The Relationship Between Sleep Health, Sleep Regularity, Optimism, and Well-Being With Self-Rated Health: A Study on Healthcare Professionals
Bibliographic record
Abstract
Background and Objective This study investigates the impact of sleep, well-being, and optimism on self-rated health among healthcare professionals in the United Arab Emirates (UAE).Methods A cross-sectional approach was employed, using Pearson correlation and linear regression to analyze the relationship between sleep, well-being, optimism, and self-rated health among health care professioansl in the UAE.Results The age range of the participants was between 20–65 years, and they were predominantly female (68.7%). Significant predictors of self-rated health included well-being (p < 0.001), optimism (p = 0.004), and sleep circadian regularity (p = 0.009), explaining 10% of the variance in self-rated health (R2 = 0.103). Among the participants, 84.1% worked in public hospitals, and 15.9% in private hospitals. Regarding body mass index, 43.9% were of normal weight, 4.8% underweight, 32.4% overweight, and 18.9% obese. Males reported higher well-being and sleep continuity scores than females.Conclusions The study highlights the critical role of sleep health, well-being, and optimism in shaping healthcare professionals’ self-rated health. These results suggest that improving these mental health factors can positively influence healthcare professionals’ self-rated health, potentially enhancing their performance and patient care quality. Further research is needed to identify additional determinants and to establish causal relationships through longitudinal studies.
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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 | 0.020 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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".