Cargando…
How Users Experience and Use an eHealth Intervention Based on Self-Regulation: Mixed-Methods Study
BACKGROUND: eHealth interventions show stronger effects when informed by solid behavioral change theories; for example, self-regulation models supporting people in translating vague intentions to specific actions have shown to be effective in altering health behaviors. Although these theories inform...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231831/ https://www.ncbi.nlm.nih.gov/pubmed/30274961 http://dx.doi.org/10.2196/10412 |
Sumario: | BACKGROUND: eHealth interventions show stronger effects when informed by solid behavioral change theories; for example, self-regulation models supporting people in translating vague intentions to specific actions have shown to be effective in altering health behaviors. Although these theories inform developers about which behavioral change techniques should be included, they provide limited information about how these techniques can be engagingly implemented in Web-based interventions. Considering the high levels of attrition in eHealth, investigating users’ experience about the implementation of behavior change techniques might be a fruitful avenue. OBJECTIVE: The objective of our study was to investigate how users experience the implementation of self-regulation techniques in a Web-based intervention targeting physical activity and sedentary behavior in the general population. METHODS: In this study, 20 adults from the general population used the intervention for 5 weeks. Users’ website data were explored, and semistructured interviews with each of the users were performed. A directed content analysis was performed using NVivo Software. RESULTS: The techniques “providing feedback on performance,” “action planning,” and “prompting review of behavioral goals” were appreciated by users. However, the implementation of “barrier identification/problem solving” appeared to frustrate users; this was also reflected by the users’ website data—many coping plans were of poor quality. Most users were well aware of the benefits of adopting a more active way of living and stated not to have learned novel information. However, they appreciated the provided information because it reminded them about the importance of having an active lifestyle. Furthermore, prompting users to self-monitor their behavioral change was not sufficiently stimulating to make users actually monitor their behavior. CONCLUSIONS: Iteratively involving potential end users offers guidance to optimally adapt the implementation of various behavior change techniques to the target population. We recommend creating short interventions with a straightforward layout that support users in creating and evaluating specific plans for action. |
---|