Artificial intelligence–based chatbots to enhance medication adherence among patients with non-communicable chronic diseases: Systematic review and meta-analysis

Siyu Chen, Yuan Fang, Liwen Ding, Phoenix K H Mo and Zixin Wang

PLOS Digital Health, 2026, vol. 5, issue 7, 1-16

Abstract: Medication adherence remains a major public health challenge among patients with non-communicable diseases (NCDs) worldwide. Artificial intelligence (AI)–based chatbots may enhance adherence by automating reminders, education, and real-time support. This systematic review and meta-analysis evaluated the effectiveness of AI-based chatbots in improving medication adherence among patients with NCDs. This review (CRD420251151031) is reported in accordance with the PRISMA guidelines. Relevant studies were identified from PubMed, MEDLINE, Embase, Web of Science, Global Health, CINAHL, Cochrane Library, APA PsycINFO, and APA PsycArticles up to August 2025. Eligible designs included randomized controlled trials (RCTs), quasi-experimental studies, and single-arm pre–post studies. Seven studies published between 2017 and 2025 were included, of which six RCTs contributed to the meta-analysis. The pooled standardized mean difference (SMD) for medication adherence was 0.69 (95% confidence interval: 0.17 to 1.22; p = 0.01), indicating a significant medium effect with high heterogeneity (I2 = 97%). Subgroup analyses revealed greater effects for cardiovascular diseases and short-term interventions (

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pdig00:0001507

DOI: 10.1371/journal.pdig.0001507

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