Factors Affecting Driving Cessation of Older Adults and Their Satisfaction with Mobility Options
Bibliographic record
Abstract
Out-of-home mobility has been identified as essential for older adults to access activities in their community that keep them healthy and well. As individuals grow older, they are more likely to experience medical conditions and other health-related changes that can affect their ability to drive. Balancing older peoples’ continued mobility against their own and others’ safety has been always a challenge. Therefore, it is important to understand elderly people’s everyday mobility issues and challenges/factors associated with driving cessation. This paper aims to identify and quantify factors contributing to older adults’ satisfaction with their everyday mobility using ordered probit (OP) modeling. Its underlying objective is to provide better understanding of factors that may influence older adults to stop driving. The data used in the analysis was obtained through an online survey of 1,000 Canadians aged 65+. The results of the OP model indicate that several factors affect older adults’ satisfaction with their everyday mobility including driving a car to reach destinations, ability to drive alone (without help from others), experiencing difficulties/challenges with driving, having a physical health issue restricting the ability to walk, fear of falling while walking, and inability to visit local places as often as desirable. The findings also suggest that factors influencing older drivers’ decisions to retire from driving (for those already retired from driving) are different from those perceived by people still driving. The study’s results provide insights about policies and countermeasures that can be implemented to improve the safety and mobility of the aging population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".