Bibliographic record
Abstract
Introduction: Adolescent media use is a potential target for detecting and preventing psychotic experiences (PEs), with evidence that adolescent media use and PEs share many psychological and social predisposing factors. However, it remains unclear whether adolescent media use is associated with subsequent PEs, and this relationship may vary according to the types and longitudinal trajectories of use.Objective: In a population-based cohort, this thesis aimed to examine the associations between adolescent media use trajectories and lifetime PEs at 23 years of age. We considered longitudinal trajectories of four types of media use between 12-17 years of age: TV viewing, video gaming, computer use, and reading. Methods: The sample included 1226 participants (713 [58.2%] female) from the Québec Longitudinal Study of Child Development, a population-based cohort of children born in 1997 and 1998 and followed up annually or biannually from 5 months through 23 years of age. Participants reported their habitual weekly amount of TV viewing, video gaming, computer use, and reading at 12, 13, 15 and 17 years of age. Lifetime occurrence of psychotic experiences was measured at 23 years of age. Covariables included sociodemographic, genetic, family, and childhood characteristics between 5 months and 12 years of age.Results: For each media category, latent class mixed modeling identified 3 group-based trajectories, with subgroups of participants following trajectories of higher use: TV viewing, 128 (10.4%); video gaming, 145 (11.8%); computer use, 353 (28.8%); reading, 140 (11.4%). Relative to lower video gaming (891 [72.7%]), a trajectory of higher video gaming was associated with higher levels of PEs at age 23 years (estimated difference, +6.6%; 95% CI, +2.4%-+11.0%). The trajectory of higher video gaming was preceded by higher levels of mental health and interpersonal problems at 12 years, and adjusting for these factors mitigated the association of higher video gaming with subsequent PEs. A curved trajectory of computer use (189 [15.4%] participants), characterized by increasing levels of use until 15 years of age followed by a decrease, was associated with higher PEs (estimated difference, +5.3%; 95% CI, +1.5%-+9.3%) relative to lower use (684 [55.8%] participants). This association was robust to covariable adjustment.Conclusion: This study found that longitudinal trajectories of media use during adolescence were differentially associated with PEs at 23 years of age. Prior mental health and relationship difficulties explained this association for the higher trajectory of video gaming, whereas a curved (increasing-then-decreasing) trajectory of computer use retained a modest association with more PEs. 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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".