Associations Between Changes in 24-Hour Movement Behaviors in Children and Adolescents During the COVID-19 Pandemic: A Systematic Review and Mediation-Based Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Although 24-hour movement behaviors are known to be interconnected, limited knowledge exists about whether change in one behavior during the COVID-19 pandemic (eg, increased screen time) was associated with change in another (eg, reduced physical activity or sleep). This review estimates mediational associations between changes in children's physical activity, screen time, and sleep during the COVID-19 pandemic. METHODS: We included studies published between January 1, 2020 and June 27, 2022, in the PubMed/MEDLINE, Embase, PsycINFO, SPORTDiscus, and Web of Science databases. Summary data were extracted from included studies and analyzed with random-effects meta-regression. RESULTS: This review included 26 studies representing 18,959 children across 18 mid-high-income countries (53% male; mean age, 11.5 [2.9] y). There was very good evidence of decreased total daily physical activity (factor change, 0.62; 90% CI, 0.47-0.81) and strong evidence of increased screen time (1.56; 90% CI, 1.38-1.77). There was very good evidence of decreased moderate to vigorous physical activity (0.75; 90% CI, 0.62-0.90) and weak evidence of increased sleep (1.02; 90% CI, 1.00-1.04). Mediational analysis revealed strong evidence that most of the reduction in total daily physical activity from before, to during, the pandemic was associated with increased screen time (0.53; 90% CI, 0.42-0.67). We observed no further mediational associations. CONCLUSION: Increased reliance on and use of screen-based devices during the COVID-19 pandemic can be linked with reduced child and adolescent physical activity. This finding links COVID-related restrictions to potential displacement effects within child and adolescent 24-hour movement behavior.
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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 | 0.018 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.038 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".