Reliability and Validity of a School-Based Physical Activity Questionnaire
Bibliographic record
Abstract
PURPOSE: To determine the reliability and validity of the School Health Action, Planning and Evaluation System (SHAPES) physical activity questionnaire, a machine-readable questionnaire designed to collect data from all students in a school from grades 6 to 12 and to provide feedback to the school for planning and evaluation. METHODS: Study 1 assessed test-retest reliability by administering the questionnaire twice, 1 wk apart to 2812 students in grades 9-12. Study 2 assessed criterion validity using MTI accelerometers worn consecutively for 7 d, and measured height and weight (N = 67, grades 6-12). RESULTS: The overall kappa/weighted kappa coefficient for the 1-wk test-retest reliability of the questionnaire items indicated moderate agreement (mean 0.57 +/- 0.24). Self-reported and accelerometer-measured average daily time spent performing moderate to vigorous physical activity were significantly correlated (Spearman r = 0.44, P < 0.01); however, students tended to overreport physical activity. Height and weight were not consistently over- or underreported. Self-reported and measured body mass index were significantly correlated (Spearman r = 0.90, P < 0.001). Classification of weight status by body mass index was similar using self-reported values compared with measured values. CONCLUSION: The findings of these studies suggest that the SHAPES physical activity questionnaire has acceptable reliability and validity and is suitable for use in large-scale school-based data collections for child and adolescent populations.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".