JMIR Publications

ABSTRACT

Background:

Diabetes-related depression refers to a depressive state triggered or exacerbated by factors such as diabetes diagnosis, the burden of treatment, and the risk of complications. The differences in efficacy among various telemedicine intervention models remain unclear, and the lack of direct and indirect comparisons across multiple methods makes it impossible to establish a clear hierarchy of relative merits.

Objective:

This study aims to conduct a systematic review and network meta-analysis of randomized controlled trials evaluating telemedicine interventions for diabetes-related depression. The study will synthesize efficacy data from various telemedicine intervention models, compare the effectiveness and acceptability of different intervention strategies, and identify the optimal intervention approach.

Methods:

We conducted a literature search in the PubMed and Web of Science (WOS) databases, covering the period from the inception of each database through January 17, 2026. We included peer-reviewed English-language studies examining the association between telemedicine interventions and psychological outcomes in patients with diabetes. The risk of bias and methodological quality of the studies was assessed using the Cochrane Risk of Bias Assessment Tool version 2.0. Data analysis was performed using the meta and metafor packages in R version 4.1.0 (R Statistical Computing Project). The standardized mean difference (SMD) was used to pool the effect sizes. We conducted a series of sensitivity analyses to assess the robustness of the results.

Results:

A total of 16 RCT studies involving 246 studies were included. The overall pooled effect size, estimated using a random-effects model, was SMD = -0.33 (95% CI: -0.43, -0.24), indicating a small-to-moderate beneficial effect of interventions compared to control conditions (p < 0.001). The overall pooled effect size, estimated using a random-effects model, was OR = 1.07 (95% CI: 0.71, 1.63). Moderate heterogeneity was observed across studies (I² = 49.4%, τ2 = 0.3292, p = 0.0133)。Subgroup analyses were conducted based on intervention type. For telephone-based interventions, the pooled odds ratio was 1.38 (95% CI: 0.98, 1.94; I² = 0.3%). For app-based interventions, the pooled odds ratio (OR) was 1.07 (95% CI: 0.49, 2.34; I² = 0.7%). For online training interventions, the pooled odds ratio (OR) was 0.33 (95% CI: 0.07, 1.64; I² = 0.0%). For video interventions, the odds ratio (OR) was 0.50 (95% CI: 0.09, 2.73). Overall, the odds ratio derived from the random-effects model was 1.07 (95% CI: 0.71, 1.63; I² = 0.5%), indicating no significant difference in all-cause dropout rates between the intervention and control groups.

Conclusions:

Digital psychological interventions are an effective means of alleviating depressive symptoms, with structured online training proving particularly effective. Clinical Trial: The study protocol has been registered in the PROSPERO database (registration number: CRD420251233353).