Single online self-compassion writing intervention reduces anxiety: With the feedback of ChatGPT - Tomoko Kishimoto; Ximing Hao; Trimble Chang; Zhiye Luo (Internet Interventions)
With the aim of universal prevention, there is still a lack of non-clinician-led or self-help interventions designed for the general population experiencing psychological distress. This study aims to address this gap by exploring a convenient, single-session, and effective method for reducing anxiety using ChatGPT feedback. Using a mixed-factorial experimental design, we recruited 98 participants online to compare changes in self-compassion and anxiety before and after the intervention among three groups: self-compassion writing with ChatGPT feedback (Experimental Group 1), self-compassion writing alone (Experimental Group 2), and an Active Control Group. Results showed that both Experimental Group 1 and 2 experienced significant increases in self-compassion and Experimental Group 1 experienced significant decreases in anxiety after the intervention, with Experimental Group 1 showing greater improvements. There were no significant changes in the control group. This study demonstrates that single online self-compassion writing intervention can effectively reduce anxiety and that using ChatGPT to provide highly empathetic feedback can enhance the effectiveness, making psychological support more accessible, cost-effective, and suitable for the general population.