Quick, Effective Screening Tasks Identify Children With Medical Conditions or Disabilities Needing Physical Literacy Support
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
PURPOSE: This study evaluated screening tasks able to identify children with medical conditions or disabilities who may benefit from physical literacy. METHOD: Children completed ≤20 screening tasks during their clinic visit and then the Canadian Assessment of Physical Literacy (2nd edition) at a separate visit. Total Canadian Assessment of Physical Literacy scores <30th percentile were categorized as potentially needing physical literacy support. Receiver operator characteristic curves identified assessment cut points with 80% sensitivity and 40% specificity relative to total physical literacy scores. RESULTS: 223 children (97 girls; 10.1 [2.6] y) participated. Physical activity adequacy, predilection, and physical competence achieved ≥80% sensitivity and ≥40% specificity in both data sets. Adequacy ≤ 6.5 had 86% to 100% sensitivity and 48% to 49% specificity. Daily screen time >4.9 hours combined with Adequacy ≤6.15 had 88% to 10% sensitivity and 53% to 56% specificity. CONCLUSIONS: Activity adequacy, alone or with screen time, most effectively identified children likely to benefit from physical literacy support. Adequacy and screen time questionnaires are suitable for clinical use. Similar results regardless of diagnosis suggest physical competence deficits are not primary determinants of active lifestyles. Research to enhance screening specificity is required.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it