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I. PROGRAM GOALS AND PROCEDURES
The singular objective of this work is to promote the
safe mobility of older persons. Mobility is central to quality of life. There
is a well-established link between restricted mobility among older persons and
the onset or acceleration of diverse physical and mental health problems. Costs
to society to provide care for seniors who lose their mobility also rise dramatically.
To preserve independent functioning, to retain the dignity and self-esteem that
result from providing for one's own mobility needs as long as it is possible
to do so without unacceptable risk to oneself or to others-- these are the overriding
goals in a U.S.DOT policy initiative, Safe Mobility for Life, that
provides the framework for application of material in this Notebook.
In our society personal mobility, to an overwhelming degree,
is tied to the ability to drive a car. People who drive automobiles can exercise
the freedom to choose where to work, live, and recreate; their social needs
and maintenance requirements can be self-fulfilled; and they can travel virtually
at any time they desire. These attributes of a contemporary lifestyle, and the
means most often used to attain them, are perceived to be among the basic rights
of every adult.
As people age, however, their ability to safely drive a
car may be compromised by a variety of functional impairments. The functional
abilities at issue include vision, attention, perceptual skills, memory, decision
making, reaction time and different aspects of physical fitness and performance.
With increasing age, the occurrence of disease and pathology are more common and,
even in their absence, declines in functional abilities are to be expected as
a normal consequence of aging. There is an accumulating body of evidence to show
that impairments in one or more areas of functional capability significantly increase
a driver's risk of a crash. And because of their higher vulnerability, older persons
involved in an automobile crash are more likely than their younger counterparts
to be seriously injured or killed. The leading cause of accidental death for older
persons is a car crash.
The changing demographics in our society underscore the
consequences of age-related driving impairments as an emerging public health issue.
The population over age 65 will grow by 60 percent in the next 20 years; during
the decade from 2020 to 2030, the proportion of Americans over the age of
65 will increase to more than 1 in 5. The development of screening procedures
for license renewal and regulatory control that are fair, accurate, and which
can be administered cost-effectively is therefore a clear priority. This was the
premise behind a NHTSA research project, "Model Driver Screening and Evaluation
Program;" the information presented in this Notebook was generated through
performance of that project.
Improved practices for assessing drivers' abilities and
driving skills are overdue. Through the decade of the 1990s and beyond, as people
age 85 and older have emerged as the fastest growing segment of our driving population,
the driving task itself has become characterized by ever-growing traffic volumes
and congestion, plus novel highway features and vehicle technologies that demand
greater attention by the driver. Most seniors are as capable of driving
safely as their younger counterparts, and when they become aware that they have
a problem they typically act responsibly by limiting or modifying their driving
habits. Still, some diminished functional capabilities are more difficult to detect
or may be denied, and the margin for 'human error' in many driving situations
has become vanishingly small. Thus the payback for more accurate prediction of
who is at greatest risk of causing a crash is substantial--both for the individual
and for society.
The Model Program's first priority has accordingly been
to identify the most useful tools for evaluation of drivers' functional capabilities.
For many reasons, it is anticipated that functional screening will not be confined
to Departments of Motor Vehicles, and that the DMV may not even be the most important
setting for early screening to occur. Providing tools for self-evaluation by older
drivers, and for screenings in various health care and social service settings
in the community, is strongly emphasized in the Notebook. A need for
multiple tiers of evaluation activities is also emphasized, such that results
of early screening for gross impairments lead to more comprehensive, diagnostic
testing by appropriate professionals whenever warranted.
While identifying and assessing the ability of older people
to remain safely mobile receives the largest share of attention in the Notebook,
other goals are also defined. When it has been determined that an individual has
one or more functional limitations that are likely to produce driving impairments,
the Model Program supports remediation of the problem if possible, and the provision
of mobility counseling to inform the individual about local alternative transportation
options and how to access available services. More broadly, the Model Program
also includes a public information and education component to help meet the assessment,
remediation, and counseling goals by informing senior citizens and care givers
about the link between functional decline and driving safety, and about resources
that exist to help preserve or extend their mobility as they grow older.
The procedures described and reported on in the Notebook
will give readers an understanding of the current state-of-the-knowledge in a
given topic area, and will identify the principal sources of information and evidence
for the included conclusions and recommendations. At the same time, the conclusions
stated in this Notebook are preliminary and current knowledge may derive
from research-in-progress. Where readers note significant omissions in material
or material that is out of date with current practices it is requested that they
bring such items to the attention of the authors. This reference document is,
and should remain, a work-in-progress as jurisdictions throughout North America
prioritize local issues relating to seniors' mobility needs, and implement the
best solutions that are feasible at the time.
I.A. IDENTIFY OLDER PEOPLE WHO ARE
AT HIGH RISK OF CRASHES
I.A.1. Epidemiology
(a) Dementia
(b) Cataracts
(c) Diabetes and Associated Conditions
(d) Glaucoma
(e) Foot Abnormalities
(f) Falls
(g) Cardiac (and Cardiopulmonary) Conditions
(h) Feet or Legs Cold on Exposure to Cold
(I) Bursitis
(j) Renal Disease
(k) Seizure Disorders
(l) Back Pain
(m) Overview: Comparative Risk Tables
The NHTSA/AAMVA (1980) document entitled, Functional Aspects of Driver
Impairment: A Guide for State Medical Advisory Boards states that "... there
is evidence that, as a group, individuals with certain types of medical impairment
constitute a greater risk on the highway than does the population at large."
However, while researchers have been trying for decades to determine the extent
to which medical impairments lead to increased crash risk, none of the commonly
studied medical conditions (e.g., diabetes, heart disease, stroke, Parkinson's
disease) have been consistently associated with a high vehicle crash rate in
older drivers (Hu, 1997). In fact, it is not the mere presence of the disease,
but instead the functional limitations caused by the disease, that is key to
predicting driving impairment. Unfortunately, as noted by Janke (1994), the
degree of severity of the medical condition has not been typically considered
in past research studies. Also, as people age, they are likely to develop multiple
medical conditions, which makes it difficult to determine which specific condition
was most impairing to the driving task. The information provided in this section
of the Notebook presents findings from recent studies conducted by physicians,
occupational therapists, epidemiologists, and other researchers who have sought
to control for many of the extraneous variables that so often cloud the investigations
of medical conditions and driving performance in older persons. From these data,
the Notebook attempts to summarize the associations between age-related diminished
functional abilities and crash risk in Section IA2. Section IC2(b)v (Test Procedures:
comprehensive physical examination), and Section IC3(b)i (Rehabilitation Procedures:
physician/occupational therapist review) provide more information about how
physicians can identify at-risk older drivers and specific diagnoses, their
effects on driving, and potential remediation.
IA1(a). Dementia
Summary:
Alzheimer's Disease (AD) is the most common cause of dementia, with a prevalence--based
on correlation between autopsy data and the outcomes of strict clinical diagnostic
procedures--estimated to be as high as 11.6 percent for those 65 and older and
47.8 percent for those over the age of 85 (Evans, Funkenstein, Albert, Scheer,
Cook, Herbert, Hennekens, and Taylor, 1989). Drivers with dementia are less
likely to report driving problems than cognitively unimpaired drivers, and their
perception of their driving ability does not correspond either to that of their
caregivers (as assessed by questionnaire) nor their actual driving performance
(Cushman, 1992; Tallman, Tuokko, and Beattie, 1993). Thus, they are less likely
to limit their exposure to high risk driving situations than are drivers who
have diminished visual and physical capabilities, but intact cognitive capabilities.
Throughout the first three years the crash rate for AD patients is only slightly
higher than that for drivers of all ages in the United States, and remains well
below that of young adults aged 16 to 24. Although the course of AD may vary
considerably, study findings suggest that the increase in crash risk develops
toward the end of the third year, and more than doubles in the fourth year (see
Staplin, Lococo, McKnight, McKnight, and Odenheimer, in press, for
a review of dementia and diminished driving skills).
A recent matched-pair, case-control study, with close (1-year) age matching
was conducted in Sweden, using the Clinical Dementia Rating (CDR) scale to measure
dementia severity. In this study, questionable dementia (CDR=0.5) and mild dementia
(CDR=1) were found significantly more often in the case group (37 drivers age
65+ with license suspended due to crashes or moving violations) than in the
matched control group (37 drivers age 65+ with no license suspensions in past
5 years). Dementia was found in 49 percent of the cases versus 11 percent of
the controls. Comparison of the 23 case subjects with crashes and the 29 control
subjects with no crashes in the past 5 years showed that the crashed drivers
had more incidence of dementia/CDR>0 (p<.001), worse cube copying (p<.015),
poorer 5-item recall (p<.003), a lower Mini-Mental Status Examination (MMSE)
score (p<.019), and more EEG abnormalities. (see Johansson, Bronge, Lundberg,
Persson, Seideman, and Viitanen, 1996; Johansson, 1997).
In a recent study to assess the reliability and stability of a standardized
road test for healthy aging people and those with dementia of the Alzheimer
type, a significant relationship between global rating on the road test and
Clinical Dementia Rating (CDR) was found, such that most CDR-0 subjects (no
dementia) were rated as "safe" drivers [78 percent (45/58) of CDR-0 subjects],
compared to 67 percent (24/36) of CDR-0.5 subjects (very mild dementia) and
41 percent (12/29) of CDR-1 subjects (mild dementia)]. Only 3 percent of CDR-0
subjects were judged "unsafe," but 19 percent of CDR-0.5 and 41 percent of CDR-1
subjects were judged "unsafe." The remaining subjects in each CDR group were
rated "marginal." (see Hunt, Murphy, Carr, Duchek, Buckles, and Morris, 1997a,
and 1997b).
In a study of healthy elderly controls (n=13; mean age=73.5; CDR score=0);
subjects with very mild dementia (n=12 ; mean age=72.5; CDR score=0.5), and
subjects with mild dementia (n=13; mean age=73.4; CDR score=1.0), the correlation
between the pass/fail outcome on the road test and performance on the Logical
Memory test was significant at the p<.0009 level. Five subjects--all in the
CDR-1 stage-- "failed" the in-car on-road test. The Logical Memory subscale
of the Wechsler Memory Scale assesses immediate or delayed recall of verbal
ideas presented in two paragraphs, read aloud by the experimenter. (see Hunt,
Morris, Edwards, and Wilson, 1993).
Most recently, Salzberg and Moffat (1998) evaluated the driving records of
46 older drivers who had psychiatric conditions (Alzheimer's, bipolar disorders,
dementia, and confusion/memory loss) who were referred to the Washington State
Special Examination Program (and passed), and 449 control group drivers. An
additional 20 drivers with psychiatric conditions failed the special exam, and
their licenses were canceled. This constituted 30 percent of the drivers with
psychiatric conditions who underwent the special exam. This program is described
in more detail in Section IA1(m) of the Notebook. A "special exam"
includes an in-depth interview, and an extended or specialized on-road drive
test, typically conducted near the driver's residence. The most common outcome
of the "special exam" is to impose driving restrictions (time of day, area,
equipment).
Crash and violation records of drivers with psychiatric conditions were compared
with that of the control group, for a period of 1.75 years before the exam,
and 3.25 years after the exam (a 5-year period). Crash and violation rates were
calculated to describe the number of incidents per 100 subjects per year, since
the pre- and post-observation periods differed in length. The crash and violation
rates for the 46 drivers with psychiatric conditions who passed the "special
exam" and the (entire) control group are presented below, for the pre-exam and
post-exam period. For comparison purposes, in Washington State during 1996 there
were 140,215 total collisions and 4,037,534 licensed drivers, yielding a rate
of 3.47 collisions per 100 licensed drivers in a one-year period.
| Group |
Pre-Exam
Collision Rate |
Post-Exam
Collision Rate |
Pre-Exam
Violation Rate |
Post-Exam
Violation Rate |
| Control (n=449) |
3.8180 |
1.1650 |
7.5087 |
2.2614 |
| Special-Exam Psychiatric
Conditions (n=46) |
12.4224 |
4.6823 |
23.6025 |
8.0268 |
Older drivers with psychiatric conditions who passed the "special exam" and
received consequent driving restrictions showed a greatly reduced collision
and violation rate. However, the rate reduction still resulted in a crash and
violation risk that was approximately 4 times that of the control group of older
drivers, who did not receive exams and consequent restrictions but also showed
reductions in their crash and violation rates over the 5-year period. Of particular
interest is that the post-exam collision rate of the psychiatric group (4.6823)
was 1.35 times higher than the collision rate of the population of licensed
drivers in the State (3.47). This point illustrates that restricting the driving
privileges of drivers with psychiatric conditions brings their crash rate more
in line (although still higher) with that of the general population of drivers,
however, the rate is still much higher than that of a comparison group of older
drivers without psychiatric conditions, who (probably) are practicing self-restriction.
Hunt (1994) describes the following situations in which demented drivers experience
difficulty:
• Familiar routes are no longer well remembered, and the demented individual
may become lost while driving.
• In an emergency, the driver may confuse the brake pedal with the gas pedal
or press on both pedals simultaneously.
• Driving situations that demand complex or rapid cognitive processing and
problem solving may cause a demented driver to stop in the middle of traffic
or otherwise fail to negotiate traffic safely. To an observer, there may seem
to be no apparent reason to stop.
• In making a left turn at an intersection, the driver may fail to yield the
right-of-way or inappropriately attempt to proceed on a green light when the
sign reads "left turn on arrow only."
• Verbal commands or suggestions from a passenger (i.e., directions; reminders
to check traffic before making a lane change) are not interpreted correctly
or in time for the proper action to occur.
The American Psychiatric Association's Position Statement on the Role of Psychiatrists
in Assessing Driving Ability was drafted by the Council on Aging, approved by
the Assembly in November 1993, and by the Board of Trustees in December 1993
(Council on Aging, 1995). It states that: (1) a mental disorder per se
does not imply impaired driving capacity; (2) persons suffering from mental
disorders may experience symptoms that can interfere with their ability to drive;
(3) usually, accurate assessment of the impact of symptoms on functional abilities
is not possible in an office or hospital setting because such an assessment
typically requires specialized equipment or actual driving observation which
goes beyond the scope of ordinary psychiatric care; and (4) since psychiatrists
do not have special expertise in assessing patients' ability to drive, they
should not be expected to make these assessments in the course of clinical practice.
However, the position statement specifies that psychiatrists do have a role
to play in advising patients about the potential impact of their illness and
treatments on driving ability, as follows: (1) when appropriate, psychiatrists
should discuss with their patients symptoms of their mental disorders that may
be serious enough to substantially impair their driving ability; (2) psychiatrists
should warn their patients about the possible effects of prescribed psychotropic
medications on alertness and coordination, and about the possibility that such
medications could magnify the effects of alcohol; and (3) when clinically appropriate,
medication with a low potential to impair ability should be chosen preferentially,
depending on the patient's driving requirements and habits. Finally, the statement
mentions that given the importance of maintaining confidentially in psychiatrist-patient
relationships, psychiatrists should not be required to report information on
a patient's driving ability to state departments of motor vehicles. However,
a statute that allows, but does not require, reporting when there is clear-cut
evidence of substantial driving impairment (e.g., a family's statement that
a moderately demented patient has had several recent minor crashes) is socially
desirable and can be clinically useful. The position is that ultimate responsibility
for assessment of patients' driving ability should lie with the DMVs. Reports
made in good faith, however, should be accompanied by immunity for psychiatrists
from subsequent liability.
Conclusions/Preliminary Recommendations:
Diagnosis is not an adequate predictor of function, since there is great heterogeneity
in the rate of progress as well as the cognitive strengths and weaknesses among
patients with dementing disorders. Diagnosis could thus be important as a way
to identify persons for tracking, with decisions on whether driver status should
be terminated then based on functional assessments.
Mental status evaluations may be useful in identifying older drivers who are
beginning to show evidence of cognitive decline, but on-road or off-road tests,
especially those requiring the driver to follow sequential directions, are more
likely to measure the skills required for driving. Cutoff scores (MMSE) must
be considered as being relative, forming a small part of the basis of making
decisions about driving, and secondary to a clinical evaluation; however, MMSE
score 10, accompanied by a diagnosis of dementia, indicates a sufficiently low
level of cognitive functioning to justify recommending immediate cessation of
driving (Lundberg, Johansson, Ball, Bjerre, Blomqvist, Braekhus, Brouwer, Blysma,
Carr, Englund, Friedland, Hakamies-Blomqvist, Klemetz, O'Neill, Odenheimer,
Rizzo, Schelin, Seideman, Tallman, Viitanen, Waller, and Winblad, 1997).
It is important to note that MMSE scores are influenced by race and level of
education, so some adjustment of cutoffs may be necessary.
Patients who have had AD for more than two years should have their driving
ability closely monitored if they are to continue driving, as the overall risk
to society during the first two years is well within the accepted range for
other drivers. This is dependent upon whether AD is defined as early stage (CDR
= 0.5) or later stage (CDR >1.0) however.
References:
• Council on Aging (1995)
• Evans, Funkenstein, Albert, Scheer, Cook, Herbert, Hennekens, and Taylor
(1989)
• Hunt (1994)
• Staplin, Lococo, McKnight, McKnight, and Odenheimer (in press)
• Excerpts from Annotated Research Compendium of Driver Assessment Techniques
for Age-Related Functional Impairments (Hunt, Morris, Edwards, and Wilson,
1993; Tallman, Tuokko, and Beattie, 1993; Cushman, 1992; Odenheimer, Beaudet,
Jette, Albert, Grande, and Minaker, 1994; Johansson, 1997; Lundberg, Johansson,
Ball, Bjerre, et al., 1997; Keyl, Rebok, Bylsma, et al., manuscript under review;
Duchek, Hunt, Ball, Buckles, and Morris, 1997; Rizzo and Dingus, 1996; Rizzo,
Reinach, McGehee, and Dawson, 1997; Hunt, Murphy, Carr, Duchek, Buckles, and
Morris, 1997a, and 1997b; Janke and Eberhard, 1998; Staplin, Gish,
Decina, Lococo, and McKnight, 1998; DriveAble Testing, March 1997; Dobbs, 1997)
IA1(b). Cataracts
Summary:
Owsley, Stalvey, Wells, and Sloane (1999) conducted a study that included
279 drivers with cataract (mean age = 71) and 67 drivers with no cataract (mean
age = 67). This on-going project is an intervention evaluation study to determine
how improvement in vision impacts crashes and driving habits. Crash data from
5 years prior to enrollment and 3 years following enrollment were obtained from
Alabama Dept. of Public Safety. Findings are as follows:
• Subjects in the cataract group averaged 20/60 and 20/40 in the worst and
best eye respectively, compared to the no cataract group who averaged 20/25
and 20/20 respectively. This difference was significant (p<.001).
• Contrast sensitivity was significantly worse in both eyes for subjects with
cataracts (p<.001). Age adjusted log CS for cataract group was 1.39 (best
eye) and 1.19 (worst eye) compared to 1.61 (best eye) and 1.52 (worst eye) for
no cataract group.
• Cataract subjects detected fewer points in their visual field than the no
cataract subjects.
• Proportionately more cataract subjects preferred to have someone else drive
when they traveled in a car, drove slower than the general traffic flow, and
received advice that they limit or stop driving (self-reports on driving habits
questionnaire).
• Cataract was associated with reduced number of days driving per week and
a reduced number of destinations. (Cataract drivers 2 times more likely to reduce
driving).
• Subjects with cataracts were (2 times) less likely to drive beyond their
neighboring towns than subjects without cataracts.
• Cataract was significantly associated with driving difficulty in the rain,
driving alone, making left turns across traffic, driving on interstates, in
high traffic, in rush hour, and at night (Cataract drivers 4 times more likely
to report these difficulties).
• After adjusting for driving exposure, the association between cataract and
at-fault crash involvement was defined as relative risk equal to 2.48, (95%
CI = 1.0-6.14).
• When adjusted for impaired health, the association between cataract and crash
involvement was defined as relative risk = 2.49, (95% CI = 1.0-6.27).
Salzberg and Moffat (1998) evaluated the driving records of 45 older drivers
with cataracts who were referred to the Washington State Special Examination
Program (and passed), and 449 control group drivers. This program is described
in more detail in Section IA1(m) of the Notebook. A "special exam"
includes an in-depth interview, and an extended or specialized on-road drive
test, typically conducted near the driver's residence. The most common outcome
of the "special exam" is to impose driving restrictions (time of day, area,
equipment).
