Sleep disturbance and psychotic-like experiences among urban adolescents with and without parental migration
Bibliographic record
Abstract
Aim: Sleep disturbance was closely associated with an increased risk of psychotic-like experiences (PLEs). This study aims to explore the association between sleep disturbance and PLEs among urban adolescents with and without parental migration. Methods: A total of 67, 532 urban Chinese adolescents were recruited in a large web-based survey during April 21st to May 12th, 2021. In our study, sleep disturbance, PLEs, family function, school climate, and a series of socio-demographic were assessed. And hierarchical logistic regression analyses were performed to examine influential factors associated with PLEs. Results: Urban left-behind children (LBC) had a higher prevalence of sleep disturbance and PLEs than non-LBC. After controlling for confounders, parental migration was associated to PLEs with weak significance (OR = 1.19). Meanwhile, sleep disturbance was found to be a robust risk factor for PLEs (OR = 3.84 and 4.09), with or without the effect of parental migration. In addition, better family function and school climate has significant association with decreased risk of PLEs. Conclusion: Adolescents with sleep disturbance are more likely to report PLEs. Adolescents' PLEs preventive strategies could focus on reducing sleep disturbance related symptoms as well as improving family function and school climate.
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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 | 0.000 | 0.000 |
| 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 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".