Cognitive Vulnerability to Depression in Canadian and Chinese Adolescents
Bibliographic record
Abstract
The goal of the current study was to compare diathesis-stress and transactional models of cognitive vulnerability to depression in samples of Canadian (n = 118) and Chinese (n = 405) adolescents. We utilized a six-month multi-wave, longitudinal design in order to examine whether (a) perceived control moderated the association between the occurrence of dependent interpersonal stressors and subsequent increases in depressive symptoms (i.e., a diathesis-stress perspective) and (b) dependent interpersonal stressors mediated the association between perceived control and subsequent increases in depressive symptoms (i.e., a transactional perspective). Results from idiographic, time-lagged, hierarchical linear modeling analyses indicated that for Canadian adolescents both diathesis-stress and transactional models were significant predictors of depressive symptomology. When examining the diathesis-stress model, boys, but not girls, who reported lower perceived control, reported higher levels of depressive symptoms following the occurrence of dependent interpersonal stress. Gender differences, however, were not present in the transactional model. In contrast, transactional, but not diathesis-stress, models were significant in Chinese adolescents, and gender differences did not emerge. Overall, these results may reflect culturally-relevant differences in the etiology of depression in Canadian and Chinese adolescents.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".