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The Role of Biological Rhythms in Generative AI Addiction: Associations with Chronotype and Sleep Quality
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- TRV-2026-2592raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Survey
- Sources
- 1 sourcePeer-reviewed
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Abstract The rapid diffusion of Generative Artificial Intelligence (GenAI) technologies among university students has introduced a novel domain of technology-related behavioral risk. Although prior research on digital addiction has predominantly focused on psychological determinants of internet and smartphone overuse, the potential role of circadian preference and sleep in problematic GenAI use remains underexplored. This study examined associations between chronotype, sleep quality, and GenAI addiction. Using a…
The problem
In a survey of 868 undergraduates at a public university, evening-type students scored higher on generative AI addiction than morning and intermediate types, and poorer sleep went with higher scores.
What this doesn’t fix
The cross-sectional design at a single public university shows associations only, and the authors say longitudinal and multi-method research is still needed.
Sources
1 on file- International Journal of Mental Health and Addictiondoi:10.1007/s11469-026-01679-3
Cite this record
v1Truvace Impact Record TRV-2026-2592, v1: “The Role of Biological Rhythms in Generative AI Addiction: Associations with Chronotype and Sleep Quality.” Truvace, 2026-11-12. /record/TRV-2026-2592 (accessed on the day you copy it). sha256 457f255f64ed3d4b…
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