Currently submitted to: Journal of Medical Internet Research
Date Submitted: May 20, 2026
Open Peer Review Period: May 21, 2026 - Jul 16, 2026
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Global trends in digital behavior change interventions for overweight/obesity: a bibliometric and scoping review
ABSTRACT
Background:
Obesity represents a major global public health challenge. Digital behavior change interventions (DBCIs) have emerged as scalable, technology-enabled strategies for delivering evidence-based behavioral interventions using behavior change techniques (BCTs). However, current evidence remains fragmented regarding global research trends and the multi-dimensional distribution of BCTs within DBCIs across populations, intervention types, and health outcomes.
Objective:
This study aims to explore DBCIs among overweight and obese adults, focusing on temporal trends in research and patterns of BCTs utilization.
Methods:
A combined bibliometric analysis and scoping review was conducted based on publications from the Web of Science Core collection up to 2025. Publication trends, global collaboration pattern, digital technologies, BCT usage, intervention outcomes, and evidence gaps were systematically analyzed.
Results:
Research on DBCIs for obesity has grown rapidly since 2007, with leading contributions from high-income countries, accompanied by strengthened international collaboration and a gradual shift toward interdisciplinary and integrated digital health approaches. BCTs are typically applied in combination, with self-monitoring (79.4%) and goal setting (73.7%) as the core techniques, mainly targeting diet and physical activity. Their distribution varies significantly across digital technology types, targeted behaviors, clinical outcomes, and comorbid conditions.
Conclusions:
Current DBCIs prioritize behavioral self-regulation and cardiometabolic risk improvement. To enhance long-term sustainability and real-world effectiveness, future interventions should adopt a theory-driven framework, integrate psychological and physiological components, and implement personalized adaptive designs. Furthermore, integrating a big data-enabled systems paradigm of behavior will enable more dynamic, mechanism-informed, and proactive DCBIs for obesity management.
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