Mental health comorbidities following peer victimization across childhood and adolescence: a 20-year longitudinal study
Bibliographic record
Abstract
BACKGROUND: Peer victimization is associated with a wide range of mental health problems in youth, yet few studies described its association with mental health comorbidities. METHODS: To test the association between peer victimization timing and intensity and mental health comorbidities, we used data from 1216 participants drawn from the Quebec Longitudinal Study of Child Development, a population-based birth cohort. Peer victimization was self-reported at ages 6-17 years, and modeled as four trajectory groups: low, childhood-limited, moderate adolescence-emerging, and high-chronic. The outcomes were the number and the type of co-occurring self-reported mental health problems at age 20 years. Associations were estimated using negative binomial and multinomial logistic regression models and adjusted for parent, family, and child characteristics using propensity score inverse probability weights. RESULTS: Youth in all peer victimization groups had higher rates of co-occurring mental health problems and higher likelihood of comorbid internalizing-externalizing problems [odds ratios ranged from 2.06, 95% confidence interval (CI) 1.52-2.79 for childhood-limited to 4.34, 95% CI 3.15-5.98 for high-chronic victimization] compared to those in the low victimization group. The strength of these associations was highest for the high-chronic group, followed by moderate adolescence-emerging and childhood-limited groups. All groups also presented higher likelihood of internalizing-only problems relative to the low peer victimization group. CONCLUSIONS: Irrespective of timing and intensity, self-reported peer victimization was associated with mental health comorbidities in young adulthood, with the strongest associations observed for high-chronic peer victimization. Tackling peer victimization, especially when persistent over time, could play a role in reducing severe and complex mental health problems in youth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".