Protective factors against depression and suicidal behaviour in adolescence.
Bibliographic record
Abstract
OBJECTIVES: To examine whether protective factors in the Protection for Adolescent Depression Study (PADS) moderate the impact of stressful events on depression and suicidal behaviour in the community and a clinical setting; and to study the influence of sex. METHOD: Participants were 283 adolescents from the community and 119 from a mood disorder clinic in Montreal. The participants were evaluated on 6 instruments measuring individual risk and protective factors. Descriptive analyses and univariate and multiple logistic regression models were carried out. RESULTS: Risk factors predicted higher levels of depression and presence of suicidal behaviour, and protective factors predicted lower levels of depression and absence of suicidal behaviour, as expected under the vulnerability-resilience stress model. Several sex differences were observed in terms of the predictive power of risk factors (for example, hopelessness among girls and keep to themselves among boys) and protective factors (for example, focusing on the positive among girls and self-discovery among boys). CONCLUSIONS: Findings from the PADS suggest that protective factors moderate the impact of stress on depression and suicidal behaviour. Developing protection appears important in the presence of chronic conditions, such as depressive disorders, to reduce the likelihood of further episodes. The influence of sex makes it all the more relevant to target different factors for boys and girls to increase protection and decrease risk in prevention and intervention programs.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".