THE ROLE OF MOBILE HEALTH TECHNOLOGIES IN TYPE 2 DIABETES MANAGEMENT: CLINICAL EFFECTIVENESS AND SOCIAL CHALLENGES – A NARRATIVE REVIEW
DOI:
https://doi.org/10.31435/ijitss.3(51).2026.6449Keywords:
Blended Care, Digital Health Literacy, mHealth, Telemedicine, Type 2 Diabetes MellitusAbstract
Background: Type 2 Diabetes Mellitus (T2DM) represents a major global healthcare challenge requiring continuous, lifelong multi-factorial self-management. While mobile health (mHealth) technologies are increasingly deployed across clinical pathways to enhance glycemic control, their long-term therapeutic effectiveness is strongly moderated by intervention software architecture, dynamic user engagement patterns, and the overarching socio-technical context.
Objective s: Guided by rigorous narrative standards, this review synthesizes contemporary meta-analytic evidence regarding the comparative clinical efficacy of mHealth modalities on glycated hemoglobin (HbA1c), evaluates the operational impact of hybrid (blended) care models on sustained patient retention, and critically identifies systemic socio-technical barriers to equitable technology adoption.
Methods: Following the Scale for the Assessment of Narrative Review Articles (SANRA) guidelines, a structured literature search of high-level secondary evidence published between 2021 and 2026 was executed across PubMed/MEDLINE, Scopus, and Google Scholar. Implementation hurdles and non-adoption patterns were interpreted through the Non-adoption, Abandonment, Scale-up, Spread, and Sustainment (NASSS) theoretical framework.
Results: Synthesized meta-analyses demonstrate that mHealth modalities achieve statistically significant and clinically meaningful reductions in HbA1c (pooled mean differences ranging from -0.32% to -0.56%). Dynamic short message service (SMS) interventions and multi-parametric smartphone applications yield significantly higher metabolic efficacy than static web platforms. However, purely automated digital interventions experience progressive user attrition over extended multi-month durations. Integrating structured, human-led clinical support markedly buffers against digital fatigue, thereby optimizing patient adherence. Key implementation barriers include disparities in digital health literacy, age-related usability constraints, and heightened data privacy apprehensions.
Conclusion s: Securing the sustained therapeutic utility of mHealth in routine diabetology necessitates shifting away from unassisted automated tools toward personalized, multi-parametric, blended care frameworks supported by transparent data governance policies.
References
Alhammad, N., Alajlani, M., Abd-Alrazaq, A., Epiphaniou, G., & Arvanitis, T. (2024). Patients’ perspectives on the data confidentiality, privacy, and security of mHealth apps: Systematic review. Journal of Medical Internet Research, 26, 1–20. https://doi.org/10.2196/50715
Azevedo, R. F. L., Varzino, M., Steinman, E., & Rogers, W. A. (2025). Evaluating effectiveness of mHealth apps for older adults with diabetes: Meta-Analysis of randomized controlled trials. Journal of Medical Internet Research, 27, 1–17. https://doi.org/10.2196/65855
Baethge, C., Goldbeck-Wood, S., & Mertens, S. (2019). SANRA—a scale for the quality assessment of narrative review articles. Research Integrity and Peer Review, 4(1), 5. https://doi.org/10.1186/s41073-019-0064-8
Contreras, I., & Vehi, J. (2018). Artificial intelligence for diabetes management and decision support: Literature review. Journal of Medical Internet Research, 20(5), 1–21. https://doi.org/10.2196/10775
Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. https://doi.org/10.7861/futurehosp.6-2-94
Davies, M. J., Aroda, V. R., Collins, B. S., Gabbay, R. A., Green, J., Maruthur, N. M., Rosas, S. E., Del Prato, S., Mathieu, C., Mingrone, G., Rossing, P., Tankova, T., Tsapas, A., & Buse, J. B. (2022). Management of hyperglycemia in type 2 diabetes, 2022. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care, 45(11), 2753–2786. https://doi.org/10.2337/dci22-0034
