Driving Cessation: What Are Family Members’ Experiences and What Do They Think about Driving Simulators?
Bibliographic record
Abstract
BACKGROUND: Driving cessation is difficult for persons living with cognitive decline (PLWCD) and their caregivers (CG). Physicians are often required to notify authorities of driving risks, and typically base decisions on paper-based cognitive assessments and on-road tests. This study examines experiences surrounding cessation and CG's views regarding simulators in the process. METHODS: Semi-structured virtual interviews were conducted with CGs of PLWCD from an academic memory clinic. Experiences around cessation were explored first, followed by discussions regarding the simulator. Framework analysis was applied to transcribed interviews. RESULTS: Six females and two males, three children and five spouses participated. PLWCD viewed driving cessation negatively, often had difficulty understanding why, and believed cessation was temporary. CGs experienced relief and/or shock. Cessation negatively impacted the relationships between the PLWCD and both the physician and CG. Isolation, coping challenges and loss of independence were experienced by the PLWCD. The lives of caregivers were adversely affected, especially regarding driving burden and worsening mental health. CGs were generally supportive of simulators. Positives included: measurement of driving skills, method of testing, and providing an understanding regarding the driving suspension. Potential drawbacks included difficulty using the machine, testing anxiety and stress induced by a crash. Caregivers were concerned about: PLWCD's disappointment of failure, requesting to retest, and reluctance to accept the decision. CONCLUSION: PLWCD and caregivers had negative experiences related to the driving cessation. Generally, caregivers viewed implementing driving simulators positively, in a context of a practice session and support for PLWCD's potential reactions to the decision.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".