing. Counseling by an optometrist or 

ophthalmologist about avoiding driving during periods of reduced lighting could encourage such 

drivers to self restrict appropriately. 

The two driver education interventions received higher effectiveness ratings to remediate 

a contrast sensitivity deficit than an acuity deficit. Comments and concerns for all 

countermeasures were discussed above (in relation to acuity deficits) with the exception of 

conformal vision enhancement systems. 

A conformal vision enhancement system overlays an image on the windshield (as a 

head’s-up display) that is directly superimposed on the object it is providing information about. 

Panelists stated that older drivers in focus groups have indicated that they don’t like anything in 

their cars that takes their focus away from the road, either on the windshield or on a head’s-down 

display in the vehicle. These drivers would choose not to drive in challenging situations rather 

than use a device that may take their attention from the road, or that may be more difficult to 

operate. Another panelist indicated that following training in equipment use, older drivers have 

accepted such countermeasures; emphasizing that training is a critical component for new 

technologies to assist older drivers. Panelists indicated that conformal vision enhancement 

systems are a logical countermeasure for a contrast sensitivity deficit, pending further research. 

Driver safety education providing only theory received a likelihood of effectiveness 

rating in the bottom third of the scale for drivers with a contrast sensitivity deficit. 

39
	
 

 

 

VISUAL FIELDS 

A visual fields deficit was associated with a failure to detect potential conflicts, hazards, 

or traffic control information (Critical Performance Error #1). As with acuity and contrast 

sensitivity deficits, this was the only Critical Performance Error that the expert panelists mapped 

to a deficit in visual fields. This performance error could cause an older driver to be involved in 

a crash in any of the five driving situations prioritized as high-risk for older drivers. 

Nine countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate a visual fields deficit. Only one was rated by the 

panelists as highly likely to be effective: training in compensatory head/eye movements 

(scanning strategies). Panelists agreed that although this is an appropriate countermeasure for 

visual field deficits, it is not appropriate for drivers with cognitive impairment. This type of 

training has been used for telescopic and amorphic lens drivers and has been effective in 

improving peripheral visual detection. 

Panelists rated seven of the nine countermeasures in the middle third of the effectiveness 

scale, indicating a need for more information/research before they could endorse the 

interventions for drivers with visual fields deficits. These were: 

 Avoidance of challenging driving situations; 

 Central vision enhancement systems; 

 Visual field expansion systems; 

 Driver safety education incorporating theory plus behind-the-wheel-training; 

 Driver safety education delivered via interactive/computer-based technology; 

 Education about driving aids (e.g., CarFit); and 

 Medical management (including pharmacy review). 

Comments and concerns for visual field expansion systems and education about driving 

aids are presented below; discussion for the other five countermeasures was presented earlier. 

Panelists indicated that visual field expansion systems have a lot of promise for 

remediation of visual field deficits (based on small-scale studies); however, larger studies need to 

be conducted and there is a need for the OT and rehabilitation communities to define and 

develop the curricula. Panelists considered prisms and other technologies for addressing visual 

field loss not appropriate for drivers with cognitive deficits. They indicated that a 100-degree 

binocular field is a good minimum standard; if a driver has less than 100 degrees and is adamant 

about driving, the standard of care should be to offer these systems to see if the driver can adapt. 

Further, a video feed may be better than amorphic lenses to expand the visual field, because the 

peripheral extent required for driving is incorporated in the lens. 4 

4

 For patients with tunnel vision, Peli, Luo, Bowers, and Rensing (2007) describe an augmented-vision system using 

a miniature video camera that provides minified edge images of the scene shown on a head-mounted display. This 

enables patients to see and detect potential obstacles and locate other objects that, without the minification, would 

fall outside of their residual visual field. Once an object is detected in the head-mounted display, patients can view it 

directly though the see-through display with the full resolution and color sensitivity of their natural vision, without 

limiting the clarity of the see-through view. 

40
	
 

 

 

With regard to education about driving aids, Panelists stated that many vehicles have 

safety features that need to be adjusted to meet the needs of the driver, and older drivers often do 

not know how to make these adjustments. Thus, education in fitting safety equipment to the 

driver has the potential to help older drivers stay on the road longer. This countermeasure merits 

further research. Several panelists (OTs) indicated that some CarFit event staff remove mirrors 

from their example bag because they don’t want to be liable for somebody getting a mirror, not 

understanding how to use it, and having a crash. Using adaptations and mirrors requires training 

and practice. At CarFit, an OT may adjust a mirror for a driver and explain how the new setting 

eliminates blind spots. The OT will then set the mirrors back as they were when the driver 

arrived at the event. This is required to prevent OTs from being liable for making a change; the 

driver must make the change. In general, more research is needed to determine optimal mirror 

positions, driver training required to use them safely, and the professionals qualified to deliver 

the training. 

Driver safety education providing only theory received a likelihood of effectiveness 

rating in the bottom third of the scale for drivers with a visual field deficit. 

DEPTH AND MOTION PERCEPTION 

A deficit in depth or motion perception was associated with two of the nine Critical 

Performance Errors: a gap-judgment error, where a driver is not able to accurately estimate 

closing speed and distance (Critical Performance Error #2); and an inability to predict the 

development of future conflicts from current traffic and contextual information (Critical 

Performance Error #3). Both errors assume there is no sensory deficit. Each of these Critical 

Performance Errors could result in any of the five crash types in which older drivers are most 

strongly overrepresented, as highlighted in the taxonomy table (see Figure 6). 

Six countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate a depth or motion perception deficit. None were 

rated as highly likely to be effective, given the present state of the knowledge. 

Four received likelihood-of-effectiveness ratings in the middle of the scale, indicating a 

need for more research: 

 Avoidance of challenging driving situations. 

 Driver safety education incorporating theory with behind-the-wheel instruction. 

 Driver safety education delivered via interactive/computer-based technology. 

 Medical management (including pharmacy review). 

Two countermeasure options received ratings at the bottom of the likelihood-ofeffectiveness scale: 

 Driver education-theory/classroom only; and 

 Education about driving aids. 

41
	
 

 

 

DARK ADAPTATION AND GLARE RECOVERY 

A deficit in dark adaptation and glare recovery was associated with a failure to visually 

detect potential conflicts, hazards, or traffic control information (Critical Performance Error #1). 

This was the only Critical Performance Error that the expert panelists mapped to this deficit. 

This driver performance error could cause a crash in three of the five driving situations identified 

as high-risk for older drivers: turning right at a yield-controlled intersection in a channelized turn 

lane and merging with traffic approaching from the left on a principal arterial (Crash Type #3); 

merging at a yield sign upon entrance to a limited access highway (Crash Type #4); and making 

a lane change on a multilane roadway (Crash Type #5). 

Seven countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood of effectiveness to remediate a dark adaptation and glare 

recovery deficit. Only one was rated by panelists as highly likely to be effective: cataract 

surgery. 

Four were rated in the middle of the scale, indicating the need for more research: 

 Avoidance of challenging driving situations; 

 Driver safety education incorporating theory with behind-the-wheel instruction;
	

 Driver safety education delivered via interactive/computer-based technology; and 

 Medical management (including pharmacy review). 

Two potential countermeasures received ratings at the bottom of the likelihood-ofeffectiveness scale: 

 Driver education-theory/classroom only; and 

 Education about driving aids. 

SPEED OF PROCESSING 

A deficit in speed of processing was associated with six of the nine Critical Performance 

Errors: a gap-judgment error, (Critical Performance Error #2); an inability to predict the 

development of future conflicts from current traffic and contextual information (Critical 

Performance Error #3); slowed vehicle control response (Critical Performance Error #4); 

inadequate visual search/improper lookout (Critical Performance Error #5); slowed decisionmaking, where the traffic situation has changed by the time a maneuver is initiated, resulting in a 

potential conflict (Critical Performance Error#6); and inappropriate response selection (Critical 

Performance Error #9). All Critical Performance Errors with the exception of inappropriate 

response selection could lead to any of the five high-priority crash types listed at the top level of 

the taxonomy table in Figure 8. Inappropriate response selection could lead to crashes at 

intersections involving a left turn at a stop sign (Crash Type 1), a left turn at a permissive signal 

(Crash Type 2), or a crash when turning right at a yield sign in a channelized right-turn lane 

(Crash Type 3). 

42
	
 

 

 

Eight countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate a speed of processing deficit. None were rated 

as highly likely to be effective, given the present state of the knowledge. 

Panelists rated seven of these eight countermeasures in the middle third of the 

effectiveness scale, indicating that there was a need for more information/research before they 

could be endorsed as likely to remediate a speed of processing deficit. These were: 

 Avoidance of challenging driving situations; 

 Speed of processing training; 

 Physical aerobic/activity training; 

 Driver safety education incorporating theory plus behind-the-wheel-training; 

 Driver safety education delivered via interactive/computer-based technology; 

 Collision warning systems; and 

 Medical management (including pharmacy review). 

Comments and concerns for all countermeasures with the exception of speed of 

processing training and physical aerobic/activity training were discussed above for contrast 

sensitivity deficits. 

With regard to speed of processing training, panelists agreed this may be a viable 

countermeasure, but there is a need to establish the link between training on the task and transfer 

to driving. Prior work has demonstrated that speed-of-processing training improves speed-ofprocessing performance on the trained task, but the question of how well such training transfers 

to the speed at which people perform everyday tasks with real-world stimuli has not yet been 

answered satisfactorily. Pending the emergence of such evidence, the duration or sustainability 

of training effects also need more research; and, the depth of training (time course, number of 

trials) needed to produce operationally significant improvements in performance is unknown. 

Because of hypothesized mobility benefits, a determination of whether speed-of-processing gains 

are associated with changes in driver exposure is also of interest. New findings from the 

ACTIVE trial may shed light on the impact of speed of processing training on driving outcomes 

at six years after entry into the study, according to one panelist; but these findings were not 

published as of the date of this report. 

With regard to physical aerobic activity/training, panelists noted that the literature in the 

area of exercise and cognitive function is mixed, with some studies showing improvement and 

others showing no effect. One problem may be that the exercise interventions are too brief to 

result in an improvement. Of the 46 drivers interviewed in this project, only 12 reported that 

they participate in regular aerobic exercise. 

Driver safety education providing only theory received a likelihood of effectiveness 

rating in the bottom third of the scale for drivers with a speed of processing deficit. 

43
	
 

SELECTIVE ATTENTION 

Critical Performance Errors associated with a deficit in selective attention mirror those 

associated with a deficit in speed of processing (namely, #2, 3, 4, 5, and 6), leading to any of the 

five prioritized Crash Types in the taxonomy table; and Critical Performance Error #9, leading to 

Crash Types 1, 2, and 3. 

Ten countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate a selective attention deficit. None were rated as 

highly likely to be effective, given the present state of the knowledge. 

Nine of the ten countermeasures were rated in the middle third of the effectiveness scale, 

indicating that there was a need for more information/research before they could be endorsed by 

the panelists as likely to be effective for a selective attention deficit. These were: 

 Avoidance of challenging situations; 

 Conformal vision enhancement systems; 

 Speed of processing training; 

 Driver safety education incorporating theory plus behind-the-wheel-training; 

 Driver safety education delivered via interactive/computer-based technology; 

 Collision warning systems; 

 Medical management (including pharmacy review); 

 Cognitive rehabilitation (including memory training) for the normally aging population; 

and 

 Compensatory cognitive/memory training for the mildly cognitively impaired (MCI) 

population. 

Comments and concerns for all countermeasures, with the two exceptions of cognitive 

rehabilitation (including memory training) for the normally aging population and compensatory 

cognitive/memory training for the mildly cognitively impaired population, were discussed above 

for contrast sensitivity and speed of processing deficits. 

With regard to cognitive rehabilitation (and memory training) for the normally aging 

population, panelists indicated that cognitive rehabilitation builds subskills for the driving task, 

but OT’s must explain how the skill a client has learned in the clinic could be applied to 

everyday practical situations such as driving. Panelists agreed that cognitive rehabilitation has 

real promise as a countermeasure, but is in its infancy as far as developing the training protocols 

and guidelines to make sure the training is appropriate for the individual, including preventative, 

restorative, and maintenance interventions. Also, few cognitive rehabilitation specialists also 

specialize in driving rehabilitation. Because many of the current tools are untested, panelists 

expressed concern with marketing cognitive retraining tools to the public, as opposed to their 

application by experts who can make informed decisions. Panelists indicated that cognitive 

rehabilitation and memory training are not appropriate for the dementia population, because 

dementia is progressive; clients with dementia cannot learn and remember the strategies. 

44
	
The panel considered compensatory strategies/memory training that target the strategic 

level of driving performance to be appropriate for the MCI population. Panelists were cautious 

about recommending cognitive interventions for people with early stage dementia, and ruled out 

restorative interventions for this group. Someone with early stage dementia may have good 

situational awareness and operational control of a vehicle, but could have a memory deficit that 

would manifest in navigational difficulties. A panelist who is a physician indicated that it is 

difficult to define where MCI begins and where it ends. It is unknown whether drivers with MCI 

can benefit from interventions because, historically, they have been excluded from studies so as 

not to confound the study results. 

One countermeasure, driver education-theory/classroom only, received a rating at the 

bottom of the likelihood-of-effectiveness scale for drivers with selective attention deficits. 

DIVIDED ATTENTION 

Critical Performance Errors associated with a deficit in divided attention mirror those 

associated with a deficit in selective attention and speed of processing (namely, #2, 3, 4, 5, and 

6), leading to any of the five Crash Types highlighted in the taxonomy table; and Critical 

Performance Error #9, leading to Crash Types 1, 2, and 3. 

Ten countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate a divided attention deficit. None were rated as 

highly likely to be effective, given the present state of the knowledge. 

Nine of the ten countermeasures were rated in the middle third of the effectiveness scale, 

indicating that there was a need for more information/research before they could be endorsed by 

the panelists as likely to be effective for a divided attention deficit. These were: 

 Avoidance of challenging situations; 

 Speed of processing training; 

 Physical aerobic activity/training; 

 Driver safety education incorporating theory plus behind-the-wheel-training; 

 Driver safety education delivered via interactive/computer-based technology; 

 Collision warning systems; 

 Medical management (including pharmacy review); 

 Cognitive rehabilitation (including memory training) for the normally aging population; 

and 

 Compensatory cognitive/memory training for the mildly cognitively impaired (MCI) 

population. 

One countermeasure, driver education-theory/classroom only, received a rating at the 

bottom of the likelihood-of-effectiveness scale for drivers with divided attention deficits. 

45
	
 

 

WORKING MEMORY 

A deficit in working memory was associated with two of the nine Critical Performance 

Errors: a gap-judgment error (Critical Performance Error #2); and an inability to predict the 

development of future conflicts from current traffic and contextual information (Critical 

Performance Error #3). Both errors could lead to any of the five Crash Types highlighted in the 

taxonomy table in which older drivers are over-involved. 

Eight countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate a working memory deficit. None were rated as 

highly likely to be effective, given the present state of the knowledge. 

Seven of the eight countermeasures were rated in the middle third of the effectiveness 

scale, indicating that there was a need for more information/research before they could be 

endorsed by the panelists as likely to be effective for a working memory deficit. These were: 

 Physical aerobic activity/training; 

 Driver safety education incorporating theory plus behind-the-wheel-training; 

 Driver safety education delivered via interactive/computer-based technology;
	

 Medical management (including pharmacy review); 

 Cognitive rehabilitation (including memory training) for the normally aging population; 

 Compensatory cognitive/memory training for the mildly cognitively impaired (MCI) 

population; and 

 Pre-trip planning. 

Comments and concerns for all countermeasures with the exception of pre-trip planning 

were discussed earlier. 

Pre-trip planning is at the strategic level in hierarchical models of driver behavior (cf. 

Michon, 1985). It involves a conscious decision to plan the intended driving route, including 

avoiding challenging or difficult intersections, and could also include other self-imposed 

restrictions relating to time of day (daytime rather than night), type of weather (dry versus in the 

rain or snow) and subjective health conditions (e.g., avoiding driving when fatigued, or when 

impaired by medication-side effects, or impairing symptoms of medical conditions). The expert 

panelists added this countermeasure to the taxonomy table. They agreed that it merits further 

research for deficits in working memory and executive function, as well as for knowledge 

deficits. Because it requires practice, pre-trip planning may also help with memory deficits. 

Panelists indicated that trip planning ties in with mobility management counseling—the 

idea of introducing other modes of transportation for those times that a driver shouldn’t drive, 

because of functional impairments. This strategy may extend driving, to the extent that nearmisses or confusion while driving can result from being lost. If people can learn an intervention 

like memorizing or previewing a (novel) route, it could translate to greater capacity for serial 

processing of the moment-to-moment demands of traffic conditions. In the older driver 

interviews conducted in this project, 43% of the crash-involved sample and 16% of the crash46
	
free sample reported that they plan their route before they leave, and that this is a change in 

driving habits made over the past 5- to 10-year period. 

