Older Drivers in Australia: Trends in Driving Status and Cognitive and Visual Impairment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To investigate self-reported driving status within three Australian states; associations between demographic, health, and functional factors and driving status; and the extent to which remaining a driver in spite of cognitive and visual impairments varies as a function of sex. DESIGN: Secondary data analysis of a pooled data set. SETTING: Australian communities. PARTICIPANTS: Adults aged 65 to 103 (N=5,206) from the Dynamic Analyses to Optimise Ageing (DYNOPTA) project. DYNOPTA is a unique data set created through the harmonization and pooling of data across nine separate Australian longitudinal studies of aging conducted between 1990 and 2007 (N=50,652). MEASUREMENTS: Driving status, demographic characteristics, Mini-Mental State Examination score, visual acuity, physical activity, and occupation. RESULTS: Men and participants with higher-level occupations had greater odds of driving. Older age, more medical conditions, and poorer vision increased the odds of not driving. Persons who were divorced, widowed, or never married were at a greater risk than married adults of not driving. Descriptive analyses revealed a large proportion of men with probable visual or cognitive impairments who reported driving. Subsequent comparative analyses between the DYNOPTA sample and other published U.S. and Canadian data revealed lower proportions of current drivers among Australian women and those at older ages, although there were consistently lower proportions of drivers within Australia and Canada than in the United States. CONCLUSION: The rate of men with probable dementia or visual impairments who reported driving is of particular concern. Research and policy need to focus on evidence-based assessment of older drivers and development of appropriate interventions and programs to maintain the mobility and independence of older adults.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it