Classroom Activity Breaks Improve On-Task Behavior and Physical Activity Levels Regardless of Time of Day
Bibliographic record
Abstract
Classroom physical activity breaks (CAB) are beneficial for increasing children’s physical activity (PA) levels as well as the amount of time spent being on-task within the classroom. Purpose: To examine the effect of CAB at different times within the school day on on-task behavior and PA levels in primary school (grade 1–3) children. Methods: Thirty-five children (6 ± 1 y, 22 = male, 13 = female) participated in four conditions in a randomized order: morning (AM), afternoon (PM), morning and afternoon (BOTH), and no CAB (CTRL). CAB followed a traditional Tabata format of 20 s work and 10 s rest repeated 8 times for a total of 4 min. PA levels were monitored (accelerometry). On-task behavior and three types of off-task (motor, verbal, passive) were recorded following each CAB (mobile application). Results: When compared to control, AM, PM, and BOTH increased on-task behavior AM: Δ10.4%, PM: Δ10.5%, BOTH: Δ14%; p < .001). AM was most beneficial for reducing off-task motor (Δ-6.5%) and off-task verbal (Δ-3%) behavior, while PM was most beneficial for reducing off-task passive (Δ-9%) behavior. These effects were greatest in those students demonstrating higher amounts off-task behavior during CTRL (r > 0.67, p < .001). Students achieved an additional 8.4 (p = .070; d = 0.93), 12.2 (p < .001, d = 0.49), and 6.3 min (p = .09, d = 0.47) of moderate-vigorous physical activity (MVPA) over 24 h following a CAB vs CTRL in AM, PM, and BOTH, respectively. Additionally, performing any of the CAB conditions increased the number of steps taken during the school day by an average of 2007 steps (p < .009). Conclusion: Overall, these results demonstrate that CAB improve both on-task behavior and PA levels, regardless of time of day. However, performing two CAB (BOTH) is recommended to derive the greatest improvements in on-task behavior across the school day.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".