Associations among screen time, sleep, mental health and cognitive functioning in school-aged children during the COVID-19 pandemic, November 2020 through to August 2022
Bibliographic record
Abstract
Objective: To examine children's screen time use and sleep patterns over 2 years of the pandemic and the downstream associations with children's executive functions and behavioural problems, as well as the moderating effects of parental factors. Method: This longitudinal cohort study examined school-aged children's lifestyle and behavioural changes over 2 years of the pandemic across 6 timepoints (November 2020 to August 2022). Latent growth modeling (LGM) was used to identify changes in screen time and sleep duration and multivariate LGM was used to determine how parental stress, positive parenting, changes in children's screen time and sleep over time were associated with children's executive functions and mental health outcomes at the final time point. Results: A total of 198 parents (children's mean age = 9.14 years) were recruited and followed up. Non-school screen time was elevated at the initial timepoint (3.6 ± 2.3 h). Positive parenting at the initial timepoint was associated with lower screen time use in children (β = -.19, p < .001; β = -.19, p < .001, in internalizing and externalizing models). Children whose screen time use was constant during the pandemic had shorter sleep durations (β = -.45, p < .05 in internalizing model). Executive function was predicted by sleep duration at the first timepoint (β = -.55, p < .001; β = .73, p < .001, in internalizing and externalizing models) and changes in screen time during the pandemic was associated with both internalizing and externalizing symptoms (β = .58, p < .05; β = .54, p < .05, in internalizing and externalizing models). Conclusion: Children's screen time decreased slightly but remained significantly higher than Canadian and International guidelines during 2 years of the pandemic. Positive parenting styles can have a significant impact on children's screen time use. Reducing excessive screen time can help improve sleep patterns and, consequently, cognitive, and emotional well-being in children.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".