Effects of flexible learning spaces, active breaks, and active lessons on sedentary behaviors, physical activity, learning, and musculoskeletal health in school-aged children: a scoping review
Bibliographic record
Abstract
BACKGROUND: Children aged 6 to 17 spend long periods of sitting at school. Reducing these behaviors and increasing physical activity has been linked to improvements in cognitive functions and decreased musculoskeletal issues. The purpose of this scoping review was to describe interventions implementing flexible learning spaces, active breaks, and active lessons and their effects on sedentary behaviors as well as on physical activity, learning, and musculoskeletal health. METHODS: A search on databases (EDUCATION SOURCE, ERIC, SPORTDISCUS, MEDLINE, EMBASE, and WEB OF SCIENCE) was carried out in April 2021 and updated in June 2022 according to the guidelines of the "PRISMA-ScR". Studies on flexible learning spaces and physical activity in elementary and secondary school classes were retained. These also had to measure the effects of the interventions on sedentary behaviors, physical activity, learning (e.g., academic achievement), and musculoskeletal health outcomes. RESULTS: Ninety-two articles were identified; twenty-four from the initial screening, thirty-two from the update, and thirty-six were manually included. Among these 92 articles, twenty-one studies used only flexible learning spaces, twenty-three used only active breaks, thirty-six used only active lessons, four used both flexible learning spaces and active breaks separately in different classes, five combined active breaks and active lessons, and three combined flexible learning spaces and active breaks. Analyses show positive changes in sedentary behaviors (32 articles/40) and physical activity (52 articles/74) including sitting time, sit-to-stand transitions, number of steps, and moderate-to-vigorous physical activity. Positive effects were also observed on learning (13 articles/26) or musculoskeletal health outcomes (3 articles/8). Although many studies found no effect of these interventions, no studies report harmful interventions on these variables. The most effective strategy to reduce sedentary behaviors seems to be flexible learning spaces with adapted teaching approaches. CONCLUSIONS: Results indicate that flexible learning spaces, active breaks, and active lessons effectively reduce sedentary behaviors and increase physical activity without negatively influencing academic achievement. Further studies are needed to understand better the effects of combining these interventions and their effects on children's learning and musculoskeletal health outcomes.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.007 |
| 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".