Prevalence of problematic psychological symptoms in samples of Canadian postsecondary students
Bibliographic record
Abstract
OBJECTIVES: To estimate the one-month prevalence of problematic psychological symptoms among Canadian postsecondary students, and to compare the prevalence by student characteristics. PARTICIPANTS: Three samples of students from two postsecondary institutions. METHODS: In a cross-sectional study conducted in 2017, we measured self-reported problems related to symptoms of depression, anxiety, and stress using questions from the functioning module of the WHO Model Disability Survey. We used modified Poisson regression modeling to compute prevalence ratios (95%CI) to compare the prevalence by student characteristics. RESULTS: Our study included 1392 students (participation rate 35%-77%). Across samples, the one-month prevalence of moderate-extreme problems ranged from 50.8%-64.7% for anxiety, 41.2%-60.8% for stress, and 29.4%-43.6% for depression. Such problems were consistently more prevalent among females, poor-quality sleepers, students with food insecurity and those with insufficient social support. CONCLUSIONS: Significant burden of problems related to psychological symptoms exists within the postsecondary student population and varies by student characteristics.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".