2017/12/07 by Yunlong Wang, Wang, Yunlong, Ahmed Fadhil +5
Computer Science · Engineering · Health Professions · Medicine · Psychology · #Artificial intelligence #Behavior change #Behavior change methods #Behavioral Health and Interventions #Behavioural sciences #Bridge (graph theory) #Computer science #Digital Mental Health Interventions #Engineering #FOS: Computer and information sciences #H.5.2 #Health intervention #Human-Computer Interaction (cs.HC) #Knowledge management #Management science #Medicine #Mobile Health and mHealth Applications #Process (computing) #Psychological Theory #Psychological intervention #Psychology #Psychotherapist #Social cognitive theory #Social psychology #Theory of planned behavior #cs.HC
paper · pdf · doi:10.48550/arxiv.1712.02548
arxiv created 2017/12/07 · openalex publication_date 2017/12/07 · arxiv updated 2017/12/08 · openalex created_date 2017/12/22 · openalex updated_date 2026/07/28
Increasing evidence has shown that theory-based health behavior change interventions are more effective than non-theory-based ones. However, only a few segments of relevant studies were theory-based, especially the studies conducted by non-psychology researchers. On the other hand, many mobile health interventions, even those based on the behavioral theories, may still fail in the absence of a user-centered design process. The gap between behavioral theories and user-centered design increases the difficulty of designing and implementing mobile health interventions. To bridge this gap, we propose a holistic approach to designing theory-based mobile health interventions built on the existing theories and frameworks of three categories: (1) behavioral theories (e.g., the Social Cognitive Theory, the Theory of Planned Behavior, and the Health Action Process Approach), (2) the technological models and frameworks (e.g., the Behavior Change Techniques, the Persuasive System Design and Behavior Change Support System, and the Just-in-Time Adaptive Interventions), and (3) the user-centered systematic approaches (e.g., the CeHRes Roadmap, the Wendel's Approach, and the IDEAS Model). This holistic approach provides researchers a lens to see the whole picture for developing mobile health interventions.