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Trajectories of Adolescent Media Use and Their Associations With Psychotic Experiences

2024· article· en· W4394693300 on OpenAlexaffabout
Vincent Paquin, Manuela Ferrari, Soham Rej, Michel Boivin, Isabelle Ouellet‐Morin, Marie‐Claude Geoffroy, Jai Shah

Bibliographic record

VenueJAMA Psychiatry · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversité de MontréalUniversité LavalJewish General HospitalMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsLongitudinal studyPsychologyCohortMental healthInterpersonal communicationAssociation (psychology)Cohort studyYoung adultMedicineDemographyDevelopmental psychologyClinical psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Importance: Adolescent media use is thought to influence mental health, but whether it is associated with psychotic experiences (PEs) is unclear. Objective: To examine longitudinal trajectories of adolescent media use and their associations with PEs at 23 years of age. Design, Setting, and Participants: This cohort study included participants from the Québec Longitudinal Study of Child Development (1998-2021): children who were born in Québec, Canada, and followed up annually or biennially from ages 5 months through 23 years. Data were analyzed between January 2023 and January 2024. Exposures: Participants reported their weekly amount of television viewing, video gaming, computer use, and reading at ages 12, 13, 15, and 17 years. Main Outcome and Measures: Lifetime occurrence of PEs was measured at 23 years of age. Covariables included sociodemographic, genetic, family, and childhood characteristics between ages 5 months and 12 years. Results: A total of 1226 participants were included in the analyses (713 [58.2%] female, 513 [41.8%] male). For each media type, latent class mixed modeling identified 3 group-based trajectories, with subgroups following trajectories of higher use: television viewing, 128 (10.4%); video gaming, 145 (11.8%); computer use, 353 (28.8%); and reading, 140 (11.4%). Relative to lower video gaming, higher video gaming was preceded by higher levels of mental health and interpersonal problems at age 12 years. Adjusting for these risk factors mitigated the association between higher video gaming and PEs at age 23 years. The curved trajectory of computer use (189 [15.4%] participants), characterized by increasing levels of use until age 15 years followed by a decrease, was associated with higher PEs (estimated difference, +5.3%; 95% CI, +1.5% to +9.3%) relative to lower use (684 [55.8%] participants). This association remained statistically significant after covariable adjustment. Conclusions and Relevance: This study found that longitudinal trajectories of media use during adolescence were modestly associated with PEs at age 23 years, likely reflecting the influence of shared risk factors. Understanding the environmental determinants and psychosocial functions of media use during adolescence may help better integrate digital technologies in the prevention and management of PEs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.293
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2024
Admission routes2
Has abstractyes

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