A network analysis of intolerance of uncertainty, screen time, and emotional problems in chinese children with autism spectrum disorder
Bibliographic record
Abstract
Objectives Emotional problems are common in children with autism spectrum disorder (ASD) and can place a heavy burden on children and their families. This study explored the relationships between intolerance of uncertainty (IU), screen time, and emotional problems in children with ASD and neurotypical (NT) children using network analysis methods.Methods This cross-sectional study involved 767 children, including 365 with ASD (agemean ± sd = 11.60 ± 3.92) and 402 NT children (agemean ± sd = 11.11 ± 4.04). Participants completed measurements of IU, screen time, and emotional problems. Networks were constructed using Gaussian graphical models.Results In the IU -Emotional Problems (IU-EP) network, EP4 (Nervousness in new situations) and EP2 (Excessive worrying) were bridge nodes in both groups; IU6 (Cannot stand sudden events) was the unique bridge node for children with ASD, while IU11 (Worry stops him/her) was for NT children. After incorporating screen time into the IU-EP network, it was found that PST (Passive screen time) became a new bridge node in the ASD network, while AST (Active screen time) emerged as a new bridge node in the NT network.Conclusion These findings suggest that interventions should target IU and consider screen type to effectively support children’s emotional well-being.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".