The Plasticity of ChatGPT's Mentalizing Abilities: Personalization for Personality Structures

Overview

Journal Front Psychiatry

Specialty Psychiatry

Date 2023 Sep 18

PMID 37720897

Authors

Dorit Hadar-Shoval

Zohar Elyoseph

Maya Lvovsky

Affiliations

Soon will be listed here.

Abstract

This study evaluated the potential of ChatGPT, a large language model, to generate mentalizing-like abilities that are tailored to a specific personality structure and/or psychopathology. Mentalization is the ability to understand and interpret one's own and others' mental states, including thoughts, feelings, and intentions. Borderline Personality Disorder (BPD) and Schizoid Personality Disorder (SPD) are characterized by distinct patterns of emotional regulation. Individuals with BPD tend to experience intense and unstable emotions, while individuals with SPD tend to experience flattened or detached emotions. We used ChatGPT's free version 23.3 and assessed the extent to which its responses akin to emotional awareness (EA) were customized to the distinctive personality structure-character characterized by Borderline Personality Disorder (BPD) and Schizoid Personality Disorder (SPD), employing the Levels of Emotional Awareness Scale (LEAS). ChatGPT was able to accurately describe the emotional reactions of individuals with BPD as more intense, complex, and rich than those with SPD. This finding suggests that ChatGPT can generate mentalizing-like responses consistent with a range of psychopathologies in line with clinical and theoretical knowledge. However, the study also raises concerns regarding the potential for stigmas or biases related to mental diagnoses to impact the validity and usefulness of chatbot-based clinical interventions. We emphasize the need for the responsible development and deployment of chatbot-based interventions in mental health, which considers diverse theoretical frameworks.

Citing Articles

The Feasibility of Large Language Models in Verbal Comprehension Assessment: Mixed Methods Feasibility Study.

Hadar-Shoval D, Lvovsky M, Asraf K, Shimoni Y, Elyoseph Z JMIR Form Res. 2025; 9:e68347.

PMID: 39993720 PMC: 11894350. DOI: 10.2196/68347.

The externalization of internal experiences in psychotherapy through generative artificial intelligence: a theoretical, clinical, and ethical analysis.

Haber Y, Hadar Shoval D, Levkovich I, Yinon D, Gigi K, Pen O Front Digit Health. 2025; 7:1512273.

PMID: 39968063 PMC: 11832678. DOI: 10.3389/fdgth.2025.1512273.

Large language models outperform general practitioners in identifying complex cases of childhood anxiety.

Levkovich I, Rabin E, Brann M, Elyoseph Z Digit Health. 2024; 10:20552076241294182.

PMID: 39687523 PMC: 11648044. DOI: 10.1177/20552076241294182.

Large Language Models for Mental Health Applications: Systematic Review.

Guo Z, Lai A, Thygesen J, Farrington J, Keen T, Li K JMIR Ment Health. 2024; 11:e57400.

PMID: 39423368 PMC: 11530718. DOI: 10.2196/57400.

An Ethical Perspective on the Democratization of Mental Health With Generative AI.

Elyoseph Z, Gur T, Haber Y, Simon T, Angert T, Navon Y JMIR Ment Health. 2024; 11:e58011.

PMID: 39417792 PMC: 11500620. DOI: 10.2196/58011.

References

Shedler J, Beck A, Fonagy P, Gabbard G, Gunderson J, Kernberg O . Personality disorders in DSM-5. Am J Psychiatry. 2010; 167(9):1026-8. DOI: 10.1176/appi.ajp.2010.10050746. View

Luyten P, Fonagy P . The stress-reward-mentalizing model of depression: An integrative developmental cascade approach to child and adolescent depressive disorder based on the Research Domain Criteria (RDoC) approach. Clin Psychol Rev. 2017; 64:87-98. DOI: 10.1016/j.cpr.2017.09.008. View

Nolte T, Guiney J, Fonagy P, Mayes L, Luyten P . Interpersonal stress regulation and the development of anxiety disorders: an attachment-based developmental framework. Front Behav Neurosci. 2011; 5:55. PMC: 3177081. DOI: 10.3389/fnbeh.2011.00055. View

Walsh D, Foster J . A Call to Action. A Critical Review of Mental Health Related Anti-stigma Campaigns. Front Public Health. 2021; 8:569539. PMC: 7820374. DOI: 10.3389/fpubh.2020.569539. View

