Unraveling the long‐term links among adolescent peer victimization and somatic symptoms: A 5‐year multi‐informant cohort study
Bibliographic record
Abstract
Abstract Purpose To examine the prospective associations among peer victimization and somatic symptoms across 5 years of adolescence using multiple informants and disaggregating effects at the within‐person and between‐person level. Methods From age 13–17 years, 612 Canadian children (54% girls; 76% White) completed measures of peer victimization and somatic symptoms. Parents (89% mothers) reported on their child's somatic symptoms. We built autoregressive latent trajectory models with structured residuals, controlling for diagnosed medical and psychiatric conditions, sex, race/ethnicity, and socioeconomic status. Results Within‐person, self‐reported somatic symptoms were stable across time and there were bidirectional associations between peer victimization and somatic symptoms across the 5‐year period. The magnitude of effect was strongest from somatic symptoms to peer victimization. Between‐person, being a girl or having a psychiatric diagnosis predicted higher mean levels and rising trajectories of somatic symptoms and higher mean levels of peer victimization. The level of peer victimization among non‐White participants increased over time. In the parent‐reported model, somatic symptoms were less stable and did not predict peer victimization. Conclusions The results highlight the dynamic processes between peer victimization and somatic symptoms. Increased effort is needed to protect adolescents with psychiatric problems, girls, and ethnic minorities from peer abuse.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".