ArticlePLOS digital health2025
Implementation and impact of mhealth in the management of diabetes mellitus in Africa: A systematic review and meta-analysis.
Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Digital Health Interventions for Type 2 Diabetes: A Narrative Review of Mobile Technologies and Their Impact on Patients' Outcomes.Health science reports · 2026Article
- Impact of technological acceptance on application-based engagement among type 2 diabetes patients: local insights and implications for developing countries.Journal of pharmaceutical policy and practice · 2026Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe World Health Organization (WHO) has proposed the concept of mobile health to support healthcare systems delivery worldwide. Mobile health (mHealth) involves using Information and Communication Technology (ICT) for health care provision or delivery services. In the context of Africa, a region that has witnessed a significant increase in mobile phone availability and usage in the last decade and a corresponding rise in the incidence and prevalence of diabetes mellitus, this study has global implications. We conducted a systematic review on the extent of mHealth implementation in managing diabetes mellitus in Africa. We estimated its impact on achieving desired glycemic targets, sustained control, and preventing complications in the past decade. METHODS AND ANALYSIS: The studies assessing the utilization of mHealth in managing patients with diabetes mellitus in Africa were considered based on the PICO method: Population, Intervention, Comparator, and Outcomes. MEDLINE, PubMed, SCOPUS, and the Pan African Clinical Trials Registry were searched. Two authors, independent of each other, screened titles and abstracts retrieved using the search strategy, retrieved the full-text articles, and assessed them for eligibility, extracting data after that. A third independent reviewer was brought in to resolve disagreements between the two authors by discussion. The revised Cochrane Collaboration Risk of Bias Tool was used to assess the quality of included studies. A narrative synthesis of extracted data was done due to the paucity of eligible studies, and the results were summarized in a meta-analysis.
resultsNone of the six included studies measured the mean FPG or percentage changes as primary outcomes. Five measured the percentage change in HbA1c from baseline to the end of the study. The percentage change in HbA1c from the baseline ranged from 3.6% to 20.53%, achieving significance in three studies. In the meta-analysis the overall WMD (95% CI) was 0.992 (0.48, 1.50). This, in combination with a high z score of 3.822, p <0.001 suggests a statistically significant overall effect that is not likely due to chance. However, a considerable heterogeneity (I2 = 63.9%, p = 0.026) was present implying that the observed effect may not be generalizable to all the studies due to differences in study characteristics in this case most likely sample size and duration of study. None of the studies addressed the secondary outcomes of measuring the direct relationships between these mHealth interventions and the prevention or early detection of diabetes complications.
conclusionOverall, there was a statistically significant reduction in HbA1c levels among individuals living with type 2 diabetes in Africa following mHealth interventions. Few studies were included in the meta-analysis with significant heterogeneity. Therefore, we recommend more well-designed randomized controlled trials to investigate the implementation and efficacy of mHealth in the management of diabetes mellitus in Africa. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021218674.
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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 OpenQuestion graph.