Mental Health Literacy and Confidence in a Sample of Student Athletic Therapists
Bibliographic record
Abstract
Intercollegiate student-athletes appear to be a high-risk population with respect to mental health. Student athletic therapists are one of the groups with whom these athletes may be comfortable disclosing concerns. The current study investigated the relationship between mental health literacy and mental health referral efficacy in a sample of intercollegiate student therapists. One hundred and eleven student athletic therapists (81 female, 29 male, 1 nondiscloure) competed a revised version of the multicomponent mental health literacy measure and a four-item measure of mental health referral efficacy. T tests revealed statistically significant differences in mental health literacy by gender and personal history, and a multiple linear regression revealed a significant model predicting referral efficacy from mental health literacy. There are several implications of these results, particularly when working with a high-risk population of student-athletes.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".