One countermeasure, driver education-theory/classroom only, received a rating at the 

bottom of the likelihood-of-effectiveness scale for drivers with working memory deficits. 

EXECUTIVE FUNCTION (JUDGMENT AND DECISION-MAKING) 

Critical Performance Errors associated with a deficit in executive function mirror those 

associated with a deficit in selective attention, divided attention, and speed of processing 

(namely, #2, 3, 4, 5, and 6), leading to any of the five Crash Types highlighted in the taxonomy 

table; and Critical Performance Error #9, leading to Crash Types 1, 2, and 3. 

The same eight countermeasures identified to remediate a working memory deficit were 

identified as appropriate for remediating a deficit in executive function, with varying degrees of 

effectiveness. None were rated as highly likely to be effective, given the present state of the 

knowledge. 

Seven of the eight countermeasures were rated in the middle third of the effectiveness 

scale, indicating that there was a need for more information/research before they could be 

endorsed by the panelists as likely to be effective for a deficit in executive function. These were: 

 Physical aerobic activity/training; 

 Driver safety education incorporating theory plus behind-the-wheel-training; 

 Driver safety education delivered via interactive/computer-based technology; 

 Medical management (including pharmacy review); 

 Cognitive rehabilitation (including memory training) for the normally aging population; 

 Compensatory cognitive/memory training for the mildly cognitively impaired (MCI) 

population; and 

 Pre-trip planning. 

One countermeasure, driver education-theory/classroom only, received a rating at the 

bottom of the likelihood-of-effectiveness scale for drivers with deficits in executive functioning. 

SPATIAL ABILITIES 

A deficit in spatial abilities was associated with four of the nine Critical Performance 

Errors: a gap-judgment error (Critical Performance Error #2); an inability to predict the 

development of future conflicts from current traffic and contextual information (Critical 

Performance Error #3); inadequate visual search/improper lookout (Critical Performance Error 

#5); and slowed decision-making, where the traffic situation has changed by the time a maneuver 

is initiated, resulting in a potential conflict (Critical Performance Error #6). All four errors could 

lead to any of the five Crash Types highlighted in the taxonomy table in which older drivers are 

over-involved. 

47
	
Five countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate a deficit in spatial abilities. None were rated as 

highly likely to be effective, given the present state of the knowledge. In addition, the panelists 

who are OTs noted a serious deficit in spatial abilities should categorically rule out driving, as 

such deficits manifest themselves in lane control difficulty. 

Four of the five countermeasures were rated in the middle third of the effectiveness scale, 

indicating that there was a need for more information/research before they could be endorsed by 

the panelists as likely to be effective for a spatial abilities deficit. These were: 

 Visual perceptual therapy; 

 Driver safety education incorporating theory plus behind-the-wheel-training; 

 Driver safety education delivered via interactive/computer-based technology; and 

 Medical management (including pharmacy review). 

One countermeasure, driver education-theory/classroom only, received a rating at the 

bottom of the likelihood-of-effectiveness scale for drivers with deficits in spatial ability. 

KNOWLEDGE 

A knowledge deficit was associated with three of the nine Critical Performance Errors: 

an inability to predict the development of future conflicts from current traffic and contextual 

information (Critical Performance Error #3); a lack of understanding of rules of the road (Critical 

Performance Error #7), or a lack of understanding of safe driving practices (Critical Performance 

Error #8). Errors 3 and 8 could result in any of the five Crash Types highlighted in the taxonomy 

table in which older drivers are overrepresented. Error 7 could lead to four of the five (the 

exception being a crash associated with a lane-change maneuver). 

Six countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate a knowledge deficit. Five of the six were rated 

as highly likely to be effective, given the present state of the knowledge. These included: 

 Driver safety education: theory/classroom only; 

 Driver safety education incorporating theory plus behind-the-wheel-training; 

 Driver safety education delivered via interactive/computer-based technology; 

 Education about driving aids (such as CarFit); and 

 Pre-trip planning. 

Knowledge deficits were the only type of deficit for which driver education was rated 

highly likely to be effective. For knowledge deficits, there was a general consensus that it makes 

sense to provide education, despite mixed results in the research literature, since it is likely to 

work for some drivers. 

One countermeasure, medical management (including pharmacy review), was rated in the 

middle third of the effectiveness scale, indicating that there was a need for more 

48
	
 

information/research before they could be endorsed by the panelists as likely to be effective for a 

knowledge deficit. 

HEAD/NECK/TRUNK RANGE OF MOTION 

A deficit in head/neck/trunk range of motion was associated with two of the nine Critical 

Performance Errors: failure to visually detect potential conflicts, hazards, or traffic control 

information (Critical Driver Performance Error #1); and slowed vehicle control response 

(Critical Driver Performance Error #4). Each of these errors could lead to four of the five Crash 

Types highlighted in the taxonomy table in which older drivers are over-involved. The only 

exception is Crash Type 2, because in that scenario a driver would be looking straight ahead at 

the signal and/or assessing gaps in oncoming traffic. This contrasts with Crash Types 1 and 3, 

where a driver needs to scan left and right for traffic approaching on a cross street; with Crash 

Type 4, where the conflict arises from traffic merging from the sides; and with Crash Type 5, 

where conflicts involve vehicles approaching from the rear. 

Ten countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate a deficit in head/neck/trunk range of motion. 

Three were rated as highly likely to be effective, given the present state of the knowledge. These 

were: 

 Training in compensatory head/eye movements (scanning strategies); 

 Strength and flexibility exercises; and 

 An aftermarket, non-planar driver side mirror. 

A panelist who is a vision specialist also indicated that eye movement training would be 

important for someone who can’t move his or her neck. 

With regard to strength and flexibility exercises, countermeasure evaluations have 

demonstrated improvements in on-road driving performance, and panelists agreed that this was 

an appropriate countermeasure with a high likelihood of effectiveness. In the older driver 

interviews conducted in this project, 62% of the crash-involved and 20% of the crash-free 

sample indicated that they regularly participated in strength and flexibility exercises. 

With regard to the use of non-planar mirrors, while panelists judged this intervention as 

likely to be effective, participating OTs were concerned that this practice could incur liability in 

a rehabilitation context. They noted that (re-)aiming mirrors for drivers during a CarFit event 

incurs liability. So, after instructing drivers about proper aiming techniques, OTs put the mirrors 

back to their original position, i.e., as they were aimed when the driver arrived at the evaluation. 

Current standards require the driver side mirror to be planar (flat), while the passenger side 

mirror may be convex or planar; however, aftermarket “bulls eye” convex mirrors are available 

that can be applied to the planar mirror. No evaluations of this countermeasure were uncovered 

in the literature review, specific to older drivers. Prior evaluations by NHTSA have found that 

detection of adjacent-lane vehicles can be enhanced by the use of driver’s side non-planar 

mirrors, but the image distortions they introduce can render drivers’ gap and distance judgments 

for vehicles approaching/overtaking from the rear inaccurate (Staplin, Lococo, Sim, & Gish, 

49
	
 

1998). Thus, non-planar mirrors would require optical distortion training, but there is no 

standard for providing such instruction. 

Six of the 10 countermeasures were rated in the middle third of the effectiveness scale, 

indicating a need for more information/research before panelists could endorse them as likely to 

be effective for a deficit in head/neck/trunk range of motion. These were: 

 Physical aerobic activity/training. 

 Driver safety education incorporating theory plus behind-the-wheel-training. 

 Driver safety education delivered via interactive/computer-based technology. 

 Education about driving aids. 

 Collision warning systems. 

 Medical management (including pharmacy review). 

One countermeasure, driver education-theory/classroom only, received a rating at the 

bottom of the likelihood-of-effectiveness scale for drivers with head/neck/trunk range of motion 

deficits. 

For all three physical deficits listed in the taxonomy table (restrictions in head/neck/trunk 

range of motion; arm strength range of motion/speed of movement; and leg strength range of 

motion/speed of movement), panelists stated that classroom driver education may be useful as it 

raises awareness of deficit so drivers can self restrict, and may also motivate individuals to 

initiate activity (e.g., to exercise). Panelists deemed education alone as unlikely to be effective. 

ARM STRENGTH/RANGE OF MOTION/SPEED OF MOVEMENT AND LEG 

STRENGTH RANGE OF MOTION/SPEED OF MOVEMENT 

These two deficits are grouped together for discussion because they underlie the same 

Critical Driver Performance Error and resulting crash types, and may be remediated with the 

same behavioral countermeasures. 

A deficit in arm or leg strength/speed of movement/range of motion was associated with 

one of the nine Critical Performance Errors: slowed vehicle control response (Critical Driver 

Performance Error #4). This error could lead to any of the five Crash Types highlighted in the 

taxonomy table in which older drivers are over-involved. 

Seven countermeasures were identified from the literature review and expert panel tasks 

with varying degrees of likelihood to remediate these deficits. Two, physical aerobic 

activity/training and strength and flexibility exercises, were rated as highly likely to be effective, 

given the present state of the knowledge. 

Four were rated in the middle third of the effectiveness scale, indicating a need for more 

information/research before they could be endorsed by the panelists as likely to be effective for 

these deficits. These were: 

 Driver safety education incorporating theory plus behind-the-wheel-training; 

50
	
 Driver safety education delivered via interactive/computer-based technology; 

 Education about driving aids (e.g., CarFit); and 

 Medical management (including pharmacy review). 

One countermeasure, driver education-theory/classroom only, received a rating at the 

bottom of the likelihood-of-effectiveness scale for drivers with deficits in arm or leg 

strength/speed of movement/range of motion. 

51
	
 

 

 

 

DISCUSSION AND CONCLUSIONS 

This study addressed the role of specific age-related functional deficits as contributing 

factors in selected types of motor vehicle crashes by older drivers, via their potential to influence 

the probability and/or severity of critical driver performance errors. To the extent these 

connections are sound, they underscore the potential for behavioral countermeasures targeted to 

the remediation or accommodation of such deficits to attenuate critical errors in performance, 

and thus reduce crash risk. The following discussion highlights several conclusions from this 

work, and identifies opportunities to advance older driver safety and mobility through continuing 

research and program development based on present findings. 

One conclusion derives from examination of the linkages of the five prioritized Crash 

Types to the nine Critical Driver Performance Errors (see Figure 6). All but two Critical Driver 

Performance Errors (which in turn manifest age-related functional deficits) could result in any of 

the major Crash Types. The only exceptions are for Error 7 (lack of understanding of rules of 

the road), which lacks a tie to Crash Type 5, and Error 9 (inappropriate response selection), 

which lacks ties to Crash Types 4 and 5. This suggests that remediation of functional deficits has 

broad potential for crash reduction; it is not specific to any particular crash type. 

Another conclusion may be drawn from a comparison of the driver interview data on 

driving difficulties and the Critical Driver Performance Errors listed in the taxonomy table. 

Overall, few drivers reported difficulty with any of the queried driving situations, with the 

exception of difficulty seeing at night (44% of the crash-free sample and 48% of the crashinvolved sample). Difficulty seeing at night could lead to Critical Driver Performance Error 1: 

failure to visually detect potential conflicts. Notably, 67% of those who indicated they had 

difficulty driving at night reported driving at night anyway. At the same time, self-reports 

indicated that two-thirds of the crash-involved drivers and a third of the crash-free drivers 

avoided night driving. And, 44 of 46 drivers interviewed (96%) indicated that they regularly 

have an eye exam, and 24% of this sample reported having cataract surgery. These data reveal 

that when older drivers are aware of a functional impairment, they will make an effort to 

compensate or correct it, but are likely to continue to drive in some instances. 

A high percentage of drivers reported no difficulty with the following situations: judging 

gaps (93%), detecting traffic in the periphery (93%), judging the actions of others (80%), and 

changing lanes/merging (87%). These difficulties feed directly into the Critical Driver 

Performance Errors listed in the taxonomy table (specifically #2, 3, and 5), which were 

associated with all five Crash Types in which older drivers are overrepresented. Very few of the 

older drivers interviewed reported avoiding the driving situations that are associated with the 

greatest increase in crash risk for this group (only 11% avoided left turns and 20% avoided 

changing lanes). This suggests that many older drivers are unaware of these consequences of 

functional aging on driving task performance, presenting a significant opportunity to improve 

safety through appropriate educational interventions. 

As emphasized in this report, determinations of the likely effectiveness of the included 

behavioral countermeasures are based largely on expert opinion, with only limited evaluation 

data available, and must therefore be regarded as preliminary. Nevertheless, the experience of 

52
	
 

 

the participating clinicians provides valuable guidance for developing and implementing 

behavioral countermeasures, even as evaluation studies proceed. 

One unavoidable conclusion is that self-awareness drives the application of any strategy 

or countermeasure unless it is absolutely passive to the client’s will. Passive measures may be 

employed without dependence on the person's will or awareness. But if an individual must 

remember to employ a countermeasure or believe it is needed, then a rehabilitation professional 

should be involved in determining if a particular intervention is appropriate. 

In this regard, the role of the professional in implementing the specialized training and/or 

adaptive equipment associated with many potential countermeasures to preserve or restore 

function among older drivers needs to be clearly stated. Attempts to keep impaired drivers on 

the road longer with devices or strategies that improve competence in very specific areas carry 

significant risk. The fact that a professional driving evaluation costs several hundred dollars, in 

most cases not reimbursable by insurance, may be cited as a rationale for the narrow application 

of a countermeasure instead of a more comprehensive approach. Research is needed to define 

the boundaries of what can be responsibly prescribed or advocated as a countermeasure for agerelated diminished capabilities outside of a formal rehabilitation context, and what interventions 

should or shall only be administered with the guidance and supervision of a driving 

rehabilitation professional. 

This study has for the most part excluded adaptive equipment in its consideration of 

behavioral countermeasures—at least the most common examples: spinner knobs, pedal 

extenders, left foot accelerators, and seat cushions. As noted earlier, research findings that 

document the effectiveness of such devices are elusive. But the manner in which these aids are 

prescribed further underscores the role of rehabilitation professionals. Under best practice, a 

driver would go to a driving rehabilitation specialist (DRS) who would consider their vehicle 

model and all the types of adaptations that might work, and tailor their choice to the individual’s 

needs. Then, the driver would purchase the adaptation that was recommended by the DRS, and 

would have it installed in their vehicle. The DRS would then inspect the installation and train 

the driver in the use of the equipment. In reality, adaptive equipment is readily available for 

purchase via the Internet or in auto parts stores, and people buy it without being evaluated for 

their need, or trained in its use; and, there are no controls for proper installation. Research is 

needed to develop standards of care for adaptive equipment installation and training. 

The work in this project provides additional guidance for behavioral countermeasures in 

two specific areas. First, the vision countermeasures require intact cognition, to realize the 

desired safety and performance gains. If cognition is not intact, then vision measures must be 

supplemented by other strategies that address the cognitive deficit. Also, some countermeasures 

are used in combination with legal restrictions on driving. Judgment and self-awareness are 

critical to the effectiveness of a restriction countermeasure. 

Finally, there is a clear need for continuing research to understand the extent to which 

age-related functional change places older drivers (and all motorists) at risk, and the extent to 

which existing or innovative countermeasures can compensate for such changes. In developing 

this taxonomy of older driver behaviors and crash risk, the current study has provided important 

53
	
 

insights about the operating conditions and traffic situations where crashes involving older 

drivers are most prevalent. Yet there is a critical gap in knowledge about how often older drivers 

are exposed to the most risky situations, either relative to the exposure of all drivers or to their 

own exposure at younger ages when they were functionally intact. Notwithstanding our efforts 

to apply induced exposure methods, without this information it will remain extremely 

problematic to apportion safety gains to interventions that preserve or restore function, or that 

compensate for functional loss, versus a simple restriction in exposure—self-imposed or 

otherwise. 

Similarly, significant gaps in knowledge exist with respect to the role of functional 

deficits in older driver crashes. The most extensive and rigorous study to date linking functional 

status to safety outcomes (Staplin, Lococo, Gish, & Decina, 2003b) has focused attention on a 

core set of capacities that, when in decline, place older drivers at significantly higher risk of 

causing a crash. Subsequent research to refine and expand the evidence base for predicting crash 

risk through functional assessment is now underway (Staplin et al., n.a.). But an understanding 

of how specific deficits mediate crash risk that is sufficient to establish benchmarks for 

countermeasure development will not result solely from case-control investigations; it requires at 

least some knowledge of the driving contexts in which performance errors reflecting those 

deficits are manifested. Again, a lack of exposure information is a major barrier. 