Crash and violation records of drivers with cataracts were compared with that
of the control group, for a period of 1.75 years before the exam, and 3.25 years
after the exam (a 5-year period). Crash and violation rates were calculated
to describe the number of incidents per 100 subjects per year, since the pre-
and post-observation periods differed in length. The crash and violation rates
for the 46 drivers with cataracts who passed the "special exam" and the (entire)
control group are presented below, for the pre-exam and post-exam period. For
comparison purposes, in Washington State during 1996 there were 140,215 total
collisions and 4,037,534 licensed drivers, yielding a rate of 3.47 collisions
per 100 licensed drivers in a one-year period.
| Washington State Special
Exam Program Analysis |
| Group |
Pre-Exam Collision
Rate |
Post-Exam Collision
Rate |
Pre-Exam Violation
Rate |
Post-Exam Violation
Rate |
| Control (n=449) |
3.8180 |
1.1650 |
7.5087 |
2.2614 |
| Special-Exam Cataracts (n=45)
|
5.0794 |
2.0513 |
15.2381 |
2.0513 |
Older drivers with cataracts had a pre-exam crash risk that was 1.33 times
that of a control group of older drivers without medical conditions, and 1.46
times higher than the population of licensed drivers in Washington State. After
taking and passing a special exam and receiving license restrictions, their
risk dropped substantially, to a level below that of the general population,
but still higher than that of the older drivers comprising the control group.
The authors explain the drop in crash and violation rate shown by the control
group as the result of lower driving exposure with increasing age, which is
a trend that has been demonstrated in many studies employing older drivers.
It is unknown to what degree the cataract group would self-restrict in the absence
of the special exam and its formal license restrictions, however, the drop in
violation rate for the cataract group as a function of having taken the exam
was over twice the reduction shown for the control group. Thus, the special
exam program (an on-road test in a driver's home area, plus the tailoring of
license restrictions) showed a beneficial effect in reducing crash and violation
risk for older drivers with cataracts.
Conclusions/Preliminary Recommendations:
Older drivers with a cataract experience a restriction in their driving mobility
and a decrease in their safety on the road. Vision impairment from cataract
is now largely reversible due to technological advances in surgical techniques
and interocular lens design, with over 85 percent of cases reaching 20/40 acuity
or better post-surgery. Cataract surgery is the most common surgical procedure
performed on medicare beneficiaries representing 12 percent of the overall Medicare
budget.
Owsley et al.'s in-progress study will determine whether improvement in vision
following cataract surgery expands driving habits and improves safety. Cataracts
are related to increased crash frequency; however, drivers with cataracts are
candidates for remediation through eye surgery. Study findings may provide the
basis for recommending earlier surgery to remove cataracts. Optometrists and
ophthalmologists should counsel patients regarding the dangers associated with
driving with cataracts, and suggest driving restrictions (e.g., at night/dusk,
in reduced visibility conditions such as rain, fog, etc.) for their cataract
patients. The findings from Washington State (Salzberg and Moffat, 1998) indicate
that such licensing restrictions reduce the crash and violation risk of older
drivers with cataracts to a level that is lower than that posed by the general
population of licensed drivers.
References:
• Owsley, Stalvey, Wells, and Sloane (1999)
• Salzberg and Moffat (1998)
IA1(c). Diabetes and Associated Conditions
Summary:
Hu, Young, and Lu (1993) state that 26 out of 1,000 persons are diagnosed as
having diabetes, based on the 1998 National Health Interview Survey, and that
the prevalence rate increases with age. Diabetes Mellitus is the most prevalent
metabolic disease that may have implications for driving (NHTSA, 1980). Hu et
al. (1993) provide the following brief description of the disease. Diabetes
Mellitus describes a variety of related medical conditions that affect the body's
ability to produce appropriate levels of insulin. Insulin regulates blood sugar
levels that provide nutrients to the brain; blood sugar levels that are too
high (hyperglycemia) or too low (hypoglycemia) may lead to unconsciousness.
Diabetes affects other parts of the body, including the circulatory system and
vision. Diabetes in all age groups is associated with thickening of the arteries
that can lead to faintness or unconsciousness. The longer a person has diabetes,
the more likely that retinal damage (vision impairment) will occur. Approximately
60 percent of patients having diabetes for 15 years or more have some blood
vessel damage in their eyes (American Academy of Ophthalmology, 1984). Diabetes
Mellitus can be controlled by diet alone, by a combination of diet and oral
medication, or by injection of insulin. NHTSA (1980) states that since the level
of successfully controlling the disease varies, the following factors should
be considered in determining whether a patient should be considered for driver
licensing: (1) whether an individual is under regular medical supervision; (2)
whether insulin is required; (3) whether the individual is in compliance with
the prescribed medical/dietary regimen; (4) whether a warning is experienced
before onset of any symptoms; and (5) whether the disease is under control.
A study by Owsley, Ball, McGwin, Sloane, Roenker, White, and Overley (1998)
included 294 older drivers, ages 56-90 years at enrollment, drawn from the population
of licensed drivers in Jefferson County over age 55. They were divided into
three groups as follows: 33 percent had 0 crashes on record; 49 percent had
1 to 3 crashes over the prior 5-year period; and 18 percent had 4 or more crashes
over the prior 5-year period. A significant, independent association with crash
risk in 3-year follow-up was found for subjects with a diagnosis of diabetic
retinopathy (5 times greater risk, 95% CI = 1.13 - 21.8).
Koepsell, Wolf, McCloskey, Buchner, Louie, Wagner, and Thompson (1994) conducted
a case-control study of 234 older drivers (age 65+) who were injured in a crash
during the previous 3-year period, and 446 older drivers who had no injury crashes
during the same period. Injury risk was 2.6 times higher in older diabetic drivers,
and higher for those treated with insulin (odds ratio = 5.8), or oral hypoglycemic
agents (OR=3.1), or those having diabetes for more than 5 years (OR= 3.9), or
those with both diabetes and coronary heart disease (OR=8.0).
Diller, Cook, Leonard, Reading, Dean, and Vernon (in press) analyzed
citation rates and crash rates (all crashes and at-fault crashes) for 10,069
drivers reporting diabetes mellitus and other metabolic conditions (including
thyroid, parathyroid, pituitary) who had unrestricted licenses, and 358 drivers
reporting diabetes and other metabolic conditions with restricted licenses [see
Notebook section IA1(m) for further details regarding methodology].
Drivers with multiple medical conditions were excluded from these analyses,
which significantly reduced the number of drivers with only diabetes, whose
operating privileges were restricted in some way. Their crash and citation rates
were compared to a control group of drivers (selected randomly from all licensed
drivers without medical conditions), matched on age, gender, and county of residence.
Accordingly, different control groups were established for restricted drivers
and for unrestricted drivers with this medical condition.
Rates for drivers with diabetes (and other metabolic conditions) and their
control groups per 10,000 license days for citations, for all crashes, and for
at-fault crashes, are presented in the following table, by license status (not
restricted and restricted). Also presented are the relative risk ratios (case
rate/control rate).
| Utah Rates and Relative
Risk Ratios of Adverse Driving Events Per 10,000 Days of Driving |
| License Status |
Adverse Driving Event |
| Not Restricted |
Citation |
All Crashes |
At-Fault Crashes |
| Drivers with Diabetes |
2.61 |
1.70 |
1.02 |
| Matched Controls |
2.52 |
1.20 |
0.64 |
| Rate Ratio |
1.04 |
1.41* |
1.58* |
| Restricted |
Citation |
All Crashes |
At-Fault Crashes |
| Drivers with Diabetes |
4.43 |
2.03 |
1.48 |
| Matched Controls |
3.16 |
1.42 |
0.82 |
| Rate Ratio |
1.40 |
1.43 |
1.79 |
* The rate for drivers with diabetes is significantly higher
than the rate for their matched controls who have no reported medical conditions.
Drivers with diabetes (both restricted and unrestricted) had a higher risk
of adverse driving events than control drivers without a medical condition.
Drivers with diabetes whose operating privileges were restricted showed higher
rates of adverse driving events than drivers with diabetes licensed without
restrictions. This is noteworthy even though their rates were not statistically
different than the rates of their control group. This may be the result of the
small number of cases with restricted licenses (n=358) and the lower number
of days of driving available to this group (54,199), as well as different population
characteristics.
Salzberg and Moffat (1998) evaluated the driving records of 14 older drivers
with diabetic retinopathy and 27 older drivers with diabetes mellitus who were
referred to the Washington State Special Examination Program (and passed), and
449 control group drivers. This program is described in more detail in Section
IA1(m) of the Notebook. A "special exam" includes an in-depth interview,
and an extended or specialized on-road drive test, typically conducted near
the driver's residence. The most common outcome of the "special exam" is to
impose driving restrictions (time of day, area, equipment).
Crash and violation records of drivers with diabetic retinopathy and diabetes
mellitus were compared with that of the control group, for a period of 1.75
years before the exam, and 3.25 years after the exam (a 5-year period). Crash
and violation rates were calculated to describe the number of incidents per
100 subjects per year, since the pre- and post-observation periods differed
in length. The crash and violation rates for the drivers with diabetes and related
conditions who passed the "special exam" and the (entire) control group are
presented below, for the pre-exam and post-exam period. For comparison purposes,
in Washington State during 1996 there were 140,215 total collisions and 4,037,534
licensed drivers, yielding a rate of 3.47 collisions per 100 licensed drivers
in a one-year period.
| Washington State Special
Exam Program Analysis |
| Group |
Pre-Exam Collision
Rate |
Post-Exam Collision
Rate |
Pre-Exam Violation
Rate |
Post-Exam Violation
Rate |
| Control (n=449) |
3.8180 |
1.1650 |
7.5087 |
2.2614 |
| Special Exam Diabetic Retinopathy
(n=14) |
12.2449 |
.0000 |
8.1633 |
2.1978 |
| Special Exam Diabetes Mellitus
(n=27) |
6.3492 |
1.1396 |
8.4656 |
2.2792 |
Older drivers with diabetic retinopathy had a pre-exam crash risk that was
3.2 times that of a control group of older drivers without medical conditions,
and 3.5 times higher than the population of licensed drivers in Washington State.
The pre-exam crash risk for drivers with diabetes mellitus was 1.67 times higher
than the control group of older drivers. After taking and passing a special
exam and receiving license restrictions, their risk dropped below that of the
control group. The authors explain the drop in crash and violation rate shown
by the control group as the result of lower driving exposure with increasing
age, which is a trend that has been demonstrated in many studies employing older
drivers. Since the drop in crash and violation rates was greater for drivers
with diabetes and related conditions than that demonstrated by the control group
of older drivers over the 5-year period, it may be concluded that the Special
Exam Program (on-road driving exam and license restrictions) was effective in
reducing crash risk without eliminating mobility for these drivers. What is
not known is the actual driving exposure of these groups of drivers and the
severity of disease in the exam group. Thus, the drop in rates for the special
exam group could have resulted from being too sick to drive for some period
of time during the study.
Finally, in the recently completed pre-pilot study conducted
in Salisbury, Maryland for the NHTSA "Model Driver Screening and Evaluation
Program" project, the present Notebook authors found that older drivers
who reported having diabetes were slightly more likely to be involved in a crash
(OR=1.34). For female subjects only (n=163), the odds ratio was 2.13. Subjects
ranged in age from 68 to 89 (mean age = 75.7); 131 of the 363 subjects were
involved in at least 1 crash in the previous 6-year period (1991-1997).
Conclusions/Preliminary Recommendations:
Diller et al. (in press) and Salzberg and Moffat (1998) found that
drivers licensed with diabetes and other metabolic conditions have a higher
rate of crashes than the general population of drivers. In the Owsley et al.
study, the association between crash rate and diabetic retinopathy was independent
of visual functional problems, since these variables were addressed separately
in the modeling. The authors state that this implies that features of eye conditions
unrelated to the visual functions assessed in the study (Letter Acuity - ETDRS
chart; Contrast Sensitivity - Pelli-Robson chart; Stereoacuity - TNO Test; Disability
Glare - MCT-8000 (VisTech); Visual Field Sensitivity) may be associated with
crash involvement; factors such as medication usage and other systemic and functional
complications. The authors also state that diabetic retinopathy is relatively
common in the elderly and is treatable (ophthalmologic laser surgery to seal
or photocoagulate the leaking blood vessels or a surgical procedure called a
vitrectomy, which is the removal of the blood-filled vitreous from the eye and
replacement with a clear artificial solution). If elevated crash rate is independent
of visual function, diabetes (not diabetic retinopathy) may actually be responsible
for the elevation in crash rate. Physicians and ophthalmologists should counsel
their patients with diabetes regarding the importance of complying with treatment
recommendations (diet and medications) for maintaining safe driving, and recommend
driving restrictions/cessation on an individual basis, depending on the extent
and severity of the symptoms.
Regarding the effectiveness of restricting the licenses of drivers with diabetes,
results are mixed. This is because actual exposure data have not been available.
Diller et al. (in press) attempted to control for the effects of exposure,
but only used available days (as opposed to actual miles driven). The reduction
in crash and violation rates shown in the Salzberg and Moffat (1998) study are
noteworthy; however, caution needs to be taken in generalizing the results.
Older drivers with medical conditions may either choose to restrict their driving
because they know that they are at an increased crash risk, or they may not
feel well enough to drive as often as healthy older drivers. Lower exposure
leads to a lower crash risk. Also, the sample size of drivers with diabetes
in this study was small. But the crash and violation rate reductions reported
above indicate that restricting the driving privileges has promise in improving
safety while maintaining mobility.
References:
• American Academy of Ophthalmology (1984)
• Diller, Cook, Leonard, Reading, Dean, and Vernon
(in press)
• Hu, Young, and Lu (1993)
• Koepsell, Wolf, McCloskey, Buchner, Louie, Wagner, and Thompson (1994)
• National Center for Health Statistics(1989)
• NHTSA (1980)
• Owsley, Ball, McGwin, Sloane, Roenker, White, and Overley (1998)
• Salzberg and Moffat (1998)
IA1(d). Glaucoma
Summary:
Glaucoma is one of the leading causes of blindness in the U.S., affecting 2
out of every 100 persons over age 35 (American Academy of Ophthalmology, 1983).
A study by Owsley, Ball, McGwin, Sloane, Roenker, White, and Overley (1998)
included 294 older drivers, ages 56-90 years at enrollment, drawn from the population
of licensed drivers in Jefferson County over age 55. They were divided into
three groups as follows:
• 33% had 0 crashes on record.
• 49% had 1 to 3 crashes over the prior 5-year period.
• 18% had 4 or more crashes over the prior 5-year period.
A significant, independent association with crash risk in a 3-year follow-up
was found for subjects with a diagnosis of glaucoma: (Relative Risk =5.20, 95%
Confidence Interval = 1.19-22.72). The relationship for glaucoma and crashes
was stronger for males (RR=9.81) than for females (RR=5.14).
The association between crash rate and glaucoma was independent of visual functional
problems, since these variables were addressed separately in the modeling. The
authors state that this implies that features of eye conditions unrelated to
the visual functions assessed in the study may be associated with crash involvement
(such as medication usage and other systemic and functional complications).
In another study of 193 older drivers between age 55-87 (mean = 71 years),
identified through Alabama Department of Public Safety Files, 78 drivers (cases)
had at least 1 crash in the prior 5-year period that resulted in an injury to
anyone in the involved vehicles, and 115 drivers (controls) had no crashes in
the same 5-year period. Glaucoma was independently associated with crash risk
in the multivariate analyses: cases were 3.6 times more likely to report glaucoma
than were controls (Owsley, McGwin, and Ball, 1998).
In a panel data analysis of remaining eligible drivers in 1993 (507 female
drivers and 375 male drivers) who participated in the Iowa 65+ Rural Health
Study from 1981-1993, none of the commonly studied medical conditions (e.g.,
diabetes, heart disease, stroke, Parkinson's Disease) were associated with crashes.
The only medical condition that increased crash risk in older drivers was glaucoma.
And, the association between glaucoma and highway crashes was evident only among
older male drivers (odds ratio = 1.7) (Hu, Trumble, Foley, Eberhard, and Wallace,
1998).
Stewart, Moore, Marks, May, and Hale (1993) found no association between
glaucoma and increased crash risk, in a sample of 1,431 older drivers. Both
independent and dependent variables, however, were comprised of self-reports
(of medical conditions and crashes, respectively).
Conclusions/Preliminary Recommendations:
Glaucoma is relatively common in the elderly and is associated with an increased
crash risk. In multiple studies, the risk of an older driver being involved
in a crash is 1.7 to 5.2 times higher if glaucoma is present. Two studies showed
that the risk appears to be higher for males than for females. The American
Optometric Association (AOA) recommends that people ages 10 to 40 see an optometrist
every 2 to 3 years; people ages 41-60 every two years; and people age 61+ every
year. Individuals age 61+ have an increasing risk for the development of cataracts,
glaucoma, and macular degeneration and other sight threatening or visually disabling
eye conditions as well as systematic health conditions. The American Academy
of Ophthalmology recommends that persons over age 35 be checked for glaucoma
every 2 or 3 years. Glaucoma is treatable (eye drops, pills to decrease pressure
either by assisting outflow of fluid from the eye or by decreasing the amount
of fluid entering the eye, or surgery to perform a new drainage canal).
References:
• American Academy of Ophthalmology (1983): Glaucoma
• Hu, Trumble, Foley, Eberhard, and Wallace (1998)
• Owsley, Ball, McGwin, Sloane, Roenker, White, and Overley (1998)
• Owsley, McGwin, and Ball (1998)
• Stewart, Moore, Marks, May, and Hale (1993)
IA1(e). Foot Abnormalities
Summary:
Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994) studied 283 community-dwelling
individuals age 72 to 92 (mean age = 77.8) from the Project Safety cohort living
in New Haven, CT who drove between 1990 and 1991. Fifty-seven percent of the
sample were males.
The number of the following foot abnormalities was noted in addition to the
ability to stand on toes and heels: toenail irregularities, calluses, bunions,
and toe deformities such as hammer toes. Analyses were conducted contrasting
driving outcomes for patients with 0 to 2 foot abnormalities versus 3 to 8 foot
abnormalities.
The outcome variable was self-reported involvement in automobile crashes, moving
violations, or being stopped by police in the year following administration
of the test battery.
Persons with 3 or more foot abnormalities were more likely to have adverse
events (23 percent had adverse events) compared to persons with 0-2 foot abnormalities
(10 percent had adverse events). The difference was significant at p<0.01
level (relative risk = 2.0, 95% CI=1.0 to 3.8).
A multivariate analysis adjusting for driving frequency and housing type found
the following factors to be associated with the occurrence of adverse events:
poor design copying on the MMSE (relative risk=2.3, 95% CI=1.5 to 5.0), fewer
blocks walked--0 versus > 1 (relative risk=2.3, 95% CI=1.3 to 4.0)
and more foot abnormalities--3 to 8 versus 0 to 2 (relative risk=1.9, 95% CI=1.1
to 3.3).
Combining these 3 factors to assess their ability to predict adverse driving
events showed that if no factors were present, 6 percent of drivers had adverse
events; if 1 factor was present, 12 percent had events; if 2 factors were present,
26 percent had events; and if all 3 factors were present, 47 percent had events.
Conclusions/Preliminary Recommendations:
There is a significant relationship between foot abnormalities in the elderly
and increased crash risk. The association between foot abnormalities and crashes
is logical, because such abnormalities may affect the ability to maneuver between
the brake and accelerator. Physicians should take notice of foot abnormalities
in older patients and include driving history-taking and counseling as part
of routine exams.
References:
• Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994)
IA1(f). Falls
Summary:
Sims, Owsley, Allman, Ball, and Smoot (1998) conducted a study to explore associations
between a history of at-fault vehicle crashing in older subjects (between 1985-1991)
and several medical and functional variables collected on them in 1991. Seven
questionnaires and 10 physical examination/ performance measures were employed
to assess medical and functional domains. Lists of drivers and number of crashes
for each driver were made available by the AL Dept. of Public Safety.
Subjects included 174 drivers ages 55-90 (mean age 71.1), residing in Jefferson
County, AL. Case drivers has at least 1 state-recorded at-fault crash in the
6 years preceding the assessment (n=99).
Controls had no state-recorded at-fault crashes in the prior 6 years (n=75).
At the univariate level, crash-involvement was significantly associated with
falling in the prior two years (p=0.004). All non-collinear variables that were
significant at the univariate level were entered into logistic regression models;
these included falling, reduction of 40 percent or more in the useful field
of view, and not taking a beta-blocking drug. The logistic regression model
indicated that having fallen in the prior two years was related to crash involvement
with an odds ratio of 2.6 (CI=1.1-6.1, p=0.025).
Note: In another study by Owsley, McGwin, and Ball (1998), subjects
with crashes were 3.6 times more likely to report a diagnosis of glaucoma compared
to controls. These authors cited Glynn et al. (1991). Although medication information
was not collected, Glynn et al. (1991) reported that the use of topical eye
medications in elderly patients with glaucoma increased their risk of falling
(an adverse mobility outcome).
