ArticleObesity reviews : an official journal of the International Association for the Study of Obesity2026
Artificial Intelligence Interventions Targeting Obesity-Related Behaviors: Protocol for a Scoping Review.
Article in Obesity reviews : an official journal of the International Association for the Study of Obesity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objective of this scoping review is to examine the nature, extent, and impact of AI-supported interventions that include an AI agent intended to influence obesity-related behavior change. Empirical studies published from 2020 to 2025 examining AI-supported interventions that provide personalized feedback, support natural language communication, or adapt content based on user progress will be included. A search of Scopus, Web of Science, and PubMed will be undertaken, limited to English-language publications, with backward and forward citation searching to improve coverage. Data will be extracted and synthesized narratively by AI agent characteristics, interaction design, targeted behaviors, and intervention outcomes using descriptive statistics and thematic analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.