Testing validity of FitnessGram in two samples of US adolescents (12–15 years)
Bibliographic record
Abstract
BACKGROUND: This study examined the validity of the FitnessGram® criterion-reference cut-points for cardiorespiratory fitness (CRF) based on two samples of US adolescents (aged 12-15 years). This study also established the CRF cut-points for metabolically healthy weight status based on a recent national fitness survey for the purposes of cross-validating with pre-existing cut-points including FitnessGram. METHODS: in mL/kg/min) was estimated from a submaximal exercise test. CRF categories based on FitnessGram cut-points, a clustered cardiometabolic risk factors score and weight status were used. A series of Receiver Operating Characteristic (ROC) curve analyses were conducted to identify age- and sex-specific CRF cut-points that were optimal for metabolically healthy weight status. RESULTS: Based on FitnessGram cut-points, having high risk CRF, but not low risk CRF, was associated with high cardiometabolic risk (OR = 3.17, 95% CI = 1.14-8.79) and unhealthy weight status (OR = 5.81, 95% CI = 3.49-9.68). The optimal CRF cut-points for 12-13-year-olds and 14-15-year-olds were 40 and 43 mL/kg/min in males and 39 and 34 mL/kg/min in females, respectively. Compared to meeting new CRF cut-points, not meeting new CRF cut-points was associated with higher odds of showing high cardiometabolic risk (OR = 2.91, 95% CI = 1.47-5.77) and metabolically unhealthy weight status (OR = 4.47, 95% CI = 2.83-7.05). CONCLUSION: FitnessGram CRF cut-point itself has rarely been scrutinized in previous literature. Our findings provide partial support for FitnessGram based on two samples of US adolescents. CRF cut-points established in this study supports international criterion-referenced cut-points as well as FitnessGram cut-points only for males. FitnessGram should be continuously monitored and scrutinized using different samples.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".