Koepsell, Wolf, McCloskey, Buchner, Louie, Wagner, and Thompson (1994) conducted
a case-control study of 234 older drivers (age 65+) who were injured in a crash
during the previous 3-year period, and 446 older drivers who had no injury crashes
during the same period. Injury risk was 1.4 times higher in older drivers who
had fallen in the previous year. The authors caution that this association could
have arisen by chance.
In the recently completed pre-pilot study conducted in Salisbury, Maryland
for the NHTSA "Model Driver Screening and Evaluation Program" project, the present
Notebook authors found that self-reported falls in the past two years
was related to crashing (Odds Ratio for all subjects=1.53; OR for females only=1.38;
OR for males only=1.61). Subjects ranged in age from 68 to 89 (mean age=75.7);
131 of the 363 subjects were involved in at least 1 crash in the previous 6-year
period (1991-1997).
Conclusions/Preliminary Recommendations:
Crash involvement in the elderly is significantly related to having fallen
in the past two years. Professionals conducting geriatric assessments should
include a question about falling as part of history-taking, and DMVs should
include a question about falling on license renewal applications for tracking
of associations between falling and automobile crashes.
References:
• Glynn, Seddon, Krug, Sahagian, Chiavelli, and Campion (1991)
• Koepsell, Wolf, McCloskey, Buchner, Louie, Wagner, and Thompson (1994)
• Owsley, McGwin, and Ball (1998)
• Sims, Owsley, Allman, Ball, and Smoot (1998)
IA1(g). Cardiac (and Cardiopulmonary) Condition
Summary:
Stewart, Moore, Marks, May, and Hale (1993) studied 1,431 participants in the
Florida Geriatric Research Program (Dunedin, FL), for whom 8 years of longitudinal
data were available (1975-1987). Subjects included 874 females (mean age = 77.8
years, s.d. = 4.6) and 596 males (mean age = 78.6 years, s.d.=4.5).
The dependent variable was self-reported crashes. Independent variables included
self-reported information on 31 diseases, 26 symptoms, 34 clinical and laboratory
values, number of drugs reported, number of symptoms reported, number of diseases
reported. Subjects completed a questionnaire containing 180 questions and a
form listing prescribed and nonprescribed medications used on a regular basis.
Biochemical profile includes hemogram, red cell indices, and SMAC-23. Clinical
assessment includes electrocardiogram and carotid auscultation, plus MMSE and
Beck Depression Inventory at 8th visit.
The correlation between irregular heartbeat (palpitations) and crashes is significant
(p=0.0017, Odds ratio = 1.83, 95% CI = 1.25-2.68). No other cardiovascular symptoms
or diseases investigated in the present study were predictive of crashes.
No other signs or symptoms were of significance in crashes (paroxysmal nocturnal
dyspnea, temporary loss of limb, dizziness/spinning, lightheadedness, syncope,
tinnitus, dysphagia, amaurosis fugax, pain in abdomen, swollen feet/ankles,
headache, paresthesia, diarrhea, recurrent cough, hematuria, incontinence (urine),
aphasia, dysphonia, dyspnea, orthopnea, nocturia, claudication, dysuria, memory
loss, feel awkward, effort angina, angina with tension, hemoptysis, constipation,
thin bowel movements, blood in stools, melena, swollen joints, ache/painful
joints, urinary hesitancy, and carotid bruits).
Diller, Cook, Leonard, Reading, Dean, and Vernon (in
press) analyzed citation rates and crash rates (all crashes and at-fault
crashes) for 18,990 drivers with cardiovascular conditions (including heart
disease, rhythm disturbances, or history of myocardial infarctions, heart surgery,
or hypertension) who had unrestricted licenses, and 160 drivers with cardiovascular
conditions with restricted licenses [see Notebook section IA1(m) for
further details regarding methodology]. Drivers with multiple medical conditions
were excluded from these analyses, which significantly reduced the number of
drivers with only cardiovascular conditions, whose operating privileges were
restricted in some way. Their crash and citation rates were compared to a control
group of drivers (selected randomly from all licensed drivers without medical
conditions), matched on age, gender, and county of residence. Accordingly, different
control groups were established for restricted drivers and for unrestricted
drivers with this medical condition.
Rates for drivers with cardiovascular conditions and their control groups per
10,000 license days for citations, for all crashes, and for at-fault crashes,
are presented in the following table, by license status (not restricted and
restricted). Also presented are the relative risk ratios (case rate/control
rate).
The data indicate that unrestricted drivers with cardiovascular disease have
significantly higher crash rates (all crashes and at-fault crashes) than their
matched controls without a medical condition. Drivers with cardiovascular disease
whose driving privileges are restricted, also have a higher rate of adverse
events than their matched control group, although the differences are not statistically
significant. The higher rate may be explained by the small sample size (n= 160)
and resulting number of eligible licensed driving days (22,290). In the time
period under analysis (1992-1996), these restricted drivers experienced only
7 citations, 3 crashes, and 2 at-fault crashes.
| Utah Rates and Relative
Risk Ratios of Adverse Driving Events Per 10,000 Days of Driving |
| License Status |
Adverse Driving Event |
| Not Restricted |
Citation |
All Crashes |
At-Fault Crashes |
| Drivers with Cardiovascular Conditions |
1.23 |
1.04 |
0.55 |
| Matched Controls |
1.60 |
0.91 |
0.47 |
| Rate Ratio |
0.77** |
1.14* |
1.15* |
| Restricted |
Citation |
All Crashes |
At-Fault Crashes |
| Drivers with Cardiovascular Conditions |
3.14 |
1.35 |
0.90 |
| Matched Controls |
2.0 |
0.83 |
0.52 |
| Rate Ratio |
1.57 |
1.61 |
1.72 |
* The rate for drivers with cardiovascular conditions is significantly
higher than the rate for their matched controls who have no reported medical
conditions.
** Differences in rates between medical conditions and control
groups are statistically significant, with higher rates for control group.
Salzberg and Moffat (1998) evaluated the driving records of 47 older drivers
with cardiovascular conditions who were referred to the Washington State Special
Examination Program (and passed), and 449 control group drivers. This program
is described in more detail in Section IA1(m) of the Notebook. A "special
exam" includes an in-depth interview, and an extended or specialized on-road
drive test, typically conducted near the driver's residence. The most common
outcome of the "special exam" is to impose driving restrictions (time of day,
area, equipment).
Crash and violation records of drivers with cardiovascular conditions were
compared with that of the control group, for a period of 1.75 years before the
exam, and 3.25 years after the exam (a 5-year period). Crash and violation rates
were calculated to describe the number of incidents per 100 subjects per year,
since the pre- and post-observation periods differed in length. The crash and
violation rates for the drivers with cardiovascular conditions who passed the
"special exam" and the (entire) control group are presented below, for the pre-exam
and post-exam period. For comparison purposes, in Washington State during 1996
there were 140,215 total collisions and 4,037,534 licensed drivers, yielding
a rate of 3.47 collisions per 100 licensed drivers in a one-year period.
| Washington State Special
Exam Program Analysis |
| Group |
Pre-Exam Collision
Rate |
Post-Exam Collision
Rate |
Pre-Exam Violation
Rate |
Post-Exam Violation
Rate |
| Control (n=449) |
3.8180 |
1.1650 |
7.5087 |
2.2614 |
| Special Exam Cardiovascular Conditions
(n=47) |
7.2948 |
1.9640 |
20.6687 |
2.6187 |
Older drivers with cardiovascular conditions had a crash rate almost twice
as high as that of the control group of older drivers prior to taking the special
exam and receiving driving restrictions, and a violation rate over 2.5 times
higher than control group drivers, during the pre-exam period. After undergoing
the special exam process, their crash and violation rates fell significantly,
to almost the level of that shown by the control group, which is less than the
crash rate of the population of licensed drivers in the State of Washington.
Thus, it appears that appropriate license restrictions (e.g., driving only within
a specific radius of residence, daylight driving only, driving only between
the hours of 10 a.m. to 3 p.m., no freeway driving, and/or driving within city
limits only) are effective in reducing the risk posed by older drivers, without
unduly restricting their mobility.
In Janke's (1994) review of cardiovascular conditions and driving, it is concluded
that increased societal risk due to the driving of patients (in personal vehicles)
with cardiovascular disease has not been shown. There is evidence that cardiac
patients cut down on their mileage considerably and reduce long-distance driving,
driving in bad weather, driving alone, driving after dark, and driving in heavy
traffic (Waller, 1981, 1987; Potvin, Guibert, Philibert, and Loiselle, 1990,
Potvin, Guibert, and Loiselle, 1993: in Janke, 1994). Potvin, Guibert and Loiselle,
1993 (in Janke, 1994) note methodological problems in the studies they review,
including low occurrence of crashes, difficulty in defining a suitable comparison
group, classification difficulties (e.g., healthy controls may develop a cardiovascular
condition in the course of the study, unknown to the experimenter), and uncontrolled
variations in exposure to crash risk.
Diller et al. (in press) also analyzed citation rates and crash rates
(all crashes and at-fault crashes) for 2,615 drivers with pulmonary conditions
(including pulmonary disease or symptoms, impaired function, or severe respiratory
difficulties) who had unrestricted licenses, and 244 drivers with pulmonary
conditions and whose licenses were restricted. Drivers with multiple medical
conditions were excluded from these analyses, which significantly reduced the
number of drivers with only pulmonary conditions, whose operating privileges
were restricted in some way. Their crash and citation rates were compared to
a control group of drivers (selected randomly from all licensed drivers without
medical conditions), matched on age, gender, and county of residence. As mentioned
earlier, different control groups were established for restricted drivers and
for unrestricted drivers with this medical condition.
Rates for drivers with pulmonary conditions and their control groups per 10,000
license days for citations, for all crashes, and for at-fault crashes, are presented
in the following table, by license status (not restricted and restricted). Also
presented are the relative risk ratios (case rate/control rate).
The relative risk ratios for all events between drivers with pulmonary conditions
who drove with unrestricted licenses and their matched controls are
significantly different (at alpha = 0.05). This finding suggests that drivers
who have pulmonary conditions and unrestricted driving privileges have a higher
risk of crash events than drivers in the general population who do not report
medical conditions. For citations, pulmonary conditions appear to have a protective
effect, possibly due to self-restriction (a factor which was not taken into
account in the data collection), or to other differing population characteristics.
However, the differences between drivers with medical conditions who were restricted
in their driving privileges and their corresponding control groups were not
significantly different.
| Utah Rates and Relative
Risk Ratios of Adverse Driving Events Per 10,000 Days of Driving |
| License Status |
Adverse Driving Event |
| Not Restricted |
Citation |
All Crashes |
At-Fault Crashes |
| Drivers with Pulmonary Conditions |
2.24 |
1.52 |
0.85 |
| Matched Controls |
2.54 |
1.22 |
0.63 |
| Rate Ratio |
0.88** |
1.25* |
1.35* |
| Restricted |
Citation |
All Crashes |
At-Fault Crashes |
| Drivers with Pulmonary Conditions |
0.69 |
1.04 |
1.04 |
| Matched Controls |
1.39 |
1.11 |
0.64 |
| Rate Ratio |
0.50 |
0.93 |
1.63 |
* The rate for drivers with pulmonary conditions is significantly
higher than the rate for their matched controls who have no reported medical
conditions.
** The rate for drivers with pulmonary conditions is significantly
lower than the rate for their matched controls who have no reported medical
conditions.
Conclusions and Preliminary Recommendations:
The correlation between irregular heartbeat and crashes in the elderly was
significant in a study that used self-reporting both of crash occurrence and
of medical conditions. Another study found that drivers with cardiovascular
conditions and drivers with pulmonary conditions who drive without restrictions
on their licenses have a significantly higher citation and crash risk than drivers
without these medical conditions. Restricted drivers in Utah have either a 3-month
interval for review (cardiovascular conditions) or a 6-month interval for review
(pulmonary conditions), and generally have the following restrictions placed
on their driving privileges: speed limitations (profile level 6); speed and
area limitations (level 7); speed, area, and time of day (level 8); and speed,
area, time of day, and must be accompanied by licensed passenger (levels 9-10).
Thus, it appears that restricting the driving privileges of persons with cardiovascular
conditions and those with pulmonary conditions reduces citation and crash risk
to the level of risk posed by the general population without these medical conditions.
One limitation to the methodology in the Diller et al. study was that no actual
measure of exposure was collected; therefore, it is unknown to what degree the
restricted drivers (whose impairments were more severe than unrestricted drivers)
reduced their own risk by lowering their exposure.
Larsen et al, 1994 (in Janke, 1994) recommended that doctors should advise
their arrhythmia patients not to drive for 7 months after discharge from the
hospital.
References:
• Diller, Cook, Leonard, Reading, Dean, and Vernon
(in press)
• Janke (1994)
• Stewart, Moore, Marks, May, and Hale (1993)
IA1(h). Feet or Legs Cold on Exposure to Cold
Summary:
Stewart, Moore, Marks, May, and Hale (1993) studied 1,431 participants in the
Florida Geriatric Research Program (Dunedin, FL), for whom 8 years of longitudinal
data were available (1975-1987). Subjects included 874 females (mean age = 77.8
years, s.d. = 4.6) and 596 males (mean age = 78.6 years, s.d.=4.5).
The dependent variable was self-reported crashes. Independent variables included
self-reported information on 31 diseases, 26 symptoms, 34 clinical and laboratory
values, number of drugs reported, number of symptoms reported, number of diseases
reported.
Subjects completed a questionnaire containing 180 questions and a form listing
prescribed and nonprescribed medications used on a regular basis. Biochemical
profile includes hemogram, red cell indices, and SMAC-23. Clinical assessment
includes electrocardiogram and carotid auscultation, plus MMSE and Beck Depression
Inventory at 8th visit.
The correlation between feet or legs cold upon exposure to cold and traffic
crashes is significant (p=.0074, odds ratio = 1.82, 95% confidence interval
= 1.17 - 2.82).
Conclusions/Preliminary Recommendations:
One study has found that older drivers who indicate that their feet/legs feel
cold upon exposure to cold are at increased crash risk. Professionals conducting
geriatric assessments should include a question about these symptoms as part
of history-taking, and important data may be obtained if DMVs included a similar
question on license renewal applications for tracking of associations between
feet/legs becoming cold upon exposure to cold and automobile crashes.
References:
• Stewart, Moore, Marks, May, and Hale (1993)
IA1(i). Bursitis
Summary:
Stewart, Moore, Marks, May, and Hale (1993) studied 1,431 participants in the
Florida Geriatric Research Program (Dunedin, FL), for whom 8 years of longitudinal
data were available (1975-1987). Subjects included 874 females (mean age = 77.8
years, s.d. = 4.6) and 596 males (mean age = 78.6 years, s.d.=4.5).
The dependent variable was self-reported crashes. Independent variables included
self-reported information on 31 diseases, 26 symptoms, 34 clinical and laboratory
values, number of drugs reported, number of symptoms reported, number of diseases
reported. Subjects completed a questionnaire containing 180 questions and a
form listing prescribed and nonprescribed medications used on a regular basis.
Biochemical profile includes hemogram, red cell indices, and SMAC-23. Clinical
assessment includes electrocardiogram and carotid auscultation, plus MMSE and
Beck Depression Inventory at 8th visit.
Bursitis is an inflammation of a bursa, especially of the shoulder or elbow.
Bursae are closed synovial spaces located at the site of friction between skin,
ligaments, tendons, muscles and bones; the most common site of bursitis is in
the shoulder. Bursitis may cause severe pain and limitation of mobility. The
correlation between bursitis and traffic crashes was significant (p=.0005, odds
ratio = 2.18, 95% confidence interval = 1.41 - 3.38).
In the recently completed pre-pilot study conducted in Salisbury, Maryland
for the NHTSA "Model Driver Screening and Evaluation Program" project, the present
Notebook authors found that self-reported bursitis was related to crashing
for females only (Odds Ratio = 1.57). Subjects ranged in age from 68 to 89 (mean
age = 75.7); 131 of the 363 subjects were involved in at least 1 crash in the
previous 6-year period (1991-1997). Only 13 of the 146 females who responded
to this health question reported having bursitis.
Conclusions/Preliminary Recommendations:
Older drivers with bursitis are at increased crash risk. Professionals conducting
geriatric assessments should include a question about bursitis as part of history-taking
(and note its presence during the assessment), and DMVs should include a similar
question on license renewal applications for tracking of associations between
bursitis and automobile crashes.
References:
• Stewart, Moore, Marks, May, and Hale (1993)
IA1(j). Renal Disease
Protein in Urine
Summary:
Stewart, Moore, Marks, May, and Hale (1993) studied 1,431 participants in the
Florida Geriatric Research Program (Dunedin, FL), for whom 8 years of longitudinal
data were available (1975-1987). Subjects included 874 females (mean age = 77.8
years, s.d. = 4.6) and 596 males (mean age = 78.6 years, s.d.=4.5).
The dependent variable was self-reported crashes. Independent variables included
self-reported information on 31 diseases, 26 symptoms, 34 clinical and laboratory
values, number of drugs reported, number of symptoms reported, number of diseases
reported.
Subjects completed a questionnaire containing 180 questions and a form listing
prescribed and nonprescribed medications used on a regular basis. Biochemical
profile includes hemogram, red cell indices, and SMAC-23. Clinical assessment
includes electrocardiogram and carotid auscultation, plus MMSE and Beck Depression
Inventory at 8th visit.
The correlation between protein in the urine and traffic crashes was significant
(p=.0021, odds ratio = 1.84, 95% confidence interval = 1.25 - 2.72).
Conclusions/Preliminary Recommendations:
Increased urinary excretion of protein is a common sign of renal disease, and
is significantly related to older driver crashes. Urinalysis should be a part
of a physical examination for older persons.
References:
• Stewart, Moore, Marks, May, and Hale (1993)
IA1(k). Seizure Disorders
Summary:
Hu, Young, and Lu (1983) state that epilepsy may cause sudden loss of consciousness,
muscular convulsions or spasms, or it may only cause a slight temporary change
in a person's conscious awareness. They report that although the actual number
of Americans who have epilepsy is unknown, the National Center for Health Statistics
(NCHS, 1989) estimated a rate of 3.8 in every 1,000 persons.
Diller, Cook, Leonard, Reading, Dean, and Vernon (in
press) analyzed citation rates and crash rates (all crashes and
at-fault crashes) for 2,620 drivers with epilepsy who had unrestricted licenses
and 775 drivers with epilepsy with restricted licenses [see Notebook
section IA1(m) for further details regarding methodology]. These groups were
not mutually exclusive, as during the study period, a number of drivers may
have fluctuated between restricted and nonrestricted licensing privileges. Their
crash and citation rates were compared to a control group of drivers (selected
randomly from all licensed drivers without medical conditions), matched on age,
gender, and county of residence. Accordingly, different control groups were
established for restricted drivers and for unrestricted drivers with this medical
condition.
This category of medical condition (epilepsy and other episodic conditions)
is defined as follows in Utah's Guidelines and Standards for Health Care
Professionals), included as Appendix A in Diller et al.: "Epilepsy includes
any recurrent loss of consciousness or conscious control arising from intermittent
changes in brain function. Because of the similarity of consequences, other
disorders affecting consciousness or control such as syncope, cataplexy, narcolepsy,
hypoglycemia, episodic vertigo interfering with function, etc., have been included
in this section, to be considered in a similar fashion."
Rates for drivers with epilepsy and their control groups per 10,000 license
days for citations, for all crashes, and for at-fault crashes, are presented
in the following table, by license status (not restricted and restricted). Also
presented are the relative risk ratios (case rate/control rate).
| Utah Rates and Relative
Risk Ratios of Adverse Driving Events Per 10,000 Days of Driving |
| License Status |
Adverse Driving Event |
| Not Restricted |
Citation |
All Crashes |
At-Fault Crashes |
| Drivers with Epilepsy |
4.06 |
2.69 |
1.76 |
| Matched Controls |
3.96 |
1.49 |
0.84 |
| Rate Ratio |
1.03 |
1.81* |
2.11* |
| Restricted |
Citation |
All Crashes |
At-Fault Crashes |
| Drivers with Epilepsy |
4.13 |
2.67 |
2.40 |
| Matched Controls |
3.94 |
1.73 |
0.97 |
| Rate Ratio |
1.05 |
1.55* |
2.47* |
* The rate for drivers with epilepsy is significantly higher
than the rate for their matched controls who have no reported medical conditions.
Drivers with epilepsy (both those with restrictions and those without restrictions)
have a higher risk of crashing than their matched control groups.
