Offsides! Surveying mental health in sport officials across Canada
Bibliographic record
Abstract
The objective of this study was to establish a baseline of knowledge surrounding sport officials’ mental health in Canada. A survey comprised of several adapted validated questionnaires was distributed to sport officials across Canada. 229 participants (77.9% male; Mage = 42.2 years) completed this survey, representing 10 sports. Results indicated a prevalence of mental health symptoms including depression (18.8%), post traumatic stress disorder (15.0%), attention deficit hyperactivity disorder (12.6%), generalized anxiety disorder (6.2%), and eating disorders (3.6%). 16.6% of officials warranted a diagnosis of a mild mental disorder, 12.5% of a moderate mental disorder, and 9.4% of a severe mental disorder. While officiating, 5.1% felt sexually harassed in the past year, 16.8% reported exposure to physical violence, and 44.4% reported being threatened, bullied, or harassed. Significant differences were present between genders on the Mental Health Literacy Scale (p = .01), Kessler 10 (p = .007), and Patient Health Questionnaire 4 (p = .001) and indicated that female officials have higher mental health literacy, but more distress than their male counterparts. The high prevalence of mental health outcomes reported by sport officials in Canada supports the current literature indicating that mental health is affecting sport officials.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".