Problematic use of generative artificial intelligence chatbots: current stage of conceptual and clinical understanding
Abstract
The potential negative consequences of generative AI are the subject of intense debate, with pragmatic and theoretical arguments and counterarguments advanced by mental health specialists, researchers, and policymakers regarding its impact on creativity, overall functioning, and psychosocial wellbeing. The current narrative review addresses historical and conceptual developments in the problematic use of generative AI chatbots (PUGAIC) and empirical findings on its epidemiology, risk factors, assessment instruments, and proposed pathophysiological mechanisms, without advancing PUGAIC as a formally established diagnostic entity. Preliminary data suggest that emotional attachment, anthropomorphism, instant reinforcement, and parasocial dynamics may contribute to compulsive use of generative AI in vulnerable individuals. However, current evidence remains limited, without clinical correlates, predominantly cross-sectional, and culturally constrained. Existing measurement tools are in early stages of validation, and diagnostic boundaries between high engagement in generative AI-related activities, problematic use, and addiction-like behavior remain unclear. While moral apprehension and overpathologization are pitfalls that should be avoided, clinicians have to remain attentive to cases involving functional impairment, psychological distress, and loss of control. In conclusion, based on the available data, PUGAIC may be conceptualized as a potential spectrum phenomenon embedded…
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