Conclusions/Preliminary Recommendations:
The data analysis conducted by Diller et al. (in press) indicates
that licensed drivers with epilepsy/episodic conditions (both those who have
restricted operating privileges and those without license restrictions) are
at a significantly higher risk of a crash than the general population of drivers.
The American Academy of Neurology, American Epilepsy Society, and Epilepsy
Foundation of America (1994) have drafted consensus statements on driver licensing
and epilepsy, based on a Consensus Workshop held in 1991. These groups agree
that a seizure-free interval should be stated, and that 3 months is preferred,
starting from the date of the seizure. Both favorable and unfavorable modifiers
could alter the interval. The groups also agree that "restricted licenses may
be appropriate under certain circumstances in which such restrictions will allow
driving with an acceptable risk of seizure occurrence." They further state that
physician and/or medical advisory board input should be obtained for individualized
determination of the terms of each restricted license. There is unanimous agreement
among the groups that physicians should not be required to report their patients
to the DMV; they should, however, advise patients about the medical risks involved,
about DMV requirements, about self-reporting obligations, and should tell the
patient the physician's own recommendation about driving. The patient should
be responsible to self-report the condition initially to the DMV and to report
recurrent seizures. However, the group stated that if the physician believes
the patient has not self-reported and is endangering the public by driving,
the physician should have the right to report the patient, with immunity. The
participants of the Consensus Workshop determined that medical criteria for
licensing are best handled in the form of medical guidelines or regulations.
Sample statutory language is provided in the document; many are based on Wisconsin
Statutes.
References:
• American Academy of Neurology, American
Epilepsy Society, and Epilepsy Foundation of America (1994)
• Diller, Cook, Leonard, Reading, Dean, and Vernon
(in press)
• Hu, Young, and Lu (1993)
• National Center for Health Statistics (1989)
IA1(l). Back Pain
Summary:
Hu, Trumble, Foley, Eberhard, and Wallace (1998) conducted a panel data analysis
of the remaining eligible drivers in 1993 (507 female drivers and 375 male drivers)
who participated in the Iowa 65+ Rural Health Study from 1981-1993. The study
included all noninstitutionalized individuals in two counties age 65+. The resulting
sample was 6,553 female person-years and 5,414 male person-years.
The survey data were obtained from in-home and telephone interviews, and included
demographic attributes, onset of medical conditions, symptoms and ailments,
functional status, physical functioning, physical activities, vision, drug use,
cognitive abilities, and annual miles driven. The survey data were linked to
crash files maintained by the Iowa DMV. The association between
crash risk and persistent back pain was significant for combined gender (6,553
female person-years and 5,414 male person-years). The risk ratios (RR) are as
follows, for the specified mileage levels: RR=1.25 for 3,000; 6,000, and 12,000
miles driven annually; RR = 1.54 for 9,000 and 18,000 annual miles.
Foley, Wallace, and Eberhard (1995) interviewed 1,791 of the Rural Health Study
participants in 1989. Between the period of 1985 and 1989, 206 drivers were
involved in 245 state-recorded crashes. They found that a large proportion of
drivers with existing back pain or an episode of back pain in the previous year
(42%) had a significantly increased risk of crashing. Interestingly, none of
the other disease histories obtained were related to crashing (heart disease,
cancer, stroke, hypertension, diabetes, asthma, arthritis, osteoporosis, and
emphysema). The crash involvement rate (number of drivers involved in crashes
per 1,000 estimated person-years of driving) for older drivers with back pain
in the past 12 months was 33. The relative risk was 1.5, with a confidence interval
ranging from 1.2 to 2.0.
Conclusions/Preliminary Recommendations:
Foley et al. (1995) stated that the association of back pain with crash risk
corroborates concern over the impact of musculoskeletal dysfunction on driving.
Reasons for this association may include decreased motor function in driving
tasks because of pain or underlying neurologic deficit in the lower extremities,
as well as a dysfunction resulting from more generalized arthritic conditions.
Since the presence of self-reported arthritis did not correlate with crashes
it seems reasonable to conclude that license renewal forms should specifically
cite symptoms, as opposed to diagnoses alone, to query drivers about health
risks that may be related to crashes.
References:
• Hu, Trumble, Foley, Eberhard, and Wallace (1998)
• Foley, Wallace, and Eberhard (1995)
IA1(m). Overview: Comparative Risk Table
Summary:
Tables permitting comparison of the risk associated with each of the conditions
addressed in this section are presented below. First, the results of a recent
and ongoing analysis of Utah's medical conditions database are presented, summarized
in the form of relative risk values for all of the included conditions compared
to matched control groups of drivers (Diller, Cook, Leonard, Reading, Dean,
and Vernon, in press). These values are
presented on page 36; a synopsis of the methodology used to derive these values
is also given. Next, data from Washington State are presented in a table on
page 37, along with a description of the study methodology (Salzberg and Moffat,
1998). Immediately following the relative risk table for the Utah and Washington
data is another table labeled "Risk Ratios for Identified Medical Conditions."
This table, shown on page 38, extracts risk ratios and odds ratios for crash
involvement for various conditions as they could be extracted from the studies
cited in each area, i.e., Notebook sections IA1(a) - IA1(l).
In Utah, driver license applicants must complete a general questionnaire designed
to identify medical conditions related to physical, mental, and emotional health.
Applicants who report a medical condition are placed into at least one of 12
functional ability categories (diabetes mellitus and other metabolic conditions;
cardiovascular; pulmonary; neurologic; epilepsy and other episodic conditions;
learning/memory/communications; psychiatric or emotional conditions; alcohol
and other drugs; visual acuity; musculoskeletal abnormalities/chronic medical
debilities; functional motor ability; and hearing) and further by functional
ability level (1-12) within the functional category. Passenger vehicle drivers
in functional ability profile levels 1-5 may drive without restrictions (speed,
area, time of day, licensed passenger). Although severity of impairments increase
with increases in assigned functional profile level, drivers in levels 4 and
5 are deemed safe to drive without license restriction, but may be required
for reexam/medical review at intervals shorter than the standard renewal period,
depending on their functional (medical) category. Drivers assigned to functional
ability profile level 6 have a speed restriction placed on their licenses. A
profile level of 7 indicates that the driving risk posed by the functional impairment
justifies a speed and area limitation. A profile level of 8 indicates a speed,
area, and time of day limitation. Drivers in profile level 9 must be accompanied
by a licensed driver, and may have speed, area, and/or time of day limitations
as recommended by their health care professional. Levels 10 and 11 are associated
with special driving limitations recommended by health care providers or the
Director of Licensing. A person assigned to level 12 may not drive until ability
improves and functional ability can be assigned at a lower level.
Utah's Guidelines and Standards for Health Care Professionals (provided
as Appendix A to Diller et al., in press) contains descriptions of
basic concepts, definitions, and ground rules for each functional ability category.
A brief description of conditions, symptoms, impairments, etc., that are subsumed
under each category is presented next.
Diabetes Mellitus and Other Metabolic Conditions: Disturbances in the
function of the endocrine glands cause many symptoms from generalized asthenia,
muscle weakness, and spasm or tetany to sudden episodes of dizziness or unconsciousness.
This category includes diabetes mellitus, parathyroid disorders, thyroid disorders,
and hypoglycemia.
Cardiovascular: Cardiovascular disease may affect a driver's ability
in a variety of ways, and therefore profile guidelines and standards are provided
for four of the most common circumstances: general heart disease; rhythm; after
myocardial infarction or cardiac surgery; and hypertension. The 12 profile levels
are determined by the history and severity of these four circumstances. General
heart disease, for example, is divided into four classes based on the functional
classification of the American Heart Association, with Class I containing patients
with heart disease but with no limitations of physical ability (ordinary physical
activity causes no undue dyspnea, anginal pain, fatigue, or palpitation) and
Class IV containing patients with inability to carry on any physical activity
without discomfort (symptoms of cardiac insufficiency or of the anginal syndrome
may be present, even at rest, and are intensified by activity).
Pulmonary: Although impaired pulmonary function is seldom the cause
of sudden death, it may seriously affect operators of vehicles in the following
ways: (1) sudden severe coughing while driving may result in a crash; (2) cough
syncope may occur while driving; (3) impaired cerebral oxygenation caused by
impaired pulmonary function may result in mental confusion and/or impaired judgment.
In assessing the severity of pulmonary impairment, effort is made to limit the
tests to those found in most medical offices, although occasionally, more sophisticated
studies may be needed (e.g., arterial blood gases, maximal voluntary ventilation,
etc.). The basic function tests (FVC and FEV) are the principal guidelines and
standards currently recommended.
Neurologic: A wide variety of neurologic conditions may affect driving
safety, that includes (but is not limited to) strokes; head injuries; Cerebral
Palsy; Multiple Sclerosis; Parkinson's Disease; progressive conditions such
as muscular atrophies and dystrophies; myasthenia gravis; and other spinal cord
and brain diseases. The common element in all of these is the disturbance of
sensory, motor, or coordinating functions sufficient to effect driving.
Epilepsy and Other Episodic Conditions: Epilepsy includes any recurrent
loss of consciousness or conscious control arising from intermittent changes
in brain function. Because of the similarity of consequences, other disorders
affecting consciousness or control such as syncope, cataplexy, narcolepsy, hypoglycemia,
episodic vertigo interfering with function, etc., have been included in this
section, to be considered in a similar fashion.
Learning, Memory, and Communication: This broad category includes retardation;
learning problems related to general intelligence; impairments relating to the
recovery of head injuries; closed head injuries (resulting in diffuse cognitive
deficits such as impaired judgment, impulsiveness, distractibility, impaired
attention, neglect, slowed reaction time, or impaired cognitive endurance);
Alzheimer's Disease; aphasia, and inadequate language skills.
Psychiatric or Emotional Conditions: Psychiatric history and medications
determine the functional levels under this category. There are a variety of
behavioral conditions, extremes of mood, and impairments in thinking associated
with psychiatric disorders which may correlate with accident proneness or driver
risk. These include: inattentiveness which may accompany even minor disturbances;
impulsivity, explosive anger, and impaired social judgment characteristic of
personality disorders, especially antisocial personality; and suicidality, perceptual
distortions, psychomotor retardation or frank irrationality in addition to the
previously described symptoms which are common features of major psychiatric
illnesses such as schizophrenia, major depressive disorder, bipolar (manic depressive)
disorder, and organic brain syndromes.
Alcohol and Other Drugs: This category includes chronic use of alcohol;
use of mood altering and hallucinogenic drugs (amphetamines, LSD, antihistamines,
barbiturates, benzodiazepines, and anti-psychotics such as phenothiazine, haloperidol,
and sleeping pills of all types); marijuana; and excessive or inappropriate use
of drugs for the purpose of intoxication or stimulation (including prescription,
nonprescription, legal, and illegal drugs). Users of alcohol and other drugs are
well known for their tendency to under-report amounts used, and there is wide
individual variation in the effects of such substances; therefore, the only valid
basis for evaluating a person's probable safety as a driver is careful appraisal
of the person's history including, but not limited to, the past effect on driving.
Visual Acuity: Guidelines for placing drivers in functional ability
categories are based on acuity and visual fields. Correction must be less than
10 diopters to qualify for profile level 1 (20/25 vision in each eye; monocular
visual fields 120 in each eye; binocular visual fields 70 to the right and to
the left in the horizontal meridian). Other eye conditions that require special
consideration, but which have no set standards, include: color vision; dark
adaptation; heterophoria; stereopsis; monocular vision; refractive states; telescopic
lenses; and chronic and recurrent disease.
Musculoskeletal Abnormality or Chronic Medical Debility: Includes chronic
conditions not listed elsewhere, including osteoporosis, HIV, amputations, congenital
abnormalities (unless compensatory devices are used as outlined in the Functional
Motor Ability Category), that according to medical judgment may be of primary
importance in determining limitations on driving.
Functional Motor Ability: Evaluations of this ability consist of an
appraisal of an individual's ability to operate a vehicle with reference to
muscular strength, coordination, range of motion of joints, spinal movement
and stability, amputations or the absence of body parts, and/or other abnormalities
affecting motor skill. The health care professional should indicate in their
best judgment a provisional profile level without and with compensating devices.
This will help the driver examiner who tests the applicant in the vehicle using
compensatory devices, and makes the final determination of the functional motor
ability profile.
Hearing: No hearing requirements have been formulated for drivers of
private vehicles. For Meniere's Disease, see Episodic Disorders.
Recently, Diller et al. (in press) evaluated the medical conditions
program by comparing the crash and citation rates per eligible licensed days
for restricted and unrestricted drivers who had single medical conditions, by
functional ability category (levels 3-5 vs 6-11) to the rates of control drivers
(drivers licensed without a medical condition) matched on age group, gender,
and county of residence. The relative risk ratios are shown in the table presented
on page 36.
Salzberg and Moffat (1998) evaluated the Washington State Department of Licensing's
Special Examination Program. A "special exam" includes an in-depth interview,
and an extended or specialized on-road drive test, typically conducted near
the driver's residence. The requirements of the "special" on-road exam are dependant
of the Licensing Service Representative's (LSRs) assessment of the driver during
the interview. The "special" drive test may be limited to specific roads or
routes (e.g., form home to the doctor's office). Drivers come to the "special
exam" program by being referred to the Department by law enforcement, physicians,
family, or by LSRs who observe an impairment or disability when the driver comes
in for license renewal. These drivers must undergo and pass a drive test (a
"re-exam") and possibly a knowledge test. Drivers who fail the "re-exam" or
those with medical/vision certificates who do not meet Department of Licensing
standards have their license canceled. However, they may request a "special
exam" that more completely assesses their driving ability. The most common outcome
of the "special exam" is to impose driving restrictions, such as time of day
(e.g., 10 a.m. to 3 p.m., daylight only); area (e.g., within an x-mile radius
of residence, within city limits only, no freeway driving); and equipment (e.g.,
corrective lenses, hand controls, outside vehicle mirrors, power steering, power
brakes). In some cases, drivers who retain their licenses must submit periodic
medical or visual reports.
The study included 380 older drivers who were required to undergo a "special
examination" (and passed) in 1994, and 449 control drivers matched on age, gender,
and city of residence. Sixty-nine drivers failed the "special exam" and are
not included in this analysis, because they have no post-exam driving exposure
(97 percent had their licenses canceled and 3 percent voluntarily surrendered
their licenses). Control group drivers averaged 75.6 years of age, and drivers
who passed the "special exam" averaged 75.2 years of age. Documents retrieved
to describe the medical conditions and driving performance of the subjects included
medical certificates, vision certificates, driver license status and restrictions,
and traffic violations and convictions. The most common reasons that drivers
were given "special exams" were because of failing a re-exam (36 percent), a
vision certificate being filed with the Department of Licensing (30 percent),
or a medical certificate being filed (15 percent). Law enforcement accounted
for 4 percent of the referrals, physicians for 6 percent, Licensing Service
Representative for 7 percent, and family/friend/self for 3 percent of the referrals.
The following visual and medical conditions were represented among the "special
exam" group: cataracts, diabetic retinopathy, macular degeneration, diabetes
mellitus, cardiovascular conditions, neurological conditions, psychiatric conditions,
and stroke/cerebral vascular conditions. The primary medical condition for a
subject listed on the Department of Licensing record is the condition that was
associated with a particular subject for this study.
Crash and violation records of drivers who underwent the "special exam" were
compared with that of the control group, for a period of 1.75 years before the
exam, and 3.25 years after the exam (a 5-year period). Since control group drivers
did not undergo a special exam (by definition), an arbitrary date that was the
same as the date for the matched exam group drivers was chosen to measure driving
performance. Crash and violation rates were calculated to describe the number
of incidents per 100 subjects per year, since the pre- and post-observation
periods differed in length. For comparison purposes, in Washington State during
1996 there were 140,215 total collisions and 4,037,534 licensed drivers, yielding
a rate of 3.47 collisions per 100 licensed drivers in a one-year period. Driving
records for the "special exam" (passing) and control groups are shown below.
| Washington State Special
Exam Program Analysis |
| Group |
Pre-Exam Collision
Rate |
Post-Exam Collision
Rate |
Pre-Exam Violation
Rate |
Post-Exam Violation
Rate |
| Control (n=449) |
3.8180 |
1.1650 |
7.5087 |
2.2614 |
| Passed Special-Exam (n=380) |
7.0677 |
3.2389 |
13.3835 |
5.2632 |
Control group drivers (who did not receive exams and consequent restrictions)
showed reductions in their crash and violation rates over the 5-year period.
The authors explain this phenomenon by noting that a normal trend exists among
older drivers that as they age, they tend to reduce their driving, or to stop
altogether. Although the exam group drivers also showed a reduction in crash
and violation rate after passing the exam and receiving restrictions, their
rates were significantly higher than the control group during the post-exam
period. Comparing the post-exam collision rates of the "special exam" drivers
(3.24 per 100 licensed drivers) with collision rates for the entire licensed
population in Washington State over a 1-year period (3.47 per 100 licensed drivers)
shows that drivers who pass special exams and receive driving restrictions are
no larger a threat to the public than the population of drivers across all age
groups. Rates for control- and exam-group drivers by medical condition are presented
on page 37.
A discussion of the results found for drivers with neurological conditions
and stroke/cerebral vascular conditions is provided here, instead of in a separate
sub-section for several reasons. First, the sample sizes are rather small (~20).
Second, the type of neurological condition is not specified (e.g., epilepsy,
cerebral palsy, muscular dystrophy, poliomyelitis, multiple sclerosis, Parkinson's
Disease, myasthenia gravis, tumors of the brain, etc.). Third, there is not
a separate section under epidemiology in this Notebook that deals with
strokes, because, depending on what area of the brain is affected, a stroke
could have minimal, moderate, or severe effects that are either temporary or
permanent. Also, a stroke may affect any of the following capabilities needed
for driving: vision, perception, physical functionality, reaction time, and
cognitive skills needed for decision making and judgment.
What is interesting about the drivers with neurological and stroke/cerebral
vascular conditions in Salzberg and Moffat's study is that their post-exam crash
and violation rates remained among the highest of all exam-group drivers with
medical conditions, and these rates were well above (2.6 to 3.8 times) the post-exam
rates of the control group of older drivers. In addition, drivers with strokes/cerebral
vascular conditions had a post-exam crash rate that was 1.27 times that of the
population of licensed drivers in the State of Washington. Therefore, restricting
the licenses of drivers with these medical conditions was not sufficient to
reduce their crash risk to the level posed by drivers across all age groups,
nor did these drivers appear to reduce their exposure to the level of their
age peers in the control group, who showed a reduction in crash risk over the
5-year period without any intervention. It is possible that drivers with these
medical conditions are unaware of the risks they pose while driving, and demonstrate
poor judgment and impulse control leading to adverse driving events. The number
of incidents per year per 100 drivers in each group is presented below.
| Washington State Special
Exam Program Analysis |
| Group |
Pre-Exam ollision
Rate |
Post-Exam Collision
Rate |
Pre-Exam Violation
Rate |
Post-Exam Violation
Rate |
| Control (n=449) |
3.8180 |
1.1650 |
7.5087 |
2.2614 |
| Special Exam Neurological Conditions
(n=20) |
8.5714 |
3.0769 |
17.1429 |
7.6923 |
| Special Exam Stroke/Cerebral Vascular
Conditions (n=21) |
5.4422 |
4.3956 |
8.1633 |
7.3260 |
Note: For comparison purposes, in Washington State
during 1996, there were 140,215 total collisions and 4,037,543 licensed drivers,
yielding a rate of 3.47 collisions per 100 licensed drivers during this one-year
period.
Conclusions/Preliminary Recommendations:
Study findings from Diller et al. are currently in press; it is expected that
a report will be submitted to NHTSA later in 1999. Based on the preliminary
findings cited in this Notebook, the Utah report is expected to present
evidence to indicate which medical conditions are associated with a higher rate
of at-fault crashes and citations for licensed drivers who have full privileges
than for the general population of drivers. With this information, health care
professionals will be better equipped to counsel their patients who have medical
conditions about the effects of their conditions on driving, and will have the
knowledge to support suggestions about potential restrictions on when and where
they should drive to remain as safe as possible. Health care professionals should
also emphasize to their patients the importance of informing the DMV of medical
conditions that effect driving performance, for their own safety.
The following caveats regarding epidemiology data collection methods also apply.
First, eligible driving days was the exposure measure; actual or estimated miles
driven data were not obtained in this analysis. Next, the results are dependent
upon the drivers who reported their medical conditions during the study period
and not on all drivers who have medical conditions. The proportion of drivers
with medical conditions who report them to the Utah Driver License Division
is unknown. Also, the extent to which health care professionals assign functional
ability levels according to the Medical Conditions program specifications is
unknown. For example, a driver who has been assigned a functional ability rating
that requires a restriction may shop around for a professional who will assign
a more favorable rating, thus allowing him or her to drive unrestricted. Finally,
the compliance rates for restricted drivers were not obtained at the time of
crash or citation, nor did the analysis take into account the number of drivers
who are repeat offenders.
