Stress and Depression in Students
Bibliographic record
Abstract
BACKGROUND: The prevalence of mental health issues appears to be increasing. Stress that leads to depression may be mediated if people believe that they have the wherewithal to manage it. OBJECTIVE: The aim of this study was to examine the extent to which the relationship between adverse stress and depression is mediated by university students' perceived ability to manage their stress. METHOD: Students were sampled randomly at a Canadian university in 2006 (n = 2,147) and 2008 (n = 2,292). Data about students' stress (1 item), depression (4 items), stress management self-efficacy (4 items), and their demographics were obtained via the online National College Health Assessment survey and analyzed using confirmatory factor analysis and latent variable mediation modeling. RESULTS: Greater stress management self-efficacy was associated with lower depression scores for students whose stress impeded their academic performance, irrespective of their gender and age (total Rdepression = 41%). The relationship between stress and depression was mediated partially by stress management self-efficacy (37% to 55% mediation, depending on the severity of stress). CONCLUSIONS: Identifying students with limited stress management self-efficacy and providing them with appropriate supportive services may help them to manage stress and prevent depression.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".