Just-In-Time Adaptive Interventions to Promote Behavioral Health: Protocol for a Systematic Review
Bibliographic record
Abstract
BACKGROUND: The goal of just-in-time adaptive interventions (JITAIs) is to use mobile, digital tools to provide individuals with personalized interventions at the optimal time and in the optimal context. Accordingly, JITAIs are promising for advancing accessible, equitable, and evidence-based treatment for behavioral health. To guide future inquiry in this space, a review of the literature is needed to describe the state of research on JITAIs for behavioral health. OBJECTIVE: This study aims to systematically review the literature to describe the landscape of existing JITAIs for behavioral health at any stage of intervention development. In addition, conditional upon a sufficiently homogeneous literature, we will conduct meta-analyses to investigate the effectiveness of JITAIs for promoting distal outcomes (here, aspects of behavioral health) and proximal outcomes (eg, emotion regulation). METHODS: This systematic review is being conducted in accordance with the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols). We developed our search strategy and executed the literature search in collaboration with biomedical librarians; 5 databases (PubMed, Embase, Cochrane Library, Web of Science: Core Collection, and APA PsycINFO) were searched, and results were managed using EndNote 20 (Clarivate). We are screening (title, abstract, and full text) all records in duplicate in Covidence according to eligibility criteria. Data items will be extracted, and risk of bias will be assessed in duplicate from the included articles in Covidence. We will summarize JITAI characteristics in tables and text. We will conduct meta-analyses for the distal and proximal outcomes conditional upon sufficient homogeneity in subgroups. Moderation (conditional upon sufficient heterogeneity of outcomes) and mediation (ie, whether changes in proximal outcomes mediate the relation between JITAIs and distal outcomes) will be conducted as appropriate. We will investigate publication bias and use the Grading of Recommendations Assessment, Development and Evaluation to characterize the quality of evidence of our estimates. RESULTS: The search strategy was developed between July 2023 and November 2023. The literature search was executed between November 2023 and December 2023. Title and abstract screening began in December 2023, and full-text screening began in May 2024. Data extraction and analyses have not begun. CONCLUSIONS: Here, we propose a systematic review to assess the state of the literature on JITAIs for behavioral health. The insights derived from this study will describe the literature on JITAIs in promoting behavioral health, reinforce JITAI definitions, clarify JITAI elements, and inform the next steps in JITAI research. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/58917.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.092 | 0.106 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.021 | 0.020 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.081 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".