Test–retest reliability of a battery of field-based health-related fitness measures for adolescents
Bibliographic record
Abstract
The main aim of this study was to determine the test-retest reliability of existing tests of health-related fitness. Participants (mean age 14.8 years, s = 0.4) were 42 boys and 26 girls who completed the study assessments on two occasions separated by one week. The following tests were conducted: bioelectrical impedance analysis (BIA) to calculate percent body fat, leg dynamometer, 90° push-up, 7-stage sit-up, and wall squat tests. Intra-class correlation (ICC), paired samples t-tests, and typical error expressed as a coefficient of variation were calculated. The mean percent body fat intra-class correlation coefficient was similar for boys (ICC = 0.95) and girls (ICC = 0.93), but the mean coefficient of variation was considerably higher for boys than girls (22.2% vs. 12.2%). The boys' coefficients of variation for the tests of muscular fitness ranged from 9.0% for the leg dynamometer test to 26.5% for the timed wall squat test. The girls' coefficients of variation ranged from 17.1% for the sit-up test to 21.4% for the push-up test. Although the BIA machine produced reliable estimates of percent body fat, the tests of muscular fitness resulted in high systematic error, suggesting that these measures may require an extensive familiarization phase before the results can be considered reliable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".