Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Apr 28, 2025
Date Accepted: Oct 31, 2025
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Just-In-Time Adaptive Interventions for Weight Management among Adults with Excess Body Weight: A Scoping Review
ABSTRACT
Background:
Just-In-Time-Adaptive-Interventions (JITAIs) hold potential for improving lifestyle behaviors for weight management
Objective:
Aims: To present an overview of how Just-In-Time Adaptive Interventions (JITAIs) have been used or developed for weight management in adults with excess body weight.
Methods:
A scoping review was conducted using Arksey and O’Malley’s five-step framework. Eight electronic databases (PubMed, Cochrane-Central, Embase, CINAHL, PsycINFO, IEEE Xplore, Scopus and Web of Science) were searched from journal inception till 13 November 2024, along with grey literature and hand-searching references.
Results:
Thirty-five studies on JITAIs for weight management were included, focusing on dietary behavior (28/35, 80%), physical activity (21/35, 60%), and self-weighing (6/35, 17.1%). Types of support were prompts (n=29), feedback (n=25), recommendations of coping strategies (n=7) and educational information (n=3). 28.6% of studies used machine learning for decision-making, while the rest used rule-based algorithms. Attrition rates varied from 0% to 31.9%, and compliance from 42.2% to 94.6%. Greater user engagement was associated with improved weight loss outcomes. There were user preferences for lower-demand, context-sensitive interventions and milder feedback. Discussion: While JITAIs show potential for improving lifestyle habits by providing the right intervention, at right time and right setting, most studies lacked theoretical grounding. Nevertheless, most studies have incorporated varied distal and proximal outcomes, behavioral theories support types, intervention delivery methods and data acquisition methods.
Conclusions:
While JITAIs show potential for improving lifestyle habits by providing the right intervention, at right time and right setting, most studies lacked theoretical grounding. Nevertheless, most studies have incorporated varied distal and proximal outcomes, behavioral theories support types, intervention delivery methods and data acquisition methods. This review demonstrates JITAIs’ potential in weight management but highlights the field’s early stage of development. Future research should focus on improving reporting standards, integrating behavioral theories, optimizing user engagement, and exploring machine learning to enhance scalability and effectiveness.
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