An online driving decision aid for older drivers reduces ambivalence and regret about driving decisions: Randomized trial

Betz, Marian E.; Fowler, Nicole R.; Fowler, Nicole R.; Han, S. Duke; Hill, Linda L.; Knoepke, Christopher E.; Matlock, Daniel D.; Johnson, Rachel L.; Peterson, Ryan A. · 2025 · Journal of the American Geriatrics Society

DOI: 10.1111/jgs.19293

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Summary

This randomized controlled trial evaluated the efficacy of an online driving decision aid (DDA) in reducing psychosocial distress among older adults facing decisions about driving cessation. The study was motivated by the significant emotional burden associated with driving retirement, which is often linked to declines in health and cognitive function. While driving cessation is necessary for safety, it can lead to feelings of powerlessness, depression, and reduced quality of life. Few older adults plan for this transition, and clinicians lack standardized tools to facilitate these complex discussions. The researchers hypothesized that a structured DDA would reduce decisional conflict (ambivalence) and decision regret compared to general informational resources, without negatively impacting mobility or safety. The study enrolled 301 licensed drivers aged 70 and older who had at least one medical diagnosis associated with increased risk of driving cessation but no significant cognitive impairment. Participants were randomized to either the intervention group, which used the Healthwise® online DDA addressing “Is it time to stop driving?”, or the control group, which viewed general safety information from the National Institute on Aging. Outcomes were assessed at baseline and at 6, 12, 18, and 24 months. Primary outcomes included decisional conflict, decision regret, and depression, measured using validated scales. Secondary outcomes included community mobility (Life-Space Assessment), driving comfort, crash reports, and driving frequency. Data were analyzed using generalized linear mixed models to account for repeated measures and missing data. Results indicated that the DDA significantly reduced decisional conflict immediately post-intervention (adjusted mean ratio [aMR] = 0.87) and decision regret at 12 months (aMR = 0.45) and 18 months (aMR = 0.57) compared to the control group. The reduction in regret persisted longer than the reduction in conflict. However, the DDA did not significantly reduce the overall odds of depression during the follow-up period, although exploratory analysis suggested the DDA’s benefit on decisional conflict was limited to participants without baseline depression. Importantly, the intervention did not adversely affect secondary outcomes; there were no significant differences between groups in community mobility, crash rates, or reductions in driving frequency. Most participants leaned toward continuing to drive, and the DDA did not force cessation but rather supported informed decision-making. The findings suggest that online driving decision aids can effectively reduce uncertainty and regret associated with driving decisions among older adults, potentially improving the psychological experience of this transition. The DDA did not compromise safety or mobility, indicating it is a safe adjunct to clinical care. The authors conclude that integrating DDAs into clinical settings may help older adults and their families navigate driving retirement with greater clarity and less distress. Future research should explore adaptations of the DDA for individuals with mild cognitive impairment or dementia, who may benefit most from structured decision support but were excluded from this trial.

Key finding

An online driving decision aid reduced uncertainty and post-decision regret about whether to keep driving for two years among older drivers, without harming community mobility or increasing crashes.

Methodology

mixed_methods

Sample size: N=301 (DDA n=150; control n=151); mean age 77.1 years; 51% female

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• mci dementia driving
• older driver retraining
• cognitive impairment
• decision making risk perception

Information type

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• Methodological Resource: validation psychometrics, tool software
• Theoretical Contribution: computational model