Behavioral Components and Their Tailoring in Participatory Health Interventions for Precision Prevention

Objective: To study which behavioral components are implemented within participatory health interventions for precision prevention, specifically how they are realized as part of the interventions and how the tailoring of the interventions is implemented. Methods: We selected three case studies of pa...

Descripción completa

Detalles Bibliográficos
Autores: Denecke, Kerstin, Rivera-Romero, Octavio, Sánchez Bocanegra, Carlos Luis, Miron-Shatz, Talya, Wynn, Rolf
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/173109
Acceso en línea:https://hdl.handle.net/11441/173109
https://doi.org/10.1055/s-0044-1800715
Access Level:acceso abierto
Palabra clave:Participatory health informatics
Behavior change
Precision prevention
Digital health intervention
Descripción
Sumario:Objective: To study which behavioral components are implemented within participatory health interventions for precision prevention, specifically how they are realized as part of the interventions and how the tailoring of the interventions is implemented. Methods: We selected three case studies of participatory health interventions for precision prevention for three different target groups (children, parents, older adults with chronic conditions). One author with a background in psychology mapped the interventions and the digital functionalities to the 9 intervention functions of the behavioral change wheel (education, persuasion, incentivisation, coercion, training, enablement, modeling, environmental restructuring, restrictions). Results: While the intervention functions persuasion, incentivisation, education, modeling and coercion are implemented in all three interventions under considerations, two techniques (restrictions, and environmental restructuring) were not implemented in any of the three solutions. Training was only applied in one application and enablement in two interventions. We identified significant evidence gaps in both the tailoring process and the effectiveness of behavior change techniques in precision prevention. Conclusion: We conclude that there is a need for more focused studies on the effects of behavior interventions functions in digital health interventions and for design guidelines to improve these interventions for personalized health outcomes, thereby advancing precision prevention in digital health.