Consequently, there is a need to collect functional status data for a large group of (older) 

drivers whose exposure can be characterized in terms of road, traffic, and environmental 

characteristics, and for whom reliable crash data can be obtained over a multi-year interval. 

Any State that introduces even limited functional screening at license renewal would be an ideal 

venue for such research. Failing this, appropriate incentives coupled with a credible guarantee of 

confidentiality must be offered to recruit study participants. The administrative as well as the 

technical hurdles involved in a project of this magnitude would be substantial. However, this 

integration of function, exposure, and safety data would not only describe a true taxonomy of 

older driver problems, it would permit evaluations of countermeasure effectiveness that are free 

of the most serious confounds in work performed to date. 

54
	
REFERENCES 

Andersen, G. J., & Enriquez, A. (2006). “Aging and the Detection of Observer and Moving 

Object Collisions.” Psychology and Aging, 21(1), pp. 74-85. 

Ball, K., Berch, D., Helmers, K., Jobe, J., Leveck, M., Marsiske, M.,... Willis, S. (2002). 

“Effects of Cognitive Training Interventions with Older Adults.” Journal of the 

American Medical Association, 288(18), 2271-2281. 

Decina, L.E. & Staplin, L. (1993). “Retrospective Evaluation of Alternative Vision Screening 

Criteria for Older and Younger Drivers.” Accident Analysis and Prevention, 25(3), 267-

275. 

Hing, J., Stamatiadis, N., & Aultman-Hall, L. (2003). "Evaluating the Impact of Passengers on 

the Safety of Older Drivers." Journal of Safety Research, 34(4), pp. 343-351. 

Johnson, C. A. & Leibowitz, H. W. (1974). “Practice, Refractive Error, and Feedback as Factors 

Influencing Peripheral Motion Thresholds.” Perception and Psychophysics, 15(2), 276-

280. 

Lococo, K.H. & Staplin, L. (2006). Final Report of Polypharmacy and Older Drivers: 

Identifying Strategies to Collect Drug Usage and Driver Functioning Among Older 

Drivers. (Report No. DOT HS 810 681). Washington, DC: National Highway Traffic 

Safety Administration. Available at 

http://www.nhtsa.gov/people/injury/olddrive/polypharmacy/images/Polypharmacy.pdf 

Lococo, K. H., & Tyree, R. (2008). Medication-Related Impaired Driving. Curriculum CoSponsored by Walgreens and NHTSA, accredited by the Accreditation Council for 

Pharmacy Education, ACPE Number 254-99-07-036-H05-P. Available at 

https://webapp.walgreens.com/cePharmacy/viewpdf?fileName=transportation_pharm.pdf 

Michon, J. A. (1985). A critical view of driver behaviour models: What do we know, what 

should we do?, In: Evans, L. & Schwing, R.C., (Eds.), Human Behaviour and Traffic 

Safety. New York: Plenum Press. 

Peli, E., Luo, G., Bowers, A., & Rensing, N. (2007). “Applications of Augmented Vision HeadMounted Systems in Vision Rehabilitation.” Journal of the Society for Information 

Display, 15(12), 1037-1045. Accessible at 

www.ncbi.nlm.nih.gov/pmc/articles/PMC2171331/. 

55
	
Driver

Reinfurt, D. W., Stewart, J. R., Stutts, J. C., & Rodgman, E. A. (2000, November). Investigations 

of Crashes and Casualties Associated With Older Drivers. Report prepared for General 

Motors Corporation and the U.S. Department of Transportation. Chapel Hill, NC: 

University of North Carolina Highway Safety Research Center. Available at 

http://www.hsrc.unc.edu/research_library/PDFs/investigations2000.pdf 

Ross, L.A., Clay, O.J., Edwards, J.D., Ball, K.K., Wadley, V.G., Vance, D.E., Cissell, G.M., 

Roenker, D.L., & Joyce, J.J. (2009). “Do Older s At-Risk for Crashes Modify 

Their Driving Over Time?” Journal of Gerontology Series B: Psychological Sciences and 

Social Sciences, 64, 163-170. 

Staplin, L, Gish, K, & Wagner, E. (2003). "MaryPODS revisited: Updated crash analysis and 

implications for screening program implementation," Journal of Safety Research, 34(4), 

389-397. 

Staplin, L., Lococo, K.H., Gish, K.W., & Decina, L.E. (2003a). Model Driver Screening and 

Evaluation Program. Vol. 1: Project Summary and Model Program Recommendations. 

DOT HS 809 582. Washington , DC : National Highway Traffic Safety Administration. 

Staplin, L., Lococo, K.H., Gish, K.W., and Decina, L.E. (2003b). Model Driver Screening and 

Evaluation Program. Vol. 1I: Maryland Pilot Older Driver Study. DOT HS 809 583. 

Washington , DC : National Highway Traffic Safety Administration. Available at 

www.nhtsa.gov/people/injury/olddrive/modeldriver/vol2scr.pdf 

Staplin, L., Lococo, K. H., Gish, K. W., Martell, C. A., Srinivasan, R., Levitt, D., & Joyce, J.( n.a.) 

Older Drivers: The Relationship Between Assessment Tool Scores and Safety Outcomes. 

Unpublished manuscript, NHTSA Contract DTNH22-05-D-05043, Task Order 10. Washington, 

DC: National Highway Traffic Safety Administration. 

Staplin, L., Lococo, K., McKnight, A. J., McKnight, A. S., & Odenheimer, G. (1998). 

Intersection Negotiation Problems of Older Drivers, Volume II: Background Synthesis on 

Age and Intersection Driving Difficulties. (Reort No. DOT HS 808 850). Washington, 

DC: National Highway Traffic Safety Administration. 

Staplin, L., Lococo, K., Sim, J., & Gish, K. (1998). Simulator Based Assessment of Driver-Side 

Mirrors for Passenger Cars. (Report No. DOT HS 808 807). Washington, DC: National 

Highway Traffic Safety Administration. 

Stutts, J., Martell, C., & Staplin, L. (2009). Identifying Behaviors and Situations Associated 

With Increased Crash risk for Older Drivers. (Report No. DOT HS 811 093). 

Washington, DC: National Highway Traffic Safety Administration. Available at 

http://www.nhtsa.gov/DOT/NHTSA/Traffic%20Injury%20Control/Articles/Associated%20Files/811093.p 

df 

Wang, C. C., Kosinski, C. J., Schwartzberg, J. G., & Shanklin, A. V. (2003). Physician’s Guide 

to Assessing and Counseling Older Drivers. (Report No. DOT HS 809 647). 

Washington, D.C. Available at 

http://www.nhtsa.gov/people/injury/olddrive/OlderDriversBook/ 

56
	
57
 

Appendix A: 

Expert Panel Commentary for Countermeasures 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Appendix A: Expert Panel Commentary for Countermeasures.
	

Countermeasure A: Refractive Correction (Including Wavefront Technology) 

Description 

Refractive examination by optometrist or ophthalmologist and prescription for corrective lenses. 

A panel member (vision specialist) recommended inclusion of Wavefront technology as part of 

refractive correction. Wavefront technology diagnoses higher-order vision errors represented by th 

way the eye refracts or focuses light; such aberrations defocus images even with 20/40 acuity. 

Wavefront guided lenses can reduce certain higher-order aberrations, which potentially can improve 

low light image quality during activities such as driving at night. 

e 

Countermeasure Evaluation 

No before-after studies on refraction correction (updating prescription for corrective glasses) and 

driving safety uncovered. 

Studies on effectiveness of Wavefront technology are currently limited to that conducted by lens 

manufacturer (so caution must be exercised in interpreting the results; see Haddrill, 2007). Another 

caution noted by the panelist regarding the lens company research is that improvements in vision 

with the wavefront lenses were compared to patients' vision as they appeared for the study. But it is 

well known that many patients, especially those over age 60, haven’t had regular eye check-ups or 

new prescriptions. 

Haddrill (2007): Ophthonix founder A. Dreher reports that Ophthonix iZon wavefront guided lenses 

provide higher definition vision in the daytime and significantly improve night driving responses 

when compared with conventional lenses. Night vision improved a driver's ability to identify 

pedestrians by an average of 330 ms (30 ft sooner at 55 mi/h) when compared to conventional 

lenses. www.allaboutvision.com/lenses/wavefront-lenses.htm; 

http://ophthonix.izonlens.com/globals/faqs.asp; www.allaboutvision.com/whatsnew/lenses1.htm. 

Expert Commentary 

Panelist with expertise in the area stated that in the ophthalmology literature there is quite a bit of 

research on age and satisfaction for refractive errors corrective surgery. There is actually quite 

ample literature on people’s feelings about their improved performance in everyday tasks there, 

discussing the clarity with which they can see things. It would seem reasonable that one would 

have asked the question about improved driving performance as a result of refractive error 

correction, but the panelist was not aware of anything done. 

Even without research on effectiveness, panelists agreed that refractive correction should be 

advocated just on the prevalence of the problem and the inexpensiveness of the solution, 

particularly as there appears to be a decline in the number of older people who get annual eye 

exams. Annual eye exams, refractive correction, and sooner diagnosis of treatable conditions (e.g., 

cataracts) are inexpensive solutions for reaching a substantial number of people for remediation. 

Vision specialist feedback to drivers regarding the driver licensing laws in their State in relation to 

their own level of impairment is important (and presently rare in practice); increasing awareness of 

impairments may lead to appropriate self-restriction. One of the early findings of the Salisbury Eye 

Study was that among the proportion of older individuals who had worse than 20/40 vision, more 

than half of them could be corrected just with glasses. 

Functional Deficits Targeted  Acuity: 11/11 panelists; (MLE = 4.0) 

by this Countermeasure  Contrast Sensitivity: 11/11 panelists; (MLE = 3.89) 

Mean likelihood of MLE ratings for both functional deficits indicate panelists’ confidence that countermeasure is likely 

effectiveness (MLE) ratings to be effective as an intervention for these deficits, in promoting safe driving practices (MLE 

1=extremely unlikely to 5= ratings in the top third). 

extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

A-1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure B: Cataract Surgery 

Description 

Cataracts cause acuity and contrast sensitivity deficits, and increased dis 

McGwin, Sloane, Wells, Stalvey, & Gauthereaux, 2002). They are treat 

the crystalline lens followed by intraocular lens (IOL) insertion. 

ability glare (Owsley, 

able by surgical removal of 

Countermeasure Evaluation 

McGwin, Scilley, Brown, and Owsley (2003) found improvements in acuity with cataract surgery, 

and that improvement in visual acuity had a significant, independent association with the change in 

activities of daily vision scale (that includes daytime and nighttime driving). 

Wood and Carberry (2006) found that improvement in acuity that accompanied cataract surgery 

was related to improvement in overall driving score. 

Monestam and Wachtmeister (1997): Self reported problems with distance judgment declined from 

37% to 6% of sample following cataract surgery. 

McGwin et al. (2003): contrast sensitivity improved significantly in the sample that underwent 

surgery, and day and night driving scores on Activities of Daily Vision Scale significantly 

improved post-operatively in surgery group. 

McGwin et al. (2003): disability glare improved significantly post surgery in group of patients with 

cataract. First surgery eye improvement in acuity significantly related to change in overall activities 

of daily vision scale and night driving and glare disability subscales. Change in disability glare in 

second surgery eye significantly assoc. w/change in ADVS score as well as change scores in night 

driving, near vision, and disability glare subscales. 

Owsley et al. (2002): Patients with a cataract who underwent surgery and IOL implantation had half 

the crash rate of drivers with cataract who did not undergo surgery (4.74 crashes per million miles 

of travel vs. 8.95). 

Wood and Caraberry (2006): Bilateral cataract surgery resulted in significant improvements in onroad performance, related to improvements in CS. 

Expert Commentary 

Panelists agree this is a relatively inexpensive treatment and improvements result in crash 

reduction. Cataracts are often the only medical condition affecting driving performance. Even if 

crash reduction benefit is small, cataract surgery may provide a large public health benefit because 

of the large number of people affected by cataracts. 

Functional Deficits Targeted  Acuity: 11/11 panelists; (MLE = 4.60) 

by this Countermeasure  Contrast Sensitivity: 11/11 panelists; (MLE = 4.56) 

 Dark Adaptation and Glare Recovery: 11/11 Panelists; (MLE = 4.14) 

Mean likelihood of 

effectiveness (MLE) ratings MLE ratings for all three functional deficits indicate panelists’ confidence that counte rmeasure is 

1=extremely unlikely to likely to be effective as an intervention for these deficits, in promoting safe driving pr actices (MLE 

5= extremely likely ratings in the top third). 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

A-2 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure C: Avoidance of Challenging Driving Situations (Includes License Restriction, Driver 

Rehabilitation Specialist Initiated, and Self-Restriction) 

Description 

Avoidance of (or restricted exposure to) situations that are difficult or challenging for older drivers, 

such as night, high-traffic roads, rush-hour traffic, high-speed interstates/ expressways, driving 

alone, making left-hand turns across oncoming traffic, and rain. May also include restrictions 

imposed by a licensing agency such as driving only within a prescribed distance from home. 

Countermeasure Evaluation 

Gallo, Rebok, and Lesikar (1999). Self-reported vision impairment was related to avoidance of 

challenging driving situations, but not to self-reported citations or crashes in prior 2 years. Authors 

conclude that vision impaired drivers who self restrict are less likely to crash. Vision impairment 

categories: no trouble seeing; a little trouble, a lot of trouble (i.e., may not be specific to acuity). 

Ball, Owsley, Stalvey, Roenker, Sloane, and Graves (1998): No relationship between avoidance 

score and crashes in subsequent 3 year period. 

De Raedt and Ponjaert-Kristoffersen (2000): poor performers on a road test but were free of (selfreported) at-fault crashes (prior 12 mo) used significantly more strategic compensation tactics 

(avoidance of challenging situations) than poor-performing drivers with a history of at-fault crashes. 

Hennessy (1995): poorer visual field ability (modified Synemed perimeter) was significantly 

associated with greater avoidance of driving at night, rain, dusk, dawn, and making left turns, but 

the predictive value of visual fields performance on crash rate (prior 3 yrs) was mediated only for 

avoidance of left turns; But avoidance did not reduce risk, it increased it (inadequate 

compensation). 

Hennessy (1995): older drivers with poor contrast sensitivity (CS) and who (sometimes or often) 

avoided heavy traffic had a reduced crash risk compared to those with poor CS who did not avoid 

heavy traffic. Avoidance brought risk equal to that of drivers with good CS. Avoidance of the other 

situations did not moderate the relationship between CS and crash risk. 

Hennessy (1995): poorer speed of processing (SOP) ability was significantly associated with greater 

avoidance of driving at night, rain, dusk, dawn, alone, left turns, and heavy traffic, but the 

predictive value of the SOP subtask on crash rate (prior 3 yrs) was mediated only for avoidance of 

left turns; But avoidance did not reduce risk, it increased it (inadequate compensation). 

Hennessy (1995): poorer divided attention ability was significantly associated with greater 

avoidance of driving at night, rain, dusk, dawn, alone, left turns, and heavy traffic, but the 

predictive value of the divided attention subtask of UFOV on crash rate (prior 3 yrs) was not 

mediated by any of the forms of self restriction. 

Owsley et al. (1998) found that older drivers with UFOV reduction of 40% or more and who 

reported driving fewer than 7 days per week had a 45% decreased crash risk compared to older 

drivers with a 40% or more reduction in UFOV who reported driving 7 days/week. 

A-3 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure C: Avoidance of Challenging Driving Situations (Includes License Restriction, Driver 

Rehabilitation Specialist Initiated, and Self-Restriction) 

Expert Commentary 

Panelists indicate this may or may not be effective; "we don't know if this works." People try to 

self-regulate when there are alternative transportation options, but there are times when they feel 

they must drive even if they'd rather not (e.g., winter when it gets dark earlier, or no other driver to 

take them). Making people aware of deficits is the first step in getting people to self restrict, if they 

will self restrict. Studies show that there are many unaware vision-impaired drivers. 

Ophthalmologists and optometrists need to be included as targets of outreach, similarly to the AMA 

guide, and other outreach efforts that NHTSA has done for specialized populations because, eyecare 

specialists are a group that does not know their red flags to tell patients that "these are the laws in 

our state and this is what you need to be concerned about." 

For depth and motion perception deficits, panelists indicated that drivers could choose the route that 

has a protected turn. 

The effectiveness really depends on which avoidance behavior is being used and how well it fits 

with the functional decline for which the driver is trying to compensate. If a person is having 

difficulty with dark adaptation and glare recovery, choosing to avoid driving at night and in 

inclement weather would be very effective. However, if he or she chooses to limit driving to 

familiar areas, that would be less effective in addressing that specific functional decline. So, 

particularly for this category (avoiding challenging situations), one panelist specifically noted that 

rating effectiveness it was not at all clear cut. 

