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Record W7114987144 · doi:10.1093/pch/pxaf116.067

67 Early screen use and academic achievement in elementary school: A longitudinal cohort study

2025· article· en· W7114987144 on OpenAlexaffabout

Bibliographic record

VenuePaediatrics & Child Health · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsMcMaster UniversityWilfrid Laurier UniversityToronto Metropolitan UniversityHospital for Sick Children
Fundersnot available
KeywordsAcademic achievementCohortStandardized testOddsCohort studyLongitudinal studyAssociation (psychology)Sample size determination

Abstract

fetched live from OpenAlex

Abstract Background Higher levels of screen use are linked to lower academic achievement in school-aged children and youth. Few studies have investigated the longitudinal associations between different types of early screen use (0 to 8 years) and later academic achievement. Objectives To examine the association between different types of early screen use and academic achievement in Grades 3 and 6, as measured by the Ontario provincial standardized tests. Design/Methods A longitudinal cohort study was conducted among children in the TARGet Kids! primary care cohort in Ontario, Canada between 2008 and 2023. Participant data were linked to Grades 3 and 6 provincial annual standardized test results in reading, writing, and math from 2012 to 2023. Exposures were parent-reported child total screen time, TV/digital media time, and video gaming time, collected prior to academic achievement test. Academic achievement outcomes for Grades 3 and 6 were categorized as below, at, or above the provincial standard for each subject area. Proportional odds mixed effects model accounting for family-level random effect was used to examine the association between each type of screen use and ordinal achievement in each subject area adjusting for confounders. Models were analyzed for the total sample and stratified by child sex. Results This study included 3,322 Grade 3 children (52% male) and 2,084 Grade 6 children (51% male). Screen use was measured at 5.5 years (SD=2.4) for Grade 3 children, with a mean of 1.6 hr/day, and at 7.5 years (SD=2.9) for Grade 6 children, with a mean of 1.8 hr/day. Males had higher screen use, while females outperformed males in reading and writing in both grades. Each additional hour of total screen time was associated with approximately a 10% decrease in the odds of higher achievement in Grade 3 reading (OR=0.91, 0.86-0.96, p=0.001), Grade 3 math (OR=0.91, 0.86-0.96, p<.001), and Grade 6 math (OR=0.90, 0.84-0.96, p=0.002). Similarly, higher levels of TV/digital media were associated with lower achievement in reading and math in Grade 3 and math in Grade 6. Among females, all screen types, especially video gaming (OR=0.55, 0.35-0.86, p=0.009), were associated with lower achievement in math in Grade 3. Conclusion High levels of parent-reported total screen time and TV/digital media in early childhood were associated with lower reading and math achievement in elementary school. Females with high video game use had lower math achievement in Grade 3. Our findings highlight the need to develop and test early interventions to reduce total screen time and TV/digital media exposure, considering the sex-specific associations, to enhance academic achievement in elementary school.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.865

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.031
GPT teacher head0.332
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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