Notwithstanding these methodological limitations, this pending publication
represents the most comprehensive analysis to date of the relationship between
type and severity of medical conditions and associated risks of adverse driving
events.
Based on the Salzberg and Moffat (1998) findings, it appears
that the process used by Washington State to identify older drivers who are
at an increased crash risk (e.g., referral by physicians, law enforcement, family/friends,
and licensing personnel) does in fact detect individuals who have significantly
poorer driving records than their age-matched peers. Also, the requirement to
undergo a re-exam in a familiar area and the consequent tailoring of restrictions
serves to (generally) lower their crash risk to a level that does not pose any
more of a safety hazard to the public than that of the general driving population.
But, the program has differential effects for differing medical conditions.
Positive outcomes are shown for drivers with diabetic retinopathy, cataracts,
cardiovascular conditions and diabetes mellitus. On the other hand, licensing
restrictions did not lower the crash risk of drivers with macular degeneration;
and, for drivers with neurological, psychiatric, or stroke/cerebral vascular
conditions, the obtained reductions in crash risk still left these drivers at
a 3- to 4-fold greater risk level when compared to the control group drivers.
Finally, drivers with psychiatric and stroke/cerebral vascular conditions continued
to have a crash risk higher than that of the overall population of licensed
drivers.
Two points should be considered in generalizing the results of the Washington
State study to other populations. First, there are no actual measures of driving
exposure. Second, comparisons are made between drivers with certain medical
conditions (a subset of the special exam group) and the control group as
a whole. Since the overall age distribution for all study subjects was
12.5 percent under age 60, 40.4 percent between ages 60 and 80, and 47.3 percent
over age 80, and since the incidence of many medical conditions increases as
age increases, it is possible that the control group of drivers could be younger
than any given subset of drivers who were selected for the analysis because
they presented a particular medical condition.
References:
• Diller, Cook, Leonard, Reading, Dean, and Vernon
(in press)
• Foley, Wallace, and Eberhard (1995)
• Hemmelgarn, Suissa, Huang, Boivin, and Pinard (1997)
• Hu, Trumble, Foley, Eberhard, and Wallace (1998)
• Koepsell, Wolf, McCloskey et al. (1994)
• Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994)
• Owsley, Allman, Ball, and Smoot (1998)
• Owsley, Ball, McGwin, Sloane, Roenker, White, and Overley
(1998)
• Owsley, McGwin, and Ball (1998)
• Owsley, Stalvey, Wells, and Sloane (1999)
• Salzberg and Moffat (1998)
• Sims, Owsley, Allman, Ball and Smoot (1998)
• Stewart, Moore, Marks, May, and Hale (1993)
Preliminary Analysis of Drivers with Medical Conditions
Compared to Control Group Drivers, Presented as Relative Risk (per 10,000 eligible
licensed days) for Specified Driving Events (Citation, All Crashes, At-Fault
Crashes).
Excerpted from: Diller, E., Cook, L., Leonard,
D., Reading, J., Dean, J.M., and Vernon, D (in press). Evaluating
Drivers with Medical Conditions in Utah, 1992-1996. NHTSA Tech. Report,
Contract DTNH22-96-H-59017. Preliminary Report, Utah CODES Project.
| Functional Ability Category |
License Restriction Status and Number of Drivers
in Each Group: Not Restricted (FA Levels 3,4,5) vs Restricted (FA Levels
6-11) |
Citations |
All Crashes |
At-Fault Crashes |
| Diabetes & Other Metabolic Conditions |
Not Restricted (n=10,069) |
1.04 |
1.41* |
1.58* |
| Restricted (n=358) |
1.40 |
1.43 |
1.79 |
| Cardiovascular |
Not Restricted (n=18,990) |
0.77** |
1.14* |
1.15* |
| Restricted (n=160) |
1.57 |
1.61 |
1.72 |
| Pulmonary |
Not Restricted (n=2,615) |
0.88** |
1.25* |
1.35* |
| Restricted (n=244) |
0.50 |
0.93 |
1.63 |
| Neurologic |
Not Restricted (n=887) |
0.93 |
1.67* |
2.27* |
| Restricted (n=194) |
0.77 |
1.40 |
1.51 |
| Epilepsy & Other Episodic Conditions |
Not Restricted (n=2,620) |
1.03 |
1.81* |
2.11* |
| Restricted (n=775) |
1.05 |
1.55* |
2.47* |
| Learning, Memory, & Communication |
Not Restricted (n=107) |
1.31 |
2.49* |
3.57* |
| Restricted (n=6) |
11.76* |
zero rate |
zero rate |
| Psychiatric or Emotional Conditions |
Not Restricted (n=6,763) |
1.24* |
1.65* |
1.96* |
| Restricted (n=305) |
0.83 |
1.97* |
2.97* |
| Alcohol & Other Drugs |
Not Restricted (n=143) |
2.37* |
1.88* |
2.33* |
| Restricted (n=24) |
5.83* |
4.21* |
5.75* |
| Visual Acuity |
Not Restricted (n=10,363) |
1.37* |
1.49* |
1.70* |
| Restricted (n=1,535) |
1.37* |
1.39* |
1.72* |
| Musculoskeletal Abnormality or Chronic Medical
Debility |
Not Restricted (n=370) |
1.23 |
1.66* |
1.92* |
| Restricted (n=32) |
zero rate |
4.25 |
10.63* |
| Functional Motor Impairment |
Not Restricted (n=214) |
1.42* |
1.18 |
1.87* |
| Restricted (n=13) |
zero rate |
zero rate |
zero rate |
* Differences in rates between medical conditions and control
groups are statistically significant, with higher rates for medical conditions
group.
* *Differences in rates between medical conditions and control
groups are statistically significant, with higher rates for control group.
zero rate: there were no adverse driving events in one of the
driver groups, so a rate could not be calculated.
Driving Records (number of incidents per 100 drivers
per year) for Control Group Drivers and Drivers with Medical Conditions Who
Were Required to Take a Special Driving Exam.
(Excerpted from: Salzberg and
Moffat, 1998: Washington State Department of Licensing Special Exam Program
- An Evaluation.)
| Group |
Pre-Exam Collision
Rate |
Post-Exam Collision
Rate |
Pre-Exam Violation
Rate |
Post-Exam Violation
Rate |
| Control (n=449) |
3.8180 |
1.1650 |
7.5087 |
2.2614 |
| All Conditions: Failed Exam (n=69) |
12.4224 |
.0000
(license canceled)
|
15.7350 |
.0000
(license canceled)
|
| All Conditions: Passed Exam (n=380) |
7.0677 |
3.2389 |
13.3835 |
5.2632 |
| Cataracts (passed exam: n=45) |
5.0794 |
2.0513 |
15.2381 |
2.0513 |
| Diabetic Retinopathy (passed exam:
n=14) |
12.2449 |
.0000 |
8.1633 |
2.1978 |
| Macular Degeneration (passed exam:
n=71) |
3.2193 |
3.4670 |
6.4386 |
5.2004 |
| Diabetes Mellitus (passed exam:
n=27) |
6.3492 |
1.1396 |
8.4656 |
2.2792 |
| Cardiovascular Conditions (passed
exam: n=47) |
7.2948 |
1.9640 |
20.6687 |
2.6187 |
| Neurological Conditions (passed
exam: 20) |
8.5714 |
3.0769 |
17.1429 |
7.6923 |
| Psychiatric Conditions (passed
exam: n=46) |
12.4224 |
4.6823 |
23.6025 |
8.0268 |
| Stroke/Cerebral Vascular Conditions (passed
exam: n=21) |
5.4422 |
4.3956 |
8.1633 |
7.3260 |
Note: For comparison purposes, in Washington State during 1996,
there were 140,215 total collisions and 4,037,543 licensed drivers, yielding
a rate of 3.47 collisions per 100 licensed drivers during this one-year period.
Risk Ratios for Identified Medical Conditions [ref.
Notebook sections IA1(a) through IA1(l)]
| Condition |
Study |
Results |
| Cataracts |
Owsley, Stalvey, Wells, and Sloane (1999) |
Significant association between cataract and crash involvement:
• Adjusted for driving exposure...RR=2.48, 95% CI=1.0-6.14*
•
Adjusted for impaired health...RR=2.49, 95% CI=1.0-6.27
|
| Diabetic Retinopathy/ Diabetes |
Owsley, Ball, McGwin, Sloane, Roenker, White, and Overley
(1998)
Koepsell, Wolf, McCloskey et al. (1994)
|
Crash risk 5 times greater with diagnosis of diabetic
retinopathy.... 95% CI = 1.13-21.8
Injury-crash risk odds ratios (OR) for older drivers
= 2.6 for diabetes mellitus (any); 5.8 for diabetics treated with insulin;
3.1 for diabetics treated with oral hypoglycemic agents; 8.0 for diabetes
and coronary heart disease together.
|
| Glaucoma |
Owsley, Ball, McGwin, Sloane, Roenker, White, and Overley
(1998) |
Significant association between glaucoma and crash risk....RR=5.20,
95% CI = 1.19-22.72
• Males- RR=9.81 • Females-RR=5.14
|
| Owsley, McGwin, and Ball (1998) |
Crash risk cases 3.6 times more likely to report glaucoma
than controls |
| Hu, Trumble, Foley, Eberhard, and Wallace (1998) |
Association between highway crashes and glaucoma significant
only for older males (OR=1.7) |
| Foot Abnormalities |
Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994) |
Association between 3+ foot abnormalities and adverse
driving events RR=2.0, 95% CI = 1.0-3.8 |
| Falls |
Sims, Owsley, Allman, Ball and Smoot (1998) |
Significant association between crash involvement and
having fallen in the past two years: OR=2.6, 95% CI=1.1-6.1* |
| Persistent Back Pain |
Hu, Trumble, Foley, Eberhard, and Wallace (1998)
Foley, Wallace, and Eberhard (1995).
|
Association between crash risk and persistent back pain
significant for combined gender (6,553 female person-years and 5,414 male
person-years); RR=1.25 for 3,000; 6,000, and 12,000 miles driven annually.
RR = 1.54 for 9,000 and 18,000 annual miles.
Significant association between episodes of back pain
and increased risk for crashes in a sample of 1,791 drivers age 68+ (RR=1.4,
p<.05)
|
| Cardiac Conditions (Irreg. Heartbeat) |
Stewart, Moore, Marks, May and Hale (1993) |
Significant correlation between irregular heartbeat and
crashes: OR=1.83, 95% CI=1.25-2.68 |
| Feet/Legs Cold on Exposure to Cold |
Stewart, Moore, Marks, May and Hale (1993) |
Significant correlation between feet or legs cold on exposure
to cold and traffic crashes: OR = 1.82, 95% CI = 1.17-2.82 |
| Bursitis |
Stewart, Moore, Marks, May and Hale (1993) |
Significant correlation between bursitis and traffic crashes:
OR = 2.18, 95% CI = 1.41-3.38 |
| Renal Disease (Protein in urine) |
Stewart, Moore, Marks, May and Hale (1993) |
Significant correlation between protein in urine and traffic
crashes: OR = 1.84, 95% CI = 1.25-2.72 |
| Use of Antidepressant/
Antianxiety drugs
|
Hu, Trumble, Foley, Eberhard, and Wallace (1998); Hemmelgarn,
Suissa, Huang, Boivin, Pinard (1997) |
Significant association between antidepressant use and
crash risk (males only). RR= 1.98
Significant association between half-life benzodiazepine
use (within 1st week of use) and crash risk (RR=1.45, CI=1.04-2.03) .
RR for continuous use up to 1 yr significant (RR=1.26,
CI=1.09-1.45). In contrast, no increased risk within first week of short-half-life
benzodiazepines (RR=1.04, CI = 0.81-1.34) or with continued use (RR=0.91,
CI=0.82-1.01)
|
| *RR=Relative Risk; OR= Odds Ratio; CI=Confidence
Interval |
I.A. IDENTIFY OLDER PEOPLE WHO ARE
AT HIGH RISK OF CRASHES
|
I.A.2. Driving and/or Functional Assessment
Outcomes
|
|
(a) Physical Performance Deficits
|
| (b) Sensory (Vision) Deficits |
| (c) Deficits in Visual Attention/Speed of Processing |
| (d) Perceptual Skills |
| (e) Memory/Cognition Deficits |
| (f) Navigation Errors on Road Test |
| (g) Discriminating Maneuver Errors on Road Test |
| (h) Decision-Making and Response Selection in Driving Simulators |
1A2(a). Physical Performance Deficits
Summary:
Lower Limb Mobility: In a sample of 283 community-dwelling individuals
age 72 to 92 (mean age=77.8), Marottoli, Cooney, Wagner, Doucette, and Tinetti
(1994) found that the timed performance test most strongly associated with adverse
events (traffic crash, violation, stopped by police) in the year following testing
was the rapid-pace walk (> 7 seconds versus < 7 seconds [relative
risk=2.0, 95% confidence interval=1.0-3.8]). Nine percent of the faster walkers
had adverse driving events, compared to 17 percent of the slow walkers. This
difference was significant at the p<.05 level. In the activity domain, walking
less than 1 block per day was associated with adverse events (relative risk
[RR]=1.9, 95% confidence interval [CI]=1.1-3.5). Twenty-one percent of the subjects
who walked less than 1 block per day had adverse driving events, compared to
11 percent of the subjects who walked 1 block or more each day. This difference
was significant at the p< .05 level. Foot tap time showed a trend toward
association with adverse events in the study, and is face valid as a measure
of ability to move leg/foot from gas to brake pedal.
In the recently completed pre-pilot study conducted in Salisbury, Maryland
for the NHTSA "Model Driver Screening and Evaluation Program" project, the present
Notebook authors found that subjects who took longer than 7 seconds
to complete the rapid-pace walk (walk 10 ft, turn around, walk 10 ft back) were
1.25 times more likely to be involved in a crash compared to subjects who could
complete the walk in 7 seconds or less. The mean walk time for the crash-free
drivers was 6.78 seconds, and the mean walk time for the crash-involved drivers
was 7.12 seconds. Also, subjects whose alternating foot-tap time was 10 seconds
or more were 2.61 times more likely to be in a crash, compared to subjects whose
foot tap times were less than 10 seconds. The mean foot-tap time for the crash-free
subjects was 6.6 seconds, and the mean foot-tap time for the crash-involved
subjects was 7.1 seconds. This difference was significant at the 0.04 level.
Subjects ranged in age from 68 to 89 (mean age=75.7); 131 of the 363 subjects
were involved in at least 1 crash in the previous 6-year period (1991-1997).
Upper Limb Mobility: In a panel data analysis of remaining eligible drivers
in 1993 (507 female drivers and 375 male drivers) who participated in the Iowa
65+ Rural Health Study from 1981-1993, older females who had difficulty extending
their arms above their shoulders had an increased probability of being involved
in a crash (Hu, Trumble, Foley, Eberhard, and Wallace, 1998). In other words,
an older female with difficulty extending her arms above shoulder height is
more than twice as likely to be crash involved than another female with no difficulty,
given that both drive 6,000 mi/yr.
Sims, Owsley, Allman, Ball, and Smoot (1998) conducted a study of 174 drivers
ages 55-90 (mean age 71.1). Case drivers had at least 1 state-recorded at-fault
crash in the 6 years preceding the assessment (n=99) and controls had no state-recorded
at-fault crashes in the prior 6 years (n=75). Results at the univariate level
indicated that crash-involvement was significantly associated with difficulty
reaching out (p=.042).
In the pre-pilot study conducted in Salisbury, Maryland for the NHTSA "Model
Driver Screening and Evaluation Program" project, the present Notebook
authors found that subjects who could not raise their arms above shoulder height
were 1.91 times more likely to be involved in a crash, compared to subjects
who could perform this action.
Head/Neck Range of Motion: The behavior of drivers at simulated T-intersections
was investigated to determine the relationships between the range of movement
of the head and neck, the visual field, and the decision time for a simulated
traffic maneuver (Hunter-Zaworski, 1990). Impairment was defined by a combined
static range of movement of the head/neck and visual field of less than 285
degrees. Younger (ages 30-50) impaired drivers were able to compensate for their
impairment (their decision times were not affected by their reduced head/neck
flexibility), but older impaired drivers (ages 60-80) were not.
In a study of 125 community-living cohort of older persons who were active
drivers (ages 77+), limited neck range of motion (RR = 6.1, CI = 1.7-22.0) was
one of the factors independently associated with (self-reported) adverse driving
events (crash, moving violation, being stopped by police during previous 5.75
years) in multivariate analyses adjusting for driving frequency (Marottoli,
Richardson, Stowe, Miller, Brass, Cooney, and Tinetti, 1998). Range of motion
of the neck was measured by having the subject stand against a wall, and turn
his or her head to identify a number placed behind either shoulder.
In the pre-pilot study conducted in Salisbury, Maryland for the NHTSA "Model
Driver Screening and Evaluation Program" project, the present Notebook
authors found that subjects who could not turn their heads (including upper
torso) to view the time on a clock placed directly behind them were 1.38 times
more likely to be involved in a crash compared to subjects who could perform
this action.
Conclusions/Preliminary Recommendations:
Older drivers with reductions in physical flexibility and range of motion of arms,
legs, and neck are at increased crash risk. Physicians and other health care providers
should include physical performance measures in their assessments of geriatric
patients, ask questions to determine driving habits and problems, and counsel
older drivers about the consequences of limited mobility/flexibility on driving
performance. In addition, they should recommend exercises to help improve strength
and flexibility, make suggestions about where and when patients should drive,
and refer patients to occupational/physical therapists for remediation or fitting
with adaptive equipment, when appropriate. In addition, increasing the public's
awareness about the effects of diminishing physical capabilities on driving performance
should enable drivers to make their own responsible decisions.
References:
• Hu, Trumble, Foley, Eberhard, and Wallace (1998)
• Hunter-Zaworski (1990)
• Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994)
• Marottoli, Richardson, Stowe, Miller, Brass, Cooney, and Tinetti (1998)
• Sims, Owsley, Allman, Ball, and Smoot (1998)
IA2(b). Sensory (Vision) Deficits
Summary:
Static Acuity. With respect to driving, static visual acuity has consistently
been found to have weak relationships to traffic crashes and convictions. For
example, in a large sample study investigating the relationship between visual
function and crash rate, Burg (1967) reported that the three static visual tests
evaluated in their protocol had the second strongest relationship with crashes,
with dynamic acuity having the strongest relationship. These three correlations,
ranging from -0.053 to -0.129, were small but significant given the large sample
size (n > 17,000). In Marottoli, Richardson, Stowe, Miller, Brass, Cooney,
and Tinetti's (1998) study of 125 community-living older persons who were active
drivers (ages 77+), corrected near visual acuity worse than 20/40 (Risk Ratio
= 11.9; 95% Confidence Interval 1.3 - 109.1) was one of the factors independently
associated with (self-reported) adverse driving events (crash, moving violation,
being stopped by police during previous 5.75 years) in multivariate analyses
adjusting for driving frequency.
Meta-analysis across studies investigating acuity and crash risk confirms that
there is a weak, but consistent relationship between these variables (Staplin,
Ball, Park, Decina, Lococo, Gish, and Kotwal, 1997). While the overall comparison
of effect sizes is significant (2=19.79, p=0.00054) these
differences are largely due to the level of significance that varies with sample
size. There are several reasons why one might not expect to find a strong relationship
between acuity and crash rate. Good acuity is probably beneficial to driving
in instances where the vehicle is stopped or moving at a slow rate, such as
at an intersection or in a parking lot. It is of less benefit while driving
at normal speeds. Furthermore, unlike real visual scenes that vary in complexity,
contrast, and illumination, the stimuli used to measure static visual acuity
are small, of high contrast, and of low complexity. Therefore, many have argued
that this type of measure bears little resemblance to the visual requirements
of driving, and should not be expected to be strongly tied to crash involvement.
Studies that have correlated the on-road driving performance of older subjects
and static acuity are described below.
In a study of 82 drivers (age 60-91) referred to CA DMV, correlations between
static acuity score (20/20, 20/80, and 20/200) measured with MultiCAD
(square wave gratings with vertical bars were used), and weighted errors on
driving test were not significant. However, correlations between static acuity
response time at each level of acuity and weighted error scores on driving exam
were as follows: 20/40 time: r=.3395 (p<.004); 20/80 time: r=.4230 (p<.000);
20/200 time: r=.1970 (p<.090) (Janke and Eberhard, 1998; Janke and Hersch,
1997; Staplin, Gish, Decina, Lococo, and McKnight, 1998).
