Treasured but not measured ?: Impact of the COVID-19 pandemic on physical literacy in children and adolescents
Bibliographic record
Abstract
Objective: Physical literacy is treasured because it underpins participation in physical activity and sport in children and adolescents. Physical literacy might have declined following COVID-19 movement restrictions, but whether such a decline took place is uncertain. This study aimed to examine if a post-COVID-19 decline in physical literacy occurred in children and adolescents. Methods: A systematic review, registered on PROSPERO CRD42025646499 in February 2025, was used to assess changes in physical literacy following the COVID-19 pandemic in healthy, typically developing 3-18 year olds. Searching in June 2025 used 7 databases: Scopus, Web of Science, SPORTDiscus, PsychINFO, CINAHL, PubMed, Sports Medicine & Education Index and a grey literature search in Global Think Tanks.Risk of bias assessment used the Effective Public Health Practice Project (EPHPP) instrument. Results: Only one eligible study was identified, which reported declining physical literacy in 8-14 year olds in Canada between 2019 and 2020.Evidence quality was moderate as assessed using the EPHPP. Conclusion: The impact of COVID-19 movement restrictions on physical literacy in children and adolescents could not be assessed due to lack of evidence. The lack of evidence on such an important topic is a valuable finding in itself. Understanding trends in physical literacy will require greater monitoring, and the inclusion of physical literacy measurement in public health surveillance. If physical literacy is really treasured it should be measured.
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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 | 0.016 | 0.095 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".