1075 Factors Associated with the Use of Self-help Strategies for Sleep in Children and Adolescents with Epilepsy
Bibliographic record
Abstract
Abstract Introduction Sleep problems are common in children and adolescents with epilepsy. Our previous analyses have shown that this population used a variety of self-help strategies to improve sleep. However, factors associated with the use of these self-help strategies have not been investigated. Exploring these factors is crucial for identifying the groups of children and adolescents most in need of intervention. This cross-sectional observational study aims to examine factors associated with the use of self-help strategies for sleep in children and adolescents with epilepsy. Methods A convenience sample of 251 children and adolescents with epilepsy aged 1-18 years and their parents or caregivers were recruited from a university-affiliated hospital in Northern Taiwan. Participants completed a socio-demographic form and 1-week diaries documenting their self-help strategies for sleep. Multivariate regression analyses were conducted to explore factors associated with the use of self-help strategies for sleep in children and adolescents with epilepsy. Results The mean age of children and adolescents with epilepsy was 6.1 ± 4.47 years, and 56.2% were male. A total of 177 (70.5%) parents reported using self-help strategies to help their children’s sleep. The most commonly used self-help strategies were accompanying the child (46.6%) and relaxation techniques (25.1%). Multivariate analyses revealed that younger age (β = -.071, p <.01), having an employed mother (β = 0.371, p <.01), being an only child (β = 0.312, p <.01), and a higher frequency of seizures over the past 3 months (β =.284, p <.01) were significantly associated with greater strategy use. Conclusion This study shows that various demographic and clinical factors are associated with the use of self-help strategies for improving sleep in children and adolescents with epilepsy. Future studies should explore how these factors influence the choice and effectiveness of self-help strategies for sleep in this population. Support (if any) This work was supported by the National Science and Technology Council, Taiwan, MOST 104-2314-B-002-115-MY3 and NSTC 112-2628-B-002-003.
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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 | 0.000 | 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) | 0.000 | 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".