Activity Level, Performance and Exposure among Older Drivers
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Summary
This study investigated the relationship between physical activity levels, functional status, and driving performance and exposure among older drivers. Motivated by the aging population and the need to identify countermeasures for crash reduction, the research aimed to determine if drivers aged 70 and older who engage in regular physical activity perform better on driving evaluations and drive more frequently than sedentary peers. The study hypothesized that higher activity levels and cognitive status would correlate with safer driving performance and greater driving exposure. The researchers recruited 67 participants (mean age 78.6) from senior residential communities in Chapel Hill, North Carolina. Inclusion criteria required participants to be licensed drivers with access to a vehicle, while excluding those using adaptive controls or with medical conditions affecting driving safety. Data collection involved three primary components: functional assessments, physical activity measurement, and driving evaluation. Functional status was assessed via head/neck/torso flexibility tests, rapid pace walk tests for lower limb strength, and cognitive tests including the Snellgrove Maze Test and Trail-Making Test Parts A and B. Physical activity was measured using the Phone-FITT questionnaire, VO2max estimates, and ankle-worn pedometers recording steps, gait speed, and active minutes over one month. These metrics were combined into a Unified Physical Activity Index (UPAI). Driving performance was evaluated through a standardized 34-mile on-road test administered by a certified driver rehabilitation specialist, while driving exposure was captured via GPS and video recorders installed in participants’ vehicles for approximately one month of naturalistic driving. The results did not support the hypothesis that higher physical activity levels correlate with better driving performance or greater exposure. Correlations between UPAI scores and road test performance were very weak, accounting for less than 3% of the variance. Similarly, UPAI scores explained less than 1.5% of the variance in driving exposure metrics, such as trip frequency, distance, and scanning behavior. Functional status measures also showed weak correlations with performance and exposure, with the strongest relationship being between head/neck flexibility and shoulder checks, accounting for only 5% of the variance. However, cognitive measures demonstrated stronger predictive value. Logistic regression analysis revealed that poorer performance on the Snellgrove Maze Test and Trail-Making Test Part B significantly predicted failure on the road test. Additionally, Trail-Making Test Part B scores were statistically significant predictors of daily driving minutes. The study concludes that older drivers’ operational behaviors are primarily influenced by habits acquired through years of experience rather than current physical fitness levels. While physical activity did not directly improve driving performance in this sample, the authors suggest that fitness may indirectly support safe driving by preserving cognitive function through improved cardiovascular health. The findings imply that future research should monitor long-term changes in cardiovascular health and cognitive status rather than relying on short-term snapshots of physical activity. Furthermore, the results highlight the importance of cognitive assessments, particularly executive function, in evaluating older driver safety, as these measures showed stronger associations with driving outcomes than physical activity indices.
Key finding
Physical activity levels accounted for less than 3% of the variance in driving performance and exposure, whereas cognitive function tests significantly predicted road test pass/fail outcomes and daily driving minutes.
Methodology
mixed_methods
Sample size: 67
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- exposure measurement
- older drivers
- fitness to drive assessment
- cognitive capacity variation
- mci dementia driving
- sex gender
Information type
What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).
- Empirical Findings: observational prevalence, physiological data
- Methodological Resource: validation psychometrics