The predictive relationship between parents’ perceptions of physical activity and children’s physical literacy
Bibliographic record
Abstract
Parents play an important role in children’s physical literacy development (across cognitive, physical, affective, and behavioral domains) and physical activity participation. The purpose of this study was mainly to ascertain the predictive effects of parents’ perceptions of physical activity (PPPA) on children’ physical literacy and its four domains. Children ( N = 195; M age = 9.09 ± 1.08) from five classes at one primary school in Central China completed the simplified Chinese version of Canadian Assessment of Physical Literacy version two (CAPL-2). Their parents completed the PPPA questionnaire that measured parental attitude, awareness, value, understanding, and appreciation. We also gathered data on demographic and anthropometric factors including gender, age, socioeconomic status (SES), and body mass index (BMI). Hierarchical linear modeling (HLM; child nested in classes) was used to examine the predictive effects of PPPA on children’s physical literacy and its four domains, after controlling for gender, age, SES, BMI, and gender of participating parent. The children’s total physical literacy level was at the progressing stage ( M = 66.91 ± 10.13) and their parents’ PPPA averaged at 92.50 ± 3.81 (87.62%). PPPA significantly predicted physical literacy ( β = 0.61, p < 0.01) and its cognitive ( β = 0.11, p = 0.03) and physical domains ( β = 0.17, p < 0.01). Parental valuing significantly predicted physical literacy ( β = 0.88, p = 0.01) and its physical ( β = 0.27, p = 0.03) and affective domains ( β = 0.32, p = 0.02). Parental understanding also predicted physical literacy ( β = 0.91, p = 0.04). PPPA, especially valuing and understanding, is an influential factor to consider when fostering children’s physical literacy.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".