THE ROLE OF MOBILE HEALTH APPLICATIONS IN CHRONIC DISEASE MANAGEMENT: CURRENT EVIDENCE ON DIABETES, HYPERTENSION, OBESITY, AND REMOTE PATIENT MONITORING- NARRATIVE REVIEW
DOI:
https://doi.org/10.31435/ijitss.3(51).2026.6451Keywords:
Mobile Health (mHealth), Wearable Technologies, Chronic Disease Management, Disease Prevention, Physical Activity, Digital Health, Remote Patient Monitoring, Artificial IntelligenceAbstract
Background Chronic non-communicable diseases (NCDs), including diabetes mellitus, hypertension, and obesity, remain the leading causes of morbidity, mortality, and healthcare expenditure worldwide [1]. Effective management of these conditions requires continuous monitoring, long-term adherence to treatment, and sustained lifestyle modification. The rapid development of mobile health (mHealth) technologies has created new opportunities to support chronic disease management through smartphone applications, wearable devices, remote patient monitoring (RPM), and artificial intelligence (AI) [52-55].
Objective This review aimed to critically evaluate current evidence regarding the effectiveness of mobile health applications in diabetes mellitus, hypertension, and obesity, with particular emphasis on wearable technologies, remote patient monitoring, and artificial intelligence.
Methods A narrative literature review was performed using PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar. Systematic reviews, meta-analyses, randomized controlled trials, observational studies, and international guidelines published between 2018 and 2026 were included.
Results Current evidence indicates that mobile health technologies improve glycaemic control, blood pressure management, body weight reduction, medication adherence, patient engagement, and lifestyle modification [7–18,29–39,46–51].
Conclusions Mobile health technologies represent valuable tools facilitating long-term chronic disease management and preventive healthcare. Upcoming research should focus on implementation strategies, lasting effectiveness, interoperability, and safe embedding of artificial intelligence into routine clinical practice [46–58].
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Copyright (c) 2026 Natalia Wiktorzak, Olga Stasiak, Bartosz Gawior, Paweł Klimas, Justyna Laskus, Gracjan Koźma, Longin Rudnicki, Dominika Kochan-Olszewska, Jagoda Prządka, Julia Lipska, Jakub Pawlicki, Alicja Sołtan, Małgorzata Witaszczyk, Marta Borkowska
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