One panelist indicated that effectiveness ratings would be higher with self-regulation than with 

DRS initiated or licensing agency imposed restrictions, because driver compliance with externally 

imposed restrictions is unknown. Another noted that a driver must have adequate judgment, 

memory and self awareness to appropriately employ a restriction and believe it is needed. 

Functional Deficits Targeted  Acuity: 11/11 panelists; (MLE = 2.91) 

by this Countermeasure  Contrast Sensitivity: 11/11 panelists; (MLE = 3.18) 

 Visual Fields: 11/11 panelists; (MLE = 2.91) 

Mean likelihood of  Depth and Motion Perception: 11/11 panelists; (MLE = 3.09) 

effectiveness (MLE) ratings  Dark Adaptation and Glare Recovery: 11/11 panelists; (MLE = 3.45) 

1=extremely unlikely to  Speed of Processing: 11/11 panelists; (MLE = 2.82) 

5= extremely likely  Selective Attention: 11/11 panelists; (MLE = 2.70) 

 Divided Attention: 11/11 panelists; (MLE = 2.70) Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 MLE ratings for all eight functional deficits indicate a need for more information/research (MLE Bottom third: 1.0 – 2.33 ratings in the middle third). 

A-4 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure D: Conformal Vision Enhancement System 

Description 

An in-vehicle vision enhancement system that overlays an image (on the windshield, in the case of 

a head-up display) that is directly superimposed on the object it is providing information about. For 

example, conformal vision enhancement of moving and parked vehicles may consist of a horizontal 

blue bar superimposed on the bumpers of other vehicles. As the vehicles approach, the blue bar 

would increase in size (corresponding to the increasing size of the bumper). Conformal 

enhancement of a traffic light at an intersection may be accomplished by placing a blue bar behind 

the traffic light, such that it surrounds the light with a sort of halo. 

Countermeasure Evaluation 

Caird, Horey, and Edwards (2001). Simulator study with 24 younger and 24 older drivers. 

Conformal enhancement of a traffic light resulted in fewer drivers running the light. Drivers 

indicated conformal vision enhancement system (VES) would be helpful when environmental 

conditions restrict visibility, but not under heavy traffic, cluttered environments, or in daytime. 

Less than 25% indicated they would use VES regularly if available. 

Oxley and Mitchell (1995) reported that in a sample of older 31 ultraviolet vision enhancement 

systems (UVES) and 15 infrared vision enhancement systems IVES users, 100% found it easy to 

use, and 60-73% indicated it would encourage them to drive outside of their usual driving 

situations. 

Gish, Staplin, and Perel (1999) found that 3 of 4 older drivers did not use VES to detect targets, but 

instead used it to detect curves in the road (controlled field study). 

Expert Commentary 

Panelists stated that older drivers in focus group studies have indicated that they don't like anything 

in their cars that takes their focus away from the road (either on the windshield or on a heads-down 

display in the vehicle). They would choose not to drive in challenging situations rather than to use 

a device that may take their attention from the road, or that may be difficult to operate. Another 

panelist indicated that following training in equipment use, older drivers are ok with such 

countermeasures; emphasizing that training is a critical component for new technologies to assist 

older drivers. 

Panelists indicated that this countermeasure is logical for a contrast sensitivity deficit, and may be 

relevant for selective attention deficits pending the results of research on its effectiveness. 

Functional Deficits Targeted  Contrast Sensitivity: 11/11 panelists; (MLE = 3.14) 

by this Countermeasure  Selective Attention: 10/11 panelists; (MLE = 2.83) 

Mean likelihood of MLE ratings for both functional deficits indicate a need for more information/research (MLE 

effectiveness (MLE) ratings ratings in the middle third). 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

A-5 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure E. Central Vision Enhancement Systems (Bioptic Telescopic Lenses; 

Implantable Telescopes) 

Description 

A bioptic telescopic lens (BTL) is a lens system with a telescope attached to a pair of glasses, 

mounted above the normal line of sight. This allows a trained user the opportunity to detect objects 

or movement within the driving scene using the wide field of view available through the regular 

spectacle lens (the “carrier” lens) and to resolve fine details such as road sign messages and traffic 

light status by glancing briefly and intermittently into and out of the miniature telescopic unit (by a 

downward tilt of the head). 

Countermeasure Evaluation 

Janke and Kazarian (1983): Crash rate in users is 1.5 times higher than population rate, but less than 

the crash rate of drivers licensed with other medical conditions. 

Clark (1996): Crash rates for BTL users 1.9 times higher than comparison group, but citation rates 

0.7 of that for comparison group. 

Szlyk et al. (2000): Training in the use of BTL lenses (both lab and on-road) significantly increased 

performance in recognition, peripheral identification, and scanning compared to performance of 

non-trained BTL users. 

Expert Commentary 

Panelists supported the countermeasure if accompanied by training and assessment of driving safety 

after training. Recommend licensing with restrictions after low-vision driving program/rehab. Use 

lens only for spotting (5-10% of time). Training curriculum and design of lenses needs to be 

standardized. Training curriculum needs to be developed by Occupational Therapists. 

Countermeasure appropriate if no cognitive deficit. 

Functional Deficits Targeted 

by this Countermeasure  Acuity: 11/11 panelists; (MLE = 3.33) 

 Contrast Sensitivity: 11/11 panelists (MLE = 2.78) 

Mean likelihood of  Visual Fields: 11/11 panelists; (MLE = 3.00) 

effectiveness (MLE) ratings 

1=extremely unlikely to MLE ratings for all three functional deficits indicate a need for more information/research (MLE 

5= extremely likely ratings in the middle third). 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

A-6 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure F: Visual Field Expansion Systems (Prism, Bioptic Amorphic 

Lenses, Video Feeds) 

Description 

Amorphic lenses are spectacle-mounted cylindrical reversed telescopes that increase the peripheral 

visual field by minifying the horizontal meridian. 

Other field expansion systems include video feeds and prisms ground into the lens (although 

optometrists do not often prescribe them; it is not part of most optometry curricula), and according 

to one panelist, there are only one or two clinicians applying prism lenses to low vision driving (Eli 

Peli, O.D., a low-vision clinician for 20 years who heads a large research team at the Schepens Eye 

Institute, Harvard Medical School, and Evelyn Koenig). 

Szlyk et al. (1998) used a bioptic form of an amorphic lens system, with the amorphic lens mounted 

inferiorly on both the left and right carrier lenses, and provided a 12-week training curriculum in the 

use of the amorphic system for navigation, mobility, and driving an automobile. Patients’ distance 

prescriptions were incorporated into the carrier lens as well as into the amorphic lens. The study 

included 15 patients ages 27 to 67. Following training with the lenses (lab and on-road), patients 

showed improvements in all visual skill categories, including peripheral detection and selecting 

appropriate gaps. Specific effects of the lenses and training on driving skills per se (i.e., as opposed 

to the visual skills noted above), or on a global driving score, were not reported. However, 86 

percent of the subjects in this study reported that they were “satisfied to extremely satisfied” with 

their lenses and improvement in visual function, although they expressed concerns with their weight 

and cosmetic appearance, and high cost if they had to be replaced. Authors note further research is 

necessary to determine safety while driving. 

Countermeasure Evaluation 

Bowers, Keeney, and Peli (2008) evaluated peripheral prism glasses for their ability to improve a 

patient's walking mobility, which includes obstacle avoidance. Forty-three patients were fitted with 

prism glasses in 15 community-based clinics around the country. The clinicians interviewed them at 

six weeks and after 12 months. Success was measured by how many patients continued wearing the 

prism glasses and by their ranking of the prisms' effectiveness in assisting with obstacle avoidance 

while walking. Thirty-two participants (74 percent) continued wearing the glasses at week six. At 

12 months, 20 (47 percent) were still wearing the spectacles eight hours a day and rating them as 

"very helpful" for obstacle avoidance. These 12-month-plus patients reported significant benefits 

for a variety of obstacle avoidance scenarios (e.g. walking in crowded areas, unfamiliar places, 

shopping malls). A new, higher power, version of the permanent prism glasses recently developed 

by Chadwick Optical should further expand the visual field and be even more beneficial for 

patients' mobility, according to Peli. The prototype used in the study expanded the peripheral upper 

and lower visual fields by 20 degrees without obstructing central vision. The new glasses expand 

the field by 30 degrees. 

Expert Commentary 

Panelist stated that 100 degree binocular field is a good minimum standard; if < 100 degrees and 

adamant about driving, a driver should be offered these systems to see if he/she can adapt to it 

(should be the standard of care). Target audience would be a driver with 50 degree binocular fields 

in a State with no visual field requirement, and prisms (ref. Eli Peli) could be used to expand the 

field to 100 degrees to make driving safer. Video feed may be better than amorphic lenses, because 

the peripheral extent required for driving is incorporated in the lens. 

Visual field expansion systems show promise in small-scale studies, however, larger studies need to 

be conducted and the OT community and rehab community needs to develop curricula. 

Prisms and other technologies for drivers with visual field loss would not be appropriate 

countermeasures if the driver also has cognitive deficits. 

A-7 
 

 

 

 

 

 

Countermeasure F: Visual Field Expansion Systems (Prism, Bioptic Amorphic 

Lenses, Video Feeds) 

Functional Deficits Targeted 

by this Countermeasure 

Mean likelihood of 

effectiveness (MLE) ratings 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

 Visual Fields: 11/11 panelists; (MLE = 3.40) 

MLE rating indicates a need for more information/research (MLE ratings in the middle third). 

A-8 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure G: Training in Compensatory Head/Eye Movements, Scanning Strategies 

Description 

Compensatory viewing strategies for drivers with peripheral visual field defects (inability to notice 

objects in the periphery) consist of scanning to enlarge the field of view. Compensatory viewing 

strategies for drivers with central visual field defects (inability to notice objects in the fixation area) 

consists of eccentric fixation as well as scanning to assure that no information is concealed by the 

area of decreased vision. 

Countermeasure Evaluation 

Coeckelbergh et al. (2001): Training in compensatory viewing strategies, particularly on-road 

training, improved viewing behavior for people with central or peripheral visual field constriction, 

and increased the number of subjects who passed a road test who previously failed. Subjects had 

visual field defects due to ocular pathology; those with severe cognitive impairments were excluded 

from participation. 

Laderman, Szlyk, Kelsch, and Seiple (2000): Conducted a 4-week training program on a task in a 

rehab center setting to teach peripheral detection, scanning, and tracking. Clients sat close to a 

screen and detected slide images in the periphery using amorphic lenses, then turned their heads 

toward the object to identify it more clearly through the carrier. Following the rehab center 

training, an 8-week training program was conducted in-vehicle on a closed course with driving 

instructor to practice the skills. Before-after training results indicated 39% improvement in tasks 

involving peripheral detection, and 27% improvement in scanning tasks. Authors note further 

research is needed to define standards and evaluation methods for training curricula. 

Dynavision apparatus has been used in office rehabilitation settings to train compensatory scanning 

strategies for visual inattention and visual field deficit in people with intact attentional mechanisms. 

Klavora et al. (1995) found that Dynavision training with 10 older (age 46-73) post-CVA 

individuals resulted in significantly improved behind-the-wheel driving performance when 

compared with expected outcomes. All failed their first BTW assessment pre-Dynavision training. 

Training involved three 40-minute Dynavision Training sessions per week for 6 weeks. On the 

second BTW assessment, 6 of the 10 subjects earned a “safe to resume driving and/or receive onroad driving lessons.” 

Expert Commentary 

Panelists agreed that this is an appropriate countermeasure for visual field deficits, but candidates 

must be cognitively intact. This type of training has been used for telescopic and amorphic lens 

drivers ("search and destroy" method referred to by panelist, described by Laderman et al, 2000) 

and has been effective in improving peripheral visual detection. It was noted that Mary Warren has 

a compensatory training program for drivers with visual field defects, but none of the panelists 

thinks she has published anything. In a follow-up with Mary Warren, she indicated she does not 

have a specific protocol for behind-the-wheel training that emphasizes head turning, but during predriver training, she set a Dynavision criterion of 1 light per second and a score of over 200 on the 4 

minute test (based on the Klavora research), and concentrated heavily on divided attention tasks on 

the apparatus. She also discussed a lot of cognitive strategies with the client in terms of predicting 

where they were likely to experience difficulty because of hemianopsia: turns and merges towards 

the deficit side, evasive maneuvers towards the side of the deficit (how to avoid them), parking lots 

and unpredictable traffic flow. She looked at where they drove, and evaluated those areas for 

potential threats and looked for alternative routes. She also considered vehicle modifications, such 

as mirrors. 

One panelist mentioned a book that may be useful in this training older adults to scan effectively by 

Ken Mills "Disciplined Attention: How to Improve Your Visual Attention When You Drive." The 

book (directed toward young driver training) is not a countermeasure that's ready to go, but it's one 

ready to be researched. 

The vision specialist panelist indicated that training eye movements would be important for 

someone who can’t move their neck. 

A-9 
 

 

 

 

 

 

 

 

Countermeasure G: Training in Compensatory Head/Eye Movements, Scanning Strategies 

Functional Deficits Targeted 

by this Countermeasure 

Mean likelihood of 

effectiveness (MLE) ratings 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

 Visual Fields: 11/11 panelists; (MLE=3.82) 

 Head/Neck/Trunk Range of Motion: 11/11 panelists; (MLE = 4.0) 

MLE ratings for both functional deficits indicate panelists’ confidence that countermeasure is likely 

to be effective as an intervention for these deficits, in promoting safe driving practices (MLE 

ratings in the top third). 

A-10 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure H: Speed of Processing Training 

Description Visual search skills and the ability to identify and locate visual information quickly in a divided 

attention format. 

Countermeasure Evaluation 

 Roenker et al. (2003): Speed of processing (SOP) training using all 3 subtests of UFOV compared 

to Doron simulator training and untrained reference group. Global ratings of on-road driving 

performance improved for both training groups, but only SOP group maintained performance at 18 

mo. For "dangerous maneuvers" component, both training groups showed improvements, but only 

SOP training maintained improvement at 18 mo. Dangerous maneuvers included 6 opportunities 

for unprotected turns across traffic and 9 left-turn entrances to a high-traffic road. 

Expert Commentary 

Panelists agreed this may be a viable countermeasure for cognitive rehabilitation, but there is a need 

to establish the link between training on the task and transfer to driving. 

A panelist indicated that data were recently presented at a Gerontological Society of America 

meeting describing speed of processing training on outcomes such as driving frequency, driving 

exposure, driving difficulty, and crashes. The training was part of an ACTIVE trial described by 

Ball, Berch, Helmers, Jobe, Leveck, et al., 2002) that found that SOP training improved SOP 

performance, but that did not transfer to everyday speed at which participants interacted with realworld stimuli (e.g., looking up a telephone number, finding food items on a crowded shelf, etc.). 

New findings presented at GSA showed an impact for speed of processing training on driving 

outcomes, at 6 years after entry into the study. The training was associated with increased 

frequency of driving and increased exposure, prolonged duration of driving in the people that 

received this kind of training (they ceased driving later than people who did not receive this 

training), they perceived that they had less driving difficulty and, for the first time, a reduction in 

crash rate risk was demonstrated prospectively six years after entry into the study. 

Functional Deficits Targeted  Speed of Processing: 11/11 panelists (MLE = 3.64) 

by this Countermeasure  Selective Attention: 10/11 panelists; (MLE = 3.40) 

 Divided Attention: 10/11 panelists; (MLE = 3.40) 

Mean likelihood of 

effectiveness (MLE) ratings MLE rating for all three deficits indicates a need for more information/research (MLE ratings in the 

1=extremely unlikely to middle third). 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

A-11 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure I: Physical Aerobic Activity/Training 

Description 

Evidence is mounting that physical aerobic activity can increase cognitive function, and provide a 

protective effect against dementia. An example of a physical aerobic activity intervention in the 

research is walking for 45-minute periods 3 times per week (Colcombe et al., 2006). In another 

study, exercise was defined as leisure time physical activity lasting at least 20 to 30 minutes at least 

twice a week and intense enough to cause breathlessness and sweating (Rovio et al., 2005). 

No studies on improvement in driving. 

Countermeasure Evaluation 

In a study by Colcombe et al. (2006), subjects who participated in aerobic exercise showed 

increased brain volumes in regions associated with age-related decline in both structure and 

cognition. In their study, 59 healthy but sedentary community-dwelling volunteers ages 60 to 79 

participated in a 6-month randomized clinical trial. Half of the older adults were assigned to an 

aerobic training group and the other half participated in a toning and stretching control group (nonaerobic stretching exercises 3 times per week). Twenty younger adults served as controls on the 

measure of effectiveness (magnetic resonance imaging) and did not participate in the exercise 

intervention. Significant increases in brain volume, in both gray and white matter regions were 

found in the older adults who participated in the aerobic fitness training, but not in the adults who 

participated in the stretching and toning exercises (nonaerobic) or in the younger controls. During 

their magnetic resonance imaging protocol, participants performed a focused attention task which 

required them to focus on a single central object while ignoring irrelevant distractor objects that 

flanked the target item. Older adults who participated in the aerobic walking protocol were better 

able to ignore the misleading flanking items, but the control adults were not (Kramer, Erickson, and 

Colcombe, 2006). 

