Simple mental and physical health measures predict long-term older adult driving difficulty
I’m excited to share that my latest published article entitled “On the road to retirement: Predicting nighttime driving difficulty and cessation using self-reported health factors” has been published in the Journal of Transport & Health.
Examining predictors of older driver nighttime driving difficulty is important because avoiding nighttime driving is often the first self-regulation behavior by older drivers. Being knowledgeable about the risk factors like the ones we evaluated could help practitioners identify those at risk for near-term driving difficulty and develop a driving maintenance or driving retirement plan.
Indeed, we found many self-reported physical and mental health factors were predictive of 5-year and 10-year changes in nighttime driving difficulty!
An interactive transition probability matrix tool based on our modeling is freely available as a download. The tool guides a user through entering an older driver’s demographics (like age, sex) and simple health status measures (like anxiety symptoms, physical functioning). Based on our modeling, this information is used to calculate probabilities that the older driver will transition to different levels of nighttime driving difficulty (none, some or much difficulty, unable to do) in the next five years. Varying exactness in matching the model inputs and the study sample are offered for comparison.
The article and the transition probability matrix tool are freely available through my author link until January 7th, 2024.
Partial screenshot of the transition matrix tool.
Users can enter data on the left and see how it changes the probability of 5-year changes in nighttime driving difficulty in the table on the right.
Article Abstract
Introduction
Older drivers now expect to drive longer than previous cohorts and will make up about 25% of licensed U.S. drivers by 2050. Identifying early predictors of nighttime driving difficulty, a precursor to driving retirement, can inform screening procedures and timely linkage to interventions supporting driving or transitioning to driving cessation.
Methods
We examined self-reported physical and mental health baseline predictors of greater nighttime driving difficulty in five and ten years using weighted multivariate logistic analyses of 2261 drivers, aged 57 to 85, from the National Social Life, Health, and Aging Project (NSHAP). Transition matrix models describe probabilities of having greater, lesser, or the same nighttime driving difficulty after five years based on baseline driving conditions and the significant logistic model factors. We built a transition matrix tool that offers users the ability to calculate expected probabilities of change in nighttime driving difficulty based on the identified salient factors.
Results
Five-year predictors of greater nighttime driving difficulty included perceived poor physical health (OR = 3.75), limitations to activities of daily living (ADLs; OR = 1.97), and clinical levels of depressive and anxiety symptoms (OR = 1.63; OR = 1.71). Excellent physical health (OR = 0.52), mental health (OR = 0.60), and any frequency of physical activity compared to ‘never’ were protective (OR = 0.37–0.51). Physical health, walking pain, and limitations to ADLs were predictive at ten-years. Transition models showed physical health and anxiety were most indicative of greater nighttime driving difficulty at 5-years for those reporting no difficulty at baseline, but limitations to ADLs were more predictive otherwise.
Conclusions
Lay practitioners could capitalize on the use of self-report screening measures to identify older adults who may experience near-term nighttime driving difficulty. Earlier identification may better guide long-term driving retirement planning or engagement in appropriate health interventions. The transition matrix modeling tool is freely available to facilitate development and validation of related measures.