Rates of Mental Illness and Associated Academic Impacts in Ontario’s College Students
Bibliographic record
Abstract
Staff at campus-based counselling and disability centres in 15 of Ontario’s 24 community colleges completed 3,536 surveys on 1,964 individual students querying the presence of mental illness and academic challenges as reported by students accessing these services. Survey data were analyzed to determine prevalence rates of mental disorders and investigate for the presence of a relationship between specific mental illnesses and any associated academic impacts. More than half of these students had diagnoses with mood and anxiety disorders being the most common individual and comorbid diagnoses. The academic challenges reported by students with mental illnesses occurred in particular patterns relative to specific diagnoses; alertness/attention challenges were associated with mood disorders, whereas memory/executive function problems were linked to anxiety disorders. Implications for training and service practices of counselling and disability staff are reviewed as are future research directions for accommodating the academic needs of students with mental illnesses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 teacher head, 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".