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II.C. PHYSICAL CAPABILITIES


1. Balance

(a) Tandem Stand

2. Gross Mobility

(a)Number of Blocks Walked
(b)Number of Foot Abnormalities
(c) Rapid Pace Walk
(d)Usual Pace Walk

3. Range of Motion

(a) Left-Knee Flexion
(b) Neck Flexibility
(c) Multiple Measures (Trunk, Neck, Shoulder)

4. Reaction Time

(a) Brake Reaction Time (Doron)


PHYSICAL CAPABILITIES

Balance:

Tandem Stand

101 licensed drivers (39 females and 62 males) age 72-90 (mean age = 78.3) who were members of a preexisting study cohort engaged in longitudinal studies of a community-dwelling cohort of older people (at Buck Center for Research in Aging)

Subjects were required to stand with the heel of one foot touching the toe of the other foot, with both feet pointing straight ahead, for 10 seconds. This test was scored in terms of pass vs fail.

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), and using the same scoresheet as used for the MDPE given in San Jose by these researchers. A weighted error score was calculated as total # of unweighted errors, plus twice the sum of critical and hazardous errors. Concentration errors were also noted.

Critical errors = errors which would in normal circumstances cause test termination (turning from improper lane, dangerous maneuver, examiner intervention needed).

Hazardous errors = dangerous maneuver or examiner intervention.

Concentration errors = subject unable to proceed to field office at end of test, or drove past the street on which the field office was located and did not recognize their error.

(See On-road Performance Measures of Driving Safety: California MDPE at the end of this Compendium).

Novato, Marin County California; Buck Center for Research in Aging

Performance on the tandem stand was not significantly correlated with weighted error score on the road test (r=0.108, p=.284)

Janke and Hersch (1997)

PHYSICAL CAPABILITIES

Gross Mobility:

Number of Blocks Walked

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. 57% were males.

An assessment of activity level included (1) self-reported independence in basic and instrumental activities of daily living (6-9 activities vs 0-5 activities); (2) number of flights of stairs walked in an average day; (3) number of blocks walked in an average day (0 v.s. 1+); and (4) higher level physical activity assessed using Yale Physical Activity Survey. Driving frequency was also assessed: daily vs every other day vs 1-2 times per week vs less than I time per week.

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.

New Haven, CT. Subjects were interviewed and given the assessments in their homes by a trained research nurse.

In the activity domain, walking less than 1 block per day was associated with adverse events (relative risk 1.9, 95% CI, 1.1-3.5). 21% of the subjects who walked less than 1 block per day had adverse driving events, compared to 11% of the subjects who walked 1 block or more each day. This difference was significant at the p< .05 level.

Driving frequency was not significantly associated with the occurrence of adverse events.

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% of drivers had adverse events; if 1 factor was present, 12% had events; if 2 factors were present, 26% had events; and if all 3 factors were present, 47% had events.

Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994)

PHYSICAL CAPABILITIES

Gross Mobility:

Number of Foot Abnormalities

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. 57% 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 for 0-2 foot abnormalities and for 3-8 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.

New Haven, CT. Subjects were interviewed and given the assessments in their homes by a trained research nurse.

Persons with 3 or more foot abnormalities were more likely to have adverse events (23% had adverse events) compared to persons with 0-2 foot abnormalities (10% had adverse events). The difference was significant at p<0.01 level. The relative risk = 2.0, CI 95%, 1.0-3.8.

Four of the factors in this study that were significantly associated in bivariate analyses (design copying, number of blocks walked, number of foot abnormalities, and rapid pace walk time) were entered into binomial relative risk models and were adjusted for driving frequency and housing type. The factors that remained significantly associated with adverse driving events were impaired design copying, fewer blocks walked and more foot abnormalities.

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% of drivers had adverse events; if 1 factor was present, 12% had events; if 2 factors were present, 26% had events; and if all 3 factors were present, 47% had events.

Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994)

PHYSICAL CAPABILITIES

Gross Mobility:

Rapid Pace Walk

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. 57% were males.

Timed performance measures included in this battery of tests included hand signature, 3 chair stands, usual pace walk (walk 10 feet each up and back including a turn at usual pace), rapid pace walk (10 feet each up and back as fast as the participant felt safe and comfortable), and foot tap (10 taps alternating between two circles on a mat).

Procedures for rapid pace walk are as follows: Measure out 10 foot walk. Say, "I want you to walk just as you normally do. If you use a cane or walker, you may use it if you feel more comfortable. I want you to walk all the way past the end of the course at the other end, turn around, and walk back like this." (Demonstrate).

"Now, I want you to walk down and back at a comfortable pace" (usual-pace walk).

"Now I am going to time you. Go as fast as you feel safe and comfortable."(rapid-pace walk)

Start timing when subject picks up first foot. Stop timing when last foot crosses finish line.

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.

New Haven, CT. Subjects were interviewed and given the assessments in their homes by a trained research nurse.

