Should I Drive Today? Development of a daily driving decisions model for older adults |
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| Institution: | 1. University of Cagliari — CRiMM, via San Giorgio 12, Cagliari 09124, Italy;2. Technical University of Denmark — DTU, Bygningstorvet 116B, Lyngby 2800, Denmark;1. University of Lyon, France;2. CNRS Research Engineer, France;3. University of Lyon-CNRS, France;1. The School of Psychology, the University of Newcastle, Callaghan, NSW, Australia;2. The School of Psychology, the Australian National University, Canberra, ACT, Australia;1. Postdoctoral Research Associate, Department of City and Regional Planning, University of North Carolina, Chapel Hill, New East Building, CB3140, Chapel Hill, NC 27599, United States;2. Humphrey School of Public Affairs, University of Minnesota, Twin Cities, United States;1. School of Population and Global Health, The University of Western Australia, Clifton Street Building, Nedlands, Perth, WA 6009, Australia;2. Western Australian Centre for Road Safety Research, School of Population and Global Health, The University of Western Australia, Clifton Street Building, Nedlands, Perth, WA 6009, Australia;1. Department of Sociology and Gerontology, Miami University, Oxford, OH, USA;2. University of Michigan Transportation Research Institute, Ann Arbor, MI, USA;3. Center for Advancing Transportation Leadership and Safety (ATLAS Center), Ann Arbor, MI, USA;4. Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA;5. Department of Health, Behavior and Society, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA;6. Department of Anesthesiology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA;7. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA;8. Bassett Research Institute, Bassett Healthcare Network, Cooperstown, NY, USA;9. Institute of Gerontology, Division of Geriatric and Palliative Medicine, University of Michigan, Ann Arbor, MI, USA;10. Institute for Social Research, University of Michigan, Ann Arbor, MI, USA;11. Monash University Accident Research Centre, Clayton, Victoria, Australia |
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| Abstract: | BackgroundOlder adults in communities make daily decisions about how to meet their transportation needs so they can access services and stay socially connected. With the aging of populations in developed countries, the travel decisions of older adults will have increasing impacts. Research studies have identified different sets of factors that contribute to certain travel decisions, but little research has been directed towards understanding how individuals select information from all available factors, what information they include in their decisions under different circumstances, and the processes they use in making their transportation decisions.MethodsThis exploratory study involved 20 men and 17 women, mean age 78.6 years (range 70–96), who drove weekly. All participants were involved in each phase of the 3-phase study. In Phase 1, a review of the literature and interviews with the participants was used to collect information, and inductive thematic analysis was employed to construct a draft conceptual model of older driver decision-making. In Phase 2, participants completed a stated preference task of written scenarios to demonstrate their decision-making strategies. Results were tabulated and used to refine a final Daily Driving Decisions model. In Phase 3, a card sorting decision task was used to test the model with participants.ResultsThe final dynamic Daily Driving Decisions Model was confirmed to describe decision processes used by the participants in making decisions about how they would meet their transportation needs. The model describes three categories of factors used in decisions, labelled Motivators, Constraint/Enablers and Context, each containing four attribute themes. A significant finding was the variable use of the same item to either constrain or enable the decision to drive depending on the variation of other factors in the scenario. Participants demonstrated use of compensatory and noncompensatory (heuristic, habitual) decision processes that were accommodated by the model.ConclusionThe proposed Daily Driving Decisions Model addresses a gap in our understanding of how older drivers make their decisions about meeting their transportation needs. The model presents a template for classifying the types of information used, ignored or discarded by older adults, and the pathways that they take to arrive at their decisions. The model provides opportunities for further research in testing the influence of other factors such as urban/rural residence, income, health status and culture on driving decisions. Further, the model can be used by practitioners to gain insight into the decision-making behaviours of individuals and to develop interventions to enhance their decision-making skills. |
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| Keywords: | Decision heuristic Transportation choice Driving self-regulation Driver education Noncompensatory habit |
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