Effectiveness of eHealth Interventions in Alleviating Burden on Informal Caregivers of People With Dementia: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Background: Informal caregivers of people with dementia frequently experience substantial psychological burden, including elevated stress and depressive symptoms. eHealth interventions have emerged as a scalable solution to support caregivers. However, their effectiveness and the influence of intervention characteristics remain unclear. Objective: This study aimed to evaluate the effectiveness of eHealth interventions in reducing caregiver burden and depressive symptoms among informal caregivers of people with dementia, and to explore potential moderators of intervention effectiveness, including delivery modality, human support, and intervention duration. Methods: This systematic review and meta-analysis was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 and PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Search extension) guidelines. Eight electronic databases and clinical trial registries were searched from inception to March 10, 2026. Eligible studies were randomized controlled trials involving informal caregivers of people with dementia receiving interactive eHealth interventions compared with usual care or inactive controls. Study selection, data extraction, and risk-of-bias assessment were conducted independently by 2 reviewers (ML and JXR). Meta-analyses were conducted using a random-effects model with the Hartung-Knapp-Sidik-Jonkman adjustment. Heterogeneity was assessed using the I2 statistic, and 95% prediction intervals (PIs) were calculated for the primary analyses. The certainty of evidence was evaluated using GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) criteria. Results: Thirty-five trials (N=3388) were included. eHealth interventions were associated with a statistically significant reduction in caregiver burden (k=35, standardized mean difference [SMD] -0.26, 95% CI -0.42 to -0.10; P=.002; τ2=0.16, τ=0.40; 95% PI -1.10 to 0.58) and a modest reduction in depressive symptoms (k=23, SMD -0.27, 95% CI -0.53 to -0.01; P=.04; τ2=0.31, τ=0.55; 95% PI -1.45 to 0.91). While average effects were statistically significant, wide PIs indicate substantial between-study heterogeneity and variability in real-world effectiveness. Subgroup analyses suggested that short-term (≤8 weeks) intervention was associated with borderline significantly stronger effects for caregiver burden, while human-supported and mobile-based interventions demonstrated larger point estimates with substantial heterogeneity. Meta-regression indicated that caregiver age was a potential moderator (P=.05) in univariate analysis, with decreasing effectiveness observed in older populations. Sensitivity analysis of 27 high-quality studies confirmed robust effects (SMD -0.31, P=.002). No significant small-study effects were detected (Egger test: P>.35). The overall certainty of evidence was moderate. Conclusions: eHealth interventions provide modest but variable benefits in reducing burden and depressive symptoms among informal caregivers of people with dementia. This review is timely, given the rapidly expanding digital dementia care and extends prior evidence using a more conservative Hartung-Knapp-Sidik-Jonkman framework with PIs, showing that effects vary from minimal to substantial. While average effects support effectiveness, wide PIs and moderate certainty evidence indicate that outcomes are context-dependent and influenced by heterogeneity and methodological limitations. Hybrid digital-human models should be prioritized to enhance consistency and real-world impact.