In McKnight and McKnight's (1998) study of 360 drivers age 62+, correlations
between static visual acuity (measured with Automated Psychophysical Test [APT])
and observed driving performance were relatively low but significant; correlations
between on-the-road performance and time to respond to the acuity stimuli (r=.30)
were higher than acuity errors (r=.18).
Salzberg and Moffat (1998) evaluated the driving records of 380 older drivers
who were referred to the Washington State Special Examination Program (and passed),
and 449 control group drivers. This program is described in more detail in Section
IA1(m) of the Notebook. Static acuity readings were available for 357
of these drivers. A "special exam" includes an in-depth interview, and an extended
or specialized on-road drive test, typically conducted near the driver's residence.
The most common outcome of the "special exam" is to impose driving restrictions
(time of day, area, equipment).
Crash and violation records of special exam group drivers were compared with
that of the control group, for a period of 1.75 years before the exam, and 3.25
years after the exam (a 5-year period). Crash and violation rates were calculated
to describe the number of incidents per 100 subjects per year, since the pre-
and post-observation periods differed in length. The crash and violation rates
for the exam group drivers by acuity score (20/20+, 20/40+, 20/100+, and 20/200+)
who passed the "special exam" and the (entire) control group are presented below,
for the pre-exam and post-exam period. For comparison purposes, in Washington
State during 1996 there were 140,215 total collisions and 4,037,534 licensed
drivers, yielding a rate of 3.47 collisions per 100 licensed drivers in a one-year
period. It is important to note that approximately 60 percent of exam group
drivers had other medical conditions; only 123 of the 380 drivers (32%) were
referred to the program because a vision certificate was filed with the Department
of Licensing. Other reasons for referral included: law enforcement noting signs
of unsafe driving (3%); Licensing Service Representative noticing diminished
capabilities (6%); medical certificate filed with Department of Licensing (15%);
physician referral (5%); and because a driver failed the initial re-exam test
(35%). Therefore visual acuity is confounded with other medical conditions,
and no direct relationship with crashes or violations can be drawn.
| Group |
Pre-Exam Collision Rate |
Post-Exam Collision Rate |
Pre-Exam Violation Rate |
Post-Exam Violation Rate |
Control
(n=449) |
3.8180 |
1.1650 |
7.5087 |
2.2614 |
Special Exam
No vision info. available (n=23) |
4.9689 |
6.6890 |
22.3602 |
4.0134 |
|
Special Exam
20/20+ (n=44)
|
10.3896 |
1.3986 |
24.6753 |
3.4965 |
Special Exam
20/40+ (n=219) |
7.8278 |
2.5290 |
12.0026 |
4.3555 |
Special Exam
20/100+ (n=45) |
7.6190 |
2.0513 |
16.5079 |
6.1538 |
Special Exam
20/200+ (n=49) |
1.1662 |
7.5353 |
2.3324 |
10.6750 |
What is interesting to note about the pre-exam crash rates is that the drivers
with the best acuity (20/20) had the highest rates, and that drivers with the
poorest vision (20/200) had the lowest crash rates. Obviously, drivers with
20/20 vision were not part of the special program because of poor vision. It
is instructive to look just at drivers with 20/40-20/100 acuity, whose crash
rates are about double that of the control group during the pre-exam period.
The requirement to undergo a special exam and the consequent licensing restrictions
had the effect (at least on the surface) of lowering their crash rates to a
level that does not pose any more risk than the population of licensed drivers
in the State of Washington. But the reduction still puts these drivers at twice
the risk of control group (older) drivers. The authors explain the decline in
crash risk for the control group (who did not have any intervention) as decreased
driving exposure through increased self-restriction over the 5-year study period.
The significant increase in the 20/200 group from the pre-exam to the post-exam
period could be the result of increased exposure by these drivers who possibly
misinterpreted the decision to allow them to retain driving privileges as positive
feedback about their ability to drive safely.
Dynamic Acuity. Dynamic visual acuity (DVA), like static acuity, also
declines with age (Burg, 1967; 1968; 1971), with some suggestion that the age-related
declines in DVA are larger than for static visual acuity (Burg, 1966). Dynamic
acuity reflects the ability to resolve the details of a moving target, and therefore
it has been proposed that this measure of acuity should be more relevant to
driving. Some activities that appear to rely on dynamic acuity are reading street
signs while in motion, locating road boundaries when negotiating a turn, and
making lateral lane changes. In these situations, greater speeds are associated
with poorer DVA. The earlier studies on driving and the elderly that have assessed
both static and dynamic acuity have indeed found that DVA is more strongly associated
with crash risk than static acuity. However, the statistically significant correlations
between dynamic visual acuity and crash rate have also been consistently weak
(Staplin et al, 1998). For example, the correlation between DVA and crash rate
for the older drivers, as reported by Hills and Burg (1977), was too low (r=0.054)
to be of any practical significance for identifying at-risk drivers. As stated
earlier, dynamic visual acuity has been found to be weakly associated with crash
involvement in several correlational studies (Burg, 1968; Shinar, McDowell,
and Rockwell, 1977; Laux and Brelsford, 1990). In a study of professional drivers
over age 50, the top 10 percent with respect to dynamic acuity were found to
have lower than average crash rates. The bottom 10 percent with respect to dynamic
acuity were found to have higher than average crash rates (Henderson and Burg,
1974). In other studies, Shinar, Mayer and Treat (1975) noted that drivers found
recently to be at fault in a crash had poorer dynamic visual acuity than a group
of persons who had not been in a crash for 2 years. As with static acuity, however,
the strength of the relationships is generally weak, and meta-analysis confirms
the consistency of these findings that differ primarily due to sample size discrepancies
(Staplin et al., 1998). Studies that have correlated the on-road driving performance
of older subjects and dynamic acuity are described below.
In a study of 82 drivers (age 60-91) referred to CA DMV, correlations between
dynamic acuity score (20/20, 20/80, and 20/200) measured with MultiCAD (square
wave gratings with vertical bars were used, with a rate of movement across the
screen of 12 degrees per second) and weighted errors on driving test were not
significant. However, correlations between dynamic acuity response time at each
level of acuity and weighted error scores on driving exam were as follows: 20/40
time: r=.3092 (p<.010); 20/80 time: r=.3256 (p<.005); 20/200 time: r=.3297
(p<.004). (See Janke and Eberhard; Staplin, Gish, Decina, Lococo, and McKnight,
1998).
In a study of 360 drivers age 62 and older, correlations between dynamic visual
acuity (measured with APT) and observed driving performance were relatively low
but significant; correlation between on-the-road performance and time to respond
to the acuity stimuli was r=.24; correlation between on-road performance and acuity
errors was r=.21 (McKnight and McKnight, 1998).
Static Contrast Sensitivity. Contrast sensitivity tests measure both the
response to sharply-defined, black-on-white targets and those with grayer, less-distinct
edges. Recent studies that have included contrast sensitivity as a predictor of
driving crashes have shown that, while it is a slightly better predictor than
acuity, the strength of the relationship is still relatively weak (r<0.25)
(Ball and Owsley, 1991; Owsley et al., 1991; Ball et al., 1993). More recently,
Hennessy (1995) studied 3,669 randomly-selected Class C license renewal applicants
who were licensed in California for at least 12 years. Four driver age groups
were studied: 26-39, 40-51, 52-69, and 70+. The 48-letter test designed by Pelli,
Robson, and Wilkins, 1988, of contrast sensitivity at one spatial frequency was
one of the independent measures examined. In this test, the contrast between letters
and background decreases as one moves down and toward the right of wall-mounted
chart, viewed at distance of 2 meters under normal room illumination. The letters
from left to right and from top to bottom progressively fade out as if they must
be read in thicker and thicker fog. Letters (in groups of 3) range from 90 percent
contrast (upper left) to 0.5 percent contrast (lower right). Testing requires
no more than 3 minutes. The dependent measure was the crash frequency during the
previous 3-year period, extracted from the DMV database. Results showed that for
all age groups combined, the contrast sensitivity test score was not significantly
associated with total prior 3-year crash involvement when considered in isolation.
There was a very small percentage of drivers age 70+ with good low-contrast acuity.
Using a pass-fail criterion of 36 or more correctly identified letters as pass
and less than 36 letters fail, Pelli-Robson specificity was 53 percent and sensitivity
was 29 percent in predicting citations for age 70+ drivers; accuracy of predicting
citation occurrence was 6.5 percent. For subjects ages 52-69, specificity was
65 percent, sensitivity was 19 percent, and positive prediction was 7 percent.
Studies that have correlated older drivers on-road performance with static contrast
sensitivity are described below.
In a study of 82 drivers (ages 60-91) referred to CA DMV, static contrast sensitivity
response time for the high contrast 20/80 target measured with MultiCAD
was significantly correlated with weighted error score on the driving test (r
= .3884, p< .001). (See Janke and Eberhard, 1998; Janke and Hersch, 1997; Staplin,
Gish, Decina, Lococo, and McKnight, 1998).
In Janke and Eberhard's (1998) study of 102 "referred" subjects aged 60-91 (34
of which were identified as probably being cognitively impaired to some degree)
and 33 paid "volunteers" ages 56-85, the correlation between Pelli-Robson errors
and weighted error score on a road test was significant (r=.4009, p<.0001)
for combined referrals and volunteers (n=135). For the referral group only (n=102),
the correlation between Pelli-Robson errors and weighted error score on the road
test was also significant (r= .2069, p<.044).
In Brown, Greaney, Mitchel, and Lee's (1993) study of 1,475 ITT Hartford Insurance
Co. policyholders (age 50-80+) divided into two groups based on the presence or
absence of recent at-fault crashes, the Pelli-Robson Letter Sensitivity Chart
consistently yielded the highest correlation to crashes in the sample during 1989-1991
(r=-0.11, p < 0.05).
In a study of 12,400 drivers ages 16 to 75+ in Pennsylvania, who came to Photo
ID centers for license renewal, failure on the combined criteria that incorporates
the current PennDOT standard (binocular acuity of 20/40 and horizontal visual
field of 140 degrees) and a broadly defined contrast sensitivity criterion
(scores below normal for 1 or more of the 3 spatial frequencies tested using Vistech
contrast sensitivity gratings via an Optec 1000 vision tester) produced the strongest
relationship linking poor vision and high crash involvement, especially for 66-75
and 76+ driver age groups (Decina and Staplin, 1993). Neither visual acuity nor
horizontal field measures in isolation were significantly related to crash involvement.
The study authors recommended periodic screening using the combined criterion,
for drivers over age 55.
In McKnight and McKnight's (1998) study of 360 drivers age 62 and older, correlations
between low contrast acuity (measured with APT) and observed driving performance
were low but significant; correlations between on-the-road performance and time
to respond to the acuity stimuli (r=.23) were higher than contrast sensitivity
errors (r=.18).
Dynamic Contrast Sensitivity. In a study of 82 drivers (ages 60-91) who
were referred to CA DMV, the correlation between dynamic contrast sensitivity
response time for the high contrast 20/80 target (using MultiCAD) and weighted
errors on the road test was significant (r=.2466, p<.049). The stimuli in this
study consisted of square wave gratings with vertical bars, with a rate of movement
across the screen of 12 degrees per second (see Janke and Eberhard, 1998; Janke
and Hersch, 1997; Staplin, Gish, Decina, Lococo, and McKnight, 1998).
Conclusions/Preliminary Recommendations:
Contrast sensitivity is a visual capability, where deficits have been shown to
be related to traffic crashes and poor driving performance in older drivers. Correlations
between driving performance and contrast sensitivity response time (for correct
responses) as well as percent correct responses have been found to be significant.
Contrast sensitivity test slides are available for DMV-model vision screener devices,
and would be easily implementable in a DMV vision screening protocol. Other presentation
methods include wall charts and computer displays of test stimuli.
For acuity, it appears that the time to respond is more strongly related to driving
performance than other dependent measures, such as percent correct. This result
should be interpreted with caution, however, because as usual, the range of responses
on this dependent measure (i.e., correctness) was restricted, and there was potential
for substantial "noise" in the data from other sources of variance. Time to respond
would be a more difficult measure to implement in a DMV setting unless stimuli
were presented by computer.
References:
• Ball and Owsley (1991)
• Ball, Owsley, Sloane, Roenker, and Bruni (1993)
• Brown, Greaney, Mitchel, and Lee (1993)
• Burg (1966, 1967, 1968, 1971)
• Decina and Staplin (1993)
• Henderson and Burg (1974)
• Hennessy (1995)
• Hills and Burg (1977)
• Janke and Eberhard (1998)
• Janke and Hersch (1997)
• Laux and Brelsford (1990)
• Marottoli, Richardson, Stowe, Miller, Brass, Cooney, and Tinetti (1998)
• McKnight and McKnight (1998)
• Owsley, Ball, Sloane, Roenker and Bruni (1991)
• Shinar, Mayer and Treat (1975)
• Shinar, McDowell, and Rockwell (1977)
• Staplin, Ball, Park, Decina, Lococo, Gish, and Kotwal (1997)
• Staplin, Gish, Decina, Lococo, and McKnight (1998)
IA2(c). Deficits in Visual Attention/Speed of Processing
Summary:
A current and potentially most-promising area of inquiry relating crash risk to
functional impairment is the study of visual attention deficits and underlying
divided attention and speed-of-processing functions. Prominent among studies in
this area are those addressing measures of information processing efficiency such
as "useful field of view" and "channel capacity;" research summaries are presented
below.
A prospective study was conducted with 294 older drivers (ages 56-90) to identify
measures of visual processing associated with crash involvement by older drivers
(Owsley, Ball, McGwin, Sloane, Roenker, White, and Overley, 1998). This sample
had been previously drawn for a case-control study by Ball et al. (1993) from
the population of all licensed drivers in Jefferson County, Alabama age 55 and
older. The subjects represent 3 crash categories (0 crashes, 1-3 crashes, and
4+ crashes during the previous 5-year period) and 7 age categories (55-59, 60-64,
65-69, 70-74, 75-79, 80-84, and 85+ years of age). Of the 302 subjects drawn for
sample, 6 were excluded because they had ceased driving, and 2 did not complete
the protocol. The study focused on the prospective 3-year follow-up of the 294
drivers who were assessed in 1990 to determine what visual characteristics were
associated with future crash involvement. Subjects received the following sensory
tests in 1990: Letter Acuity - ETDRS chart; Contrast Sensitivity - Pelli-Robson
chart; Stereoacuity - TNO Test; Disability Glare - MCT-8000 (VisTech); Visual
Field Sensitivity -Humphrey Field Analyzer 120-point program for central 60 degree
radius field; and visual attention and visual processing speed - Useful Field
of View. Impaired useful field of view (UFOV) was the only visual processing
variable associated with increased crash risk. A significant, independent association
with crash risk in 3-year follow-up was found for UFOV reduction of >
40 percent: RR=2.3; 95% CI=1.27-4.29. Of UFOV component scores, speed of processing
(subtest 1) and selective attention (subtest 3) were NOT associated with crash
occurrence. Impairment in divided attention (subtest 2) was significantly associated
with a 2.3 fold increased risk of crashing (95% CI=1.24-4.38, p=0.01). For every
10 points of UFOV reduction, subjects had a 16 percent increase in crash risk.
Estimates are that 24 percent of older driver crashes are due to UFOV reduction
>40 percent.
Owsley, McGwin, and Ball (1998) studied 193 older drivers between ages 55-87 (mean=71
years) to identify visual risk factors for vehicle crashes by older drivers that
result in injury. Univariate analyses showed that older drivers involved in injurious
crashes were more likely to have UFOV reductions (Odds Ratio [OR]=5.3 for reductions
of 23 to 40 percent; OR=16.3 for reductions of 41 to 60 percent; and OR=22.0 for
reductions greater than 60 percent). Only two variables were independently associated
with crash risk in the multivariate analyses: UFOV and glaucoma. UFOV reductions
of 22.5-40 percent, 41-60 percent, and >60 percent were associated with 5.2,
16.5, and 21.1-fold increased risk of an injurious crash, respectively compared
to those with reductions of less than 22.5 percent. This sample was a subset of
the sample described above, consisting of 78 drivers (cases) who had at least
1 crash in the prior 5-year period that resulted in an injury to anyone in the
involved vehicles, and 115 drivers (controls) who had no crashes in the same 5-year
period. Excluded were 101 subjects who were involved in crashes where no injury
was reported.
Goode, Ball, Sloane, Roenker, Roth, Myers, and Owsley (1998) studied 239 older
drivers (ages 56-90) to examine the utility of a set of commonly used neuropsychological
tests in comparison to the UFOV in predicting state-recorded, at-fault crashes
in the prior 5 year period in a group of older drivers, a model using UFOV alone
was significant (p<.001). This model was as predictive as a model using UFOV
and traditional tests (MOMSSE, Trails, Wechsler Memory Scale subtest, and Rey-Osterreith
Complex Figures). The classification success was 85.4 percent, with sensitivity
of 86.3 percent and specificity of 84.3 percent. The estimated probability of
crashing with a UFOV score of 20 was 22 percent; for a UFOV score of 60, the probability
of crashing increased to 81 percent. The subjects in this study were recruited
from the larger sample of drivers participating in the larger study (Ball et al.,
1993). Of the original sample of 294 subjects, 251 received all of the cognitive
tests. Those with poor visual acuity (n=12) were excluded (since those with acuity
worse than 20/50 uniformly fail the first subtest of the UFOV).
Owsley, Ball, Sloane, Roenker, and Bruni (1991) studied 53 drivers ages 57-83
(mean age = 70), to determine whether incorporating eye health, visual function,
UFOV (Visual Attention Analyzer), and mental status could predict the number of
crashes in the sample. Only the mental status total score and UFOV were significantly
related to state-reported crashes. The subjects were recruited from the Primary
Care Clinic of the School of Optometry at the University of Alabama at Birmingham,
had valid AL licenses, and drove at least 1,000 miles/year. Results indicated
that only the UFOV was related to traffic citations. Subjects who failed the UFOV
had 4.2 times more crashes than those who passed. For intersection crashes, subjects
who failed the UFOV had 15.6 times more intersection crashes than subjects who
passed. Subjects with high MOMSSE scores had 6.3 times more intersection crashes.
Together, these variables predicted 29 percent of the variance in intersection
crashes, R=.54, F(2,49) =9.8, p<0.001. For intersection crashes, UFOV had 26
correct rejections, 14 false alarms, 1 miss, 11 hits.
In Ball, Owsley, Sloane, Roenker, and Bruni's (1993) retrospective study of 294
drivers ages 55-90, UFOV and mental status were the only variables that had a
direct effect on crash frequency, accounting for 28 percent of the variance in
crash frequency. The test battery included tests described for Owsley, Ball, Sloane,
Roenker, and Bruni (1991), plus the following cognitive tests assessing visuospatial
abilities: Rey-Osterreith test; Trail-Making test; and the WAIS block design test.
As a predictor, UFOV resulted in 142 hits, 18 misses, 25 false-positives, and
109 correct rejections. Of the 25 false-positives, 19 were subjects who reported
avoiding driving in general, avoided driving alone, and/or avoided left turns,
thus minimizing their driving exposure. Removing these people from the data set
increases the correlation between UFOV and crash frequency from r=0.52 to r=0.62.
UFOV had high sensitivity (89%) and high specificity (81%); mental status had
sensitivity and specificity values of 61 percent and 62 percent, respectively.
Another, ongoing research study, has yielded results showing UFOV's relationship
to performance during an on-road driving evaluation. Of the clients who passed
the UFOV test (less than 40 percent reduction in UFOV), the majority pass the
on-road evaluation, and of the clients who failed the UFOV test (have more than
a 40 percent reduction in UFOV), the majority fail the on-road evaluation. Of
the 23 drivers who passed the UFOV, 18 passed the on-road, 4 failed on-road, and
1 is pending. Of the 25 drivers who failed UFOV screening, 6 passed the on-road
evaluation, 16 failed the on-road test, and 3 are pending (pers. comm.,
Tom Kalina, Bryn Mawr Rehab, 10/97).
Hennessy (1995) conducted a study using 3,669 randomly-selected Class C license
renewal applicants, licensed in California for at least 12 years, and unable to
renew by mail. Four driver age groups were studied: 26-39, 40-51, 52-69, and 70+.
