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The plasticity of ChatGPT’s mentalizing abilities: personalization for personality structures
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...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503434/ https://www.ncbi.nlm.nih.gov/pubmed/37720897 http://dx.doi.org/10.3389/fpsyt.2023.1234397 |
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author | Hadar-Shoval, Dorit Elyoseph, Zohar Lvovsky, Maya |
author_facet | Hadar-Shoval, Dorit Elyoseph, Zohar Lvovsky, Maya |
author_sort | Hadar-Shoval, Dorit |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10503434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105034342023-09-16 The plasticity of ChatGPT’s mentalizing abilities: personalization for personality structures Hadar-Shoval, Dorit Elyoseph, Zohar Lvovsky, Maya Front Psychiatry Psychiatry 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. Frontiers Media S.A. 2023-09-01 /pmc/articles/PMC10503434/ /pubmed/37720897 http://dx.doi.org/10.3389/fpsyt.2023.1234397 Text en Copyright © 2023 Hadar-Shoval, Elyoseph and Lvovsky. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychiatry Hadar-Shoval, Dorit Elyoseph, Zohar Lvovsky, Maya The plasticity of ChatGPT’s mentalizing abilities: personalization for personality structures |
title | The plasticity of ChatGPT’s mentalizing abilities: personalization for personality structures |
title_full | The plasticity of ChatGPT’s mentalizing abilities: personalization for personality structures |
title_fullStr | The plasticity of ChatGPT’s mentalizing abilities: personalization for personality structures |
title_full_unstemmed | The plasticity of ChatGPT’s mentalizing abilities: personalization for personality structures |
title_short | The plasticity of ChatGPT’s mentalizing abilities: personalization for personality structures |
title_sort | plasticity of chatgpt’s mentalizing abilities: personalization for personality structures |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503434/ https://www.ncbi.nlm.nih.gov/pubmed/37720897 http://dx.doi.org/10.3389/fpsyt.2023.1234397 |
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