Screen Time Among and Youth Children With Disabilities: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVE: This paper aimed to review and synthesize screen time research among children and youth with disabilities. METHODS: Seven online databases were searched, and a machine learning-assisted systematic review model was used to identify relevant studies. English and French papers reporting on screen time among children and youth with a disability were eligible. Extracted data were synthesized by participant age, followed by type of screen time reporting. Meta-analyses were conducted to estimate daily screen time and adherence to screen time guidelines using random effects meta-analysis. RESULTS: Eighty-one studies were included. Screen time ranged from 0.5 to 7.27 h/day and varied widely based on disability type. Pooled average screen time was 3.70, 3.28 and 3.39 h/day for children and youth with ASD, ADHD and CP, respectively. CONCLUSION: Screen use is prominent among children and youth with disabilities. Limiting screen time in this group is critical in preventing numerous related consequences of excessive, prolonged use. POLICY IMPLICATIONS: Interventions targeting children and youth with disabilities are needed to decrease excessive screen time among this population and to inform future public health policy and setting-specific practice.
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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 | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.021 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".