School's out: Parenting stress and screen time use in school-age children during the COVID-19 pandemic
Bibliographic record
Abstract
Background During the COVID-19 pandemic, millions of children abruptly moved to online schooling, which required high levels of parental involvement. Family routines were disrupted, potentially increasing parental stress, and may be reflected in greater media screen time use in children. Objectives To determine whether (1) parenting styles and (2) parenting stress were associated with children's screen time use during the pandemic compared to the pre-pandemic period. Methods Parents (> 18 years of age) were recruited to complete an online survey regarding changes in their children's (6–12 years) screen time use and daily activities before and during the pandemic. Stress and parental involvement were assessed using the Perceived Stress Scale (PSS) and Alabama Parenting Questionnaires respectively. General linear models assessed whether parenting style and parent stress were associated with children's screen time during the pandemic, adjusting for demographic variables and daily activities. Results 104 parents were enrolled, and 73 (70.2%) parents completed the surveys. Children's screen time (e.g., watching television and playing video games) increased significantly, from 2.6 to 5.9h a day (p = .001) during pandemic-related school closures. Fewer changes in children's screen time use were significantly associated with greater parental involvement (p = .017). Parent stress (p = .018) significantly predicted children's screen time use. Lower household income was associated with increased hours of screen time in both models (both, p < .05). Conclusions: Children's screen time increased significantly during the initial months of the pandemic. Parent stress and parenting styles may be modifiable risk factors to promote children's well-being during the ongoing pandemic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".