An Examination of Risky Media Use by Preschoolers During the COVID-19 Pandemic
Bibliographic record
Abstract
Abstract Background Risky media use in terms of accumulating too much time in front of screens and usage before bedtime in early childhood is linked to developmental delays, reduced sleep quality, and unhealthy media use in later childhood and adulthood. For this reason, we examine patterns of media use in pre-school children and the extent to which child and family characteristics contribute to media use during the COVID-19 pandemic. Methods A cross-sectional study of digital media use by preschool-aged children (mean age =3.45, N=316) was conducted at the start of the COVID-19 pandemic between April and August of 2020. Parents completed a questionnaire and 24-hour recall diary in the context of an ongoing study of child digital media use. From these responses we estimated hours of average daily screen time, screen time in the past 24 hours, average daily mobile device use, and media use before bedtime. Parents also answered questions about their child (i.e., age, sex, temperament), family characteristics (parental mediation style, parental screen time, education, income), and contextual features of the pandemic (ex., remote work, shared childcare). Daycare closures were directly assessed using a government website. Results Our results indicate that 64% of preschoolers used more than 2 hours of digital media hours/day on average during the pandemic. A majority (56%) of children were also exposed to media within the hour before bedtime. Logistic regression results revealed that child age, temperament, restrictive mediation, family income and education were all correlates of risky digital media use by children. Conclusions Our results suggest widespread risky media use by preschoolers during the pandemic. Parenting practices that include using more restrictive mediation strategies may foster benefits in regulating young children’s screen time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".