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TRUVACE RECORD VERSION
record: TRV-2026-2544
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T07:51:26.699708Z
status: published
lens: p_space
sector: health
headline: Generative artificial intelligence addiction is prospectively associated with psychotic-like experiences: Evidence from a two-wave longitudinal mediation and network study
dek: Objectives With the rapid adoption of generative artificial intelligence (GAI) in learning, work, and daily life, concerns have grown about its mental health implications. Evidence beyond affective outcomes is limited. This study examined whether GAI addiction is prospectively associated with psychotic-like experiences and assessed indirect associations involving information overload and rumination. Methods A two-wave longitudinal design was used with 582 adolescents and young adults. GAI addiction, information…
gain_title: (none)
problem_title: In a two-wave study of 582 adolescents and young adults, those with higher generative AI addiction at baseline reported more psychotic-like experiences one month later (β = 0.19), partly through rumination.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: In a two-wave study of 582 adolescents and young adults, those with higher generative AI addiction at baseline reported more psychotic-like experiences one month later (β = 0.19), partly through rumination.
problem_evidence: Baseline GAI addiction was significantly associated with psychotic-like experiences at follow-up ( β = 0.19, p < .001).
quick_read: A longitudinal study of 582 adolescents and young adults found that addiction to generative AI at baseline was associated with more psychotic-like experiences at a 1-month follow-up (β = 0.19, p < .001).

Rumination, the tendency to dwell on thoughts, mediated part of that link. Information overload was not an independent mediator, but it fed into a significant serial pathway that ran through rumination.

The authors frame the results as longitudinal evidence on possible mental health correlates of generative AI use, and say the association may partly involve cognitive processes rather than being fully explained by them.
limitation: Follow-up lasted only 1 month, and the authors describe the findings as prospective associations and potential correlates, not proof that generative AI addiction causes psychotic-like experiences.
tag: Evidence-backed problem
key_points: The study followed 582 adolescents and young adults across two waves, at baseline and 1-month follow-up. | Participants were assessed on generative AI addiction, information overload, rumination and psychotic-like experiences at both points. | Baseline generative AI addiction predicted psychotic-like experiences at follow-up (β = 0.19, p < .001). | Rumination showed a significant mediating effect on the link. | Information overload was not an independent mediator but contributed to a significant serial pathway through rumination. | Network analysis found baseline psychotic-like experiences were relatively strongly associated with rumination-related items at follow-up.
rundown: Researchers used a two-wave design with serial mediation models to test whether generative AI addiction was prospectively linked to later psychotic-like experiences, through information overload and then rumination.

They also ran cross-lagged panel network analysis to look at associations among individual items. It indicated that baseline psychotic-like experiences were relatively strongly associated with rumination-related nodes at the second wave.

The authors conclude that the association between generative AI addiction and psychotic-like experiences may partly involve cognitive processes, particularly rumination, and describe the findings as potential mental health correlates of generative AI use.
sources:
- peer_reviewed | Computers in Human Behavior Reports | https://doi.org/10.1016/j.chbr.2026.101301 | 2026-09-09
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