Rovio et al. (2005) studied 1,449 older people found that those who exercised during their middlelife (age 30, 40, and 50) were 60 percent less likely to develop Alzheimer’s disease in old age (65 to 

79) than sedentary adults, and 50 percent less likely to develop other forms of dementia and 

memory loss. The benefits were apparent even after adjusting for medical and lifestyle factors such 

as heart/blood vessel disease, locomotor disorders, smoking, alcohol consumption, age, gender, 

education. The benefits were especially pronounced among those who carried the APO-E4 gene— 

an inherited trait that increases a person’s risk of developing Alzheimer’s disease in old age. 

Colcombe and Kramer (2003) found the largest positive effects of fitness training and cognitive 

functioning in older (non-demented) adults was on executive control processes. Programs 

combining aerobic training with strength and flexibility training had the largest effects. Conflicting 

evidence was found by Marmeleira, Godinho, and Fernandes (2008); an exercise program 

incorporating walking with cognitive and perceptual tasks resulted in no improvement on tests of 

executive function (Stroop or Trails B) from baseline to 12-weeks post intervention. 

Marmeleira, Godinho, and Fernandes (2008) found that a 12-week exercise program with 3, 60-min 

sessions per week improved visual attention in speed of processing and divided attention (using the 

UFOV protocol) at 12 weeks follow-up in adults 60 to 81. The intervention incorporated perceptual 

and cognitive tasks (problem solving and responding to challenging situations) with aerobic 

activity. Examples are: walking while listening for auditory cues to perform fast and specific 

psychomotor responses). At 12 weeks, speed of processing and divided attention were significantly 

improved compared to baseline for the exercise group; at baseline, there was no difference between 

groups. Driving performance was not studied, and there was no exercise-only group to determine 

the contribution of physical activity alone on speed of processing or divided attention. 

A-12 
 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure I: Physical Aerobic Activity/Training 

Expert Commentary 

Panelists indicated this countermeasure merits further research for remediation of working memory 

deficits, stating a large body of research showing aerobic exercise results in alertness--hippocampul 

regeneration. 

Panelists indicated this may be an appropriate countermeasure for deficits in executive function, but 

requires further research. A panelist mentioned that the literature in the area of exercise and 

cognitive function is mixed, with some studies showing improvement and others showing no effect. 

One problem with the research may be that the exercise interventions are too brief to result in an 

improvement. 

Functional Deficits Targeted 

by this Countermeasure 

 Speed of Processing: 11/11 panelists; (MLE = 2.91) 

 Divided Attention: 11/11 panelists; (MLE = 2.73) 

 Working Memory: 10/11 panelists; (MLE = 2.50) 

Mean likelihood of 

effectiveness (MLE) ratings 

1=extremely unlikely to 

 Executive Function: 10/11 panelists; (MLE = 2.50) 

 Head/Neck/Trunk Range of Motion: 11/11 panelists; (MLE = 3.45) 

 Arm Strength/Range of Motion/Speed of Movement: 11/11 panelists; (MLE = 3.73) 

5= extremely likely  Leg Strength/Range of Motion/Speed of Movement: 11/11 panelists; (MLE = 3.73) 

Top third: 3.68 – 5.0 MLE ratings for cognitive deficits and one of the three physical deficits (head/neck/trunk) indicate a 

Middle third: 2.34 – 3.67 need for more information/research (MLE ratings in the middle third). MLE ratings for arm and leg 

Bottom third: 1.0 – 2.33 strength/range of motion/speed of motion deficits indicate panelists’ confidence that 

countermeasure is likely to be effective as an intervention for these deficits, in promoting safe 

driving practices (MLE ratings in the top third). 

A-13 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure J: Strength and Flexibility Exercises 

Description 

The intervention described in the research performed by Marottoli et al. (2007) was a weekly inhome visit by a physical therapist for 12 weeks, who guided participants through a graduated 

exercise program targeting the following physical domains and abilities potentially relevant to 

driving: 

 Axial/extremity conditioning (cervical, trunk, and axial rotation; cervical flexion and 

extension; shoulder flexion and abduction; hip flexion and abduction; knee flexion and 

extension; ankle dorisflexion and plantarflexion). 

 Upper extremity coordination/dexterity and hand strength. 

 Gait and foot abnormalties. 

Each of the coordination domains consisted of three progressive levels of exercises. The therapist 

gradually increased the number of repetitions for each exercise, once the participant demonstrated 

the ability to perform the exercises safely and correctly. Exercise programs were designed to take 

15 minutes and participants were asked to perform the exercises once daily for 7 days each week. 

Intervention participants reported completing the exercises a median of 5.4 days per week. The 

control group received monthly in-home education modules about home safety, fall prevention, and 

vehicle care. The intervention group also received these modules to ensure that the materials did 

not influence study outcomes. 

The exercise program employed by Ostrow, Shaffron, and McPherson (1992) was an 8-week range 

of motion exercise program that could be practiced at home, consisting of chin flexion/extension, 

neck rotations, head side bending, chin tucks, rotating the shoulders backward, and trunk rotations. 

Drivers in the experimental (exercise) group met weekly with a clinician who introduced new 

elements of the exercise program, reviewed previously learned skills, and monitored the subjects’ 

compliance with the program. They also kept a daily log to record their compliance, and the 

frequency and extent of their driving. Subjects in the control group did not receive the exercise 

intervention. Instead, they kept a log of the frequency and extent of their driving, and as an 

incentive to participate in the study, received in-car instruction after the project was completed. 

The physical therapy intervention implemented by McCoy, Tarawneh, Bishu, Ashman, and Foster 

(1993) consisted of a set of seven self-administered, home-based exercises designed to improve 

posture, trunk rotation, neck flexibility, and shoulder flexibility. The exercises were done 4 times 

per week for 8 weeks, following a 1-hour training session. 

Countermeasure Evaluation 

Marottoli et al. (2007): On-road driving performance was measured at baseline and postintervention for treatment and control group. Significant improvement for treatment group 

compared to control group translated to 8 to 16% lower crash occurrence over 2 year period. 

Treatment group also made 37% fewer critical errors (inattention, turning or changing lanes w/o 

looking, and disobeying signs or signals) than control group at follow up. 

Ostrow et al. (1992): Significant improvements in trunk rotation and shoulder flexibility across 

experimental subjects' 3 testing sessions (baseline, 8 and 11 weeks). Subjects in experimental group 

showed improvements in field-based assessment of driving skill: looked more frequently to the 

sides and rear of their vehicle than control drivers who did not participate in program. 

McCoy et al. (1993): Post intervention on-road drive test performance improved by 6.8 percentage 

points (significant) for the exercise group, and when physical therapy was combined with driver 

education, improvement increased by 8.7 percent. 

Expert Commentary 

Panelists agreed that this is an appropriate countermeasure for head/neck/trunk range of motion; 

arm strength/range of motion/speed of movement; and leg strength/range of motion/speed of 

movement. 

A-14 
 

 

 

 

 

 

 

Countermeasure J: Strength and Flexibility Exercises 

Functional Deficits Targeted 

by this Countermeasure 

Mean likelihood of 

effectiveness (MLE) ratings 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

 Head/Neck/Trunk Range of Motion: 11/11 panelists; (MLE = 4.20) 

 Arm Strength/Range of Motion/Speed of Movement: 11/11 panelists; (MLE = 4.0) 

 Leg Strength/Range of Motion/Speed of Movement: 11/11 panelists; (MLE = 3.90) 

MLE ratings for all three deficits indicate panelists’ confidence that countermeasure is likely to be 

effective as an intervention, in promoting safe driving practices (MLE ratings in the top third). 

A-15 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure K: Visual Perceptual Therapy 

Description 

The visual perceptual therapy intervention employed by McCoy et al. (1993) consisted of a set of 

self-administered home-based exercises designed to improve the following five components of 

visual perception: spatial relationships, visual discrimination, figure-ground, visual closure, and 

visual memory. The therapy consisted of 568 exercises, organized into five sections in a workbook, 

one for each component of visual perception, arranged in order of degree of difficulty, from the 

simplest to the most difficult. The subjects were instructed to spend about 4 minutes on each 

section during a 20-minute session, doing as many exercises as possible working at their own pace. 

The exercises were to be done for 20-minutes, four times a week, for 8 weeks. If they completed 

the exercises in one of the sections before the end of 8 weeks, they were instructed to start the 

section over from the beginning. Before the start of the exercise program, subjects were given a 1-

hour training session, during which time they practiced the exercises for each of the five 

components. 

Countermeasure Evaluation 

McCoy et al. (1993) evaluated the effectiveness of a perceptual therapy intervention for 9 older 

drivers (ages 65 to 88) in improving their on-road driving performance, compared to a control 

group of 9 older subjects who did not receive the intervention. Baseline driving performance and 

follow-performance at 2 months post-intervention were assessed using the Driver Performance 

Measurement (DPM) technique developed at Michigan State University. The mean difference in 

DPM was 7.7 percentage points higher at follow-up than at baseline, indicating an improvement in 

performance for the perceptual therapy intervention group. The mean difference for the control 

group was -0.4 (no improvement in performance). A pair-wise comparison showed these 

differences to be statistically significant, indicating that visual perceptual therapy was effective in 

improving driving performance for the intervention group, relative to the control group. 

Expert Commentary Panelists indicated this countermeasure merits further research for remediation of deficits in spatial 

abilities. 

Functional Deficits Targeted  Spatial Abilities: 11/11 panelists: (MLE = 3.33) 

by this Countermeasure 

MLE rating indicates a need for more information/research (MLE rating in the middle third). 

Mean likelihood of 

effectiveness (MLE) ratings 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

A-16 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure L: Driver Safety Education: Theory/Classroom Only 

Description 

This intervention includes programs such as the AARP Driver Safety Program and the AAA Safe 

Driving for Mature Operators program that are taught in a classroom setting, with no onroad/behind-the-wheel component. Most AARP Driver Safety Program (DSP) courses are taught 

in two, 4-hour sessions, although an on-line course is available for those wishing to take the course 

over the Internet. The course teaches participants the effects of aging on driving behaviors and 

how to adjust driving behaviors to accommodate these changes. Safe Driving for Mature 

Operators program delivers tips and techniques to help experienced drivers compensate for 

changing vision, reflexes and response time; understand how prescription medications may affect 

driving; and drive defensively in a variety of situations. It can be presented over 4 hours, 6 hours 

or 8 hours. 

Countermeasure Evaluation 

 Owsley, McGwin, Phillips, McNeal, and Stalvey (2004) found no difference in crash rate during 

2 year follow up period for drivers with 40% or more reduction in UFOV or a visual acuity 

deficit (20/30 to 20/60) in an educational intervention group ("Knowledge Enhances Your 

Safety") who reduced their overall exposure and avoided driving at night, in the rain, in rush 

hour, and made right turns around the block to avoid left turns across traffic. Avoidance and 

exposure were self-reported, so social desirability may have been operative; or restriction was 

not frequent enough to be protective. Also, crash type was not restricted to at-fault in the study. 

 Eby, Molnar, Shope, Vivoda, and Fordyce (2003): Driving Decisions Workbook (a self 

assessment tool) was effective in increasing older drivers' awareness of changes in driving 

abilities related to aging, and effects of changes on driving. Participants stated they would seek 

2nd tier assessment and change driving habits. 

 Skufca (2008): AARP DSP participants indicated course encouraged them to change certain 

driving behaviors (20% indicated avoiding left turns as a new behavior). 

 Kutner (2006): No difference in crash rate (self reported) in prior 12-month period for AARP 

Driver Safety program participants and comparison group of non-AARP DSP participants. 

 Bedard et al. (2004): Canadian Safety Council adaptation of AARP DSP evaluated for treatment 

and comparison group using an on-road evaluation at baseline and post-treatment. On-road 

evaluation scores improved significantly for treatment and control group from baseline to postintervention; no significant difference between treatment and comparison group on mean change 

score from the first to second evaluation. 

 Janke (1994): Completion of Mature Driver Improvement Program was associated with more 

total fatal injury crashes and fewer citations compared with group who did not attend course. 

 McCoy et al. (1993): Completion of AAA Safe Driving for Mature Operators was associated 

with a significant increase in on-road driving performance (baseline and post intervention road 

test using DPM technique) of 3.7 percentage points. Education plus physical therapy increased 

score by 8.7 percentage points; education plus perceptual therapy increased score by 13.9 

percentage points. 

 Nasvadi and Vavrik (2007): Evaluation of British Columbia Safety Council adaptation of 

AARP DSP comparing police-reported at-fault crash and violation rate for participants vs. nonparticipants in prior 2-year period, to determine whether self-selection bias exists for those who 

attend remedial safety courses. Significantly more participants than controls had crashed, but 

there was no difference in violation rate. A follow-up comparison of crash rate for subsequent 2-

year period for attendees and controls with matched pre-course crash rate showed that more 

attendees had crashes than non-attendees, but the difference was not significant. However, when 

stratifying by age group and gender, males age 75+ who attended the course were 3.8 times 

more likely to be involved in a crash than controls who did not attend class. No difference in 

crash rate for men 55 to 74 or women 55 to 74 and those 75+. 

A-17 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure L: Driver Safety Education: Theory/Classroom Only 

Expert Commentary 

Panelists stated driver safety education/theory may be useful for the visual deficits including 

acuity, contrast sensitivity, visual field, dark adaptation/glare recovery, and depth/ motion 

perception deficits, because it raises awareness of the deficit so drivers can self restrict. Also 

important is to provide education to physicians and eyecare specialists so they can educate their 

patients. Education by OT may be a reimbursable intervention. Education alone may never be 

enough, however; it may need to be coupled with skills training. Panelist (a KEYS study author) 

noted that he has always questioned whether those self reported changes in driving habits were 

real; people may have been invested due to time spent in intervention and reported more avoidance 

than they really engaged in. Also, candidates for education intervention should not have advanced 

cognitive deficits (e.g., dementia). 

Similarly, for all the cognitive deficits, panelists stated that classroom driver education may be 

useful to raise awareness of deficit so drivers self restrict, and again, panelists agreed that 

education alone may never be enough; it may need to be coupled with skills training. OTs use 

commentary driving and building skills through progressively more challenging situations. In the 

case of spatial abilities, the OT panelists noted that if there is a serious deficit, driving should be 

ruled out. Spatial abilities deficits manifest themselves in lane control difficulty. OTs will start 

with easy situations and progress to more difficult situations if there is improvement. 

For knowledge deficits, there was a general consensus that it makes sense to provide education, 

even if it isn't adequate; people will be people, and it may work for some and not others. 

Education (theory) alone may never be enough; may need to be coupled with skills training. 

For all three physical deficits, panelists stated that classroom driver education may be useful as it 

raises awareness of deficit so drivers can self restrict. Education by OT may be a reimbursable 

intervention. Education alone may never be enough; may need to be coupled with skills training. 

OTs use commentary driving and building skills through progressively more challenging 

situations. 

Functional Deficits Targeted 

by this Countermeasure 

 Acuity: 11/11 panelists; (MLE = 1.64) 

 Contrast Sensitivity: 11/11 panelists; (MLE = 1.82) 

 Visual Fields: 11/11 panelists; (MLE = 1.82) 

 Depth and Motion Perception: 10/11 panelists; (MLE = 1.50) 

 Dark Adaptation/Glare Recovery: 10/11 panelists; (MLE = 1.80) 

 Speed of Processing: 10/11 panelists; (MLE = 2.00) 

 Selective Attention: 10/11 panelists; (MLE = 1.80) 

Mean likelihood of 

effectiveness (MLE) ratings 

1=extremely unlikely to 

 Divided Attention: 10/11 panelists; (MLE = 1.80) 

 Working Memory: 10/11 panelists; (MLE = 1.70) 

 Executive Function: 11/11 panelists; (MLE = 2.18) 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

 Spatial Abilities: 10/11 panelists; (MLE = 1.80) 

 Knowledge: 11/11 panelists; (MLE = 3.82) 

 Head/Neck/Trunk ROM: 10/11 panelists; (MLE = 2.00) 

 Arm Strength/ROM/Speed: 10/11 panelists; (MLE = 1.70) 

 Leg Strength/ROM Speed:10/11 panelists; (MLE = 1.70) 

With the exception of knowledge deficits, MLE scores indicate that driver safety education 

(theory/classroom alone) is not likely to be an effective intervention for promoting safe driving 

practices (scores in the bottom third). For knowledge deficits, the MLE ratings indicate panel 

members’ confidence that driver safety education (theory/classroom alone) can be an effective 

intervention (scores in the top third). 

