Digital Interventions for Depression in the AI Era: A Network Meta-Analysis to Compare and Rank Therapeutic Chatbots and AI-Augmented Therapy

Main Article Content

Joyceline Chika Tanely
Cing
Airen Wang
Chalista
Aurel

Abstract

INTRODUCTION: Artificial Intelligence (AI) is increasingly used in mental health care, with conversational agents offering scalable support for depression. However, the comparative effectiveness of AI-based therapies relative to other digital approaches remains unclear, and prior reviews have not provided treatment rankings.


OBJECTIVE: To compare and rank the effectiveness of AI-driven therapeutic chatbots (AI-DTA) versus non-AI digital interventions (NAI-DI) and control conditions in reducing depressive symptoms among adults.


METHOD: This network meta-analysis followed PRISMA-NMA guidelines. A systematic search across five databases (last updated September 17, 2025) identified randomized controlled trials involving adults (≥18 years) with Major Depressive Disorder or clinically significant depressive symptoms. The primary outcome was the standardized mean difference (SMD) in post-intervention depressive severity. Seven RCTs (n = 1,238) contributed to the connected evidence network. A frequentist random-effects NMA compared four intervention nodes. Transitivity was supported by comparable populations, delivery formats, and outcome timing. Heterogeneity was negligible (τ² = 0; I² = 0%; Q = 1.98, p = 0.37).


RESULTS: AI-DTA produced significantly greater reductions in depressive symptoms compared to NAI-DI (SMD = −0.55, 95% CI: −0.98 to −0.13). Differences for Sham and Information Control versus NAI-DI were not significant. AI-DTA ranked highest within the network (P-score = 0.943), and node-splitting analyses showed no significant inconsistency.


CONCLUSIONS: AI-driven therapeutic chatbots demonstrate superior effectiveness compared to non-AI digital interventions and may serve as a clinically useful adjunct or interim alternative when access to therapist-led care is limited. Further trials should evaluate long-term outcomes and direct comparisons with human-delivered therapy.

Article Details

How to Cite
Tanely, J. C., Wistara, D. M., Wang, A., Angelim, C. and Kimberly, A. (2026) “Digital Interventions for Depression in the AI Era: A Network Meta-Analysis to Compare and Rank Therapeutic Chatbots and AI-Augmented Therapy”, Journal of Asian Medical Students’ Association. Kuala Lumpur, Malaysia. doi: 10.52629/jamsa.vi.986.
Section
EAMSC 2026 Nepal Scientific Paper