Associations Between Screen Exposure, Home Media Environments, and Indicators of School Readiness in Toddlers and Preschoolers from Kakamega County, Kenya
Bibliographic record
Abstract
Objective . Early childhood screen-time impacts school readiness, particularly in low- and middle-income countries. This study examined associations between screen-time and readiness for formal schooling among toddlers and preschoolers in Kakamega County, Kenya. Methods. A cross-sectional study of 144 children aged 2 to 5 years was conducted using the Denver II developmental screening and ECDI2030 to assess school readiness. Parent-reported questionnaires captured demographic data and screen media exposure. Results . Participants’ median age was 48 months (IQR = 20.75), with an average screen-time of 2.0 hours/day (IQR = 1.425), exceeding recommended guidelines of 1 hour. Children exceeding recommended screen-time had 52% lower odds of readiness, while parental supervision increased readiness odds by 68%. While parental age was associated with readiness, child sex, household income, and educational content showed no significant associations. Conclusion . Excessive screen-time may result in lower readiness, emphasizing risks in low-resource settings. Parental involvement and culturally tailored interventions are vital for early childhood development.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".