Volume 17, Issue 1 (9-2026)
3 2026, 17(1): 25-38 |
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Hosseini H S, Sohrabi M, Kiaei M. Artificial Intelligence and Mobile Health Applications in Community Health Education: A Systematic Review between 2015 and 2026. 3 2026; 17 (1) :25-38
URL: http://ndhj.lums.ac.ir/article-1-493-en.html
URL: http://ndhj.lums.ac.ir/article-1-493-en.html
Abstract: (6 Views)
Background and Objectives: Artificial intelligence (AI) and mobile health (mHealth) applications are promising tools for enhancing community health education. This systematic review aimed to synthesize the available evidence on the effectiveness of AI- and mHealth-based interventions in community health education.
Materials and Methods: This systematic review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A comprehensive search was performed in PubMed, Scopus, CINAHL, Web of Science, and Embase for studies published from January 1, 2015, to June 30, 2026. Quantitative, qualitative, and mixed-methods studies evaluating AI- or mHealth-based interventions in community health education were included.
Results: Twenty-eight studies met the inclusion criteria. Of these, 21 studies (75.0%) reported significant improvements in health-related knowledge, and 17 studies (60.7%) demonstrated positive behavioral changes. AI-based interventions were associated with greater potential for personalized education and increased user engagement. Several studies also reported favorable clinical outcomes, including reductions in HbA1c levels. The main barriers identified were limited digital literacy and inadequate internet access, particularly in rural areas.
Conclusion: AI- and mHealth-based interventions can improve community health education. However, their effectiveness depends on intervention design quality, technological infrastructure, digital literacy, and cultural adaptation. These findings may guide community health nurses and healthcare policymakers in settings similar to Iran.
Keywords: Artificial Intelligence, Mobile Health (mHealth), Community Health Education, Community Health Nursing, Health Promotion, Systematic Review
Materials and Methods: This systematic review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A comprehensive search was performed in PubMed, Scopus, CINAHL, Web of Science, and Embase for studies published from January 1, 2015, to June 30, 2026. Quantitative, qualitative, and mixed-methods studies evaluating AI- or mHealth-based interventions in community health education were included.
Results: Twenty-eight studies met the inclusion criteria. Of these, 21 studies (75.0%) reported significant improvements in health-related knowledge, and 17 studies (60.7%) demonstrated positive behavioral changes. AI-based interventions were associated with greater potential for personalized education and increased user engagement. Several studies also reported favorable clinical outcomes, including reductions in HbA1c levels. The main barriers identified were limited digital literacy and inadequate internet access, particularly in rural areas.
Conclusion: AI- and mHealth-based interventions can improve community health education. However, their effectiveness depends on intervention design quality, technological infrastructure, digital literacy, and cultural adaptation. These findings may guide community health nurses and healthcare policymakers in settings similar to Iran.
Keywords: Artificial Intelligence, Mobile Health (mHealth), Community Health Education, Community Health Nursing, Health Promotion, Systematic Review
Keywords: Artificial Intelligence, Mobile Health (mHealth), Community Health Education, Community Health Nursing, Health Promotion, Systematic Review
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