Exploring the impact of COVID-19 on the movement behaviors of children and youth: A scoping review of evidence after the first year
Bibliographic record
Abstract
PURPOSE: The objective of this scoping review was to summarize systematically the available literature investigating the relationships between the coronavirus disease 2019 (COVID-19) pandemic and movement behaviors (physical activity, sedentary behavior, and sleep) of school-aged children (aged 5-11 years) and youth (aged 12-17 years) in the first year of the COVID-19 outbreak. METHODS: Searches for published literature were conducted across 6 databases on 2 separate search dates (November 25, 2020, and January 27, 2021). Results were screened and extracted by 2 reviewers (DCP and KR) independently, using Covidence. Basic numeric analysis and content analysis were undertaken to present thematically the findings of included studies according to the associated impact on each movement behavior. RESULTS: A total of 1486 records were extracted from database searches; of those, 150 met inclusion criteria and were included for analysis. Of 150 articles, 110 were empirical studies examining physical activity (n = 77), sedentary behavior/screen time (n = 58), and sleep (n = 55). Results consistently reported declines in physical-activity time, increases in screen time and total sedentary behavior, shifts to later bed and wake times, and increases in sleep duration. The reported impacts on movement behaviors were greater for youth than for children. CONCLUSION: The COVID-19 pandemic is related to changes in the quantity and nature of physical activity, sedentary behavior, and sleep among children and youth. There is an urgent need for policy makers, practitioners, and researchers to develop solutions for attenuating adverse changes in physical activity and screen time among children and youth.
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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 | 0.021 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".