SynthesisFrontiers in psychology2026
Addicted, attached, or just delegating? A scoping review on "problematic artificial intelligence use".
Synthesis in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- The dark side of AI in education: AI dependency as a mediator linking academic self-efficacy and teacher support to learning burnout among university students.Frontiers in psychology · 2026Article
- Are students dependent on AI in writing courses? Analyzing factors influencing dependence on generative AI through the I-PACE model.Frontiers in psychology · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
Background: The rapid diffusion of generative and conversational AI has raised concerns about problematic AI use and AI dependence. This led to a proliferation of studies addressing the problem, despite the lack of a common framework. This scoping review maps: (RQ1) definitions, (RQ2) measurement approaches, (RQ3) correlates and outcomes, and (RQ4) preliminary evidence across operationalization. Methods: Following PRISMA-ScR guidelines, we searched Web of Science and Scopus using predefined strings on artificial intelligence and problematic use. Thirty-seven empirical peer-reviewed studies were included. Results: Findings highlight inconsistent terminology and considerable heterogeneity in how problematic AI use is conceptualized, exacerbated by a frequent gap between constructs and operationalization that limits interpretation of outcomes. After recoding measures by their substantive operationalization, we analyzed evidence for three main strands: (1) behavioral addiction and/or compulsive use, consistently associated with depression, loneliness, social anxiety, escapism, flow state and low self-esteem/self-efficacy, where younger age and male gender emerge as risk factors; (2) cognitive (over)reliance, linked to performance expectations, academic stress/frustration of needs and literacy/trust in AI, with converging evidence of an erosion of downstream skills (and a decline in performance when AI is unavailable); and (3) Psychological and emotional dependence, associated with loneliness, anxious attachment, anthropomorphizing, and the perception of warmth/emotional intelligence, reliability and availability of AI. Conclusion: The field is fragmented and would benefit from clearer construct specification, AI-specific validated scales capturing all features of the phenomenon, and more longitudinal and experimental designs to clarify causal mechanisms and support safer system design. Systematic review registration: OSF, accessible at: https://osf.io/cxqrz.
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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 OpenQuestion graph.