A-18 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure M: Driver Safety Education: Theory Plus Behind the Wheel 

Description 

This countermeasure involves providing driver safety education, such as that provided in the AAA 

and AARP classroom programs, but supplementing what is taught in the classroom with actual onroad instruction, to reinforce concepts learned in class. 

The intervention in the Bédard et al. (2008) study consisted of the Canadian Safety Council’s 

adaptation of the AARP 55-Alive Mature Driving Program, presented in two sessions that lasted 

for 4 hours. In addition, participants were given the opportunity to reinforce the concepts learned 

in the classroom by engaging in two 30- to 40-minute sessions with a certified instructor, driving 

either in their own vehicles or in a dual-brake vehicle. The instructor provided participants with 

constructive feedback on their driving habits. 

Intervention drivers in the Marottoli (2007) study participated in two, 4-hour classroom sessions 

based on the AAA Driver Improvement Program (Safe Driving for Mature Operators) and two 1-

hour on-road driving sessions focused on common problem driving areas for older drivers. The 

classroom sessions followed the outline and videos of the AAA program, but were supplemented 

with the following additional topics: a review of all road signs, neck rotation for head checks, 

checking blind spots, the use of side mirrors, steering-wheel hand placement, steps for changing 

lanes and merging in traffic, right-on-red rules, limiting distractions and focusing on driving, 

search strategies for intersections, scanning to the rear, backing-up strategies, the consistent use of 

turn signals, and strategies for left turns across traffic or how to avoid such turns. The on-road 

instruction was based on common errors made by older drivers, which included failure to scan side 

to side, to the rear, and make head checks; failure to use a seat belt, keep the car centered in the 

lane, maintain a safe following distance, and use directional signals; and errors in backing up, 

making lane changes, and in speed regulation. The topics therefore that were included in the onroad instruction were vehicle orientation (adjusting seat position and mirrors, seat belt, head 

restraints, hand position, and distance from wheel); parking lot maneuvers (parking, backing up, 

using mirrors, looking over shoulder); maneuvers for low volume streets (K-turns, intersection 

strategies such as stopping position, search strategies, signaling, yielding to pedestrians, and left 

turns across traffic); maneuvers for moderate- and high-volume roads (looking 30 seconds ahead, 

watching for pedestrians and vehicles changing directions or slowing down, strategies for stop 

lights, turning strategies, lane change strategies, speed and space management, mirrors and head 

checks, and signaling); and maneuvers on highways (entering, exiting, merging, changing lanes, 

mirror and head checks, blind spots, speed regulation, space management). The first session also 

addressed any errors the driver made during the baseline assessment. 

Countermeasure Evaluation 

The measures of effectiveness in the Bédard et al. (2008) study were (1) scores on a 15-item 

multiple choice safe driving knowledge questionnaire given before the classroom session and 

again after completion of the classroom sessions, but before the on-road training sessions (for the 

treatment group); and (2) performance on a standardized on-road driving evaluation given before 

the intervention and again 4- to 8-weeks post-intervention (both the treatment and control group). 

Five driving actions were evaluated: (1) starting/stopping/slowing; (2) signal violations/right of 

way/inattention; (3) moving in the roadway; (4) speed/passing; and (5) turning. Bédard et al. 

(2008) found a significant improvement in knowledge of safe driving practices, with an increase 

from 61 percent of the questions answered correctly at baseline to 81 percent answered correctly at 

follow-up. Driving performance improved significantly for the intervention group (fewer 

violations were made) compared to the control group, but only for the category of moving in the 

roadway. Examples of violations in this category included straddling the traffic lane, failing to 

check traffic when changing lanes, wandering, and failing to drive in the proper lane. 

A-19 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure M: Driver Safety Education: Theory Plus Behind the Wheel 

Countermeasure Evaluation 

(Cont’d) 

Marottoli (2007) conducted a randomized, controlled trial with blinded endpoint assessment to 

determine whether an educational intervention consisting of classroom and on-road training 

focused on commonly encountered problem areas for older drivers, could enhance driving 

performance among 126 active drivers age 70 or older. Control drivers received one-on-one 

sessions about vehicle maintenance and safety devices, home safety, and environmental safety. 

These were conducted in the participants’ homes and included education on falls and tripping 

hazards, lighting, handrails, appropriate footwear, crime prevention, tire pressure, vehicle lights 

and mirrors, pedestrian issues, etc. BTW performance was assessed at baseline and 8 weeks postintervention. The road test covered 10 miles, included a 1.7-mile highway segment, and took 45 

minutes to complete. It included urban and residential areas with low- medium- and high-traffic 

densities, with speed limits ranging from 10 to 35 mi/h on access roads and city streets to 55 mi/h 

on the highway. There were 63 intersections on the route (32 crossing and 31 T-type); 45 were 

signalized, 2 were controlled by flashing lights, and 11 were controlled by stop signs. There were 

15 right and 15 left turns, 12 merges, and several opportunities to make a right on red at a traffic 

signal. Mean baseline road test scores were comparable in the intervention and control groups, for 

those who drove daily or less than daily (60.9 vs. 60.7, respectively, out of 72 points). 

Intervention drivers showed a mean increase in road test score of 8.5 percent compared to a 4.2 

percent increase for control subjects. The improvement in on-road test performance at 8 weeks for 

the intervention group was 2.87 points higher (least-squares mean change) on a 72-point scale than 

that in the control group. This difference was significant, and translates to a 9.5 percent decrease 

in crash risk over a 2-year period. The items showing the most improvement with intervention 

were: scanning to the rear, lane selection, right turns, and judgment. Intervention drivers showed a 

mean increase in knowledge test score of 22.5 percent compared to a 6.2 percent increase for 

control subjects. The improvement in written-test performance at 8 weeks was 3.45 points higher 

(least-squares mean change) on a 28-point scale for the intervention group than for the control 

group, which was also significant. 

Expert Commentary 

Panelists stated driver safety education (theory plus behind the wheel) may be useful for the visual 

deficits including acuity, contrast sensitivity, visual field, dark adaptation/glare recovery, and 

depth/ motion perception deficits, because it raises awareness of the deficit so drivers can self 

restrict. Also important is to provide education to physicians and eyecare specialists so they can 

educate their patients. Education by OT may be a reimbursable intervention. Education alone may 

never be enough, however; it may need to be coupled with skills training. 

Similarly, for all the cognitive deficits, panelists stated that classroom driver education combined 

with a behind the wheel component may be useful to raise awareness of deficit so drivers self 

restrict. It was reinforced that education alone may never be enough; it may need to be coupled 

with skills training. OTs use commentary driving and building skills through progressively more 

challenging situations. In the case of spatial abilities, the OT panelists noted that if there is a 

serious deficit, driving should be ruled out. Spatial abilities deficits manifest themselves in lane 

control difficulty. OTs will start with easy situations and progress to more difficult situations if 

there is improvement. 

For knowledge deficits, there was a general consensus that it makes sense to provide education, 

even if it isn't adequate; it may work for some and not others. Education should be coupled with 

skills training. 

For all three physical deficits, panelists stated that classroom driver education with a behind-thewheel component may be useful as it raises awareness of deficit so drivers can self restrict. 

A-20 
Countermeasure M: Driver Safety Education: Theory Plus Behind the Wheel 

Functional Deficits Targeted 

by this Countermeasure 

Mean likelihood of 
	

effectiveness (MLE) ratings 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

 Acuity: 10/11 panelists; (MLE = 2.10) 

 Contrast Sensitivity: 11/11 panelists; (MLE = 2.56) 

 Visual Fields: 11/11 panelists; (MLE = 2.55) 
	

 Depth and Motion Perception: 11/11 panelists; (MLE = 2.36)
	

 Dark Adaptation/Glare Recovery: 10/11 panelists; (MLE = 2.40)
	

 Speed of Processing: 11/11 panelists; (MLE = 2.73)
	

 Selective Attention: 11/11 panelists; (MLE = 2.45) 

 Divided Attention: 11/11 panelists; (MLE = 2.64) 
	

 Working Memory: 9/11 panelists; (MLE = 2.67) 
	

 Executive Function: 11/11 panelists; (MLE = 3.0) 

 Spatial Abilities: 10/11 panelists; (MLE = 2.50) 

 Knowledge: 11/11 panelists; (MLE = 4.0) 

 Head/Neck/Trunk ROM: 11/11 panelists; (MLE = 2.91) 

 Arm Strength/ROM/Speed: 10/11 panelists; (MLE = 2.70) 

 Leg Strength/ROM Speed:10/11 panelists; (MLE = 2.70) 

With the exception of acuity and knowledge deficits, MLE scores indicate a need for more 

information/research (MLE rating in the middle third) to determine whether driver safety 

education theory/classroom combined with a behind-the-wheel component will be effective as an 

intervention in promoting safe driving practices. 

MLE rating in the bottom third for acuity deficits indicates that this countermeasure is not likely to 

be an effective intervention for promoting safe driving practices. 

MLE rating in the top third for knowledge deficits indicates panel members’ confidence that driver 

safety education theory/classroom with a BTW component can be an effective intervention for 

promoting safe driving practices. 

A-21 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure N: Driver Safety Education: Interactive/Computer-Based Technology 

Description 

This countermeasure was added by panelists as an outgrowth of the discussions on 

classroom/theory driver education and on-road/behind the wheel driver training. 

Interactive/computer-based technology is a new approach to driver education being used with teens, 

and also with seniors that addresses all of the listed deficits. It could include driver simulator 

training, or computer-based training on a desk-top platform with a steering wheel for input. But the 

computer-based, interactive component addresses the attentional and cognitive aspects of driving, 

as well as imparting knowledge/theory. 

Countermeasure Evaluation None uncovered in the literature (with the interactive component), and none offered by the 

panelists. 

Expert Commentary This is an emerging application that needs more research, and could apply to all listed deficits. 

Functional Deficits Targeted 

by this Countermeasure 

Mean likelihood of 

effectiveness (MLE) ratings 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

 Acuity: 10/11; (MLE = 2.20) 

 Contrast Sensitivity: 11/11 panelists; (MLE = 2.64) 

 Visual Fields: 11/11 panelists; (MLE = 2.73) 

 Depth and Motion Perception: 11/11 panelists; (MLE = 2.55) 

 Dark Adaptation/Glare Recovery: 11/11 panelists; (MLE = 2.36) 

 Speed of Processing: 11/11 panelists; (MLE = 3.27) 

 Selective Attention: 11/11 panelists; (MLE = 3.27) 

 Divided Attention: 11/11 panelists; (MLE = 3.45) 

 Working Memory: 10/11 panelists; (MLE = 3.40) 

 Executive Function: 11/11 panelists; (MLE = 2.91) 

 Spatial Abilities: 11/11 panelists; (MLE = 2.91) 

 Knowledge: 11/11 panelists; (MLE = 3.82) 

 Head/Neck/Trunk ROM: 11/11 panelists; (MLE = 2.45) 

 Arm Strength/ROM/Speed: 11/11 panelists; (MLE = 2.55) 

 Leg Strength/ROM Speed:11/11 panelists; (MLE = 2.55) 

With the exception of acuity and knowledge deficits, MLE scores indicate a need for more 

information/research (MLE rating in the middle third) to determine whether interactive/computerbased driver education will be effective as an intervention in promoting safe driving practices. 

MLE rating in the bottom third for acuity deficits indicates that this countermeasure is not likely to 

be an effective intervention for promoting safe driving practices. 

MLE rating in the top third for knowledge deficits indicates panel members’ confidence that 

interactive/computer-based driver safety education can be an effective intervention for promoting 

safe driving practices. 

A-22 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure O: Education about Driving Aids (CarFit, Features, Adaptive Equipment, Diabetic 

Shoes, etc.) 

Description 

CarFit is an in-car safety program that teaches older drivers how to adjust their vehicles to help 

reduce crashes and injuries. It was developed through collaboration among the American Society 

on Aging, AARP, the American Occupational Therapy Association, and AAA. It includes a 12-

point checklist to ensure that senior drivers are sitting properly in their vehicle and that the driver’s 

seat, seat belts, mirrors, steering wheel, head rest, gas/brake pedals, and other controls are properly 

positioned. Each CarFit evaluation takes approximately 15 minutes, and is administered by 

specially trained volunteers and health professionals such as occupational therapists. 

Countermeasure Evaluation 

None published to date. A panelist indicated that there was one initial preliminary study that people 

had retained the knowledge imparted during the session, making some changes following the 

session. The panelist also indicated that there's a proposal in from UCLA to do a bigger study of it 

if they get funded (but they haven't heard yet). The panelist indicated there have been some small 

studies that have not been compiled in any way. Different master's level OT students have done a 

number of small studies at different CarFit events; she stated that we could use more research on 

CarFit. 

Smart, Safe, and Sober Newsletter (2007) indicates that a trial version of the program was 

administered in 2006 with over 300 senior citizens and found that: 37% had at least one ‘red flag” 

issue; 10% did not have the right spacing between their steering wheel and chest; and almost 20% 

did not have the right line of sight over their steering wheel. 

Expert Commentary 

Panelists state that vehicles have safety features but many need to be adjusted, and older drivers 

don't know how to do this. Education about driving aids is a positive theme to staying on the road 

longer. Countermeasure merits further research. 

Another panelist indicated that there's some interesting work that's being done in Australia in terms 

of developing and evaluating educational programs. There is some work by an occupational 

therapist named Liddle, who has developed a program using the public health behavioral change 

theory of stages of change. This has been a successful approach in smoking cessation programs, for 

example, that takes into account the stage at which people are active and respond to their readiness 

to change. 

Several panelists (OTs) indicated that at CarFit events, they have been removing the mirrors from 

their example bag because they don't want to be liable for somebody getting a mirror and not 

having enough training in its use, and then getting in a crash. There's a lot of learning involved in 

using adaptations and mirrors. At CarFit, if a mirror is adjusted for a driver (and the explanation 

provided about elimination of blind spots), the OT sets the mirrors back as they were when the 

driver arrived at the event. That is a requirement, because OTs can’t be liable for making a change; 

the driver must make the change. 

There are other concerns with adaptive equipment. With adaptations, theoretically, a driver would 

go to a driving specialist who would look at their model of car and all the types of adaptations that 

might work and recommend the one that would work for their car and the individual. Then the 

driver would get the device the specialist indicated and would have it installed. The specialist 

would check and make sure that the device is installed the right way and then train the driver in its 

use. OTs voiced concern about adaptive equipment being readily available from the internet or in 

car parts stores, and people buying it without being evaluated for their need or trained in its use. 

Panelists were concerned about who installs the equipment; is the mechanic down the street putting 

the equipment in, and is it being installed correctly? There needs to be a standard of care. Ideally, 

devices would be available to those who need them, but a professional should be involved in 

selecting a device and training the driver to use it. There is no standard of care; more research is 

needed on mirrors, the training required to use them safely, and the professionals qualified to 

deliver the training. 

A-23 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure O: Education about Driving Aids (CarFit, Features, Adaptive Equipment, Diabetic 

Shoes, etc.) 

(Cont’d) 

More research is needed to identify unintended consequences of safety devices, including 

submarining under the seatbelt if a seat cushion is used and effects of aftermarket add-ons to the 

seat belt to make it comfortable across the neck. There is dissention between automakers and OTs 

and even among the OTs themselves with regard to aftermarket devices such as seat cushions and 

seat belt adjustors. 

One panelist raised the issue of pedal confusion among drivers with diabetes and neuropathy, 

related to the characteristics of therapeutic shoes that reduce a driver’s ability to feel the pedals. She 

stated that there are not studies for OTs to turn to for support in guiding their clients. 

Functional Deficits Targeted 

by this Countermeasure 

Mean likelihood of 

effectiveness (MLE) ratings 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

 Visual Fields: 11/11 panelists; (MLE = 2.55) 

 Depth and Motion Perception: 10/11 panelists; (MLE = 1.89) 

 Dark Adaptation/Glare Recovery: 10/11 panelists; (MLE = 2.40) 

 Knowledge: 11/11 panelists; (MLE = 4.0) 

 Head/Neck/Trunk ROM: 11/11 panelists; (MLE = 3.55) 

 Arm Strength/ROM/Speed: 10/11 panelists; (MLE = 3.10) 

 Leg Strength/ROM Speed:10/11 panelists; (MLE = 3.10) 

MLE scores for visual fields, and all three physical abilities indicate a need for more 

information/research (MLE rating in the middle third) to determine whether education about driving 

aids will be effective as an intervention in promoting safe driving practices. 

