Response inhibition in neurodiverse children and the association with excessive screen time use
Bibliographic record
Abstract
Abstract The aim of this study was to examine response inhibition using a gamified version of the Stroop task in a heterogeneous cohort of neurodiverse and neurotypical children, and to identify any key risk factors of screen time associated with performance-based measures of cognition. A total of 229 participants ages 3-16 (89 neurotypical children [54% boys] 90 children with ADHD [51% boys], and 50 children with ASD [72% boys]) were recruited to the study. Using a validated online cognitive battery, participants completed the Stroop task. Parents completed questionnaires regarding children’s screen time use (passive TV watching, social media, video games), sleep, daily/weekly physical activities, socializing, reading, and extracurricular activities. Very few children in the study met national guidelines for screentime, regardless of their neurodiagnostic group (X2=3.71, p=0.16). Based on a multivariate model, performance on congruent and incongruent trials on the Stroop task were comparable between the groups, however autistic children were more likely to make more attempts on the tasks (F(2)=4.35, p=0.014), indicative of reduced impulse control. In a subsequent model examining screen time and other lifestyle factors in relation to performance on the Stroop task, increased video game use was a significant predictor of more attempts. An interaction analysis revealed that only autistic children who spent more time playing video games used more attempts on the Stroop task (B=0.095, p<0.001). Conclusion: Autistic children demonstrated reduced impulse control compared to neurotypical children and children with ADHD. Further, time spent playing video games was associated with decreased response inhibition only in autistic children. Findings indicate that screen time use, particularly video games, may be a modifiable risk factor for response inhibition processes in autistic children. Findings could inform school- or community-based programs focused on screen time awareness and monitoring screen time use in neurodiverse children.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".