The timed performance test most strongly associated with adverse events (traffic accident, violation, stopped by police) in the year following testing was the rapid-pace walk (> 7 seconds versus < 7 seconds [relative risk, 2.0, CI 1.0-3.8]). 9% of the faster walkers had adverse driving events, compared to 17% of the slow walkers. This difference was significant at the p<.05 level.

Four of the factors in this study that were significantly associated in bivariate analyses (design copying, number of blocks walked, number of foot abnormalities, and rapid pace walk time) were entered into binomial relative risk models and were adjusted for driving frequency and housing type. The factors that remained significantly associated with adverse driving events were impaired design copying, fewer blocks walked and more foot abnormalities.

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.

Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994)

PHYSICAL CAPABILITIES

Gross Mobility:

Usual Pace Walk

101 licensed drivers (39 females and 62 males) age 72-90 (mean age = 78.3) who were members of a preexisting study cohort engaged in longitudinal studies of a community-dwelling cohort of older people (at Buck Center for Research in Aging)

Subjects walked back and forth along a 10 ft path for a 60-second period. This test was scored in terms of pass vs fail.

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), and using the same scoresheet as used for the MDPE given in San Jose by these researchers (see On-road Performance Measures of Driving Safety: California MDPE at the end of this Compendium). A weighted error score was calculated as total # of unweighted errors, plus twice the sum of critical and hazardous errors. Concentration errors were also noted.

Critical errors = errors which would in normal circumstances cause test termination (turning from improper lane, dangerous maneuver, examiner intervention needed).

Hazardous errors = dangerous maneuver or examiner intervention.

Concentration errors = subject unable to proceed to field office at end of test, or drove past the street on which the field office was located and did not recognize their error.

 

Novato, Marin County California; Buck Center for Research in Aging

Performance on the 10 ft walk was not significantly correlated to weighted error score on the drive test (r=0.174, p=0.083)

Janke and Hersch (1997)

PHYSICAL CAPABILITIES

Range of Motion:

Left-Knee Flexion

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. 57% were males.

A battery of physical performance items included balance (side-to-side stand, tandem stand, single-leg stand, and withstanding a sternal nudge), and was scored on a 4-point scale, with 1 point given for each item done without instability. Strength and range of motion were determined using manual muscle testing of shoulder abduction, grasp, hip flexion, knee flexion, and knee extension: these were categorized as good (full resistance and full range of motion versus fair or poor (less than full resistance or range of motion).

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.

 

New Haven, CT. Subjects were interviewed and given the assessments in their homes by a trained research nurse.

Impaired left-knee flexion was associated with adverse events (relative risk 2.9, CI 95%, 1.2-6.7). 13% of those with intact left-knee flexion had adverse driving events compared to 36% of drivers with impaired left-knee flexion. This difference was significant at the p< .05 level. Left-knee flexion was not entered into the relative risk model due to the small number of participants in the group displaying impaired ability (n=11). Differences in performance on the balance or other range of motion measures were not associated with the occurrence of adverse driving events.

Marottoli, Cooney, Wagner, Doucette, and Tinetti (1994)

PHYSICAL CAPABILITIES

Range of Motion:

Neck Flexibility

60 subjects across 4 groups (15 S=s each group):

*Age 30-50 with impairment

*Age 30-50 no impairment

*Age 60-80 with impairment

*Age 60-80 no impairment

Impairment was defined by a combined static range of movement of the head/neck and visual field of less than 285 degrees. 285 degrees was based on the functional requirements for driving, in the absence of a definition of impairment in the literature.

S=s were recruited through local ads and agencies (AARP and Arthritis Foundation). All held valid driver=s license and drove at least 10 mi/wk

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.

18 video-taped intersection scenarios provided 2 levels of traffic volume (light traffic = gap lengths of 8 s or more; moderate traffic = gap lengths of less than 8 s) and 3 levels of intersection sight distance (AASHTO standard, less than standard, and above standard). Each scene covered a 180-degree field of view.

Subjects depressed the brake in the simulator at the beginning of each scene, and released the pedal when they thought it was safe to turn left. An audible beep signaled that decision timing was beginning for each scene. Subjects= response time was the principal dependent measure.

Static range of motion was measured with a goniometer, and visual field was measured with an Ortho Rater.

Turner Fairbank Highway Research Center at FHWA

*Differences in average decision time between young/middle aged and older drivers were significant (11.3 s vs 13.3 s, p=.04). Older drivers took 2 seconds longer to decide to turn at T-intersections than younger drivers. [A smaller left-turn decision time indicates better driving performance, because it provides a driver with a larger gap into which he/she can maneuver and accelerate without affecting the speed of the traffic stream]

*Average decision times by age and impairment level are shown below. Differences were significant at the p=.08 level.

Age 30-50 with impairment 11.4 s

Age 30-50 no impairment 11.3 s

Age 60-80 with impairment 14.4 s

Age 60-80 no impairment 12.1 s

*Younger 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 were not.

*Older impaired drivers are at a greater risk at intersections as a result of their slowed decision making ability coupled with their inability to turn their heads/necks to check for intersecting traffic. Intersections with limited sight distance or skewed geometry further exacerbate problems for this group.