MLE ratings in the bottom third for depth/motion perception and dark adaptation/glare recovery 

indicate that this countermeasure is not likely to be an effective intervention for promoting safe 

driving practices. 

MLE rating in the top third for knowledge deficits indicates panel members’ confidence that 

education about driving aids can be an effective intervention for promoting safe driving practices. 

A-24 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure P: Collision Warning Systems 

Description Collision warning systems provide an audio warning to the driver in advance of an impending 

emergency event. 

Countermeasure Evaluation 

Caird (2004) notes that few evaluation studies have included a sample of older drivers, and those that 

do, don’t analyze age effects. 

Maltz, Sun, Wu, and Mourant (2004) found that drivers, both younger and older, benefited from the 

use of a headway and detection alerting device. Age had no effect on the amount of time drivers 

spent in the optimal following distance zone (2 to 4 seconds). Older drivers were less likely to 

respond to false alarms when they were distracted by an auditory task (listening to a book on tape) 

than when they were not distracted. However, younger drivers responded more to false alarms when 

they were distracted than when they were not distracted. This age effect occurred only when the 

headway and detection alerting device was highly reliable. Maltz et al. indicate that the explanation 

for older drivers ignoring more false alarms when they were distracted may be due to their greater 

difficulty dividing attention, particularly when the two tasks share the same output modality 

(auditory stimuli, in this case). 

Oxley and Mitchell (1995): collision warning system tested in a simulator was effective in 

preventing older drivers from turning across traffic through gaps that were dangerously short. They 

found that this technology was even more effective for a small sample of younger drivers than for the 

main sample of older drivers. 

Expert Commentary 

Suggested by panelists as countermeasure that merits further research. Need forward as well as sidecollision warning. Would be helpful if it caused the vehicle to brake, in addition to providing a 

warning. 

An OT mentioned that although adaptive cruise control systems might enable elders to drive safer for 

a longer period of time, they also may allow unsafe drivers to drive for a longer period of time. If 

the person has a system in the car that is going to drive the car for them, it may enable them to drive 

past the time they should have stopped. 

Panelists were concerned about drivers relying completely on the technology to detect hazards (esp. 

for backing up). Older drivers who have backed up without doing head/shoulder checks and have 

backed into (and killed) pedestrians. Also older people may be more distracted rather than assisted 

by some of the advanced technologies. And, most rehab centers’ adapted cars are not high-end/high 

tech, so it would be difficult for OTs to train people to use these technologies. 

Panelists noted that training is a key element with advanced technology countermeasures, 

particularly for older drivers. 

One panelist noted that collision warning systems aren’t a panacea for drivers with visual decline; in 

combination with other countermeasures, they may be helpful, but shouldn’t be relied on to prevent 

crashes for drivers who don’t see well. 

Several panelists discussed the fact that some higher-end vehicles (e.g., 7 Series BMW) have a 

display on the dashboard or on the mirrors that shows if you are getting too close to someone or if 

someone is in your blind spot. However, the systems aren’t always reliable; they may miss detecting 

a following vehicle in an adjacent lane, resulting in a driver who does not also do a head check 

changing lanes and colliding with the adjacent-lane vehicle. Another problem is that due to the 

display being visual, drivers may be distracted by looking at the display instead of the actual traffic 

scene. One panelist who has looked at auto insurance claims found that blind spot detection systems 

have resulted in a reduction in severity but not in frequency of crashes (which is not what would be 

expected). 

A-25 
 

 

 

 

 

 

 

 

 

 

Countermeasure P: Collision Warning Systems 

Functional Deficits 

Targeted by this 

Countermeasure 

Mean likelihood of 

effectiveness (MLE) 

ratings 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

 Acuity: 11/11 panelists; (MLE = 3.36) 

 Contrast Sensitivity: 11/11 panelists; (MLE = 3.45) 

 Speed of Processing: 11/11 panelists; (MLE = 3.45) 

 Selective Attention: 11/11 panelists; (MLE = 3.40) 

 Divided Attention: 11/11 panelists; (MLE = 3.30) 

 Head/Neck/Trunk Range of Motion: 11/11 panelists; (MLE = 3.09 

MLE scores for all listed functional deficits abilities indicate a need for more information/research 

(MLE rating in the middle third) to determine whether collision warning systems will be effective as 

an intervention in promoting safe driving practices. 

A-26 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure Q: After-Market Non-Planar Driver-Side Mirror 

Description 

Title 49, Part 571, Standard Number 111 of the Code of Federal Regulations requires the driver side 

mirror to be planar (flat), while the passenger side mirror may be convex or planar. In Europe, nonplanar rearview mirrors are allowed on both the driver’s and passenger’s side of the vehicle. There is 

anecdotal evidence that drivers attach after-market convex mirrors on the driver side mirror to 

eliminate the blind spot, and there are multiple vendors who provide such after-market mirrors. 

Convex mirrors provide a wider field of view, but produce a minified image that may cause 

inaccurate judgments about the speed and distance of following/overtaking vehicles. No research 

was uncovered on the effectiveness or safety benefit of this behavioral adaptation, but research has 

been performed in the U.S. and Europe on the benefits and difficulties experienced by drivers using 

convex and multiradius mirrors on the driver’s side. 

Countermeasure Evaluation 

 No research on "bullseye" convex mirror affixed to standard planar mirror, however Staplin et al. 

(1998) found that approx 13% of older driver sample in laboratory simulator study made unsafe gap 

acceptance judgments to change lanes in front of an adjacent-lane vehicle overtaking at 25 mi/h 

differential while using full-sized non-planar mirrors. Also one-third of sample indicated sole 

reliance on mirror when changing lanes. 

De Vos (2000) reported that older drivers look over their shoulders less frequently than younger 

drivers when changing lanes. Drivers accepted smaller gaps when using non-planar mirrors, due to 

image minification. 

Expert Commentary 

Panelist OTs were concerned that the recommendation could pose a liability, but merits further 

research. Even aiming mirrors for drivers during CarFit is a liability and OTs put the mirrors back to 

their original position (as they were aimed when the drivers arrived at the evaluation). Non-planar 

mirrors would require optical distortion training, and there is currently no standard of care. 

Functional Deficits 

Targeted by this 

Countermeasure 

Mean likelihood of 

effectiveness (MLE) 

ratings 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

 Head/Neck/Trunk Range of Motion: 11/11 panelists; (MLE = 4.11) 

MLE rating in the top third for this deficit indicates panel members’ confidence that this 

countermeasure can be an effective intervention for promoting safe driving practices. 

A-27 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure R: Medical Management (Including Pharmacy Review) 

Description 

This countermeasure arose from discussions among the expert panelists that physicians and other 

healthcare providers need to have the information linking medical conditions and medications to 

crash risk, so they can provide remediation when possible, and educate their patients (leading to selfrestriction when necessary). This began as extension of the discussion of cataract surgery as a 

remediation for contrast sensitivity and acuity deficits. So, in addition to older drivers being the 

targets of brochures describing driving with certain medical conditions, physicians must also be the 

targets of such interventions. 

Allard, Hébert, Rioux, Asselin, and Voyer (2001) found that the consumption of 3 or more drugs per 

day increased the risk of functional decline in elderly people by 60 percent. Decreases in functional 

ability brought on by polypharmacy have been associated with an increased risk of motor vehicle 

crashes (LeRoy, 2004), raising public health and safety concerns. Therefore, pharmacy reviews can 

serve to educate patients about the potential driver impairing effects of medications, leading to better 

decisions about when and if it is safe to drive. Pharmacy reviews can also be beneficial in reducing 

crash risk, because they uncover dangerous drug interactions, redundant prescriptions, unnecessary 

prescriptions, and dosing problems. 

Countermeasure Evaluation 

Sleep apnea has been associated with a 2- to a 7-fold increase in crash risk (Teran-Santos, JimenezGomez, and Cordero-Guevara, 1999). Sleep apnea/sleep deprivation is an active area of research. 

One investigator (Maycock, 1996) has correlated scores on the Epworth sleepiness scale with crash 

risk. Many additional studies have documented increased crash risk or impaired driver performance 

due to fatigue; and it has been shown that treatment for sleep disorders can reduce crash risk to 

baseline levels (George, 2001). 

Nathan, Goodyer, Lovejoy, and Rashid (1999) reported on medication use of 205 patients (mean age 

64.5 years) who volunteered to participate in a pharmacist-led brown-bag review. The number of 

drugs reviewed per patient ranged from 1 to 14, with an average of 6.2. Pharmacists made 

interventions in 87 percent of the reviews. Interventions included: providing information about the 

purpose of at least one medication (65% of the reviews); improving or correcting usage of at least 

one medication (46%); providing knowledge on common or important adverse drug reactions or side 

effects (52% of reviews). Fifty-eight percent of patients admitted to or were suspected of either not 

using at least one of their medications at all or not using them according to prescribed directions. 

Interactions between medications (sometimes between prescribed and over-the-counter medicines) 

were identified in 4 percent of the reviews. 

Fillit, Futterman, Orland, et al., (1999) conducted a prospective study with a follow-up survey to 

examine the effects of a brown bag review by primary care physicians on prescriptions written for 

elderly members of a Medicare managed care organization who were at risk of risk related to 

polypharmacy. Ninety-six percent of the 1,087 members who participated in the medication review 

reported that they had a discussion concerning prescription medications and 72% indicated that 

nonprescription medications were also discussed. As a result of the medication review, 20% 

indicated that the doctor stopped or discontinued a medication, 29% indicated that the doctor 

changed the dosage of medication, 11% indicated that the doctor discovered medications purchased 

without a prescription that he or she did not know the patient was taking, and 17% indicated that the 

doctor discovered medications prescribed by another physician that he or she did not know the 

patient was taking. 

Expert Commentary 

Panelists stated that medical management leads to early detection of impairments and remediation. 

They indicated that it is important for researchers/sponsors of research to provide education to 

physicians, pharmacists, and eyecare specialists linking medical conditions to functional impairments 

and driving risk so they can educate their patients. They pointed to cataract surgery as a remediation 

for acuity and contrast sensitivity deficits; patients rely on their healthcare providers to diagnose, 

treat, and counsel, so the physicians need to be educated. Panelists provided examples of arthritis 

and sleep apnea. Impairments in psychomotor functioning may result from musculoskeletal disease 

leading to weakening, frailty, and/or restricted range of motion. Medical management of arthritis is 

important. Medical management of sleep apnea is another countermeasure to promote safe driving, 

but the panelist didn’t know if there was a model for a sound medical management of sleep apnea. 

A-28 
 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure R: Medical Management (Including Pharmacy Review) 

The panelists also proposed the idea of a model stroke rehab program, as stroke was another medical 

condition associated with high crash risk. Panelists indicated that medical management was an 

appropriate countermeasure for all 15 listed functional deficits. 

Functional Deficits 

Targeted by this 

Countermeasure 

 Acuity: 11/11 panelists; (MLE = 3.50) 

 Contrast Sensitivity: 10/11 panelists; (MLE = 3.0) 

 Visual Fields: 10/11 panelists; (MLE = 3.0) 

 Depth and Motion Perception: 10/11 panelists; (MLE = 2.67) 

 Dark Adaptation/Glare Recovery: 10/11 panelists; (MLE = 3.0) 

 Speed of Processing: 11/11 panelists; (MLE = 3.18) 

 Selective Attention: 11/11 panelists; (MLE = 3.30) 

Mean likelihood of 

effectiveness (MLE) 

ratings 

 Divided Attention: 11/11 panelists; (MLE = 3.09) 

 Working Memory: 11/11 panelists; (MLE = 3.20) 

 Executive Function: 11/11 panelists; (MLE = 3.27) 

1=extremely unlikely to 

5= extremely likely 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

 Spatial Abilities: 11/11 panelists; (MLE = 2.40) 

 Knowledge: 11/11 panelists; (MLE = 3.30) 

 Head/Neck/Trunk ROM: 10/11 panelists; (MLE = 3.20) 

 Arm Strength/ROM/Speed: 10/11 panelists; (MLE = 3.50) 

 Leg Strength/ROM Speed:10/11 panelists; (MLE = 3.50) 

MLE scores for all listed functional deficits abilities indicate a need for more information/research 

(MLE rating in the middle third) to determine whether medical management can be effective as an 

intervention in promoting safe driving practices. 

A-29 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure S: Cognitive Rehabilitation (Including Memory Training ) for the Normally Aging 

Population 

Description 

Cognitive rehabilitation was added to the list of countermeasures by expert panelists as an outgrowth 

of the discussion about divided attention. This could include reasoning training and memory training 

such as that included in the ACTIVE trial (Ball et al., 2002). The memory training was focused on 

verbal episodic memory; participants were taught mnemonic strategies for remembering word lists 

and sequences of items. The exercises involved laboratory memory tasks (recalling a list of nouns, 

recalling a paragraph) and memory tasks related to cognitive activities of daily life (recalling a 

shopping list, recalling the details of a prescription label). The reasoning training focused on the 

ability to solve problems that follow a serial pattern; the exercises involved abstract reasoning tasks 

(e.g., letter series) and reasoning problems related to activities of daily living. 

Countermeasure Evaluation 

Ball et al. (2002) found that the reasoning training improved reasoning ability (tasks requiring 

identification of patterns in letter or word series problems) and the memory training improved 

performance on episodic verbal memory tasks, durable to 2 years. Subjects were volunteers ages 65 

to 94; with approximately 700 in each training group. Training effects were of a magnitude equal to 

the amount of decline expected in older people without dementia over 7 to 14 year intervals. No 

training effects were found on everyday functioning tasks (paper and pencil tests and behavioral 

simulations of everyday tasks) at 2 years following enrollment. 

Preliminary findings from the ACTIVE trial evaluating cognitive interventions and crash risk 5 years 

prospectively are pending. 

Laderman, Szlyk, Kelsch, and Seiple (2000) found improvement in visual memory (remembering 

store names subjects had walked past) after practice in the laboratory recalling sequences of 

numbers, letters, and shapes presented briefly on 35-mm slides. This practice was part of a protocol 

for amorphic lens wearers, prior to participating in a driver training protocol on a closed course and 

riding as passengers in traffic. The purpose of the driving protocol was to learn how to incorporate 

the search and scanning techniques learned in the laboratory into the driving task. The finding that 

visual memory showed significant improvement indicated that patients realized the importance of 

exiting the amorphic lenses as quickly as possible and the necessity of remembering what was just 

seen through them. 

Expert Commentary 

Panelists indicated that cognitive rehabilitation is really building subskills for the driving task. An 

OT panelist noted that you cannot just do a lot of the cognitive retraining tasks and assume that it 

will generalize to driving. You need to make that part of the therapy program. Therapists need to 

“connect-the-dots” for their patients when doing cognitive therapy for driving; explain how the skill 

they just developed during the last hour in the clinic could be applied to everyday practical situations 

(in this case, driving). This makes it more likely that they will show functional improvement. 

One cognitive rehabilitation model, recommended by an OT for its application to behavior change 

and driving, is the “Trans-Theoretical” model of change, which focuses on the decision making of 

the individual. It has been the basis for developing effective interventions to promote health 

behavior change such as smoking cessation and low fat diets, and could help drivers make decisions 

about reducing risk when driving with functional deficits. It is described at 

www.uri.edu/research/cprc/TTM/detailedoverview.htm. Another pertinent model is 'Motivational 

Interviewing.' It helps the client achieve the “ah ha” moment, where s/he develops insight into the 

existence and nature of a (driving) problem, and what can be done to deal with it. It is described at 

www.motivationalinterview.org/clinical/interaction.html. 

A-30 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure S: Cognitive Rehabilitation (Including Memory Training ) for the Normally Aging 

Population 

Expert Commentary 

(Cont’d) 

Panelists agreed that cognitive rehabilitation has tremendous promise as a countermeasure but it is in 

its infancy; training protocols and validation testing are not yet complete. Protocols and treatments 

differ based on the clinicians and therapy settings. There is a need for good research to make sure 

that rehab specialists use this appropriately. Current treatment protocols for cognitive rehab vary 

from simple exercises, to counseling, to computer-based drills and video games; and rehabilitation 

specialists from multi-disciplinary fields (psychologists, neuropsychologists, speech pathologists, 

OTs, PTs, etc) are using the method. There aren’t many cognitive rehabilitation specialists who also 

specialize in driving rehabilitation. An OT indicated that cognitive rehab has a history that is tainted 

by excitement over new protocols such as video games, so it is important that good research is 

performed to determine its efficacy, and that it is used appropriately. These tools tend to be marketed 

to the public rather than to the experts who can make informed decisions. Many of the current tools 

are untested. There is a proliferation of memory training programs on the Internet, according to one 

panelist. 

