Authors
Chang Ying Li, Zhen Zhu Jiao, Li Qin Zhang, Hang Li, Meng Yao Wang, Wen Hui Guo, Yu Xin Wang, Yang Wang
Published in
Journal of medical Internet research. Volume 28. Pages e92139. Jul 16, 2026. Epub Jul 16, 2026.
Abstract
Just-in-time adaptive interventions (JITAIs) use real-time data to deliver personalized support at moments of heightened need and may improve dietary behaviors in real-world settings.
The aim of this study is to systematically review the application, characteristics, and effectiveness of JITAIs in dietary health management.
We included human studies evaluating JITAIs-based dietary interventions delivered through digital platforms that used real-time or near-real-time data to tailor intervention content, timing, or intensity. Eligible studies reported at least one behavioral, engagement, physiological, or clinical outcome; reviews, protocols, editorials, commentaries, and studies without outcome data were excluded. We searched PubMed, Embase, Scopus, CINAHL, Web of Science, ClinicalTrials.gov, WHO ICTRP (International Clinical Trials Registry Platform), and ISRCTN (International Standard Randomized Controlled Trial Number) from inception. The initial search was conducted on August 20, 2025, and updated on March 16, 2026; reference lists were also screened manually. Two reviewers independently screened studies and extracted data. Methodological quality was assessed using the 2018 Mixed Methods Appraisal Tool, and reporting quality was assessed using the Mobile Health Evidence Reporting and Assessment checklist. Because of substantial heterogeneity, findings were synthesized narratively. The review was registered in PROSPERO (International Prospective Register of Systematic Reviews; CRD420261285292).
Twenty studies involving 2948 participants were included. Target populations comprised individuals with overweight or obesity, chronic conditions, and eating disorders and the general population engaged in dietary management. Interventions were mainly delivered via smartphone apps, SMS text messaging, wearable-device feedback, and context-triggered notifications. More consistent benefits were observed for proximal behavioral and process outcomes, including fruit and vegetable intake, sodium-restriction behaviors, drinking automaticity, self-monitoring, eating-related behaviors, and responsiveness to prompts. Some studies also reported improvements in distal clinical outcomes, such as body weight, BMI, waist circumference, blood pressure, blood glucose, and selected biochemical indicators. However, these findings were inconsistent, and most studies did not show clear between-group advantages. Common implementation barriers included device incompatibility, variability in digital literacy, geolocation or signal limitations, and burden from frequent prompts.
JITAIs-based dietary interventions appear promising for supporting timely and individualized dietary behavior change, particularly for proximal behavioral outcomes, although evidence for sustained clinical effects remains inconsistent. This review contributes to the JITAIs literature by examining dietary health management as a distinct application domain and by synthesizing evidence that has otherwise been dispersed across broader reviews of digital behavior change and weight management. By integrating intervention characteristics, delivery approaches, triggering mechanisms, and effects across diverse populations, it clarifies methodological and implementation gaps and informs more standardized intervention design and reporting. These findings support the development of scalable, context-sensitive digital dietary interventions for clinical care, chronic disease self-management, weight management, and public health nutrition.
PMID:
42462070
Bibliographic data and abstract were imported from PubMed on 17 Jul 2026.
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