ArticleArthritis care & research2026
A Scoping Review on Artificial Intelligence-Supported Interventions for Nonpharmacologic Management of Chronic Rheumatic Diseases.
Article in Arthritis care & research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- A Beginner's Guide to Applying Large Language Models in Behavioral Interventions.JMIR mHealth and uHealth · 2026Article
- Evaluating the performance and acceptability of an artificial intelligence digital health exercise platform in females with and without axial spondyloarthritis: a phase I study.Advances in rheumatology (London, England) · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review summarizes artificial intelligence (AI)-supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI-supported interventions for adults with chronic rheumatic diseases. Eligible interventions targeted clinical outcomes (pain, function, disability, fatigue), psychological measures (depression, anxiety), or behavioral outcomes (physical activity, nutrition). All publication types (journal articles, conference abstracts, protocols) published in the English language until January 19, 2025, were considered, and interventions of any duration, frequency, country of origin, or setting (inpatient, outpatient, community, home setting) were included. Two reviewers independently screened studies, and one extracted data on study characteristics, intervention components, AI methodologies, and outcomes. Fifteen AI-supported interventions were identified, primarily targeting osteoarthritis (73%) and focusing on education and exercise advice (67%). The most common AI tool was rule-based expert systems (40%), followed by natural language processing systems (33%) and machine learning algorithms (27%). The interventions ranged from 3 weeks to 12 months, whereas sample sizes ranged from 7 to 427 participants, reflecting huge variability across studies. Most interventions demonstrated high usability, engagement, and adherence. Improvements in exercise compliance, physical activity, and symptoms, such as pain and physical function, were reported, though effects varied across studies and were sometimes not sustained long term. AI-supported interventions show promise in promoting education, exercise, and behavioral guidance for adults with chronic rheumatic diseases. There is evidence for high usability and engagement, but the clinical impact on long-term symptom management is uncertain.
Indexed as
Identifiers
What Socratic holds
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.