Caring with AI: The efficacy of a customised ChatGPT-delivered self-compassion intervention on college students' well-being and academic functioning

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Authors: X. Chen, Chi-Ying Cheng, Andree Hartanto
Cited by: 1
References: 144

Abstract

College students face various challenges, including academic pressure, social stress, and the transition into adulthood, which can lead to increased anxiety and other mental health issues. By recognizing personal struggles as part of a shared human experience and responding with kindness, self-compassion serves as a powerful strategy for enhancing resilience, facilitating better well-being and performance outcomes. Although effective, Compassion-Focused Therapy often requires substantial resources and time, limiting its applicability to college students. To overcome these barriers, the current study designed and evaluated Your Self-Compassion Companion, a ChatGPT-powered AI chatbot intervention grounded in self-compassion theory and delivered over three weekly 20-min digital sessions. A randomised controlled trial (N = 220) compared the intervention to an active control. Results indicated that the intervention significantly enhanced self-compassion and reduced self-criticism, with downstream improvements in self-esteem and academic engagement. Participant engagement with the chatbot was high, with 99.1% completion of intervention sessions, high levels of self-reported adherence to instructions (100%) and honest interaction (98.2%). The intervention's feasibility and acceptability provide initial evidence that such AI-delivered self-compassion interventions can effectively enhance self-compassion, reduce self-criticism, and improve selected psychological well-being and academic functioning outcomes among students.

Fields of Study & Subjects

Digital Mental Health Interventions Artificial Intelligence in Healthcare and Education Mindfulness and Compassion Interventions

Publication details

Journal / source
Computers in Human Behavior Reports
Publisher
Elsevier BV
Volume
23
Pages
101267–101267
Publication date
1 August 2026
Language
EN