Reducing Depressive Symptoms through AI-Guided Narrative Self-Films: A Formative Randomized Controlled Trial

Abstract Depression remains a leading global health concern, yet theory-based applications of generative artificial intelligence (AI) to mental-health support have received little empirical scrutiny. The present study tested a five-day, AI-assisted “self-film” intervention grounded in narrative-identity theory. In a 3 (value framing: independent, interdependent, neutral) × 2 (narrative arc: ideal-only, conflict-resolution) factorial randomized controlled trial, 181 Chinese undergraduates with mild-to-moderate depressive symptoms produced short AI-generated videos depicting their past, present, and future selves and then compiled them into personalised self-films. Depression, state hope, narrative coherence, and future self-continuity were measured before and after the programme. Conflict-resolution storytelling reduced depressive symptoms on the PHQ-9 compared with ideal-only conditions; the strongest decline occurred in the interdependent/conflict-resolution group. Conflict-resolution participants also recorded significant gains in hope, narrative coherence, and self-continuity. These results provide preliminary evidence that a brief, culturally attuned, AI-supported storytelling exercise can enhance multiple indices of psychological well-being, suggesting promise for scalable digital interventions beyond traditional clinical settings.Depression remains a leading global health concern, yet theory-based applications of generative artificial intelligence (AI) To mental-health support Have Received Little Empirical scrutiny. The Present Study Tested a five-day, AI-assisted “self-film” Intervention Grounded in Narrative-identity theory. In a 3 (value Framing: independent, interdependent, neutral) × 2 (narrative Arc: ideal-only, conflict-resolution) Factorial Randomized Controlled trial, 181 Chinese Undergraduates with mild-to-moderate Depressive Symptoms Produced Short AI-generated Videos Depicting their past, Present, and Future Selves and Then Compiled Them into Personalized self-films. Depression, State hope, Narrative coherence, and Future self-continuity Were Measured before and after the Study. Conflict-resolution Storytelling Reduced Depressive Symptoms on the PHQ-9 Compared with ideal-only conditions; the Strongest Decline Occurred in the interdependent/conflict-resolution group. Conflict-resolution Participants Also Recorded Significant Gains in hope, Narrative coherence, and self-continuity. These Results Provide Preliminary Evidence that a brief, Culturally attuned, AI-supported Storytelling Exercise Can Enhance Multiple Indices of Psychological well-being, Suggesting Promise for Scalable Digital Interventions Beyond Traditional Clinical Settings.

Authors

Institutions

Publication Details

Journal
Journal of Technology in Behavioral Science
Published
2026-03-05
DOI
https://doi.org/10.1007/s41347-026-00596-5
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reducing Depressive Symptoms through AI-Guided Narrative Self-Films: A Formative Randomized Controlled Trial

Elvin Yao, Harry Yang
Journal of Technology in Behavioral Science
Mental Health via Writing
article

Reducing Depressive Symptoms through AI-Guided Narrative Self-Films: A Formative Randomized Controlled Trial

Elvin Yao, Harry Yang
article en

Abstract

Abstract Depression remains a leading global health concern, yet theory-based applications of generative artificial intelligence (AI) to mental-health support have received little empirical scrutiny. The present study tested a five-day, AI-assisted “self-film” intervention grounded in narrative-identity theory. In a 3 (value framing: independent, interdependent, neutral) × 2 (narrative arc: ideal-only, conflict-resolution) factorial randomized controlled trial, 181 Chinese undergraduates with mild-to-moderate depressive symptoms produced short AI-generated videos depicting their past, present, and future selves and then compiled them into personalised self-films. Depression, state hope, narrative coherence, and future self-continuity were measured before and after the programme. Conflict-resolution storytelling reduced depressive symptoms on the PHQ-9 compared with ideal-only conditions; the strongest decline occurred in the interdependent/conflict-resolution group. Conflict-resolution participants also recorded significant gains in hope, narrative coherence, and self-continuity. These results provide preliminary evidence that a brief, culturally attuned, AI-supported storytelling exercise can enhance multiple indices of psychological well-being, suggesting promise for scalable digital interventions beyond traditional clinical settings.Depression remains a leading global health concern, yet theory-based applications of generative artificial intelligence (AI) To mental-health support Have Received Little Empirical scrutiny. The Present Study Tested a five-day, AI-assisted “self-film” Intervention Grounded in Narrative-identity theory. In a 3 (value Framing: independent, interdependent, neutral) × 2 (narrative Arc: ideal-only, conflict-resolution) Factorial Randomized Controlled trial, 181 Chinese Undergraduates with mild-to-moderate Depressive Symptoms Produced Short AI-generated Videos Depicting their past, Present, and Future Selves and Then Compiled Them into Personalized self-films. Depression, State hope, Narrative coherence, and Future self-continuity Were Measured before and after the Study. Conflict-resolution Storytelling Reduced Depressive Symptoms on the PHQ-9 Compared with ideal-only conditions; the Strongest Decline Occurred in the interdependent/conflict-resolution group. Conflict-resolution Participants Also Recorded Significant Gains in hope, Narrative coherence, and self-continuity. These Results Provide Preliminary Evidence that a brief, Culturally attuned, AI-supported Storytelling Exercise Can Enhance Multiple Indices of Psychological well-being, Suggesting Promise for Scalable Digital Interventions Beyond Traditional Clinical Settings.

Journal of Technology in Behavioral Science
Boston University (US), University of Hong Kong (HK)
Openalex Percentile: Top 43%
Mental Health via Writing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.