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The present study examined whether cancer prevention is a meaningful source of exercise motivation using Protection Motivation Theory (PMT). Participants were 427 undergraduate students randomly assigned to read one of 16 persuasive communications that independently manipulated perceived vulnerability (PV), perceived severity (PS), response ef cacy (RE) and self-ef cacy (SE). A factorial ANOVA indicated a signi cant main effect for PS and a signi cant interaction between PS and RE. The interaction was such that individuals who were led to believe that colon cancer was a severe disease (high PS) were more motivated to exercise if they also believed that exercise was effective (high RE) as opposed to ineffective (low RE) in reducing their risk of colon cancer. Conversely, individuals led to believe that colon cancer was not a very severe disease (low PS)were not differentially motivated to exercise based on their RE beliefs. It was concluded that cancer prevention may be a meaningful source of exercise motivation but that further research is required to determine the replicability and generalizability of these results.

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This study highlights a successful multi-site collaboration. Physical activity data from nine large-scale, health trials was combined and accumulated behavioral validation evidence for the physical activity SOC.

The purpose of this study was to identify the population prevalence across the stages of change (SoC) for regular physical activity and to establish the prevalence of people at risk. With support from the National Institutes of Health, the American Heart Association, and the Robert Wood Johnson Foundation, nine Behavior Change Consortium studies with a common physical activity SoC measure agreed to collaborate and share data. The distribution pattern identified in these predominantly reactively recruited studies was Precontemplation (PC) = 5% (+/- 10), Contemplation (C) = 10% (+/- 10), Preparation (P) = 40% (+/- 10), Action = 10% (+/- 10), and Maintenance = 35% (+/- 10). With reactively recruited studies, it can be anticipated that there will be a higher percentage of the sample that is ready to change and a greater percentage of currently active people compared to random representative samples. The at-risk stage distribution (i.e., those not at criteria or PC, C, and P) was approximately 10% PC, 20% C, and 70% P in specific samples and approximately 20% PC, 10% C, and 70% P in the clinical samples. Knowing SoC heuristics can inform public health practitioners and policymakers about the population's motivation for physical activity, help track changes over time, and assist in the allocation of resources.