Screen Time and Standardized Academic Achievement Tests in Elementary School
Bibliographic record
Abstract
Importance: Few studies have investigated the longitudinal associations between different types of screen time in young children and academic achievement in elementary school. Objective: To examine whether there is an association between screen time in young children and standardized academic achievement tests in grades 3 and 6. Design, Setting, and Participants: This prospective cohort study was conducted among children participating in the TARGet Kids! primary care cohort in Ontario, Canada, between July 2008 and June 2023. Participant data were linked to annual grades 3 and 6 provincial standardized academic achievement test results. Exposures: Parent-reported child total screen time, TV and digital media time, and video gaming time. The screen time measurement closest before the outcome was used. Main Outcomes and Measures: Academic achievement levels on standardized tests in reading, writing, and math for grades 3 and 6 were classified as below, at, or above the Ontario provincial standard. Results: This study included 3322 grade 3 children (mean [SD] age at test, 8.86 [0.28] years; 1714 [51.6%] male students) and 2084 grade 6 children (mean [SD] age at test, 11.86 [0.28] years; 1070 [51.3%] male students). Screen time was measured at mean (SD) age of 5.54 (2.36) years for grade 3 children and 7.54 (2.90) years for grade 6 children. From adjusted proportional odds models, each additional hour of total screen time was associated with 9% to 10% lower odds of achieving a higher academic level in grade 3 reading (odds ratio [OR], 0.91; 95% CI, 0.86-0.96; P = .001), grade 3 math (OR, 0.91; 95% CI, 0.86-0.96; P < .001), and grade 6 math (OR, 0.90; 95% CI, 0.84-0.96; P = .002). Similarly, higher TV and digital media time was associated with lower achievement levels in grade 3 reading and math and grade 6 math. Video game use was associated with lower achievement level in grade 3 reading (OR, 0.77; 95% CI, 0.62-0.94; P = .01). In the sex-stratified analysis, video game use among female students was associated with lower grade 3 reading and math achievement. Conclusions and Relevance: In this prospective cohort study of Canadian children recruited from primary care settings, high levels of total screen time and TV and digital media in young children were associated with lower achievement levels in reading and math on standardized tests in elementary school. Early interventions to reduce screen time exposure should be developed and tested to enhance academic achievement in elementary school.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".