The Influence of physical activity on driving performance and cognitive functioning in older adults : a randomized controlled trial
Bibliographic record
Abstract
As individuals age, two central concerns involve driving safely and preserving cognitive faculties. While some research examining fitness effects on elderly cognition has been conducted, little has been done to investigate whether driving performance or driving relevant cognitive abilities might be affected by increased physical activity particularly in sedentary older adults. The present study examined the effects of a 12-week combined aerobic and anaerobic fitness intervention on a sample of older adults with a sedentary lifestyle. Twenty-nine older adults (55 years of age or older, M = 62.93 years) were assigned to either an experimental (n = 16) or wait-list control group (n = 13). Cognitive, driving performance and physical functioning data were collected on all participants at baseline and after the 12-week interval. These measures were selected based on empirical relevance, however some supplementary analyses were more exploratory in nature given the paucity of literature in the area. A significant intervention effect was found for general visual attention and also for selective attention when individual visual attention domains were assessed. A statistically non-significant effect was found for set-shifting/ interference (i.e., Stroop Colour Word Test), however examination of effect size demonstrated that about 9% of group variance was explained by this variable. While expected, significant effects for physical and driving performance were not found. Given the preliminary nature of this research and limitations, more investigation is needed to provide more conclusive inferences. Future research directions are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".