Are we levelling the playing field? A qualitative case study of the awareness, uptake and relevance of the IOC consensus statements in two countries
Bibliographic record
Abstract
OBJECTIVES: Research evidence is commonly compiled into expert-informed consensus guidelines intended to consolidate and distribute sports medicine knowledge. Between 2003 and 2018, 27 International Olympic Committee (IOC) consensus statements were produced. This study explored the policy and practice impact of the IOC Statements on athlete health and medical team management in two economically and contextually diverse countries. METHODS: A qualitative case study design was adopted. Fourteen face-to-face interviews were conducted with purposively selected interviewees, seven participants from Australia (higher economic equality) and seven from South Africa (lower economic equality), representing their national medical commissions (doctors and physiotherapists of Olympic, Paralympic and Youth teams). A framework method was used to analyse interview transcripts and identify key themes. RESULTS: Differences across resource settings were found, particularly in the perceived usefulness of the IOC Statements and their accessibility. Both settings were unsure about the purpose of the IOC Statements and their intended audience. However, both valued the existence of evidence-informed guidelines. In the Australian setting, there was less reliance on the resources developed by the IOC, preferring to use locally contextualised documents that are readily available. CONCLUSION: The IOC Statements are valuable evidence-informed resources that support translation of knowledge into clinical sports medicine practice. However, to be fully effective, they must be perceived as useful and relevant and should reach their target audiences with ready access. This study showed different contexts require different resources, levels of support and dissemination approaches. Future development and dissemination of IOC Statements should consider the perspectives and the diversity of contexts they are intended for.
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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 | 0.035 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.017 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".