Use of mHealth interventions to enhance self-regulation and self-efficacy in individuals living with obesity: Scoping review

Abstract

Objectives Mobile health (mHealth) technologies are increasingly employed to facilitate lifestyle modification and weight management among individuals with obesity. However, their effectiveness depends on the integration of theory-driven design. Within Social Cognitive Theory, self-regulation and self-efficacy are considered key mechanisms for initiating and sustaining health behavior change. This scoping review aimed to map and categorize mHealth intervention components related to self-regulation and self-efficacy, explore their digital operationalization and personalization strategies, and identify the theoretical frameworks guiding their design. Methods A systematic literature search was conducted across six databases to identify studies that examined mHealth interventions targeting adults living with obesity and addressing behavioral modification in obesity management. The review applied Joanna Briggs Institute (JBI) methodology for scoping reviews and is reported following the PRISMA-ScR guidelines. Results Forty-four studies met the inclusion criteria. Theoretical grounding was present in a total of twenty-five interventions (25/44; 56.8%), with Social Cognitive Theory being the most prevalent framework (15/25; 60%). Findings indicate widespread integration of self-regulation and self-efficacy components within mHealth interventions, operationalized through in-app logs, wearable devices, prompts and reminders, gamification, and social support etc. While mHealth technologies have increasingly integrated advanced sensors and AI-enabled features, the aspect of personalization has remained predominantly static rather than adaptive. The mHealth interventions aimed at managing obesity commonly incorporate components related to self-regulation and self-efficacy, yet theoretical integration, dynamic personalization, and consistent reporting remain limited. Conclusion This scoping review highlights the need for clearer documentation of behavioral mechanisms and proposes reporting recommendations to improve transparency and replicability.