Transportation and Aging: A Research Agenda for Advancing Safe Mobility
Bibliographic record
Abstract
PURPOSE: We review what we currently know about older driver safety and mobility, and we highlight important research needs in a number of key areas that hold promise for achieving the safety and mobility goals for the aging baby boomers and future generations of older drivers. DESIGN AND METHODS: Through the use of a framework for transportation and safe mobility, we describe key areas of screening and assessment, remediation and rehabilitation, vehicle design and modification, technological advancements, roadway design, transitioning to nondriving, and alternative transportation to meet the goals of crash prevention and mobility maintenance for older adults. RESULTS: Four cross-cutting themes emerged from this review: safe transportation for older adults is important; older adults have a variety of needs, abilities, and resources; research to help meet the transportation needs of older adults may be of benefit to persons with disabilities; and transportation issues concerning older adults are multifaceted. IMPLICATIONS: Safe mobility is essential to continued engagement in civic, social, and community life, and to the human interactions necessary for health, well-being, and quality of life. When safe driving is no longer possible for older adults, safe and practicable alternative transportation must be available. Furthermore, older adults are individuals; they have specific needs, abilities, and resources. Not all older adults will have difficulty meeting their transportation needs and no single transportation solution will work for all people. Research and countermeasures intended to help meet the transportation needs of older adults will likely also benefit younger users of the transportation system, particularly those with disabilities. The issues surrounding the maintenance of safe transportation for older adults will require an interdisciplinary research approach if we are to make significant progress in the next decade as the baby boomers begin to reach age 70.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.010 | 0.023 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".