Keeping Kids Busy: Family Factors Associated with Hands-on Play and Screen Time During the COVID-19 Pandemic
Bibliographic record
Abstract
Parent-child interactions are crucial for child development. The COVID-19 pandemic has negatively affected mental health and increased parenting challenges impacting parent-child functioning. The aim of the current study was to examine the relationship between parent factors and child activities to identify parental needs. A convenience sample of parents (N = 708), primarily mothers (n = 610; 87.4%) aged 35.59 years old (SD = 5.59; range = 21-72), with children ages 2-8 years completed an online questionnaire between April 14-June 1, 2020. Participants mostly resided in Canada and had an income of >$100,000. Parent-child activities were measured as total weekly time and combined time across activities within two categories: hands-on play and screen time. Bivariate correlations informed block-wise linear regression models. For families with childcare needs, parental anxiety was associated with higher total hands-on play (F(3,142) = 14.01, p < .001), combined hands-on play (F(2,85) = 6.82, p = .011), and combined screen time (F(2,82) = 6.25, p = .014). Families without childcare needs indicated parenting stress was associated with lower total hands-on play (F(3,212) = 7.95, p < .005) and combined hands-on play (F(2,110) = 5.67, p = .019), and higher supervised screen time (F(3,138) = 6.14, p = .014). Family structure and indices of socioeconomic status were also predictive of activities across childcare needs and child ages. To promote high-quality parent-child interactions and positive developmental outcomes in the pandemic, policy makers should support childcare needs, parent mental health and stress, and provide evidence-based guidelines for child screen time.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".