Early adolescent depression symptoms and school dropout: Mediating processes involving self-reported academic competence and achievement.
Bibliographic record
Abstract
Research on adolescent well-being has shown that students with depression have an increased risk of facing academic failure, yet few studies have looked at the implications of adolescent depression in the process of school dropout. This study examined mediation processes linking depression symptoms, self-perceived academic competence, and self-reported achievement in 7th grade to dropping out of school in later adolescence. We followed 493 (228 girls and 265 boys) French-speaking adolescents from low-socioeconomic-status secondary schools in Montreal (Quebec, Canada) for 6 years. Almost 34% of participants dropped out of school during this period. Findings indicated that self-reported depression symptoms in 7th grade increased the risk of dropping out of school in later adolescence. Structural equation modeling revealed that the predictive relationship between depression symptoms and school dropout was mediated by self-perceptions of academic competence. Current findings provide support for self-perceptions of competence as mediational processes in the relationship between adolescent depression symptoms and early school leaving.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".