Sleep Patterns, Excessive Daytime Sleepiness, and Sleep Disturbance Among First Nations Children in Saskatchewan
Bibliographic record
Abstract
Sleep is essential for maintaining both mental and physical well-being. It plays a critical role in the health and development of children. This study investigates sleep patterns and habits of First Nations children, the prevalence of sleep disturbances, and excessive daytime sleepiness (EDS), along with the factors associated with EDS. Our 2024 First Nations Children Sleep Health Study assessed the sleep health of children aged 6 to 17 years living in a First Nation in Canada. Statistical analyses were performed using comparison tests and logistic regression models. A total of 78 children participated; 57.7% were boys. The average age of the participants was 10.49 years (SD = 3.53 years). On school days, children aged 6 to 9 years slept an average of one additional hour, while on weekends, they slept an extra 40 min compared to adolescents aged 10 to 17 years. Only 39.7% of the children (ages 6 to 17) slept alone in a room, with more than 80% of the children sharing a bed every night. Only 30.6% of the children aged 6 to 9 years and 7.2% of the adolescents aged 10 to 17 years adhered to the recommended maximum screen time of 2 h on school days. More than two-thirds of the children reported experiencing sleep disturbances. The prevalence of EDS was 19.7%. After adjusting for age and sex, it was determined that the children who snored loudly and those who did not sleep in their own beds were more likely to experience abnormally high levels of daytime sleepiness. A high proportion of children exceeded the recommended screen time, an important public health issue. Further, identifying sleep patterns among children will facilitate the diagnosis and treatment of disordered sleep.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".