Sensitivity, specificity, and reliability of the Get Active Questionnaire for identifying children with medically necessary special considerations for physical activity
Bibliographic record
Abstract
Physical activity is promoted for optimal health but may carry risks for children who require medically necessary activity restrictions. The sensitivity, specificity, and reliability of the Get Active Questionnaire (GAQ) for identifying children needing special considerations during physical activity was evaluated among parents of 207 children aged 3 to 14 years (97 (47%) female, mean age of 8.4 ± 3.7 years). GAQ responses were compared with reports obtained directly from the treating physician (n = 192/207) and information in the medical chart (clinic notes/physician letter, n = 111/207). Parent GAQ responses (either “No to all questions” or “Yes to 1 or more questions”) agreed with physician (κ = 0.16, p = 0.003) and medical record (κ = 0.15, p = 0.003) reports regarding the need for special consideration during physical activity (Yes/No). Sensitivity was 71% (20/28) and specificity was 59% (96/164), with few false-negative responses. The GAQ was most effective for rheumatology and cardiology patients. False positives were 29% to 46%, except among chronic pain (80%) and rehabilitation (75%) patients. Test–retest reliability was moderate (Cronbach’s α = 0.70) among 57 parents who repeated the GAQ 1 week later. The GAQ effectively identified children not requiring physical activity restrictions and those with medical conditions similar to those of concern among adults. Additional questions from a qualified exercise professional, as recommended for a “Yes” response on the GAQ, should reduce the false-positive burden. Indicating the timeframe of reference for each question and including an option to describe other special considerations (e.g., medication, supervision) are recommended.
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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 | 0.016 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".