A dynamic Bayesian network approach to modeling engagement and walking behavior: insights from a yearlong micro-randomized trial ( <i>Heartsteps II</i> )
The results demonstrate the benefits of DBNs to model the daily-level idiographic behavioral dynamics of engagement in digital intervention studies. This approach can be leveraged to support the refinement of dynamic theories of behavior change and improving personalized mHealth intervention strategies.
Authors
- Predrag Klasnja (ORCID: https://orcid.org/0000-0002-4570-703X)
- Donna Spruijt‐Metz (ORCID: https://orcid.org/0000-0002-3884-4300)
- Misha Pavel (ORCID: https://orcid.org/0000-0002-8023-6405)
- Benjamin M. Marlin (ORCID: https://orcid.org/0000-0002-2626-3410)
- Mohamed El Mistiri (ORCID: https://orcid.org/0000-0002-0973-812X)
- Daniel E. Rivera (ORCID: https://orcid.org/0000-0002-3141-0577)
- Steven A. De La Torre (ORCID: https://orcid.org/0000-0002-3303-8270)
- Eric B. Hekler (ORCID: https://orcid.org/0000-0002-7434-0775)
- Karine Tung
Institutions
- University of Southern California (US)
- Northeastern University (US)
- Amherst College (US)
- University of Massachusetts Amherst (US)
- University of Michigan (US)
- California Southern University (US)
- University of California System (US)
- University of California San Diego (US)
- Human Longevity (United States) (US)
- Arizona State University (US)
- Universidad del Noreste (MX)
Publication Details
- Journal
- Health Psychology and Behavioral Medicine
- Published
- 2025-09-18
- DOI
- https://doi.org/10.1080/21642850.2025.2552479
- Primary Topic
- Mental Health Research Topics
- Type
- article
- Field-Weighted Citation Impact
- 0.00