Effect of Values and Technology Use on Exercise: Implications for Personalized Behavior Change Interventions
This work addresses personalized behavior change interventions for health and fitness, offering incremental insights by linking values and technology use to exercise habits.
The study tackled predicting physical exercise behavior by analyzing a dataset of 15k US residents combining technology use logs with surveys on values, achieving a weighted AUROC of .673 for exercise prediction and showing app usage data improves classification performance over demographics or browsing data.
Technology has recently been recruited in the war against the ongoing obesity crisis; however, the adoption of Health & Fitness applications for regular exercise is a struggle. In this study, we present a unique demographically representative dataset of 15k US residents that combines technology use logs with surveys on moral views, human values, and emotional contagion. Combining these data, we provide a holistic view of individuals to model their physical exercise behavior. First, we show which values determine the adoption of Health & Fitness mobile applications, finding that users who prioritize the value of purity and de-emphasize values of conformity, hedonism, and security are more likely to use such apps. Further, we achieve a weighted AUROC of .673 in predicting whether individual exercises, and we also show that the application usage data allows for substantially better classification performance (.608) compared to using basic demographics (.513) or internet browsing data (.546). We also find a strong link of exercise to respondent socioeconomic status, as well as the value of happiness. Using these insights, we propose actionable design guidelines for persuasive technologies targeting health behavior modification.