Reliability of Fitness Tests Using Methods and Time Periods Common in Sport and Occupational Management
Bibliographic record
Abstract
CONTEXT: Fitness testing is used frequently in many areas of physical activity, but the reliability of these measurements under real-world, practical conditions is unknown. OBJECTIVE: To evaluate the reliability of specific fitness tests using the methods and time periods used in the context of real-world sport and occupational management. DESIGN: Cohort study. SETTING: Eighteen different Cirque du Soleil shows. PATIENTS OR OTHER PARTICIPANTS: Cirque du Soleil physical performers who completed 4 consecutive tests (6-month intervals) and were free of injury or illness at each session (n = 238 of 701 physical performers). INTERVENTION(S): Performers completed 6 fitness tests on each assessment date: dynamic balance, Harvard step test, handgrip, vertical jump, pull-ups, and 60-second jump test. MAIN OUTCOME MEASURE(S): We calculated the intraclass coefficient (ICC) and limits of agreement between baseline and each time point and the ICC over all 4 time points combined. RESULTS: Reliability was acceptable (ICC > 0.6) over an 18-month time period for all pairwise comparisons and all time points together for the handgrip, vertical jump, and pull-up assessments. The Harvard step test and 60-second jump test had poor reliability (ICC < 0.6) between baseline and other time points. When we excluded the baseline data and calculated the ICC for 6-month, 12-month, and 18-month time points, both the Harvard step test and 60-second jump test demonstrated acceptable reliability. Dynamic balance was unreliable in all contexts. Limit-of-agreement analysis demonstrated considerable intraindividual variability for some tests and a learning effect by administrators on others. CONCLUSIONS: Five of the 6 tests in this battery had acceptable reliability over an 18-month time frame, but the values for certain individuals may vary considerably from time to time for some tests. Specific tests may require a learning period for administrators.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".