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User Preferences on AI Psychotherapy Based on Moderating Effects of Individual Personality Traits: Employing a Clustering Analysis.

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Title: User Preferences on AI Psychotherapy Based on Moderating Effects of Individual Personality Traits: Employing a Clustering Analysis.
Authors: Lee, Jieon (AUTHOR), You, Jong Soo (AUTHOR), Lee, Daeho (AUTHOR)
Source: International Journal of Human-Computer Interaction. Jan2025, Vol. 41 Issue 2, p1010-1027. 18p.
Subjects: Artificial intelligence, K-means clustering, Client-centered psychotherapy, Mental health counseling, Personality
Abstract: The recent appearance of AI psychological counseling services is expected to lower physical, economic, and psychological burdens for individuals seeking psychological counseling and increase participation in the service. AI psychological counseling research is still in its infancy, and therefore it is important to consider client preference to achieve positive effects. However, no research has been conducted to investigate client preferences regarding AI therapists. Therefore, this study explores the characteristics of AI counselors preferred by clients (e.g., rapport, trust, expertise, and attraction), as well as which AI agent therapist characteristics have positive effects on the attitudes of clients (users). This study confirms the characteristics that affect client intention to use AI counseling. Groups were divided using the K-means clustering technique based on the individual's degree of introversion/extroversion and depression because characteristics desired in AI counselors may differ depending on individual client inclinations and examined differences between groups. The results of this study will help enhance and supplement the capabilities of developers and actual counselors through client-tailored counseling. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: User Preferences on AI Psychotherapy Based on Moderating Effects of Individual Personality Traits: Employing a Clustering Analysis.
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  Data: <searchLink fieldCode="AR" term="%22Lee%2C+Jieon%22">Lee, Jieon</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22You%2C+Jong+Soo%22">You, Jong Soo</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lee%2C+Daeho%22">Lee, Daeho</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. Jan2025, Vol. 41 Issue 2, p1010-1027. 18p.
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  Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22K-means+clustering%22">K-means clustering</searchLink><br /><searchLink fieldCode="DE" term="%22Client-centered+psychotherapy%22">Client-centered psychotherapy</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+health+counseling%22">Mental health counseling</searchLink><br /><searchLink fieldCode="DE" term="%22Personality%22">Personality</searchLink>
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  Data: The recent appearance of AI psychological counseling services is expected to lower physical, economic, and psychological burdens for individuals seeking psychological counseling and increase participation in the service. AI psychological counseling research is still in its infancy, and therefore it is important to consider client preference to achieve positive effects. However, no research has been conducted to investigate client preferences regarding AI therapists. Therefore, this study explores the characteristics of AI counselors preferred by clients (e.g., rapport, trust, expertise, and attraction), as well as which AI agent therapist characteristics have positive effects on the attitudes of clients (users). This study confirms the characteristics that affect client intention to use AI counseling. Groups were divided using the K-means clustering technique based on the individual's degree of introversion/extroversion and depression because characteristics desired in AI counselors may differ depending on individual client inclinations and examined differences between groups. The results of this study will help enhance and supplement the capabilities of developers and actual counselors through client-tailored counseling. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/10447318.2024.2307695
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        Text: English
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        PageCount: 18
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        Type: general
      – SubjectFull: K-means clustering
        Type: general
      – SubjectFull: Client-centered psychotherapy
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      – SubjectFull: Mental health counseling
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      – SubjectFull: Personality
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      – TitleFull: User Preferences on AI Psychotherapy Based on Moderating Effects of Individual Personality Traits: Employing a Clustering Analysis.
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              Text: Jan2025
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