Sleep Hygiene Pattern and Behaviors and Related Factors among General Population in West Of Iran
Bibliographic record
Abstract
INTRODUCTION: Sleep hygiene was found as an important predictor for sleep quality. People's sleep hygiene can have a major role in their daily function. The purpose of the study was to determine sleep hygiene patterns and sleep hygiene behaviors and factors affecting them in the general population of Kermanshah, Iran. MATERIAL & METHODS: In this cross-sectional study, 1829 men and 1262 women were selected randomly from 50 clusters of different parts of the city. The inclusion criteria were age between 12 and 65 years and living in Kermanshah. The exclusion criteria were psychiatric disorder and known general medical conditions that affecting sleep. The data collection instruments were demographic questionnaire and Sleep Hygiene Questionnaire, consisted of 13 items about biological rhythm and bed room environment and behaviors that affecting sleep. Data were analyzed by using SPSS version 16 software. RESULTS: The highest percentage was obtained for irregular woke and went up from day to day or at weekend and holidays (74.8%). Only 213 (6.9%) participants were classified as having good sleep hygiene (score 12-14). The mean age of very poor, poor, moderate, and good sleepers was 34.8 ± 14.4, 33.7 ± 17.4, 36.5 ± 13.8, and 35 ± 13.7years, respectively. There were significant differences between the age of poor and moderate sleepers and also sleep hygiene patterns with respect to sex, education level and job. CONCLUSION: Poor sleep hygiene were more frequent in Iranian peoples and the major problem in sleep hygiene in our study was inappropriate sleep schedule.
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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 | 0.001 | 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 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".