Exploring the Dynamics of Dietary Self-Monitoring Adherence Among Participants in a Digital Behavioral Weight Loss...

Area of Science:

• Behavioral science
• Cognitive science
• Digital health interventions

Background:

• Self-monitoring is key to behavioral weight loss programs.
• Understanding adherence dynamics in self-monitoring remains a challenge.

Purpose of the Study:

• Develop a prognostic model for adherence to self-monitoring dietary behaviors using the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture.
• Investigate adherence dynamics and intervention impacts through model-based analyses.

Main Methods:

• Utilized ACT-R, a cognitive architecture, to model self-monitoring adherence over 21 days in a digital weight loss program.
• Examined goal pursuit and habit formation mechanisms.
• Analyzed data from 97 participants across self-management, tailored feedback, and intensive support groups.

Main Results:

• The ACT-R model accurately captured adherence trends, with low RMSE values across all intervention groups.
• Goal pursuit dominated adherence, while habit formation decreased over time.
• Tailored feedback and intensive support enhanced goal pursuit and sustained behavioral practice.

Conclusions:

• ACT-R modeling offers potential for analyzing self-monitoring behaviors in digital interventions.
• Tailored feedback combined with intensive support may significantly improve adherence.
• Future research should explore longer interventions, integrate social cognitive factors, and adapt models for just-in-time interventions.