Subjects age 70+ showed high variability in visual divided attention ability (subtest
2) and perceptual reaction time (subtest 1 PRT). There was a very small percentage
of drivers age 70+ with very good total UFOV. Test scores had small but statistically
significant predictive value (2.9%) for subjects age 70+. After adjusting for
gender, age, and exposure, total UFOV scores explained 0.9 percent of the variance
in crash involvement, PRT explained 0.9 percent and divided attention explained
0.9 percent. The association with crashes for subjects in the 70+ age group was
stronger, with total UFOV accounting for 4.1 percent of the variation in crashes,
PRT accounting for 4.1 percent of the crashes, and divided attention accounting
for 4.3 percent of the crashes in the oldest age group. UFOV was not predictive
of crashes in the 3 younger age groups. Of 285 subjects age 70+, 84 (29%) scored
poorly. Thirty-six of the 285 subjects had a crash, and of the 36, 13 (36%) scored
poorly on the UFOV. Thus UFOV sensitivity was 36 percent, specificity was 71 percent,
and positive predictive accuracy was 15.5 percent. For citation occurrence, sensitivity
was 28 percent, specificity was 70 percent, and positive predictive accuracy was
12 percent.
Brown, Greaney, Mitchel, and Lee (1993) studied 1,475 ITT Hartford Insurance Co.
policyholders for whom past driving histories were available through insurance
records. They were divided into two groups based on the presence or absence of
recent at-fault crashes. Driver age ranged between 50 and 80+. The Visual Attention
Analyzer was employed; the overall score from the three subtests--speed of information
processing, divided attention, and a measure of distractibility--was used to describe
useful field of view loss. Results showed that 42 percent of the sample had an
at-fault crash between 1989-1991. The correlation between performance on the UFOV
test and at-fault crashes (r=0.05) was significant (p<0.05). The low correlation
was explained by the possibility that because participants were recruited through
their insurance company (as opposed to being recruited through an eye clinic and
offered a detailed eye exam, as were the subjects in the Ball et al. [1991] study),
drivers who were less confident in their driving skills may have elected not to
participate for fear that their insurance rates could be affected. Also, a noisy,
crowded test environment was described which may have yielded unrepresentative
visual attention measures.
Another study using WayPoint (a proprietary test measuring channel capacity or
information processing rate) and Subtest 1 of UFOV (measuring speed of processing)
examined 101 licensed drivers (39 females and 62 males) ages 72-90, with a mean
age of 78.3 (Janke and Hersch, 1997). In this study, WayPoint was administered
twice (in succession) to see if drivers with presumed cognitive impairment either
failed to improve from the first administration to the second, or did not improve
as much as subjects without presumed cognitive impairment. The scoring system
determines: (1) channel capacity or information-processing rate, defined as the
average speed per exercise on the first administration over two of the exercises;
and (2) high vs low risk of preventable and non preventable collisions, reflecting
the driver's situational awareness. An on-road driving exam was given by the project
driving instructor (owner/operator of a driving school in San Francisco) based
on the California Driving Performance Evaluation (DPE). Average time per exercise
on the first administration of WayPoint was significantly related to road test
weighted errors (r=.37) as was channel capacity (r=.35). Using only WayPoint 1
average time and UFOV subtest 1 as predictors of weighted error score on the road
test yielded multiple R = .428; adjusted R2=0.166.
As reported by the test's developer, in six studies with 102 drivers age 20-60,
WayPoint correctly classified 72 percent as high or low crash-risk drivers, missed
18 percent of the high crash-risk drivers, and falsely labeled 9.2 percent of
the drivers as high-risk when they were actually low risk. Also, results of a
study with emergency response (ER) trainees showed that errors on WayPoint were
(1) directly related to technical errors on the ER course (a high speed drive
circuit), (2) directly related to line-of-travel errors, and (3) positively correlated
with lap speed. On the non-emergency test, WayPoint errors were positively correlated
with driving errors and with the number of traffic cones contacted on the obstacle
course (Cantor, 1995).
In Marottoli, Richardson, Stowe, Miller, Brass, Cooney, and Tinetti's (1998) study
of 125 community-living older persons who were active drivers (ages 77+),
poor performance on a visual attention task (< 48 correct on
a number cancellation task, RR=3.0, CI=1.2-7.8) was one of the factors independently
associated with (self-reported) adverse driving events (crash, moving violation,
being stopped by police during previous 5.75 years) in multivariate analyses adjusting
for driving frequency. The number cancellation task involved marking out all of
the numbers in a row that matched a circled number at the far left-hand side of
the row, within a given amount of time.
Conclusions/Preliminary Recommendations:
Older drivers with 40 percent or greater impairment in their useful field of view--which
stems from declines in visual sensory function, visual processing speed, and/or
visual attentional skills--appear to be at an increased crash risk. Broadly speaking,
there is a strong case that age-related visual processing impairments, particularly
in the ability to divide attention, are directly related to future crash risk.
Based on the success to date of predicting crashes, it is recommended that the
UFOV protocol (or a related procedure validated on the same measurement construct)
be incorporated as a diagnostic test of cognitive deficits which predict driving
impairments for license renewal applicants; in particular, the evaluation of divided
attention (one of the UFOV subtests) is recommended. Quick and inexpensive assessments
of gross deficits in attentional and information processing abilities also appear
quite valuable; the traditional Trails protocol (see also discussion in next section
of Notebook) and derivative techniques using paper-and-pencil or computer-based
methods are most promising.
References:
• Ball, Owsley, Sloane, Roenker, and Bruni (1993)
• Brown, Greaney, Mitchel, and Lee (1993)
• Cantor (1995)
• Goode, Ball, Sloane, Roenker, Roth, Myers, and Owsley (1998)
• Hennessy (1995)
• Janke and Hersch (1997)
• Marottoli, Richardson, Stowe, Miller, Brass, Cooney, and Tinetti (1998)
• Owsley, Ball, McGwin, Sloane, Roenker, White, and Overley (1998)
• Owsley, Ball, Sloane, et al. (1991)
• Owsley, McGwin, and Ball (1998)
IA2(d). Perceptual Skills
(Visual Search,
Spatial Integration, Gap/Headway Judgment)
Summary:
Visual Search. In a study of 3,238 drivers age 65 and older, who applied
for renewal of North Carolina driver's license, performance on a paper-and-pencil
test of general cognitive function (Trails A and B), measuring speed of visual
search, attention, mental flexibility, and motor function was correlated with
crash involvement in the preceding 3-year period (Stutts, Stewart and Martell,
1996, 1997). Trails A Results: Correlational coefficient with number
of crashes = 0.065 (p<0.001). Subjects who scored in best quartile had 47
percent fewer crashes (.037 crash involvements per year) than drivers who scored
in the worst quartile (.054 crash involvements per year). Trails B Results:
Drivers in the poorest decile of performance had a predicted average annual
crash rate of 1.5 times that of drivers in the highest decile of cognitive performance.
Correlational coefficient with number of crashes = 0.072 (p<0.001). Annual
crash involvements increased with increasing (poorer) cognitive scores.
In a study of 105 drivers ages 65-88 (Tarawneh, McCoy, Bishu, and Ballard,
1993), only the Trail-Making Part B test showed a significant correlation to
performance on an on-road driving task, with a correlation coefficient of -0.42
(p<.0001). The correlation between Trails A and driving performance was -0.03
(p<.7329). Trails B showed the highest correlation of all factors (visual,
visual perception, cognitive, range of motion) included in the analysis.
In a study of 39 drivers (21 with Alzheimer's disease) to determine fitness
to drive for neurological patients, performance on Trails B was a significant
predictor of simulator crashes, with an odds ratio of 30.19 (Rizzo, Reinach,
McGehee, and Dawson, 1997).
In a study of 20 drivers age 55 and older, who were administered 11 assessment
tests and an on-road driving test, 6 subjects were classified as below minimum
standards in driving performance (a total of 19 or more errors on the NY State
Driving Exam) (Cushman, 1988, 1992). These six subjects scored more poorly on
Trails B (mean Trails B total time =130.5 s) than the subjects whose on-road
driving performance was at least adequate (mean total Trails B time = 93.07
s). The Trail-Making Test (Part B) was the only test that was significantly
correlated with driving performance for all subjects (r=0.61, p<0.01).
In the recently completed pre-pilot study conducted in Salisbury, Maryland for
the NHTSA "Model Driver Screening and Evaluation Program" project, the present
Notebook authors found that subjects who took 5 minutes or longer to
complete the Trails B protocol were 1.41 times more likely to be crash involved,
compared to subjects who completed this test in less than 5 minutes. The mean
time to complete the Trails B protocol was 161.14 seconds for the crash-free
drivers, and 180.57 seconds for the crash-involved drivers. Subjects ranged
in age from 68 to 89 (mean age = 75.7); 131 of the 363 subjects were involved
in at least 1 crash in the previous 6-year period (1991-1997).
A modified and automated version of Reitan's (1958) Trail-Making Test (Part
A) has been developed. In this test, 14 numbers are presented on a computer
monitor arranged randomly against the background of a traffic scene, as observed
by the driver through the windshield of a car. The subject must touch the numbers
(touch screen display) in numerical order as rapidly and accurately as possible.
Timing is done by the computer. This test was used in a study of 69 subjects
ages 60-91 who were referred to the California DMV for reexamination, and 31
paid "volunteers" ages 56-85, recruited through signs posted at study site or
by word of mouth (Janke and Eberhard, 1998; Janke and Hersch, 1997). An on-road
driving exam was given based on the California Driving Performance Evaluation
(DPE). The referral group performed significantly worse than the volunteer group
(correlation between Auto-Trails time and Group = .405, p<.05). Auto-Trails
mean time for referrals was 24.26 seconds; for volunteers, mean time was 16.91
seconds. Auto-Trails time correlated significantly with weighted error score
on the road test, for combined referrals and volunteers (r=.4523, p<.000)
and for referrals only ( r=.3748, p<.002). Auto-Trails time did not discriminate
the cognitively impaired referral subjects from the cognitively unimpaired referral
subjects.
Spatial Integration. In Tarawneh, McCoy, Bishu, and Ballard's (1993)
study of 105 drivers ages 65-88, among the visual perception factors, Visual
Closure response-time score (from the MVPT) correlated significantly with an
on-road driving performance measure (correlation coefficient =-0.38). As percent
of correct responses increased on the visual perception tests, performance on
the driving test increased; as the reaction time scores increased, performance
on the driving test decreased.
In a study of 42 patients with Alzheimer's Disease (mean age = 72.2 years) and
81 normal elderly controls (mean age = 69.1 years), driver simulator performance
measures correlated strongly with Visual Memory immediate scores, and Visual
Closure subscore of the Motor-Free Visual Perception Test for both AD and control
subjects (Keyl, Rebok, Bylsma, Tune, Brandt, Teret, Chase, and Sterns (manuscript
under review).
In the recently completed pre-pilot study conducted in Salisbury, Maryland for
the NHTSA "Model Driver Screening and Evaluation Program" project, the present
Notebook authors found that subjects who made 3 or more errors on the
MVPT Visual Closure subtest were 1.7 times more likely to be crash involved,
compared to subjects who made 2 errors or less. The mean number of incorrect
items was 1.91 for the crash-free drivers and 2.62 for the crash-involved drivers.
This difference was significant at the 0.002 level. Subjects ranged in age from
68 to 89 (mean age = 75.7); 131 of the 363 subjects were involved in at least
1 crash in the previous 6-year period (1991-1997).
Gap Judgment/Headway. In a study of 82 "referred" subjects ages 60-91
(26 of whom were identified as likely having cognitive impairment) where the
ability of subjects to rapidly detect changes in the relative motion of their
own versus other vehicles was measured, cognitively impaired referrals had a
significantly higher error proportion (they did not brake in 47.3% of the trials
where the lead vehicle braked ahead and the brake lights were visible) compared
to cognitively unimpaired referral subjects (who did not brake in 21% of the
trials). Also, the correlation between proportion of errors on trials where
brake lights were visible, and weighted error score on an on-road drive test,
was significant (r=.2801, p<.013). (See Staplin, Gish, Decina, Lococo, and
McKnight, 1998; Janke and Eberhard, 1998).
McKnight and McKnight (1998) evaluated the on-road driving performance of 402
drivers age 62 and older. Approximately two-thirds of the subjects were referred
to the licensing agency for reexamination based upon reports of deficient driving
incidents, and the balance were incident-free volunteers. The road test was
based on the Driver Performance Evaluation (DPE) developed by the California
Department of Motor Vehicles (see Hagge, 1994). The incident-involved drivers
tended to underestimate gap size (stating that they could safely enter gaps
of less than 6 seconds) even though they erred on the safe side in the gaps
that they actually entered.
Conclusions/Preliminary Recommendations:
Tests measuring visual perception, speed of visual search, and ability to sense
changes in angular motion (i.e., cues to the speed and distance of other vehicles)
have been shown to predict driving performance in simulators, on the road, and
prior crash rate, and also have the ability to distinguish cognitively impaired
individuals from unimpaired individuals. It is recommended that a Trail-Making
protocol be implemented in driver screening for relicensing.
References:
• Cushman (1988, 1992)
• Engum, Lambert, Womac, and Pendergrass (1988)
• Goode, Ball, Sloane, Roenker, Roth, Myers, and Owsley (1998)
• Janke and Hersch (1997)
• Janke and Eberhard (1998)
• Keyl, Rebok, Bylsma, et al. (submitted)
• McKnight and McKnight (1998)
• Rizzo, Reinach, McGehee, and Dawson (1997)
• Staplin, Gish, Decina, Lococo, and McKnight (1998)
• Stutts, Stewart and Martell (1996, 1997)
• Tallman, Tuokko, and Beattie (1993)
• Tarawneh, McCoy, Bishu, and Ballard (1993)
IA2(e). Memory/Cognition Deficits
Summary:
In a panel data analysis of 507 female drivers and 375 male drivers who participated
in the Iowa 65+ Rural Health Study from 1981-1993, having impaired cognitive
ability (low score on word recall test) was a risk factor that determined the
probability of an older male being involved in a crash (Hu, Trumble, Foley,
Eberhard, and Wallace, 1998). Foley, Wallace, and Eberhard (1995) interviewed
1,791 drivers in this cohort, and found that drivers who could remember fewer
than 3 of the 20 words given in a free-recall memory test had an increased crash
risk (Relative Risk = 1.4, Confidence Interval: 1.1 to 1.9, p< 0.05).
In a study of 37 drivers age 65 and older in a case group (suspensions + crashes)
and 37 matched controls (no suspensions or crashes), cases had significantly
lower immediate memory task performance (p=.010) compared to matched controls
(Johansson, Bronge, Lundberg, Persson, Seideman, and Viitanen, 1996; Johansson,
1997). Immediate memory was tested by a 5-item recall test, where the subject
was required to name and recall 5 objects viewed on a desk after a 10-minute
period (the items were not listed in this review). The delayed recall score
was 1 point per correct item. Comparison of the 23 case subjects with crashes
and the 29 control subjects with no crashes in the past 5 years showed that
the crashed drivers had poorer 5-item recall (p<.003).
In a study of 360 drivers age 62 and older, measures of short-term and delayed
short-term memory (measured with the Automated Psychophysical Test [APT]) showed
fairly strong correlations between accuracy and safe driving and response time
and safe driving. The correlations were significant, and ranged from 0.22 to
0.34 (McKnight and McKnight, 1998).
Hunt, Morris, Edwards, and Wilson (1993) administered the Logical Memory subscale
of the Wechsler Memory Scale, which assesses immediate or delayed recall of
verbal ideas presented in two paragraphs, read aloud by the experimenter. Each
subject then drove for 1 hour on a pre-designed route using urban streets and
highways, that included common driving situations (stop signs, traffic signals,
left turns at intersections, entering and exiting an interstate highway, changing
lanes, merging, diagonal and parallel parking). Subjects drove in low volume
conditions. A gestalt "pass/fail" rating was given by each observer in the vehicle.
In a sample of 13 healthy elderly controls (mean age = 73.5) 12 subjects with
very mild dementia (mean age = 72.5) and 13 subjects with mild dementia (mean
age = 73.4), the correlation between the pass/fail outcome on the road test
and performance on the Logical Memory test was significant at the p<.0009
level.
In a study of 146 drivers age 65 and older (mean age = 72.0), three tests: the
Brief Test of Attention (numbers), Trails A, and the Serial Sevens item in the
Mini Mental State Examination (MMSE, see section IC2b(i) of the Notebook)
were most strongly associated with crashes (Keyl, Rebok, and Gallo, in press).
Patients who had poor performance on more than one of these tests had a 6.2-fold
increase in crash occurrence in the previous two years. [A precaution by Lindal
and Stefansson, 1993 regarding gender differences: when women use serial 7's
they obtain much lower scores on the MMSE than if they use backward spelling,
and conversely, men receive a lower score if they use backward spelling as opposed
to serial 7's]
Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994) found that persons with
borderline cognitive impairment (MMSE score of 23-25) were more likely to have
adverse events (traffic crash, violation, or stopped by police) in the year
following examination than those with higher or lower scores (relative risk
2.0, 95% CI, 1.1-3.7). The authors examined the components of the MMSE individually
and by cognitive domain (orientation, memory, attention, language, and visuospatial
ability), and found that the item most closely associated with adverse events
was impaired design copying (24% of persons who could not correctly copy the
intersecting pentagons had events compared with 8% of those who could [relative
risk 3.0, CI, 1.6-5.6]).
In the recently completed pre-pilot study conducted in Salisbury, Maryland for
the NHTSA "Model Driver Screening and Evaluation Program" project, the present
Notebook authors found that inability to recall three short words was
related to crashing (Odds Ratio = 1.52). Subjects ranged in age from 68 to 89
(mean age = 75.7); 131 of the 363 subjects were involved in at least 1 crash
in the previous 6-year period (1991-1997).
Conclusions/Preliminary Recommendations:
Impaired cognitive ability, measured using immediate and delayed recall, is
associated with increased crash risk and poorer on-road driving performance
in older people. The inability to count backwards by 7's (ability to perform
a mental function) is also related to increased crash risk in older drivers,
but may have a gender bias.
References:
• Hu, Trumble, Foley, Eberhard, and Wallace (1998)
• Hunt, Morris, Edwards, and Wilson (1993)
• Foley, Wallace, and Eberhard (1995)
• Johansson (1997)
• Johansson, Bronge, Lundberg, Persson, Seideman, and Viitanen (1996)
• Keyl, Rebok, and Gallo (in press)
• Lindal and Stefansson (1993)
• Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994)
• McKnight and McKnight (1998)
IA2(f). Navigation Errors on Road Test
Summary:
In a study of 75 subjects ages 60-91 who were referred to CA DMV for reexamination
(26 of whom were identified as probably being cognitively impaired to some degree),
and 31 volunteers ages 56-85, cognitively impaired referrals had significantly
more "confusion errors" than cognitively nonimpaired referrals. Confusion (concentration)
errors occurred when subjects were unable to proceed to the field office at
the end of the drive test, or drove past the street on which the field office
was located and did not recognize their error. This particular measure was the
only on-road driving performance measure where there was a difference between
the performance of cognitively impaired and cognitively nonimpaired drivers.
(See Janke and Eberhard, 1998; Janke and Hersch, 1997).
McKnight and McKnight (1998) evaluated the on-road driving performance of 402
drivers age 62 and older. Approximately two-thirds of the subjects were referred
to the licensing agency for reexamination based upon reports of deficient driving
incidents, and the balance were incident-free volunteers. The road test was
based on the Driver Performance Evaluation (DPE) developed by the California
Department of Motor Vehicles (see Hagge, 1994). Navigation tasks included remembering
a series of directions (turning at named streets and following a sequence of
turns) and maintaining spatial orientation in order to drive around a block.
The instructions given to subjects for the location-finding task were, "Please
proceed until (name street) and turn left/right onto (name street again)." The
directions given to travel around the block in order to end up at a specified
location and traveling direction were, "In a moment, I'll ask you to make a
right turn. When I do, please turn right and then make a series of right turns
around the block, ending up on this same street, going in the same direction."
The correlation between navigation errors and unsafe driving incidents was significant
(r=0.41). The incident-involved drivers performed more poorly than the incident-free
drivers on the on-road navigation tasks.
Conclusions/Preliminary Recommendations:
A destination-finding task should be included in on-road driving tests tailored
to detect possible cognitive impairment among older drivers who are referred
for reexamination, or to determine the extent to which cognitive impairment
has progressed to the point where driving is not recommended (as in the third-year
post Alzheimer's disease onset).
References:
• Janke and Eberhard (1998)
• Janke and Hersch (1997)
• McKnight and McKnight (1998)
IA2(g). Discriminating Maneuver Errors on Road Test
Summary:
Older and cognitively impaired drivers, like all drivers, commit many
common errors both during the stage of information acquisition and in the execution
of vehicle control movements that appear to have little bearing on the likelihood
of crash involvement--or rather, that the variance that can be accounted for
by differences in these behaviors will always be lower than that accounted for
by situational factors (Staplin, Gish, Decina, Lococo, and McKnight, 1998).