OTs noted that there are protocols and treatments for retraining concentration and attention, and the 

cognitive rehab literature shows efficacy of attentional therapy in the broader rehab area ("Society 

for Cognitive Rehab"). Cognitive rehab doesn't directly address driving, but builds subskills for the 

driving task. The panelist noted that since improved attention has an impact on driving, and the 

broad rehab area shows efficacy in training attention, then it makes sense to consider improving 

attention through rehab to improve driving ability. 

A panelist noted that interventions can be enhanced by cross training/packaging interventions, rather 

than thinking of them as single interventions. As an example, combine skill-based targeted training 

with educational training. 

One panelist noted that reasoning training conducted as part of the ACTIVE trial described by Ball, 

Berch, Helmers, Jobe, Leveck, et al.(2002) showed an effect of decreased driving difficulty in the 6 

years following enrollment in the study. These findings were presented at the 2008 GSA meeting. 

Panelists indicated that cognitive rehab (preventative, restorative, maintenance) and memory training 

are not appropriate for the dementia population, because dementia is progressive; they can’t learn 

and remember the strategies. The dementia population can be abused by being sold restorative 

interventions. 

Functional Deficits 

Targeted by this  Selective Attention: 11/11 panelists; (MLE = 2.89) 

Countermeasure  Divided Attention: 11/11 panelists; (MLE = 2.80) 

 Working Memory: 11/11 panelists (MLE = 2.80) 

Mean likelihood of  Executive Function: 11/11 panelists; (MLE = 2.80) effectiveness (MLE) 

ratings MLE scores for all listed functional deficits abilities indicate a need for more information/research 

1=extremely unlikely to (MLE rating in the middle third) to determine whether cognitive rehabilitation (for the normally 5= extremely likely aging population) can be effective as an intervention in promoting safe driving practices. 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

A-31 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure T: Compensatory Cognitive/Memory Training for Impaired/MCI Population 

Description 

Compensatory strategies/memory training that the panelists deemed appropriate for the mild 

cognitive impairment (MCI) population are at the strategic level of Michon’s hierarchical model of 

driver behavior. Examples include trip planning: planning the route ahead of actually driving it, 

using tools like MapQuest, and possibly practicing the route ahead of time (if the trip involves an 

appointment in an unfamiliar area), and may include avoiding challenging situations such as rush 

hour and complex intersections, depending on the nature of the individual’s impairment. It may 

include strategies such as allowing more time to get to a location, increasing following distance to 

provide more time to react/respond to situations, using a GPS with auditory output for navigation 

assistance, and driving only in familiar areas. 

Countermeasure Evaluation 

No research studies were uncovered to evaluate the effectiveness of the strategic compensatory 

strategies. 

Unverzagt et al. (2007) reported on a subset of the ACTIVE trial population (193 subjects) who had 

mild cognitive impairment (MCI), who underwent the memory and reasoning cognitive interventions 

described by Ball et al. (2002) . MCI was defined as Rey Auditory Verbal Learning Test (AVLT) 

sum recall score 1.5 sd or more below predicted AVLT sum recall. Subjects had intact intellectual 

function (normal range MMSE) and normal ADLs at baseline. The training was conducted in 10 

sessions lasting 60 to 75 minutes over a 5- to 6-week period. Participants were instructed in 

strategies for recalling word lists and short narratives for the memory training. Reasoning training 

focused on improving the ability to solve problems that contained a serial pattern. Memory training 

outcomes were measured by verbal memory tasks; reasoning training outcomes were measured by 

tasks requiring the identification of patterns in letter and word series problems. Memory training 

showed no benefit at post test, nor after 1 year or after 2 years post training for the memory-impaired 

subjects relative to a no-contact control group. However, reasoning training was effective for the 

memory-impaired subjects at post test and at 2-years following training. The memory training was 

focused on verbal episodic memory; participants were taught mnemonic strategies for remembering 

word lists and sequences of items. The reasoning training focused on the ability to solve problems 

that follow a serial pattern; the exercises involved abstract reasoning tasks. 

Preliminary findings from the ACTIVE trial evaluating cognitive interventions and crash risk 5 years 

prospectively are pending. 

In a small sample study of 20 subjects with MCI and 9 controls, Belleville at al. (2006) found that 

adults with MCI benefited from training on some immediate post-test measures of face-name 

associations but not on measures of paragraph recall or immediate word list recall. The training 

consisted of mnemonic training techniques similar to those used in ACTIVE (imagery, organization, 

method of loci) that were imbedded within dual-task attention training. Thus, improvement in 

memory function in those with MCI may require a more multi-factorial approach than that employed 

by the ACTIVE training. It is unknown whether such training would transfer to improvements in safe 

driving ability. 

Expert Commentary 

Panelists were cautious about recommending cognitive interventions for people with early stage 

dementia, and indicated that strategies must be compensatory rather than restorative for this group. 

Because dementia is progressive, cognitive rehab is not recommended; it is not beneficial because 

people can’t learn and remember the strategies. The dementia population can be abused by being 

sold restorative interventions. Someone with early stage dementia may have good situational 

awareness and operational control of a vehicle, but could have a memory deficit that would manifest 

in navigational difficulties. 

A panelist who is a physician indicated that it is difficult to define where MCI (Mild Cognitive 

Impairment) begins and where it ends. It is unknown whether the MCI group can benefit from 

interventions because historically, they have been excluded from studies so as not to confound the 

study results. 

A panelist who is an author on the MCI ACTIVE report indicated that memory training strategies 

A-32 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure T: Compensatory Cognitive/Memory Training for Impaired/MCI Population 

used with MCI and Alzheimer’s patients should be different from those used with someone whose 

cognitive neurofunctioning is intact. 

One panelist noted that not all people with MCI progress to Alzheimer’s Disease, this may be 

appropriate for MCI (however, more research is needed). However, as AD progressively worsens, it 

is difficult to see how this countermeasure would be effective beyond the earliest AD stages, and 

would need to be reviewed for its appropriateness on a regular/frequent basis. 

Functional Deficits 

Targeted by this 

Countermeasure 

Mean likelihood of 

effectiveness (MLE) 

ratings 

1=extremely unlikely to 

5= extremely likely 

 Selective Attention: 11/11 panelists; (MLE = 2.89) 

 Divided Attention: 11/11 panelists; (MLE = 2.80) 

 Working Memory: 11/11 panelists (MLE = 2.90) 

 Executive Function: 11/11 panelists; (MLE = 2.80) 

MLE scores for all listed functional deficits abilities indicate a need for more information/research 

(MLE rating in the middle third) to determine whether compensatory cognitive/memory training for 

MCI population will be effective as an intervention in promoting safe driving practices. 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

Bottom third: 1.0 – 2.33 

A-33 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countermeasure U: Pre-Trip Planning 

Description 

 Pre-trip planning is at Michon’s strategic level in his hierarchical model of driver behavior. It 

involves a conscious decision to plan the intended driving route (including avoiding challenging or 

difficult intersections), and could also include other self-imposed restrictions, such as time of day 

(daytime rather than night), type of weather (dry vs. in the rain or snow) and under optimal health 

conditions (e.g., avoiding driving when fatigued, or when impaired by medication-side effects, or 

impairing symptoms of medical conditions). 

Countermeasure Evaluation Has not been evaluated, as far as panelists know 

Expert Commentary 

Panelists added this countermeasure and agreed that it merits further research for drivers with 

deficits in working memory and executive function, as well as for knowledge deficits. They 

indicated it may help with memory deficits, because it requires practice. 

Panelists indicated that trip planning ties in with management mobility counseling; introducing 

other modes of transportation for those times that a driver shouldn’t drive because of functional 

impairments. 

This may be a strategy to extend driving, because trip planning could prevent near-misses, 

misinterpretation or confusion that could result from being lost. If people can learn an intervention 

like memorizing or previewing a route, it could help them drive safer longer. 

Functional Deficits Targeted 

by this Countermeasure  Working Memory: 11/11 panelists; (MLE = 3.09) 

 Executive Function: 11/11 panelists; (MLE = 3.09) 

Mean likelihood of  Knowledge: 8/11 panelists; (MLE = 3.75) 

effectiveness (MLE) ratings 

1=extremely unlikely to 

5= extremely likely 

MLE scores for deficits in working memory and executive function indicate a need for more 

information/research (MLE rating in the middle third) to determine whether pre-trip planning can 

be effective as an intervention in promoting safe driving practices. MLE rating in the top third for 

Top third: 3.68 – 5.0 

Middle third: 2.34 – 3.67 

knowledge deficits indicates panel members’ confidence that this countermeasure can be an 

effective intervention for promoting safe driving practices. 

Bottom third: 1.0 – 2.33 

A-34 
 

 

 

 

 

______________________________________________________________________ 

______________________________________________________________________ 

______________________________________________________________________ 

______________________________________________________________________ 

______________________________________________________________________ 

____________________________________________________________________ 

 

 

______________________________________________________________________________ 

_____________________________________________________________________________________________________________________

 “Taxonomy of Older Driver Behaviors and Crash Risk” 

Contract Number DTNH22-05-D-05043, Task Order 08 

Task 7 – Unstructured Interviews of Older Drivers 

Driver Name: ____________________________ DL Number: ______________________ 

Date of Birth: _________________ Prior crash? ____ (1) Yes ____ (0) No 

Interview Date: ________________ 

Current Driving 

1. Do you currently drive? 

_____ (1) yes (go to question 4.) 

_____ (0) no (ask questions #2 and #3 and then stop interview). 

2. Why did you stop driving? 

3. When is the last time you drove? (month/day/year) 

4. How many days per week do you normally drive? (circle one) 

1 2 3 4 5 6 7 

5. On a typical day, how many trips do you make? _____________________ 

6. How many total miles do you drive in a normal week? ________ 

7. In a normal week, about what percent of your overall travel (miles driven) occurs at night? 

________ (if >0%, ask Q. 8) 

7a. Is most of your nighttime travel on lit or unlit roads?
	

(1)_______ lit 

(0)_______ unlit 

8. About how many miles per year do you drive? (circle one) 

Less 1,001 2,501 5,001 7,501 10,001 12,501 15,001 17,501 20,001 25,001 30,001 

than to to to to to to to to to to or 

1,000 2,500 5,000 7,500 10,000 12,500 15,000 17,500 20,000 25,000 30,000 more 

1 2 3 4 5 6 7 8 9 10 11 12 

B-1 
 

 

 

 

 

 

 

 

 

 

Driver Name: ______________________________________________ Page 2 of 6 

9. What kind of area do you live in: (circle one) 

1) the city 

2) the suburbs 

3) a rural area 

10. Do you do most or all of your driving close to home? 

(1)_______ yes 

(0)_______ no 

11. During the past year, have you driven to places that take more than 1⁄2 hour to get to or are 

more than 10 miles away? 

(1)_______ yes 

(0)_______ no 

12. During the past year, have you driven to places that take more than 1 hour to get to or are 

more than 50 miles away? 

(1)_______ yes 

(0)_______ no 

13. When driving, have any of the following situations become more difficult or challenging 

over the past 5 or 10 years? 

13a. (Check “yes” or “no” for each item in the table below.) 

13b. For each item to which they respond “yes”, then ask “Are there certain kinds of trips 

or certain destinations you would drive to, in spite of this difficulty?" And if so, 

ask: “How often do you do this?” If they volunteer other info. such as certain 

destinations or situations, record this under “Other comments.” 

13a. Check “Yes” or “No” for each of the 

following potential difficulties. 

13b. Drive anyway, despite 

difficulty? – Check “Yes” or 

“No.” If ‘yes,’ how often? 

13a(1). Harder to see at night 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(2). Harder to read signs or see traffic signals 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(3). Harder to understand the meaning of 

signs and signals 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

B-2 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Driver Name: ______________________________________________ Page 3 of 6 

13a. Check “Yes” or “No” for each of the 

following potential difficulties. 

13b. Drive anyway, despite 

difficulty? – Check “Yes” or 

“No.” If ‘yes,’ how often? 

13a(4). Harder to know when you have the right-ofway to proceed at an intersection (through 

or turn). 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(5). Harder to judge gaps in traffic 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(6). Harder to detect other vehicles or 

pedestrians in the periphery 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(7). Harder to keep up with the flow of 

traffic (on high speed roads) 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(8). Harder to judge what other drivers are 

going to do in traffic (hazard anticipation)

 (1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(9). Harder to change lanes or merge 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(10). Harder to pay attention to everything at 

the same time 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(11). Harder to turn head/neck to look for 

traffic to the sides or rear of the car 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

13a(12). Harder to stay in your lane 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(13). Harder to move your foot between gas and 

brake pedals 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

B-3 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Driver Name: ______________________________________________ Page 4 of 6 

13a. Check “Yes” or “No” for each of the 

following potential difficulties. 

13b. Drive anyway, despite 

difficulty? – Check “Yes” or 

“No.” If ‘yes,’ how often? 

13a(14). Harder to know which pedal is the brake 

pedal and which is the gas 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(15). Harder to steer when making left or right 

turns

 (1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(16). Get tired easily 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(17). Get lost or disoriented easily

 (1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(18). Harder to deal with bad weather (rain, 

snow, fog) 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

13a(19). Other (Fill in, if yes) 

(1) ___ yes (0) ___ no 

(1) ___ yes (0) ___ no 

How often? 

Other Comments: 

14. Have you changed your driving habits over the past 5 or 10 years in any of the following 

ways ? (Check “yes” or “no” for each item) 

14a. Drive fewer miles (1) ___ yes (0) ___ no 

14b(1). Make fewer trips per week? (1) ___ yes (0) ___ no 

14b(2). Avoid or limit night driving? (1) ___ yes (0) ___ no 

14b(3). Avoid or limit driving in unfamiliar areas? (1) ___ yes (0) ___ no 

14b(4). Avoid or limit driving far from home? (1) ___ yes (0) ___ no 

14b(5). Avoid or limit high speed roads? (1) ___ yes (0) ___ no 

14b(6). Avoid or limit freeways/expressways (1) ___ yes (0) ___ no 

B-4 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Driver Name: ______________________________________________ Page 5 of 6 

14b(7). Avoid or limit high traffic roads? (1) ___ yes (0) ___ no 

14b(8). Avoid or limit driving at rush hour? (1) ___ yes (0) ___ no 

14b(9). Avoid or limit changing lanes? (1) ___ yes (0) ___ no 

14b(10). Avoid or limit driving in bad weather 

(rain, snow, fog)? 

(1) ___ yes (0) ___ no 

14b(11). Avoid or limit turning left at intersections, 

unless there is a green arrow to tell you 

that it is safe to go. 

(1) ___ yes (0) ___ no 

14b(12). Limit where/when you drive in other ways? 

__________________________________ 

(1) ___ yes (0) ___ no 

14c. Drive only with a passenger (1) ___ yes (0) ___ no 

14d. Drive slower than the speed limit (1) ___ yes (0) ___ no 

14e. Use adaptive equipment 

(Fill in. e.g., seat cushions, spinner knobs, 

special mirrors, etc.) ____________________ 

(1) ___ yes (0) ___ no 

14f. Use in-vehicle technologies 

(Fill in. e.g., navigation systems, collision 

avoidance technology). _________________ 

(1) ___ yes (0) ___ no 

14g. Leave more room between your car and the car 

ahead (increase following distance) 

(1) ___ yes (0) ___ no 

14h. You plan the route you’re going to take before 

you leave 

(1) ___ yes (0) ___ no 

14i. Other changes in driving habits 

Fill in: ______________________________ 

(1) ___ yes (0) ___ no 

B-5 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Driver Name: ______________________________________________ Page 6 of 6 

15. In the past 5 years, have any of the following occurred: 

15a. You took older driver education courses 

(fill in type) ____________________ 

(1) ___ yes (0) ___ no 

15b. You had cataract surgery (1) ___ yes (0) ___ no 

15c. Your physician counseled you about safe 

driving 

(1) ___ yes (0) ___ no 

15d. You had your driving ability evaluated by 

an occupational therapist or other driver 

evaluator 

(1) ___ yes (0) ___ no 

15e. Your pharmacist counseled you about the 

effects of your medications on driving 

(1) ___ yes (0) ___ no 

16. Do you regularly do any of the following? 

16a. Strength and flexibility exercises (1) ___ yes (0) ___ no 

16b. Aerobic exercises (1) ___ yes (0) ___ no 

16c. Computer exercise program to keep 

mentally sharp 

(1) ___ yes (0) ___ no 

16d. Get regular eye exams/ updated corrective 

lens prescription 

(1) ___ yes (0) ___ no 

17. Are there social events or other occasions where you have a drink of alcohol, and then 

drive?" (1) ___ yes (0) ___ no 

If “yes,” ask: “How often does this happen?” __________________________________ 

B-6 

DOT HS 811 468A

February 2012