GPT-4 generated psychological reports in psychodynamic perspective: a pilot study on quality, risk of hallucination and client satisfaction

Namwoo Kim ^1* Jiseon Lee ² Sung-Hyun Park ³ Yoonseo On ⁴ Jieun Lee ⁵ Musung Keum ⁶ Sanghoon Oh ² Yoojin Song ⁷ Junhee Lee ⁸ Geun Hui Won ⁹ Joon Sung Shin ¹⁰ Silvia Kyungjin Lho ¹¹ Yoon Jung Hwang ⁸ Tae-Suk Kim ⁸

• ¹ Department of Clinical Medical Sciences, Seoul National University Hospital, Seoul, Republic of Korea
• ² Department of Psychiatry, Uijeongbu Eulji Medical Center, Eulji University, Gyeonggi, Republic of Korea
• ³ Department of Medical Informatics, College of Medicine, Catholic University of Korea, Seoul, Seoul, Republic of Korea
• ⁴ College of Medicine, Ewha Womans University, Seoul, Seoul, Republic of Korea
• ⁵ Department of Pediatrics, College of Medicine, Inje University, Seoul, Seoul, Republic of Korea
• ⁶ Department of Neuropsychiatry, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Gyeonggi, Republic of Korea
• ⁷ Department of Psychiatry, Kangwon National University Hospital, Chuncheon, Gangwon, Republic of Korea
• ⁸ Department of Psychiatry, Seoul St. Mary's Hospital, The Catholic University of Korea, Seoul, Seoul, Republic of Korea
• ⁹ Department of Psychiatry, Chungnam National University Sejong Hospital, Sejong, Republic of Korea
• ¹⁰ Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
• ¹¹ Department of Psychiatry, Seoul Metropolitan Government - Seoul National University Boramae Medical Center, Seoul, Republic of Korea

Background: Recently, there have been active proposals on how to utilize large language models (LLMs) in the fields of psychiatry and counseling. It would be interesting to develop programs with LLMs that generate psychodynamic assessments to help individuals gain insights about themselves, and to evaluate the features of such services. However, studies on this subject are rare. This pilot study aims to evaluate quality, risk of hallucination (incorrect AI-generated information), and client satisfaction with psychodynamic psychological reports generated by GPT-4.Methods: The report comprised five components: psychodynamic formulation, psychopathology, parental influence, defense mechanisms, and client strengths. Participants were recruited from individuals distressed by repetitive interpersonal issues. The study was conducted in three steps: 1) Questions provided to participants, designed to create psychodynamic formulations: 14 questions were generated by GPT for inferring psychodynamic formulations, while 6 fixed questions focused on the participants’ relationship with their parents. A total of 20 questions were provided. 2) Seven professors of psychiatry from different university hospitals evaluated the quality and risk of hallucinations in the psychological reports by reading the reports only, without meeting the participants. This quality assessment compared the psychological reports generated by GPT-4 with those inferred by the experts. 3) Participants evaluated their satisfaction with the psychological reports. All assessments were conducted using self-report questionnaires based on a Likert scale developed for this studyResults: A total of 10 participants were recruited, and the average age was 32 years. The median response indicated that quality of all five components of the psychological report was similar to the level inferred by the experts. The risk of hallucination was assessed as ranging from unlikely to minor. According to the median response in the satisfaction evaluation, the participants agreed that the report is clearly understandable, insightful, credible, useful, satisfying, and recommendable.Conclusion: This study suggests the possibility that artificial intelligence could assist users by providing psychodynamic interpretations.