JMIR Publications

ABSTRACT

Background:

Depression is a significant public health issue that can lead to considerable disability and reduced quality of life. With the rise of technology, mobile health (mHealth) interventions, particularly smartphone apps, are emerging as a promising approach for addressing depression. However, the lack of standardized evaluation tools and evidence-based principles for these interventions remains a concern.

Objective:

This systematic review and meta-analysis aimed to evaluate the efficacy and safety of mHealth interventions for depression and identify criteria and evaluation tools used for their assessment.

Methods:

A SR and MA of the literature was carried out, following recommendations in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The protocol for this SR and MA was prospectively registered on PROSPERO (CRD42022304684).

Results:

A total of 29 randomized controlled trials (RCTs) were included in the analysis after a comprehensive search of electronic databases and manual searches. The efficacy of mHealth interventions in reducing depressive symptoms was assessed using a random-effects meta-analysis. Twenty RCTs had an unclear risk of bias, and nine were assessed as high risk of bias. The most common element in mHealth interventions was psychoeducation, followed by goal setting and gamification strategies. The meta-analysis revealed a significant effect for mHealth interventions in reducing depressive symptoms compared to non-active control (g=-0.62, 95%CI -0.87, -0.37, I2 =87%). Blended interventions, which combined mHealth with face-to-face sessions, were found to be the most effective. Three studies compared mHealth interventions with active controls and reported overall positive results. Safety analyses showed that most studies did not report any study-related adverse events.

Conclusions:

This review suggests that mHealth interventions can be effective in reducing depressive symptoms, blended interventions achieving the best results. However, the high level of heterogeneity in the characteristics and components of mHealth interventions indicates the need for personalized approaches that consider individual differences, preferences, and needs. It is also important to prioritize evidence-based principles and standardized evaluation tools for mHealth interventions to ensure their efficacy and safety in treating depression. Overall, the findings of this study support the use of mHealth interventions as a viable method for delivering mental health care.