School Environment and Adolescent Depressive Symptoms: A Multilevel Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE: It remains unclear whether school environments can influence the emotional health of adolescents. In this large-scale prospective study, we use multilevel modeling to examine whether the school socioeducational environment contributes to the risk of developing depressive symptoms in secondary school students. METHODS: As part of a longitudinal study on school success in disadvantaged communities, 5262 adolescents from 71 secondary schools were followed annually. Socioeducational environment was assessed by a composite measure of social climate, learning opportunities, fairness and clarity of rules, and safety. Depressive symptoms were evaluated by using the Center for Epidemiologic Studies Depression scale. Multilevel regressions tested the association between school socioeducational environment in grade 8 and depressive symptoms in grades 10 to 11, adjusting for previous depressive symptoms in grade 7 and potential confounders at the individual and school levels. RESULTS: Modest but significant variation in depressive symptoms was found between schools (intraclass correlation = 3.3%). School-level socioeducational environment in grade 8 was predictive of student depressive symptoms in grades 10 to 11, even after adjusting for potential school and individual confounders. This association was slightly stronger for girls. Student perceptions of school socioeducational environment were also predictive of depressive symptoms. Other school-level factors, including school size, were not predictive of depressive symptoms once socioeducational environment was taken into account. CONCLUSIONS: Adolescents who attend a secondary school with a better socioeducational environment are at reduced risk of developing depressive symptoms. School environments appear to have a greater influence on risk in adolescent girls than boys.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".