ReviewFrontiers in public health2026
Problematic use of generative artificial intelligence chatbots: current stage of conceptual and clinical understanding.
Review in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Generative Artificial Intelligence Use and Adolescent Mental Health.Current pediatrics reports · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
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 within broader psychosocial vulnerabilities rather than as an established clinical disorder. Longitudinal research, cross-cultural validation of instruments, and neurocognitive investigations are needed to clarify its nosological status and inform preventive and therapeutic strategies.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.