 

Hunter-Zaworski (1990)

PHYSICAL CAPABILITIES

Range of Motion:

Neck Flexibility

82 "referred" subjects aged 60-91 (26 of which were identified as probably being cognitively impaired to some degree). The drivers were referred to the DMV for reexamination due to a medical condition (by physician, optometrist, ophthalmologist), a series of licensing test failures, a flagrant driving error (police referral), or some other indicator of driving impairment.

Subject=s neck rotation to the left and right was measured manually with a goniometer.

Multiple linear regressions were conducted to arrive at the best linear combination of variables for predicting performance (weighted error score) on a standard DMV road test, (see On-road Performance Measures of Driving Safety: California MDPE at the end of this Compendium), and comparisons were made between cognitively impaired and cognitively non-impaired referral drivers to determine whether there were differences in performance.

 

California DMV Field Office

No significant correlation between neck flexibility and weighted error score on drive test.

 

Janke & Hersch (1997)

Staplin, Gish, Decina, Lococo, and McKnight (in press)

PHYSICAL CAPABILITIES

Range of Motion:

Multiple Measures

*Trunk

*Neck

*Shoulder

105 drivers licensed in Nebraska, aged 65-88 (mean age = 71.4). 54 were females (mean age = 70.5 years); 51 were males (mean age = 72.2 years). All subjects were volunteers, and were paid $25.00 for participating. 36 had taken a driver education course in the past 10 years.

Measures were taken in the clinic with the subject seated upright in a straight-back chair with both feet on the floor. These included:

(1) Neck flexion, (2) Neck extension, (3) Neck rotation to the left, (4) Neck rotation to the right,

(5) Neck lateral bend to the left, (6) Neck lateral bend to the right, (7) Left shoulder flexion, (8) Right shoulder flexion, (9) Trunk rotation to the left,

(10) Trunk rotation to the right.

Measures were also taken in the car with the subject seated behind the steering wheel, the seat belt fastened, and the subject=s hands in their normal driving position on the steering wheel. These included:

(1) Neck flexion, (2) Neck extension, (3) Neck rotation to the left, (4) Neck rotation to the right,

(5) Neck lateral bend to the left, (6) Neck lateral bend to the right.

Three measures of each motion were taken and the average of the three was used.

The driving performance of the subjects was evaluated using the on-street driving performance measurement (DPM) technique developed by Vanosdall and Rudisill (1979). The subjects were evaluated by a driver education expert trained in the use of the DPM technique, while they drove in their own cars. The DPM route was a 19-km circuit designed to evaluate the subjects in the situations that are most often involved in the accidents of older drivers. Therefore, their performance was evaluated at 7 intersections where they were required to make left turns at 5 intersections and right turns at the other 2 intersections. Four of the left turns were made from left-turn lanes onto four-lane divided arterial streets in suburban areas, and one was made from a left turn lane onto a two-lane one-way street in an outlying business district.

University clinic, and in-vehicle, on-road test.

None of the range of motion measures were significantly correlated with driving performance. All of the measures had relatively low correlations; the highest correlations were for the in-clinic measures of: trunk rotation to the right (0.17, p= 0.074), trunk rotation to the left (0.14, p=0.156), and neck lateral bend to the right (0.15, p= 0.1156)

NOTE: DPM maneuvers did not include maneuvers that require extreme head/neck rotation ability (e.g., lane changing, passing on high-speed roadways).

Tarawneh, McCoy, Bishu, and Ballard (1993).

PHYSICAL CAPABILITIES

Reaction Time:

Brake Reaction Time (DORON)

105 drivers licensed in Nebraska, aged 65-88 (mean age = 71.4). 54 were females (mean age = 70.5 years); 51 were males (mean age = 72.2 years). All subjects were volunteers, and were paid $25.00 for participating. 36 had taken a driver education course in the past 10 years.

Measured with Doron L225 driving simulator. Two 2x3 cm rectangular red lights mounted 4 cm apart on the dashboard simulator flashed in alternating fashion. When both lights turned on at the same time, the subject was to release the gas pedal and press the brake pedal as fast as possible. Six trials were obtained from each subject; the mean time was used to measure the brake reaction time.

The driving performance of the subjects was evaluated using the on-street driving performance measurement (DPM) technique developed by Vanosdall and Rudisill (1979). The subjects were evaluated by a driver education expert trained in the use of the DPM technique, while they drove in their own cars. The DPM route was a 19-km circuit designed to evaluate the subjects in the situations that are most often involved in the accidents of older drivers. Therefore, their performance was evaluated at 7 intersections where they were required to make left turns at 5 intersections and right turns at the other 2 intersections. Four of the left turns were made from left-turn lanes onto four-lane divided arterial streets in suburban areas, and one was made from a left turn lane onto a two-lane one-way street in an outlying business district.

University laboratory.

The correlational coefficient between simulator brake reaction time and driving performance score was -0.15, which was not significant (p=0.1182).

Tarawneh, McCoy, Bishu, and Ballard (1993)