Problematic ChatGPT Use Scale: AI-Human Collaboration or Unraveling the Dark Side of ChatGPT

Abstract Artificial intelligence (AI)-driven tools like ChatGPT have rapidly integrated into daily life, raising concerns about problematic use and psychological impacts. However, validated tools to assess maladaptive interaction patterns are limited. This study evaluated the psychometric properties of the Problematic ChatGPT Use Scale (PCGUS) within a Turkish sample. Study I included 391 participants (61.4% female, mean age = 30.89), while study II involved 473 participants (74.4% male, mean age = 28.25). In study I, confirmatory factor analysis (CFA) confirmed the unidimensional structure of the 9-item scale, and measurement invariance (MI) was established at configural, metric, and scalar levels. The scale demonstrated acceptable reliability, and Item Response Theory (IRT) analysis showed strong item discrimination. Problematic ChatGPT use (PCGU) correlated positively with AI addiction, internet gaming disorder, and internet addiction, and negatively with conscientiousness. Study II revealed that psychological distress and self-control mediated the relationship between PCGU and well-being, highlighting the importance of these factors in predicting healthy AI engagement.

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Publication Details

Journal
International Journal of Mental Health and Addiction
Published
2025-06-11
DOI
https://doi.org/10.1007/s11469-025-01509-y
Citations
6
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
3.93

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article

Problematic ChatGPT Use Scale: AI-Human Collaboration or Unraveling the Dark Side of ChatGPT

Seydi Ahmet Satıcı, Sibel Maral, Huzeyfe Bilmez, Nagihan Naycı et al.
6 citations
International Journal of Mental Health and Addiction
Artificial Intelligence in Healthcare and Education
3.93
article

Problematic ChatGPT Use Scale: AI-Human Collaboration or Unraveling the Dark Side of ChatGPT

Seydi Ahmet Satıcı, Sibel Maral, Huzeyfe Bilmez, Nagihan Naycı, Elif İrem Erdemir
article en
6 citations

Abstract

Abstract Artificial intelligence (AI)-driven tools like ChatGPT have rapidly integrated into daily life, raising concerns about problematic use and psychological impacts. However, validated tools to assess maladaptive interaction patterns are limited. This study evaluated the psychometric properties of the Problematic ChatGPT Use Scale (PCGUS) within a Turkish sample. Study I included 391 participants (61.4% female, mean age = 30.89), while study II involved 473 participants (74.4% male, mean age = 28.25). In study I, confirmatory factor analysis (CFA) confirmed the unidimensional structure of the 9-item scale, and measurement invariance (MI) was established at configural, metric, and scalar levels. The scale demonstrated acceptable reliability, and Item Response Theory (IRT) analysis showed strong item discrimination. Problematic ChatGPT use (PCGU) correlated positively with AI addiction, internet gaming disorder, and internet addiction, and negatively with conscientiousness. Study II revealed that psychological distress and self-control mediated the relationship between PCGU and well-being, highlighting the importance of these factors in predicting healthy AI engagement.

International Journal of Mental Health and Addiction
Yıldız Technical University (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Openalex Percentile: Top 6%
Artificial Intelligence in Healthcare and Education
3.93
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