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A computational cognitive model of self-efficacy and daily adherence in mHealth
1Palo Alto Research Center, Palo Alto, CA, 94304, USA. pirolli@parc.com.
Abstract:
Mobile health (mHealth) applications provide an excellent opportunity for collecting rich, fine-grained data necessary for understanding and predicting day-to-day health behavior change dynamics. A computational predictive model (ACT-R-DStress) is presented and fit to individual daily adherence in 28-day mHealth exercise programs. The ACT-R-DStress model refines the psychological construct of self-efficacy. To explain and predict the dynamics of self-efficacy and predict individual performance of targeted behaviors, the self-efficacy construct is implemented as a theory-based neurocognitive simulation of the interaction of behavioral goals, memories of past experiences, and behavioral performance.
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Motivation, the driving force behind behavior, plays a pivotal role at every stage of the change process. The research...
