Cognitive schemas as longitudinal predictors of self-reported adolescent depressive symptoms and resilience
Bibliographic record
Abstract
Given that depression risk intensifies in adolescence, examining associates of depressive symptoms during the shift from childhood to adolescence is important for expanding knowledge about the etiology of depression symptoms and disorder. A longitudinal youth report was employed to examine the trajectory of both the content and structure of positive and negative schemas in adolescence and also whether these schemas could prospectively predict depressive symptoms and youth-reported resilience. One hundred and ninety-eight participants (aged 9 to 14) were recruited from four schools to complete measures of youth depressive symptoms, resilience, and schema content and structure. Those who consented to a follow-up study completed the same measures online (50 participants completed). Negative and positive schema content and structure were related over time. After controlling depressive symptoms/resilience at Time 1, negative schema content was the only significant predictor (trend level) of depressive symptoms and resilience at Time 2. Implications for cognitive theories and clinical practice are discussed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".