Normative-referenced values for health-related fitness among Czech youth: Physical fitness data from the study IPEN Adolescent Czech Republic
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to developed sex- and age-specific normative-referenced percentile values for health-related fitness among 12 to 18 years old Czech youth. METHODS: This study included cross-sectional data from 1,173 participants (50.7% boys) collected between 2013 and 2016. Participants were recruited from 32 elementary or secondary schools across eight cities located in the Czech Republic. Health-related fitness was objectively measured using both anthropometric (height, body mass, and sum of skinfolds) and performance (20-m shuttle run for cardiorespiratory endurance, modified push-ups for muscular strength/endurance, and V sit-and-reach for flexibility) tests. Sex- and age-specific normative values were calculated using the Lambda Mu Sigma method. Sex- and age-related differences in means were expressed as standardized effect sizes. RESULTS: Normative percentiles were tabulated and displayed as smoothed curves. Among boys, measures of health-related fitness generally increased with age, except for an age-related decline in the sum of skinfolds and a plateau in V sit-and-reach. Among girls, most measures of health-related fitness increased from age 12 to 16 years before stabilizing, except for the sum of skinfolds, which remained stable from age 12 to 18 years. The sex-related differences were large with boys having higher cardiorespiratory endurance and muscular strength/endurance than girls. Girls compared to boys had higher flexibility. CONCLUSIONS: This study presents the most up-to-date sex- and age-specific normative-referenced percentile values for health-related fitness among Czech youth. Normative values may be useful for fitness and public health screening and surveillance, for example, by helping to identify youth with low fitness who might benefit from a fitness-enhancing intervention.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".