Reed G . Progress in developing a classification of personality disorders for ICD-11. World Psychiatry. 2018; 17(2):227-229. PMC: 5980531. DOI: 10.1002/wps.20533. View

Dinger U, Fuchs M, Kohling J, Schauenburg H, Ehrenthal J . Change of Emotional Experience in Major Depression and Borderline Personality Disorder During Psychotherapy: Associations With Depression Severity and Personality Functioning. J Pers Disord. 2019; 35(Suppl A):1-20. DOI: 10.1521/pedi_2019_33_420. View

Eylem O, de Wit L, van Straten A, Steubl L, Melissourgaki Z, Danisman G . Stigma for common mental disorders in racial minorities and majorities a systematic review and meta-analysis. BMC Public Health. 2020; 20(1):879. PMC: 7278062. DOI: 10.1186/s12889-020-08964-3. View

Fitzpatrick K, Darcy A, Vierhile M . Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial. JMIR Ment Health. 2017; 4(2):e19. PMC: 5478797. DOI: 10.2196/mental.7785. View

Arboleda-Florez J, Stuart H . From sin to science: fighting the stigmatization of mental illnesses. Can J Psychiatry. 2012; 57(8):457-63. DOI: 10.1177/070674371205700803. View

10.

Luyten P, Campbell C, Allison E, Fonagy P . The Mentalizing Approach to Psychopathology: State of the Art and Future Directions. Annu Rev Clin Psychol. 2020; 16:297-325. DOI: 10.1146/annurev-clinpsy-071919-015355. View

11.

Coolidge F, Estey A, Segal D, Marle P . Are alexithymia and schizoid personality disorder synonymous diagnoses?. Compr Psychiatry. 2012; 54(2):141-8. DOI: 10.1016/j.comppsych.2012.07.005. View

12.

McWilliams N . Some thoughts about schizoid dynamics. Psychoanal Rev. 2006; 93(1):1-24. DOI: 10.1521/prev.2006.93.1.1. View

13.

Fiske A, Henningsen P, Buyx A . Your Robot Therapist Will See You Now: Ethical Implications of Embodied Artificial Intelligence in Psychiatry, Psychology, and Psychotherapy. J Med Internet Res. 2019; 21(5):e13216. PMC: 6532335. DOI: 10.2196/13216. View

14.

Timmons A, Duong J, Simo Fiallo N, Lee T, Vo H, Ahle M . A Call to Action on Assessing and Mitigating Bias in Artificial Intelligence Applications for Mental Health. Perspect Psychol Sci. 2022; 18(5):1062-1096. PMC: 10250563. DOI: 10.1177/17456916221134490. View

15.

De la Pena-Arteaga V, Berruga-Sanchez M, Steward T, Martinez-Zalacain I, Goldberg X, Wainsztein A . An fMRI study of cognitive reappraisal in major depressive disorder and borderline personality disorder. Eur Psychiatry. 2021; 64(1):e56. PMC: 8516744. DOI: 10.1192/j.eurpsy.2021.2231. View

16.

Frewen P, Lane R, Neufeld R, Densmore M, Stevens T, Lanius R . Neural correlates of levels of emotional awareness during trauma script-imagery in posttraumatic stress disorder. Psychosom Med. 2007; 70(1):27-31. DOI: 10.1097/PSY.0b013e31815f66d4. View

17.

Elyoseph Z, Geisinger D, Nave-Aival E, Zaltzman R, Gordon C . "I Do Not Know How You Feel and How I Feel About That": Mentalizing Impairments in Machado-Joseph Disease. Cerebellum. 2023; 23(4):1265-1272. DOI: 10.1007/s12311-023-01536-2. View

18.

Pham K, Nabizadeh A, Selek S . Artificial Intelligence and Chatbots in Psychiatry. Psychiatr Q. 2022; 93(1):249-253. PMC: 8873348. DOI: 10.1007/s11126-022-09973-8. View

19.

Lane R, Quinlan D, Schwartz G, Walker P, Zeitlin S . The Levels of Emotional Awareness Scale: a cognitive-developmental measure of emotion. J Pers Assess. 1990; 55(1-2):124-34. DOI: 10.1080/00223891.1990.9674052. View

20.

De Panfilis C, Schito G, Generali I, Gozzi L, Ossola P, Marchesi C . Emotions at the border: Increased punishment behavior during fair interpersonal exchanges in borderline personality disorder. J Abnorm Psychol. 2019; 128(2):162-172. DOI: 10.1037/abn0000404. View