Testing validity of FitnessGram in two samples of US adolescents (12–15 years)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it