Preschooler Screen Time During the Pandemic Is Prospectively Associated With Lower Achievement of Developmental Milestones
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to assess the developmental risks associated with total screen time, and specifically newer mobile devices, in the context of the pandemic. METHODS: This study uses parent-reported data from a prospective cohort of Canadian preschool-age children. The exposure variable is child daily screen time measured at the age of 3.5 years categorized as light (<1 hr/d), moderate (1-4 hr/d), or intensive (>4 hr/d) use (N = 315). Time spent on mobile devices was considered separately as a continuous variable. Our outcome is child global development scores, which combine assessments of communication, cognitive, personal-social, and motor skills measured at the age of 4.5 years using the Ages and Stages Questionnaire (ASQ) (N = 249, 79% retained). ASQ scores were dichotomized to distinguish children at risk of developmental delays (below the 15th percentile) from those not at risk. We estimate associations between child screen time and later global development using multiple regressions adjusted for child sex and temperament, and parent education. We also examine whether associations are moderated by child and parent characteristics. RESULTS: Logistic regressions revealed that intensive users were more at risk of global developmental delays compared with light users (OR = 4.29, p = 0.020). Mobile device use was also associated with lower global scores (β = -3.064; p = 0.028), but not with risk of delays. We found no evidence that associations were moderated by child sex and temperament, or parent education. CONCLUSION: The findings suggest that intensive screen time may be associated with delays in child global development. Early childhood professionals should encourage families with preschoolers to prioritize screen-free activities to promote optimal cognitive, language, social, and motor development.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".