Parents’ Attitudes Regarding Their Children’s Play and Sport During COVID-19
Bibliographic record
Abstract
The COVID-19 pandemic and associated public health measures have interrupted the daily routines of parents and children. The purpose of this study was to explore parents’ attitudes regarding their children’s play/sport during COVID-19. A secondary objective was to explore the influence of parent demographics and parent-reported physical activity levels and risk tolerance on these attitudes. Ontario parents of children aged 12 and younger completed an online survey (August—December 2020) that assessed their attitudes (grouped by support, safety and socialization-related attitudes; n = 14 items) regarding their child(ren)’s play/sport, their physical activity levels ( n = 2 items), and demographic details ( n = 16 items). Two open-ended items were used to gather a deeper understanding of attitudes. Parents’ tolerance for risk was measured via the validated Tolerance of Risk in Play Scale. Descriptive statistics were calculated to describe attitudes and risk tolerance. Least Absolute Shrinkage and Selection Operator regressions were conducted to examine factors influencing parents’ attitudes. Multiple linear models were computed using the identified predictors for each attitude category. Deductive content analysis was undertaken on open-ended responses. Participants ( n = 819) reported the highest scores for safety-related attitude items ( M = 3.54, SD = .63) followed by socialization and support, which all influenced attitudes regarding children’s play/sport (p < .05). Demographics and parents’ physical activity levels were identified as important predictors of parents’ attitudes. Qualitative data revealed that parents had mixed levels of comfort with respect to their children’s return to play/sport. Findings from this study reveal that increased support is needed to guide future play/sport decision-making.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".