Comparative Efficacy of Telepsychiatry Interventions for Depression in Low- and Middle-Income Countries: A Systematic...

Background: Depression represents a major public health burden, especially in low- and middle-income countries (LMICs). Telepsychiatry provides a promising solution by offering remote mental health services, overcoming barriers such as limited resources, isolation, and cost. This study aimed to evaluate the comparative efficacy of different telepsychiatry interventions in LMICs by network meta-analysis of randomized controlled trials (RCTs). Methods: We searched PubMed, EMBASE, CENTRAL, CINAHL, PsycINFO, and ProQuest Dissertations & Theses from inception to May 2024 to identify all relevant studies. Telepsychiatry interventions were categorized as: (1) CBTAppGuided, a cognitive behavioral therapy (CBT) app with professional guidance; (2) CBTChatBot, a CBT app that uses a chatbot for guidance; (3) CBTApp, a CBT app without professional guidance; (4) Reminder; and (5) Consultation. Study quality was assessed according to the Effective Practice and Organization of Care guideline. Depression severity was calculated using summary standardized mean differences with 95% confidence intervals (CIs). Results: Seven RCTs were included with a total of 1,469 adults (mean age range: 16.0-35.64 years). Compared with face-to-face usual care, the most effective telepsychiatry intervention was CBTAppGuided [-23.04, 95% CI: -26.12 to -19.96], followed by CBTChatBot [-5.27, 95% CI: -6.25 to -4.29]. Other interventions, including CBTApp [-0.83, 95% CI: -1.32 to -0.34], Reminder [-0.44, 95% CI: -0.72 to -0.16], and Consultation [-0.27, 95% CI: -0.78 to 0.26], demonstrated smaller effects. CBTAppGuided, CBTChatBot, CBTApp, and Reminder achieved statistically significant improvement, whereas Consultation did not show statistically significant improvement and was not different from face-to-face treatment. Conclusion: Telepsychiatry interventions, particularly CBTAppGuided, show potential for reducing depression severity in LMICs, with promising outcomes for both guided and unguided app-based formats. Further research is needed to confirm their effectiveness in resource-limited settings.