Mental Health Service Utilization among Students and Staff in 18 Months Following Dawson College Shooting
Bibliographic record
Abstract
Objectives The aim of this study was to investigate service utilization by students and staff in the 18 months following the September 13, 2006, shooting at Dawson College, Montreal, as well as the determinants of this utilization within the context of Canada’s publicly managed healthcare system. Methods A sample of 948 from among the college’s 10,091 students and staff agreed to complete an adapted computer or web-based standardized questionnaire drawn from the Statistics Canada 2002 Canadian Community Health Survey cycle 1.2 on mental health and well-being. Results In the 18 months following the shooting, there was a greater incidence and prevalence not only of PTSD, but also of other anxiety disorders, depression, and substance abuse. Staff and students were as likely to consult a health professional when presenting a mental or substance use disorder, with females more likely to do so than males. Results also indicated that there was relatively high internet use for mental health reasons by students and staff (14% overall). Conclusions Following a major crisis event causing potential mass trauma, even in a society characterized by easy access to public, school and health services and when the population involved is generally well educated, the acceptability of consulting health professionals for mental health or substance use problems represents a barrier. However, safe internet access is one way male and female students and staff can access information and support and it may be useful to further exploit the possibilities afforded by web-based interviews in anonymous environments.
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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 | 0.001 | 0.001 |
| 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".