Tailoring in risk communication by linking risk profiles and communication preferences: The case of speeding of young car drivers |
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| Affiliation: | 1. Department of Emergency Medicine, Faculty of Medicine, University of British Columbia, Canada;2. Queensland University, Australia;3. University of British Columbia, Canada;4. Department of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, Canada;5. British Columbia Centre for Disease Control, Canada;6. British Columbia Injury Prevention and Research Unit, Faculty of Medicine, University of British Columbia, Canada;1. School of Human Evolution and Social Change, Simon A. Levin Mathematical Computational Modeling Science Center, Arizona State University, Tempe, AZ, 85281, USA;2. Division of Applied Mathematics, Brown University, Providence, RI, 02906, USA;3. Sciences and Mathematics Faculty, College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ, 85212, USA |
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| Abstract: | Speeding is one of the most relevant risk behaviors for serious and fatal accidents, particularly among young drivers. This study presents a tailoring strategy for anti-speeding communication. By referring to their motivational dispositions toward speeding derived from motivational models of health behavior, young car drivers were segmented into different risk groups. In order to ensure that risk communication efforts would actually be capable to target these groups, the linkage between the risk profiles and communication preferences were explored. The study was conducted on the basis of survey data of 1168 German car drivers aged between 17 and 24 years. The data reveal four types of risk drivers significantly differing in their motivational profiles. Moreover, the findings show significant differences in communication habits and media use between these risk groups. By linking the risk profiles and communication preferences, implications for tailoring strategies of road safety communication campaigns are derived. Promising segmentation and targeting strategies are discussed also beyond the current case of anti-speeding campaigns. |
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| Keywords: | Speeding Young car drivers Risk communication Segmentation Targeting Quantitative analysis Cluster analysis |
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