Validity of low-cost measures for global surveillance of physical activity in pre-school children: The SUNRISE validation study
Bibliographic record
Abstract
Abstract Objectives To validate parent-reported child habitual total physical activity against accelerometry and three existing step-count thresholds for classifying 3 h/day of total physical activity in pre-schoolers from 13 culturally and geographically diverse countries. Design Cross-sectional validation study. Methods We used data involving 3- and 4-year-olds from 13 middle- and high-income countries who participated in the SUNRISE study. We used Spearman's rank-order correlation, Bland–Altman plots, and Kappa statistics to validate parent-reported child habitual total physical activity against activPAL™-measured total physical activity over 3 days. Additionally, we used Receiver Operating Characteristic Area Under the Curve analysis to validate existing step-count thresholds (Gabel, Vale, and De Craemer) using step-counts derived from activPAL™. Results Of the 352 pre-schoolers, 49.1 % were girls. There was a very weak but significant positive correlation and slight agreement between parent-reported total physical activity and accelerometer-measured total physical activity (r: 0.140; p = 0.009; Kappa: 0.030). Parents overestimated their child's total physical activity compared to accelerometry (mean bias: 69 min/day; standard deviation: 126; 95 % limits of agreement: −179, 316). Of the three step-count thresholds tested, the De Craemer threshold of 11,500 steps/day provided excellent classification of meeting the total physical activity guideline as measured by accelerometry (area under the ROC curve: 0.945; 95 % confidence interval: 0.928, 0.961; sensitivity: 100.0 %; specificity: 88.9 %). Conclusions Parent reports may have limited validity for assessing pre-schoolers' level of total physical activity. Step-counting is a promising alternative – low-cost global surveillance initiatives could potentially use pedometers for assessing compliance with the physical activity guideline in early childhood.
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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 | 0.023 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".