Meeting preschool screen time recommendations: which parental strategies matter?
Bibliographic record
Abstract
Background: High levels of screen use by preschoolers may contribute to adverse health and developmental outcomes. Little is known about which parental strategies may be protective against intensive screen use by children. Our aim is to estimate whether parent strategies for mediating child screen time including restrictive and instructive mediation and social coviewing, predict preschooler adherence to the screen time recommendation of ≤1 h/day during the COVID-19 pandemic. We also examine if parent restrictive mediation interacts with child temperament characteristics. Methods: Our sample is composed of 315 Canadian parents of preschoolers surveyed during the COVID-19 pandemic. Parents provided measures of child adherence to screen time guidelines at ages 3.5 (baseline) and 4.5 years. Parents also reported how often they used restrictive and instructional mediation, and social coviewing to manage their child's screen use. Control variables include child sex and temperament (effortful control, negative affectivity, extraversion), educational attainment, and parenting stress at age 3.5. Results: A logistic regression revealed that parental restrictiveness was associated with a 4 time increase in the odds of adherence to screen time guidelines, OR = 4.07 (95% CI [1.70-13.03]). Parental social coviewing decreased the chances of adherence by 80% (OR = 0.20, 95% CI [0.09-0.48]). Furthermore, children not meeting recommendation at 3.5 were 98% less likely to respect the recommendation 1 year later (OR = 0.02, 95% CI [0.01-0.07]). Results were adjusted for child sex, temperament, baseline screen time, and parent education and stress The interaction between the restriction mediation and child temperament on later screen time was not significant. Conclusion: Our results indicate that some parental strategies may be more effective than others for managing preschooler screen time. Parent use of restrictive mediation was most likely to forecast child adherence to later screen time recommendations. The present results may contribute to the development of targeted family-based interventions designed to promote healthy development from a young age.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".