31: Objectively Measuring Physical Activity in Early Childhood Using Accelerometers: Are Four Days Enough?
Bibliographic record
Abstract
Studies of physical activity (PA) in young children have generally included only participants with at least four days of accelerometer wear-time. It is unclear whether four days characterizes usual PA in children 5 years and under. Investigating this protocol may inform future studies of early childhood obesity. To determine the minimal number of days, and what days, of accelerometer monitoring are needed to reliably estimate usual PA in young children. Ninety children (mean age=32 [range 4 to 70] months) were instructed to wear an Actical accelerometer for seven consecutive days and had at least four valid days. Intraclass correlation coefficients (ICC) and 95% CI were calculated for mean daily total PA and moderate-to-vigorous PA (MVPA) minutes derived from four days of monitoring. The Spearman-Brown prophecy formula was used to determine the required days of monitoring needed to achieve reliability estimates of 0.70, 0.80, and 0.90. A single day produced a reliability of ICC=0.70 (95% CI 0.58–0.79) and ICC=0.69 (95% CI 0.57–0.79) for total PA and MVPA, respectively. Spearman-Brown analyses indicated that two days are needed to achieve a reliability of 0.80. There were no differences between week-days and weekend days in mean total PA (205 (95% CI 187–222) vs. 210 (95% CI 192–228); P=0.70) or in mean MVPA minutes 26 (95% CI 20–32) vs. 29 (95% CI 23–36); P=0.45). Any two weekdays or weekend days of accelerometer monitoring can be used to assess usual PA in children 5 years and under. The use of a simpler protocol may improve compliance and feasibility for studies of PA 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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.003 | 0.002 |
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".