In the study by Staplin et al., almost all of the older drivers (n=62) failed
to look both ways before entering intersections to execute a through maneuver
during the green (permissive) phase, and instead, treated their movement as
one that was protected. Such "common," or nondiscriminating errors
are therefore poor candidates for the validation of screening indices, or for
identifying individuals deserving one sort of intervention or licensing action
from another. Dobbs (1997) similarly has advocated the segregation of nondiscriminating
from discriminating (or hazardous) errors in the development and application
of screening instruments for driving competency.
Dobbs (1997) studied 279 drivers in three groups:
• 176 patients referred to a clinic with suspected decline in mental abilities
(majority were diagnosed with Alzheimer's) with mean age of 72 years;
• 70 mature healthy drivers volunteered for the research (mean age = 69 years);
• 33 young healthy controls also volunteered (age range 30-40; mean age = 36
years).
A two-part road test was administered by 2 experienced driving instructors from
the Canadian Automobile Association. Testing was conducted in a mid-sized American
car equipped with dual brakes. The first part was a closed course on paved streets
with curbs, but was undeveloped allowing traffic to be restricted and signs
to be placed as desired. The open road test consisted of 37 maneuvers, required
40 minutes to administer, and was conducted on commercial and residential streets,
and an urban freeway. Maneuvers were selected to maximize those implicated in
older-driver crashes. Some instructions for downstream maneuvers were given;
other maneuvers required planning (e.g., a lane change prior to a turn); and
some maneuvers required working memory skills (e.g., turn left after two blocks).
There was also a "take me to" instruction.
Definition and scoring of errors was as follows.
• Hazardous or potentially catastrophic driving errors: errors committed
by drivers who are no longer competent to drive (e.g., wrong-way on a freeway,
stop at green light), and would result in a crash if examiner did not intervene
or traffic did not adjust.
• Discriminating driving errors: potentially dangerous errors that signal
declining driving skill (e.g., poor positioning on turns and straightaways,
observational and scanning errors, and overcautiousness).
• Non-Discriminating driving errors: errors made equally often by good
and bad drivers, reflecting bad habits as opposed to declining ability (e.g.,
"rolling" stops and speed errors). Drivers are not penalized for non-discriminating
errors. Discriminating errors are documented and scored in terms of their severity
(5, 10, or 51 points).
Hazardous errors were renamed as Criterion errors and their commission results
in an automatic fail. A combined criterion of one or more criterion errors and/or
discriminating point total exceeding criterion, results in a failure on the
road test.
Using the joint criterion, all of the young normal drivers passed the road test,
approximately 95 percent of the mature control group drivers passed the road
test, and only 25 percent of the cognitively impaired (patient) group passed
the road test.
In McKnight and McKnight's (1998) study that compared the on-road driving performance
of incident-involved and incident-free older drivers [see Notebook
section IA2(f)], the incident-involved drivers did more poorly on the following
measures: intersection visual search (sharing attention); path maintenance through
turns; maintaining a constant speed; positioning the car at intersections and
merges; and navigating correctly. They also tended to err on the side of over-caution
by driving slowly through turns, on straight stretches, and when changing lanes,
as well as rejecting safe gaps at intersections.
Researchers who have compared the driving performance of cognitively-impaired
(mild dementia) older drivers and healthy older controls have found that older
cognitively impaired drivers make the following errors (Hunt, 1991; Hunt, Morris,
Edwards, and Wilson, 1993; Hunt, Murphy, Carr, Duchek, Buckles, and Morris,
1997a, 1997b; Cooper, Tallman, Tuokko and Beattie, 1993; Dobbs, 1997; Janke
and Hersch, 1997):
• Stopping at green lights
• Making sudden stops for no apparent reason
• Coasting to near stop in moving traffic
• Failure to check blind spot
• Delay in changing lanes when an obstacle appeared
• Drifting into other lanes
• Wrong lane prior to left or right turn
• Wrong lane after left or right turn
• Impulsive and unsafe left turn
• Attempted left turn when not allowed
• Attempted left turn on red
• Inappropriate decision-making ('judgment') in traffic
• Failed to yield right-of-way
• Misinterpretation of traffic signs
• Failure to move over or stop for ambulance
• Collisions or near collisions on hazard avoidance tasks
• Collisions/near collisions with median
• Wrong-way maneuvers
• Getting lost in familiar areas
• Require repeated step-by-step directions
• Require verbal cues to signal when changing lanes throughout the driving task
• Signaling late (when they did signal)
• Driving while pressing the brake and accelerator simultaneously
• Failing to realize why other drivers honked at them
Conclusions/Preliminary Recommendations:
Driving errors demonstrated by cognitively impaired older drivers differ from
the types of errors that many drivers, both good and poor, commit (bad habits
as opposed to cognitive decline). Therefore, road tests developed to determine
driving competency (older driver re-exams) should include the conditions and
maneuvers shown to be problematic to drivers with cognitive decline, and scoring
of errors (number and severity) should be such that drivers are not penalized
for making errors that do not discriminate impaired from unimpaired drivers.
The test must be traffic interactive, performance based, and examine cognitive
behaviors.
References:
• Cooper, Tallman, Tuokko, and Beattie (1993)
• Dobbs (1997)
• DrivAble Testing, Ltd. (1997)
• Hunt (1991)
• Hunt, Morris, Edwards, and Wilson (1993)
• Hunt, Murphy, Carr, Duchek, Buckles, and Morris (1997a, 1997b)
• Janke (1994)
• Janke and Hersch (1997)
• McKnight and McKnight (1998)
• Staplin, Gish, Decina, Lococo, and McKnight (1998)
IA2(h). Decision-Making and Response Selection in Driving
Simulators
Summary:
(Note: See Notebook section IC2(b)iv for a description of driving
simulators)
Schiff and Oldak (1993) found performance differences (EasyDriver)
between 109 older subjects (ages 55-95) and 61 younger subjects (ages 15-54)
that included:
• Slower driving speeds by older subjects, particularly in the poor visibility
conditions and under headlight glare conditions;
• Longer (but not significant) simple reaction time (RT);
• Longer RT's to traffic events such as braking in response to lead vehicle
brake lights, a pedestrian, and the basketball (dusk) scenarios;
• Late braking by 40-90 year olds in response to a school bus pulling into their
lane; and
• Lack of response by a substantial number of older subjects to the tennis ball
and basket ball (dusk) scenarios.
Using GAR score as a criterion, multiple regression analyses were performed
to determine which scenarios would best predict driving performance. A Global
Accident Risk (GAR) score was the dependent measure, which consisted of the
total number of reported at-fault crashes for each driver, with the addition
of up to 3 more points for self-reported medical or driving problems (dizziness,
attentional lapses, severe arthritis, poor vision, and poor vehicle control).
The resulting range of scores was 0-13. Regression analysis were performed separately
for older and younger subjects using 65 years as the criterion age split. For
the older subjects, RTs from hit pedestrian, tennis ball, basketball (dusk)
and city brakes yielded an R=.47, accounting for 22 percent of the variance
in GAR scores. For young subjects, schoolbus, hit pedestrian, and tennis ball
yielded an R=.41, accounting for 16 percent of the variance.
In Szlyk, Brigell, and Seiple's (1993) study of 6 subjects with hemianopic
visual field deficits (ages 53-80, mean 71 years) and 7 older controls (ages
62-83, mean 70), simulator performance measures of effectiveness (MOEs) included:
mean speed (in mi/h); average slowing and stopping to traffic signals; number
of lane boundary crossings; mean break pedal pressure; mean gas pedal pressure;
number of simulator crashes; lane position; steering angle and vehicle angle
to the road. Six staged driving simulator challenges required visuocognitive/motor
skills to avoid a crash; three of these were intersections with cross traffic.
Two of the four older subjects who had real-world crashes also had the longest
slowing times, the longest stopping times, and the most crashes in the driving
simulator.
In a study 82 older subjects ages 60-91 (26 of whom were identified as probably
being cognitively impaired to some degree) who were referred to the CA DMV for
reexamination, the proportion of errors on simulator trials where the driving
video (MultiCAD) showed a threat vehicle entering the driver's path
from the periphery at 15 degrees (divided attention trials) was significantly
correlated with weighted error score on an on-road drive test (r=.2430, p<.043).
A gross measure of the number of errors made in the driving video (angular motion
sensitivity trials) significantly correlated with weighted error score on the
road test (r=.3462, p< .002). In addition, the correlation between proportion
of errors on trials where brake lights were visible and weighted error score
on the drive test was significant (r=.2801, p<.013). (See Staplin, Gish,
Decina, Lococo, and McKnight, 1998; Janke and Hersch, 1997)
Conclusions/Preliminary Recommendations:
Ecologically valid stimuli (realistic views of the driving environment) yield
predictive assessments of the cognitive and visual motor components required
in driving. A simulation of apparent motion of self through a three-dimensional
environment (even if simulated on a two-dimensional screen) which contains the
visual scene complexity associated with the actual driving environment is important
for simulator measures for predicting actual driving performance. Simulators
are recommended for pre-testing drivers recovering from strokes, cerebral vascular
accidents, and those with progressive cognitive disorders, to determine their
progress and whether it is safe to assess them on the road. They may also be
beneficial in highlighting risks for drivers, who may not acknowledge diminished
capabilities, and as an educational tool in a rehabilitation environment.
References:
• Janke and Hersch (1997)
• Schiff and Oldak (1993)
• Staplin, Gish, Decina, Lococo, and McKnight (1998)
• Szlyk, Brigell, and Seiple (1993)
I.A. IDENTIFY OLDER PEOPLE WHO ARE AT HIGH RISK OF CRASHES
I.A.3. Avoidance of High Risk Situations and Other Compensatory
Behaviors
Summary:
Data from the 1990 Fatal Analysis Reporting System (FARS) and the 1990 Nationwide
Personal Transportation Survey (NPTS) show that people age 75 and older are
involved in more fatal crashes per mile driven than people of any other
age group (Massie and Campbell, 1993; Massie, Campbell, and Williams, 1995).
But, because they drive relatively few miles each year, their fatal involvement
rate per licensed driver is only slightly above the overall rate. While
the per capita fatal involvement rate for people age 75 and older is
lower than for people of all ages combined, this may be explained in part by
the fact that relatively lower percentages of people in older age cohorts hold
valid licenses (approximately 50 percent of women age 75+ and 80 percent of
men age 75+, compared to 84.5 percent of all women and 92 percent of all men
in the population of driving age).
At the same time, an analysis of driving and travel patterns between 1983 and
1990 showed that drivers in age categories 65 and older drove at least 30 percent
more in 1990 than in 1983, at an annual increase of 4 percent. Older drivers
continued to concentrate their driving between 9:00 a.m and 4:00 p.m. Analysis
of the fatality rates by day and night showed that the highest daytime rates
were for drivers age 75 and older, while the highest nighttime rates were for
drivers age 16-19. For older drivers, the nighttime rate is 1.1 times the daytime
rate, while for the youngest drivers, it is 6.1 times the daytime rate (Massie
and Campbell, 1993; Massie, Campbell, and Williams, 1995).
A panel data analysis found that although annual miles driven is the single
most influential risk factor in crash involvement for older male and female
drivers, the influence of mileage on the likelihood of being involved in vehicle
crashes is significantly smaller in men than in women (Hu, Trumble, Foley, Eberhard,
and Wallace, 1998). For female drivers, the amount of annual driving and limitation
in gross mobility (inability to raise arms above shoulder height) were the two
significant risks in older women being involved in crashes. For males, being
employed and cognitively disabled, having a history of glaucoma, and using anti-depression
drugs amplify the likelihood of being involved in vehicle crashes. Use of antidepressants
by male drivers is the second most important risk next to the amount of annual
driving, doubling the risk compared to drivers who do not use antidepressant
drugs. After controlling for the amount of annual driving, men who are cognitively
impaired (low score on word recall test), are 40 percent more likely to be involved
in a crash than men who are not; cognitive ability is irrelevant in older females
being involved in crashes.
In driving habits surveys, older drivers report driving fewer miles and avoiding
demanding driving situations compared to younger drivers (Tallman, Tuokko, and
Beattie, 1993; Janke and Eberhard, 1998; Gutman and Milstein, 1998). In one
study, drivers with the highest avoidance scores were those who performed most
poorly on an on-road exam, but avoidance score did not discriminate between
cognitively impaired and unimpaired drivers (Janke and Hersch, 1997). In another
study, drivers who were more visually and/or cognitively impaired tended to
report more avoidance and less exposure (e.g., avoid night driving, high-traffic
roads, rush-hour traffic, high-speed interstates, driving alone, making left-hand
turns across traffic, driving in the rain; and reported driving fewer days per
week); however, relationships between mental status and the avoidance items
were weaker than those between visual function and avoidance (Ball, Owsley,
Stalvey, Roenker, Sloane, and Graves, 1998). In this study, older drivers with
cataracts (n=83) reported more avoidance of driving on high-traffic roads, in
rush-hour traffic, on high-speed roadways, alone, and in the rain than drivers
with no eye health problems (n=126); however, drivers with cataracts did
not report higher levels of avoidance of driving at night and making
left turns. Older drivers with age-related macular degeneration (n=19) reported
higher overall avoidance than the no-eye-disease group for all avoidance categories.
Older drivers with multiple impairments (visual and cognitive) restricted their
driving to a larger extent and in more situations than those with visual impairments
alone, or those who were functionally normal. Drivers with higher numbers of
crashes in the prior 5-year period reported more avoidance of driving in the
rain, making left turns, and driving during rush hour.
In a sample of 3,238 drivers age 65 and older who were administered a battery
of visual and cognitive assessment tests, the prevalence odds of reduced driving
exposure were higher for the cognitive function variables than for the visual
function variables, and higher for males than for females (Stutts, 1998). Men
who scored in the lowest quartile on the Trail-Making A and Short Blessed tests
(cognitive measures) were 6 to 9 times more likely to report driving less than
3,000 miles per year than men scoring in the highest quartiles, and women with
low scores were three times more likely to report driving less than 3,000 miles
than women with higher scores. The effect of reduced high-contrast visual acuity
was greater at higher age levels than at lower age levels. A model developed
to predict high risk avoidance (not driving after dark, during rush hour or
in heavy traffic, on expressways or interstate highways, on busy multi-lane
roads, in rain, or other bad weather conditions) found that the cognitive and
visual function measures were associated less strongly with avoidance of particular
driving situations than with an overall reduction in mileage. Also, in this
model, the odds ratio for the cognitive function measures were only slightly
higher than those for the visual function measures.
Although Marottoli and Richardson (1998) found that individuals who drove more
miles were more likely to rate themselves as being better drivers than their
peers, results of their study showed that on-road driving performance and history
of adverse driving events were not related to drivers' ratings of self confidence
in their driving ability. The subjects in their study were 125 active older
drivers age 77 and older, 40 percent of whom reported a history of adverse driving
events. In terms of self-ratings of driving ability, none of the 125 participants
rated themselves as being worse than other drivers. Of the 50 participants with
a history of an adverse driving event, 34 (68%) rated themselves as being better
or much better than other drivers their age; this is identical to the proportion
of individuals who rated themselves as better or much better and had no history
of adverse driving events. In addition, all nine individuals who were rated
by a driving therapist as having moderate or major difficulties on a road test,
rated their driving ability at least as good as their peers, and 3 of the 9
rated their ability as better or much better than their same-age peers. Of the
125 drivers, 34 (27%) had a discrepancy in their self-rating of ability (i.e.,
they had adverse driving events or were rated by a driving evaluator as being
poor drivers, but they rated their driving ability as better than that of their
peers). The authors state that this indicates a lack of awareness, as these
drivers may exceed their limitations and place themselves and others at risk.
Turning to a consideration of whether older drivers know when to stop driving,
Stutts, Wilkins, and Schatz (submitted) found that older drivers think they
will be the first to know when they should stop driving, and most seniors have
not considered the possibility that they may not realize when it is time for
them to stop driving. The majority of the focus group participants indicated
that seniors do not plan for the possibility that they could outlive their driving
ability. This information was obtained through focus group discussions with
44 older drivers who had recently stopped driving (half of the group) or believed
that they may stop driving within two years.
Stutts et al. also reported that men are particularly reluctant to stop driving,
and often deny any deterioration in their driving skills. Some seniors continue
to drive "in spite of everything," regardless of physician recommendations against
driving and injury-producing, at-fault crashes. On the other hand, there is
a subset of older drivers, typically women, who give up driving prematurely.
Generally, these drivers never really enjoyed driving, are uncomfortable in
today's driving environment, and have a spouse who drives. Although an event
like a hospitalization may trigger their decision to stop driving, often they
just drive less and less until they no longer feel comfortable behind the wheel.
Wilkins, Stutts, and Schatz (submitted) conducted one-hour, on-road evaluations
of eight senior women who wanted to drive more, but had either voluntarily stopped
driving or voluntarily drove infrequently (once per week or less). Subjects
were screened by telephone to eliminate those who had a vision or other health
problem that prevented them from driving more. The evaluations were provided
at no cost to the participants, and were conducted by a certified driving instructor
under the auspices of a local driving school. Driving evaluations began at each
woman's home. The instructor completed a standard evaluation form (Miller Road
Test), and provided each woman verbal feedback describing her driving performance,
and whether additional practice and/or driving lessons were recommended. When
contacted for a telephone follow-up interview, all of the women described the
evaluation as a useful experience, and several indicated that it had given them
confidence in their driving ability; these women indicated that they were driving
more as a result of the evaluations. All three of the women who had previously
ceased driving indicated that they planned to resume driving, at least enough
to maintain their skills. The authors state that although it is unknown how
much the women would be willing to pay for an evaluation and lessons, such a
countermeasure would help keep older women on the road safely, longer than they
would without such intervention. Education for older drivers as a rehabilitation
procedure is described in Notebook section IC3a(i).
Conclusions/Preliminary Recommendations:
Mileage-based crash risk increases with age, and this risk can be offset to
some degree by self-regulation (driving less frequently and fewer miles, and
under less demanding conditions). Many older drivers (who are aware of diminished
abilities) compensate for age-related functional declines at the strategic level
by planning to avoid rush hour or nighttime driving, and at the tactical level
by adjusting speed (driving slower) and accepting larger gaps at intersections.
Sensory and physical declines are easier to identify and compensate for (and
potentially correct) than are cognitive declines. But, recent research has shown
that the prevalence of undetected eye disease increases with age (Decina and
Staplin, 1993; Shipp, 1998). Possibly more serious is the driver with diminished
cognitive decline. Drivers with dementia overestimate their capabilities (Cushman,
1992) and may not restrict their driving to times and situations that reduce
risk (they don't compensate because they are not aware of their decline). Janke
and Eberhard (1998) found that the amount of avoidance reported in a driving
habits questionnaire did not discriminate between cognitively impaired
referral subjects and cognitively unimpaired referral subjects. Also, drivers
who have no access to alternative transportation and who live alone may be more
likely to drive in situations, even when they realize they are at higher risk;
reports from older driver focus groups consistently indicate that when there
is no choice but to drive to get to doctor appointments, grocery shopping, etc,
they will do so.
As reported by Stutts (1998), while approximately half of the drivers in the
lowest quartiles of performance on a cognitive function test (Trail-Making A
and B), reported driving less than 3,000 miles per year, the other half of this
population is driving over 3,000 miles per year, and 20 percent of the entire
sample reported driving more than 10,000 miles per year. While many older drivers
with cognitive and visual impairments limit their driving exposure, self-regulation
alone does not adequately protect the public's health.
A program that provides materials to help older drivers assess their own capabilities
and provides tips for reducing driving risk must be accompanied by a coordinated
effort that includes health-care professionals, individuals in the community
who come in contact with older persons, DMV counter personnel, and law enforcement
officers to ensure that older drivers remain safely mobile. In addition, driving
evaluations and on-road lessons may help provide confidence in driving ability
for older drivers who are fit to continue to drive but cease or restrict driving
prematurely.
References:
• Ball, Owsley, Stalvey, Roenker, Sloane, and Graves (1998)
• Cushman (1992)
• Decina and Staplin (1993)
• Gutman and Milstein (1988)
• Hu, Trumble, Foley, Eberhard, and Wallace (1998)
• Hu, Young, and Lu (1993)
• Janke and Eberhard (1998)
• Janke and Hersch (1997)
• Marottoli and Richardson (1998)
• Massie and Campbell (1993)
• Massie, Campbell, and Williams (1995)
• Ranney (in press)
• Shipp (1998)
• Stutts, Wilkins, and Schatz (submitted)
• Stutts (1998)
• Stutts, Stewart, and Martell (1996)
• Tallman, Tuokko, and Beattie (1993)
• Wilkins, Stutts, and Schatz (submitted)
