International Olympic Committee (IOC) Sport Mental Health Assessment Tool 1 (SMHAT-1) and Sport Mental Health Recognition Tool 1 (SMHRT-1): towards better support of athletes’ mental health
Bibliographic record
Abstract
OBJECTIVES: To develop an assessment and recognition tool to identify elite athletes at risk for mental health symptoms and disorders. METHODS: We conducted narrative and systematic reviews about mental health symptoms and disorders in active and former elite athletes. The views of active and former elite athletes (N=360) on mental health symptoms in elite sports were retrieved through an electronic questionnaire. Our group identified the objective(s), target group(s) and approach of the mental health tools. For the assessment tool, we undertook a modified Delphi consensus process and used existing validated screening instruments. Both tools were compiled during two 2-day meeting. We also explored the appropriateness and preliminary reliability and validity of the assessment tool. SPORT MENTAL HEALTH ASSESSMENT TOOL 1 AND SPORT MENTAL HEALTH RECOGNITION TOOL 1: The International Olympic Committee Sport Mental Health Assessment Tool 1 (SMHAT-1) was developed for sports medicine physicians and other licensed/registered health professionals to assess elite athletes (defined as professional, Olympic, Paralympic or collegiate level; aged 16 years and older) potentially at risk for or already experiencing mental health symptoms and disorders. The SMHAT-1 consists of: (i) triage with an athlete-specific screening tool, (ii) six subsequent disorder-specific screening tools and (iii) a clinical assessment (and related management) by a sports medicine physician or licensed/registered mental health professional (eg, psychiatrist and psychologist). The International Olympic Committee Sport Mental Health Recognition Tool 1 (SMHRT-1) was developed for athletes and their entourage (eg, friends, fellow athletes, family and coaches). CONCLUSION: The SMHAT-1 and SMHRT-1 enable that mental health symptoms and disorders in elite athletes are recognised earlier than they otherwise would. These tools should facilitate the timely referral of those athletes in need for appropriate support and treatment.
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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 | 0.022 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".