ElSayed, N. A., McCoy, R. G., Aleppo, G., Balapattabi, K., Beverly, E. A., Briggs Early, K., Bruemmer, D., Ebekozien, O., Echouffo-Tcheugui, J. B., Ekhlaspour, L., Gaglia, J. L., Garg, R., Khunti, K., Lal, R., Lingvay, I., Matfin, G., Pandya, N., Pekas, E. J., Pilla, S. J., … Bannuru, R. R. (2025). 2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes—2025. Diabetes Care, 48(Supplement_1), S27–S49. https://doi.org/10.2337/dc25-S002
Greenhalgh, T., Wherton, J., Papoutsi, C., Lynch, J., Hughes, G., A’Court, C., Hinder, S., Fahy, N., Procter, R., & Shaw, S. (2017). Beyond adoption: A new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. Journal of Medical Internet Research, 19(11). https://doi.org/10.2196/jmir.8775
He, Q., Zhao, X., Wang, Y., Xie, Q., & Cheng, L. (2022). Effectiveness of smartphone application–based self‐management interventions in patients with type 2 diabetes: A systematic review and meta‐analysis of randomized controlled trials. Journal of Advanced Nursing, 78(2), 348–362. https://doi.org/10.1111/jan.14993
International Diabetes Federation. (2025). Idf diabetes atlas (11th ed.). https://diabetesatlas.org/
Khunti, K., Gomes, M. B., Pocock, S., Shestakova, M. V., Pintat, S., Fenici, P., Hammar, N., & Medina, J. (2018). Therapeutic inertia in the treatment of hyperglycaemia in patients with type 2 diabetes: A systematic review. Diabetes, Obesity and Metabolism, 20(2), 427–437. https://doi.org/10.1111/dom.13088
Kruse, C. S., Frederick, B., Jacobson, T., & Monticone, D. K. (2017). Cybersecurity in healthcare: A systematic review of modern threats and trends. Technology and Health Care, 25(1), 1–10. https://doi.org/10.3233/THC-161263
Shariful Islam, S. M., Mishra, V., Siddiqui, M. U., Moses, J. C., Adibi, S., Nguyen, L., & Wickramasinghe, N. (2022). Smartphone apps for diabetes medication adherence: Systematic review. JMIR Diabetes, 7(2), 1–14. https://doi.org/10.2196/33264
Sun, S., Simonsson, O., McGarvey, S., Torous, J., & Goldberg, S. B. (2024). Mobile phone interventions to improve health outcomes among patients with chronic diseases: An umbrella review and evidence synthesis from 34 meta-analyses. The Lancet Digital Health, 6(11), e857–e870. https://doi.org/10.1016/S2589-7500(24)00119-5
Sze, W. T., Waki, K., Enomoto, S., Nagata, Y., Nangaku, M., Yamauchi, T., & Ohe, K. (2023). StepAdd: A personalized mHealth intervention based on social cognitive theory to increase physical activity among type 2 diabetes patients. Journal of Biomedical Informatics, 145(February), 104481. https://doi.org/10.1016/j.jbi.2023.104481
World Health Organization. (2021). Global strategy on digital health 2020–2025. https://www.who.int/publications/i/item/9789240020924
Xue, H., Zhang, L., Shi, Y., Zhang, H., Zhang, C., Liu, Y., Tan, W., & Liu, Y. (2025). The effectiveness of digital health intervention on glycemic control and physical activity in patients with type 2 diabetes: A systematic review and meta-analysis. Frontiers in Digital Health, 7(July), 1–13. https://doi.org/10.3389/fdgth.2025.1630588
Zaghloul, H., Fanous, K., Ahmed, L., Arabi, M., Varghese, S., Omar, S., Al-Najjar, Y., El-Khoury, R., Gray, J., Rakab, A., & Arayssi, T. (2025). Digital health literacy in patients with common chronic diseases: Systematic review and Meta-Analysis. Journal of Medical Internet Research, 27, 1–12. https://doi.org/10.2196/56231
Zhang, X., Zhang, L., Lin, Y., Liu, Y., Yang, X., Cao, W., Ji, Y., & Chang, C. (2023). Effects of e-health-based interventions on glycemic control for patients with type 2 diabetes: A bayesian network meta-analysis. Frontiers in Endocrinology, 14(May), 1–11. https://doi.org/10.3389/fendo.2023.1068254
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Aleksander Kamecki, Alicja Maria Wielogórska, Filip Sarek, Karol Jóźwik, Stanisław Kucharczyk, Zuzanna Rak, Zuzanna Ignatowska, Karolina Dzień

This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles are published in open-access and licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Hence, authors retain copyright to the content of the articles.
CC BY 4.0 License allows content to be copied, adapted, displayed, distributed, re-published or otherwise re-used for any purpose including for adaptation and commercial use provided the content is attributed.

