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dc.contributor.authorFernández-Rodríguez, Rubén
dc.contributor.authorZhao, Lijun
dc.contributor.authorBizzozero-Peroni, Bruno
dc.contributor.authorMartínez-Vizcaíno, Vicente
dc.contributor.authorMesas, Arthur Eumann
dc.contributor.authorWittert, Gary
dc.contributor.authorHeilbronn, Leonie K.
dc.date.accessioned2024-06-19T04:40:10Z
dc.date.available2024-06-19T04:40:10Z
dc.date.issued2024
dc.identifier10.1089/tmj.2023.0374
dc.identifier.issn15305627
dc.identifier.urihttps://hdl.handle.net/20.500.12728/11317
dc.description.abstractBackground: e-Health refers to any health care service delivered through the internet or related technologies, to improve quality of life. Despite the increasing use of e-health interventions to manage type 2 diabetes (T2D), there is a lack of evidence about the effectiveness on diabetes distress and depression, which are common issues in those living with T2D. Purpose: To synthesize and determine the effects of e-health interventions on diabetes distress and depression among patients with T2D. Methods: We systematically searched PubMed, Scopus, Cochrane CENTRAL, and Web of Science for randomized controlled trials (RCTs), non-RCTs and observational cohort studies for the effects of e-health interventions on diabetes distress and depression in patients with T2D up to September 14, 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 recommendations were followed. The risk of bias was assessed according to the Risk-of-Bias 2 tool (RCTs), the Risk Of Bias In Non-randomised Studies-of Interventions (ROBINS-I) (non-RCTs) and the National Institute of Health tool (observational). The standardized mean difference (SMD) and its related 95% confidence intervals (CIs) were estimated with the DerSimonian-Laird method through random-effect models. A pooled raw mean difference (MD) meta-analysis was conducted for RCTs comparing the effects of e-health versus control on diabetes distress screening to display the clinical impact. Results: A total of 41 studies (24 RCTs, 14 non-RCTs, and 3 observational) involving 8,667 individuals were included. The pooled SMD for the effect of e-health versus the control group on diabetes distress was −0.14 (95% CI = −0.24 to −0.04; I2 = 23.9%; n = 10 studies), being -0.06 (95% CI = −0.15 to 0.02; I2 = 7.8%; n = 16 studies) for depression. The pooled raw MD on diabetes distress screening showed a reduction of −0.54 points (95% CI = −0.81 to −0.27; I2 = 85.1%; n = 7 studies). Conclusion: e-Health interventions are effective in diminishing diabetes distress among adults with T2D, inducing clinically meaningful reductions. Copyright 2024, Mary Ann Liebert, Inc., publishers.es_ES
dc.description.sponsorshipMinisterio de Educación, Cultura y Deporte, MECD, (FPU 19/00167); Ministerio de Educación, Cultura y Deporte, MECD; European Social Fund Plus, ESF, (2020-PREDUCLM-16746); European Social Fund Plus, ESF; Universidad de Castilla-La Mancha, UCLMes_ES
dc.language.isoenes_ES
dc.publisherMary Ann Liebert Inc.es_ES
dc.subjectdepressiones_ES
dc.subjectdiabetes distresses_ES
dc.subjecte-healthes_ES
dc.subjectemotional burdenes_ES
dc.subjectmeta-analysises_ES
dc.subjecttelemedicinees_ES
dc.subjecttype 2 diabeteses_ES
dc.titleAre e-Health Interventions Effective in Reducing Diabetes-Related Distress and Depression in Patients with Type 2 Diabetes? A Systematic Review with Meta-Analysises_ES
dc.typeArticlees_ES


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