Fit to Play? Health-Related Fitness Levels of Youth Athletes: A Pilot Study
Bibliographic record
Abstract
ABSTRACT: Pfeifer, CE, Sacko, RS, Ortaglia, A, Monsma, EV, Beattie, PF, Goins, J, and Stodden, DF. Fit to play? Health-related fitness levels of youth athletes: A pilot study. J Strength Cond Res 36(1): 245-251, 2022-A recent National Strength and Conditioning Association position statement suggests that many youth are not prepared for the physical demands of sport. The purpose of this study was to compare health-related fitness (HRF) of youth athletes with normative findings from the general population. We recruited 136 athletes (63 male and 73 female athletes) aged 11-19 (16.01 ± 1.35) years and collected HRF (body composition, cardiorespiratory endurance, musculoskeletal strength and endurance). Results were categorized based on FITNESSGRAM® standards and compared with Canadian youth general population normative data. Most male athletes were classified as "needs improvement" for cardiorespiratory and muscular endurance, and body mass index (BMI). Conversely, most female athletes were at or above the "healthy fitness zone" for all measures. Male athletes at both age groups (11-14, 15-19; p < 0.001) and female athletes aged 11-14 (p < 0.05) demonstrated lower cardiorespiratory endurance compared with Canadian general population. Female athletes (both age groups) demonstrated greater muscular strength, and male athletes (age, 15-19 years) demonstrated lower BMI than the Canadian general population. The results are concerning as male athletes demonstrated poorer HRF compared with the general population. Although most female athletes were within healthy ranges, a portion of them were still at risk. Considering the demands sport places on the body, evaluating HRF is paramount for performance and injury prevention but more importantly for overall health. Youth sport and strength coaches should evaluate and aim to enhance HRF, as participation in sport does not guarantee adequate HRF. Promoting long-term athletic development and life-long health should be a priority in youth.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".