Sleep deprivation in two Saskatchewan First Nation communities: a public health consideration
Bibliographic record
Abstract
OBJECTIVES: Sleep deprivation is a common problem in Canada and is associated with many health problems. More than a quarter of Canadians get fewer than the recommended sleep hours (<7 h). This paper examines the prevalence and risk factors for sleep deprivation in two First Nation communities in Saskatchewan, Canada. METHODS: The baseline cross-sectional survey was completed between 2018 and 2019 in collaboration with the two Cree First Nation communities in Saskatchewan, Canada. There were five hundred and eighty-eight participants participated in the survey from two communities. A Multivariate logistic regression model was used for analysis. RESULTS: The prevalence of sleep deprivation (<7 h of sleep) was 25.4%. The multivariate logistics regression revealed that middle and older age groups, visible mold in the house, and being male with nighttime insomnia symptoms were significantly associated with a higher risk of sleep deprivation among study participants in the study. CONCLUSIONS: In these two First Nation communities, a higher proportion of the participants reported having sleep deprivation. This was a unique study, which evolved from ongoing research collaboration with two First Nation communities in Saskatchewan, Canada. Findings will be helpful in the management of patients with sleep deprivation in these communities; as well as for co-creating policy with the communities and future research priorities.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".