Mental health need of students at entry to university: Baseline findings from the U‐Flourish Student Well‐Being and Academic Success Study
Bibliographic record
Abstract
AIM: Transition to university is associated with unique stressors and coincides with the peak period of risk for onset of mental illness. Our objective in this analysis was to estimate the mental health need of students at entry to a major Canadian university. METHODS: After a student-led engagement campaign, all first year students were sent a mental health survey, which included validated symptom rating scales for common mental disorders. Rates of self-reported lifetime mental illness, current clinically significant symptoms and treatment stratified by gender are reported. The likelihood of not receiving treatment among those symptomatic and/or with lifetime disorders was estimated. RESULTS: Fifty-eight per cent of all first-year students (n = 3029) completed the baseline survey, of which 28% reported a lifetime mental disorder. Moreover, 30% of students screened positive for anxiety symptoms, 28% for depressive symptoms, and 18% for sleep problems with high rates (≅45%) of associated impairment. Only 8.5% of students indicated currently receiving any form of treatment. Females were more likely to report a lifetime diagnosis, anxiety and depressive symptoms, as well as current treatment. Over 25% of students reported lifetime suicidal thoughts and 6% suicide attempt(s). Current weekly binge drinking (25%) and cannabis use (11%) were common, especially in males. CONCLUSIONS: There is limited systematically collected data describing the mental health needs of young people at entry to university. Findings of this study underscore the importance of timely identification of significant mental health problems as part of a proactive system of effective student mental health care.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".