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Problematic ChatGPT use: Manifestations, etiologies, and evaluation
Hui-Yuan Liao1, Chih-Hung Ko1, Cheng-Fang Yen2
1Department of Psychiatry, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan; Department of Psychiatry, School of Medicine, and Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
Problematic ChatGPT use is common in young adults, linked to mental health issues and cognitive deficits. Further research is needed to validate assessment tools and explore interventions for healthier AI engagement.
Area of Science:
- Artificial Intelligence
- Psychology
- Neuroscience
Background:
- ChatGPT's widespread adoption across various sectors presents both benefits and risks.
- Excessive reliance on ChatGPT can negatively impact mental health, cognition, and social functioning.
- Understanding problematic ChatGPT use is crucial for mitigating adverse effects.
Purpose of the Study:
- To synthesize evidence on the manifestations, causes, assessment, and neurophysiological underpinnings of problematic ChatGPT use.
- To provide a cross-cultural perspective on problematic ChatGPT use.
Main Methods:
- A narrative review of empirical studies, psychometric developments, theoretical models, and electroencephalogram (EEG) findings.
- Cross-cultural comparison of data from Taiwan, Turkey, China, Korea, Singapore, and the United States.
Main Results:
- Problematic ChatGPT use is prevalent in young adults, associated with depression, stress, poor self-control, and functional impairments.
- Existing psychometric tools require further validation, while theoretical models explain its development through emotional regulation deficits and cognitive biases.
- Preliminary EEG studies indicate altered brain connectivity patterns similar to digital addiction.
Conclusions:
- Problematic ChatGPT use involves complex psychological, behavioral, and neurobiological factors.
- Future research should focus on psychometric validation and EEG studies.
- Interventions like digital literacy, self-regulation, CBT, and neurofeedback are proposed for healthier AI interaction.
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