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dc.contributor.authorRodríguez Montes, Oscar Eduardo
dc.contributor.authorGogeascoechea Trejo, María Del Carmen
dc.contributor.authorBermúdez-Tamayo, Clara
dc.date.accessioned2026-02-02T12:18:32Z
dc.date.available2026-02-02T12:18:32Z
dc.date.issued2026-01-31
dc.identifier.citationRodríguez-Montes, O. E., Gogeascoechea-Trejo, M. d. C., & Bermúdez-Tamayo, C. (2026). Characteristics of Digital Health Interventions Associated with Improved Glycemic Control in T2DM: A Systematic Review and Meta-Analysis. Journal of Clinical Medicine, 15(3), 1123. https://doi.org/10.3390/jcm15031123es_ES
dc.identifier.urihttps://hdl.handle.net/10481/110586
dc.description.abstractBackground/Objective: Type 2 Diabetes Mellitus (T2DM) represents a major increasing burden for primary care systems worldwide. Digital health interventions (DHIs) have been proposed as scalable tools to improve glycemic control, yet uncertainty remains regarding which intervention characteristics yield the greatest benefit. To evaluate the effectiveness of DHIs on HbA1c levels in adults with T2DM and to examine whether intervention duration, engagement intensity, glucometer integration, and healthcare provider involvement modify glycemic outcomes. Data Sources: PubMed, Embase, Cochrane Library, and JMIR databases were systematically searched for relevant studies published between January 2020 and May 2025. Study Eligibility Criteria: Randomized controlled trials comparing DHIs plus usual care versus usual care alone in adults with T2DM and reporting HbA1c as the primary outcome. Methods: Data were extracted using the Jadad scale and TIDieR framework. Random-effects meta-analysis estimated pooled mean differences (MD) in HbA1c with 95% CIs. Subgroup analyses examined effects by intervention characteristics. Heterogeneity and sources of variance were assessed through Cochran’s Q, I2, meta-regression, and sensitivity analyses (leave-one-out and trim-and-fill). Results: Thirteen RCTs (n ≈ 20,000) met inclusion criteria. DHIs achieved significant HbA1c reductions (range 0.01% to 1.57%; pooled MD −1.08%; 95% CI −1.18 to −0.99; p = 0.001). Short-term (≤6 months), low-intensity interventions showed the largest effect sizes (MD −1.16%, 95% CI 0.94 to 1.39). Glucometer integration and healthcare provider involvement contributed minimally to additional benefit. Meta-regression confirmed substantial heterogeneity, but no single factor explained variance across studies. Limitations: Considerable heterogeneity across interventions and variability in engagement measurement may limit the generalizability of findings. Conclusions: Short-term, low-intensity DHIs significantly improve glycemic control in primary care populations with T2DM. Advanced meta-analytic techniques confirm the robustness of these effects, providing practical guidance for selecting and implementing effective digital interventions in routine diabetes care.es_ES
dc.description.sponsorshipCentre for the Development of Industrial Technology (CDTI) co-funded by NextGenerationEU – (PAIS-20241102)es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectDiabetes mellituses_ES
dc.subjectType 2es_ES
dc.subjecttelemedicinees_ES
dc.titleCharacteristics of Digital Health Interventions Associated with Improved Glycemic Control in T2DM: A Systematic Review and Meta-Analysises_ES
dc.typejournal articlees_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EU/PRTR/PAIS-20241102es_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.3390/jcm15031123
dc.type.hasVersionVoRes_ES


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