Protocol for Candrive II/Ozcandrive, a multicentre prospective older driver cohort study
DOI: 10.1016/j.aap.2013.02.009
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Summary
This paper outlines the protocol for Candrive II/Ozcandrive, a multicentre prospective cohort study designed to develop a valid, easy-to-use in-office screening tool for identifying older drivers who may be unsafe to drive. The research is motivated by the rapid growth of the older adult population and the associated public health concern regarding medical fitness to drive. While driving cessation negatively impacts quality of life and independence, health-related impairments increase the risk of motor vehicle collisions. Currently, clinicians lack reliable scientific data to make individualized decisions regarding driving safety, creating a need for a clinical decision rule that can accurately identify at-risk drivers without generating excessive false positives. The study follows a cohort of drivers aged 70 years or older (minimum age 75 in Australia/New Zealand) for up to four years. Recruitment occurred across seven Canadian cities, two Australian sites, and one New Zealand site, enrolling 928 Canadian participants and 302 Australian/New Zealand participants. Participants undergo comprehensive annual assessments lasting 2.5 to 4 hours, evaluating sensory, physical, cognitive, and psychosocial factors. Specific measures include the Montreal Cognitive Assessment, Mini-Mental Status Examination, Trail Making Test, and various physical function tests. Additionally, participants complete home-based psychosocial questionnaires and are contacted every four months to report health changes or collisions. To objectively quantify driving exposure, an in-vehicle recording device collects data on speed, distance, and location via the vehicle’s on-board diagnostic system. Driving records, including collision reports and violations, are obtained annually from licensing authorities. The primary outcome is the rate of at-fault motor vehicle collisions per kilometre driven, determined by independent experts reviewing collision reports. Secondary outcomes include all collisions and traffic violations. The study design prioritizes high specificity and positive predictive value over sensitivity to minimize the inappropriate identification of safe drivers as at-risk, which could lead to unnecessary license revocation. Statistical analysis will employ logistic regression and recursive partitioning to identify predictor variables associated with at-fault collisions, accounting for repeated measures. Candrive II/Ozcandrive is the largest and longest prospective study of older drivers to date. Its significance lies in its potential to derive a clinical decision rule that helps clinicians identify medically at-risk older drivers with high precision. By combining comprehensive clinical assessments with objective driving exposure data and official collision records, the study aims to provide evidence-based tools for managing older driver safety. This approach addresses the critical balance between maintaining older adults’ independence and ensuring public road safety, offering a robust framework for future validation and implementation of screening protocols in primary care settings.
Key finding
The study protocol describes a large-scale prospective cohort design intended to derive a high-specificity clinical prediction rule for identifying older drivers at risk of at-fault collisions.
Methodology
field_study
Sample size: 1230
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via openalex_abstract on 2026-05-08 (9 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | — | — | — | 1 | 2026-05-07 |
| archive | success | unpaywall | — | — | 2 | 2026-06-06 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-04 |
| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | pubmed | — | — | 10 | 2026-05-27 |
| promote | success | — | — | — | 1 | 2026-05-07 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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- Methodological Resource: dataset resource, tool software, validation psychometrics