Pubertal timing and depressive symptoms in late adolescence: The moderating role of individual, peer, and parental factors
Bibliographic record
Abstract
This longitudinal study examined personal-accentuation and contextual-amplification models of pubertal timing. In these models, individual and contextual risk factors during childhood and adolescence can magnify the effects of early or late puberty on depression symptoms that occur years later. The moderating role of prepubertal individual factors (emotional problems in late childhood) and interpersonal factors (deviant peer affiliation, early dating, perceived peer popularity, and perceived parental rejection during adolescence) were tested. A representative sample of 1,431 Canadian adolescents between 10-11 and 16-17 years of age was followed biannually. In line with the personal-accentuation model, early puberty has been shown to be a predictor for depression in both girls and boys who presented emotional problems in childhood. This effect was also noted for late maturing boys. Consistent with the contextual-amplification model, early puberty predicted later depression in youth who perceived greater parental rejection. Interpersonal experiences such as early dating in girls and deviant peer affiliation in boys predicted depression in early maturers as well. For girls, early dating was also found to be amplified by childhood emotional problems. In line with biopsychosocial models, results indicate that the effect of pubertal timing on depressive symptoms must be conceptualized through complex interactions between characteristics of adolescents' interpersonal relationships and prepubertal vulnerabilities.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".