Children's activities, parental concerns, and child care service utilization in the early stages of the COVID-19 pandemic
Bibliographic record
Abstract
Introduction In the early stages of the COVID-19 pandemic, most Canadian provinces and territories enacted public health measures to reduce virus spread, leading most child care centers across the country to limit or halt in-person service delivery. While it is broadly known that the range of activities available to children and youth reduced drastically as a result, research has yet to explore if and how children's activities shifted in relation to changes in child care arrangements. Method Children's activities during the early months of the pandemic were assessed based on parent-report data (n = 19,959). Activity patterns were extracted via latent profile analysis. Thereafter, differences in child-care related outcomes across profiles were compared via logistic regression models. Results Latent profile analysis yielded three distinct activity patterns: Screenies (91.5%) were children who engaged in high amounts of screen use relative to all other activities; Analog children (3.1%) exhibited mostly off-screen activities (e.g., reading, physical exercise); and children in the Balanced group (5.4%) appeared to pursue a wide variety of activities. Children were more likely to fall into the Screenies or Balanced profiles when caregivers reported changes in child care arrangements. Moreover, parents of children with Balanced activity profiles were more likely to be planning to use child care when services reopened post-pandemic, compared to parents of children in the Analog group. Discussion The present findings call attention to heterogeneity in children's activities during COVID-19, which should be considered in the context of pandemic-related child care closures. Implications for children, families, and child care services during and beyond COVID-19 are discussed.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".