SynthesisDiabetic medicine : a journal of the British Diabetic Association2026
A systematic review of the use of artificial intelligence in mental health-based diabetes care: Current applications and future directions.
Synthesis in Diabetic medicine : a journal of the British Diabetic Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of the use of artificial intelligence in mental health-based diabetes care: Current applications and future directions.Diabetic medicine : a journal of the British Diabetic Association · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsTo map and systematise existing research on the use of artificial intelligence (AI) in mental health-based diabetes care contexts, identify trends and potential gaps in the literature, examine methodological limitations and highlight future research directions.
methodsThe review adhered to PRISMA guidelines and was pre-registered on PROSPERO (CRD420251167053). Comprehensive searches were conducted across nine databases, including MEDLINE, EMBASE, PsycINFO and IEEE Xplore, using a Boolean strategy that combined terms related to diabetes, AI and clinical mental health. Inclusion criteria encompassed peer-reviewed, empirical, quantitative studies involving humans, diabetes contexts, mental health factors and AI-based methodologies. Screening and data extraction were performed independently by two reviewers. Forty-one studies ultimately met the inclusion criteria.
resultsResearch on AI in mental health-based diabetes care contexts has grown substantially since 2020. Most studies employed observational (83%) and cross-sectional (56%) designs, focused on assessment rather than intervention (88%) and targeted depression (56%). Supervised learning algorithms were most frequently used (83%); however, deep learning models achieved the highest performance. Despite technological advances, no temporal improvement in algorithmic performance was observed. Methodological limitations included limited diversity in samples and outcomes, minimal use of prospective experimental and randomised controlled trial-based designs and overreliance on supervised learning algorithms.
conclusionsAI shows promise in addressing mental health needs in diabetes care. However, current research is narrow in scope and lacks methodological rigour in some respects. Future studies might profitably prioritise diverse populations, prospective designs, interpretability and clinical utility to enable safe, effective and equitable integration of AI into person-centred diabetes care.
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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 OpenQuestion graph.