Clinical Exercise Physiology Accreditation: An Audit Of Existing Standards
Bibliographic record
Abstract
Health professions such as clinical exercise physiology (CEP) are founded on a set of standards that outline base level knowledge, skills and competencies to define the roles and scope of practice of the profession. Despite the practice of CEP having many common features regardless of the country in which it is conveyed, a harmonised set of international standards does not exist. PURPOSE: To systematically audit the professional standards for the five countries recognised as having existing national certification systems for CEP. METHODS: The audit process was conducted using a modified scoping review protocol based on the documentation provided by the American College of Sports Medicine (ACSM), Exercise & Sports Science Australia (ESSA), British Association of Sport and Exercise Sciences (BASES), Canadian Society for Exercise Physiology (CSEP), and Sport and Exercise Science New Zealand (SESNZ). Two reviewers independently extracted data from the standards documents and results were cross checked by relevant experts from each jurisdiction. RESULTS: There was commonality of themes for 60% of all content extracted. The overall coverage of themes was 60%, 67%, 76%, 88% and 98% from New Zealand, Canada, USA, UK and Australia respectively. CONCLUSION: There is a common core of themes covered by all current national standards for CEP across the five nations audited, but there is variable coverage in the remaining 40%. These findings are important for understanding the differences in current training and certification of CEP professionals, and how this might influence the internationalisation of the profession.
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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 | 0.391 | 0.582 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".