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Sleep Med Res > Volume 15(3); 2024 > Article
Amiri, Boyd, Alajlouni, Al-Rawi, Samra, Kieu, and Khan: The Relationship Between Sleep Health, Sleep Regularity, Optimism, and Well-Being With Self-Rated Health: A Study on Healthcare Professionals

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.

INTRODUCTION

The well-being of healthcare professionals is crucial for the efficient functioning of healthcare systems globally. However, a significant proportion of healthcare workers report suboptimal self-rated health, which raises concerns about their overall well-being and the potential impact on healthcare delivery [1-3]. Studies have shown that up to 28.6% of healthcare professionals rate their health poorly, with the figure rising to 58% among nurses [4].
Self-rated health encompasses mental, physical, social, and functional dimensions and is linked to morbidity, mortality, chronic diseases, depression, anxiety, and stress [5-7]. Sleep disturbances, characterized by disruptions in sleep onset, irregular schedules, and excessive drowsiness, significantly impact self-rated health [8,9]. Insufficient sleep is associated with increased risks of dementia, inflammation, myocardial infarction, mortality, type 2 diabetes, suicidal thoughts, and depressive symptoms [10].
Psychological well-being, which includes positive emotions and a sense of purpose, is another critical factor influencing health. It promotes reduced disease risk and improved health outcomes [11,12]. Optimism, defined as the expectation of positive outcomes, is similarly linked to better health and reduced mortality [13,14]. Among healthcare professionals, optimism is associated with better function, patient satisfaction, and therapeutic outcomes [15].
Despite the extensive study of these factors, there is a notable gap in research specifically focusing on healthcare professionals in the United Arab Emirates (UAE). Region-specific studies are limited, particularly in the Middle East, where cultural, social, and occupational contexts may uniquely influence health and wellbeing. This study addresses this gap by examining sleep, wellbeing, and optimism in relation to self-rated health among UAE healthcare professionals, including clinical shift workers such as doctors, nurses, pharmacists, paramedics, and technicians.
Using the Socio-Ecological Model [16], we hypothesize that poor sleep health, irregular sleep patterns, lower optimism levels, and diminished psychological well-being correlate with poor self-rated health. We also consider the roles of social support, workplace dynamics, and organizational policies. By focusing on the UAE, this research aims to provide insights that are relevant to similar contexts and offer evidence-based recommendations to enhance the well-being of healthcare professionals.

METHODS

Study Design

This is a cross-sectional study aimed at evaluating the health and well-being of healthcare professionals across the UAE.

Ethical Considerations

Ethical approval was secured from the Social Sciences Research Ethics Committee (Reference: ERS_2021_8423). The study adhered to ethical guidelines laid out by Helsinki [17].

Study Population and Sampling

Healthcare professionals who are actively employed in the UAE and are 18 years of age or older and are willing to participate were included in the study. Healthcare professionals in this study include clinical workers such as medical doctors, nurses, paramedics, technicians, physical assistants, therapists, psychologists, and pharmacists. Participants who were not healthcare professionals were excluded from the study. Furthermore, healthcare professionals who were not currently practicing in the UAE, individuals below 18 years, and those unable to provide informed consent were excluded from the study.

Sample Size Calculation

The sample size was calculated based on the population size of 50000 healthcare professionals in the UAE, a 95% confidence level (Z = 1.96), a margin of error of 5%, and a design effect of 1. Considering an expected response rate of 50%, the required sample size was initially calculated to be approximately 382 participants [18].

Questionnaires

Sociodemographic survey

Survey respondents were asked questions about their demographic characteristics. The variables used in the current analysis are self-reported height, weight, gender, smoking status, and nature of healthcare occupation.

Self-rated health question from the 5-level EQ-5D version

The single question, “We would like to know how good or bad your health is today,” was utilized from the 5-level EQ-5D version (EQ-5D-5L) to measure self-rated health. For this question, the participant was asked to indicate his or her answer on a scale of 0–100.

Health and well-being from WHO-Five Well-Being Index

This questionnaire was formed from the WHO (Ten) Well-Being Index [19,20]. This questionnaire intends to measure emotional well-being during the previous two weeks. It contains five items with a 6-point Likert scale ranging from 0 (at no time) to 5 (all of the time). Raw scores are converted to a 0–100 scale with lower scores indicating poorer well-being with a cut-off score ≤50 suggested for depression [21,22].

Sleep health

To measure sleep health, five self-reported items were utilized with each item being scored on a 3-point scale: 0 (rarely/never), 1 (sometimes), and 2 (usually/always) [23]. A higher score is indicative of better sleep health. The study shows the psychometric properties of this sleep health measurement tool [24].

The Revised Life Orientation Test

This questionnaire has 10 items that are intended to measure optimism. Six of these 10 items are scored on a 5-point Likert scale: 0 (strongly disagree), 1 (disagree), 2 (neutral), 3 (agree), and 4 (strongly agree). Four of the items are not included in the scoring. A higher score in this questionnaire indicates more optimism [25].

Sleep Regularity Questionnaire

The Sleep Regularity Questionnaire (SRQ) was used to assess the degree to which individuals engage in consistent sleep behaviors. The SRQ items were selected to evaluate the full breadth of sleep-related behaviors. Participants rated each of the 10 items on a scale from 0 (not at all) to 4 (very much) regarding how much they agreed with each statement. The minimum and maximum score of this questionnaire is 0 and 24, respectively. The SRQ is a unique tool among the numerous self-reported sleep questionnaires frequently used in both clinical and research settings. Commonly used self-reported sleep measurement tools query about sleep disturbance, insomnia symptoms, daytime sleepiness, and beliefs and attitudes about sleep. However, none of the commonly used sleep questionnaires contain a single item on the regularity or inconsistency in which these sleep-related thoughts and behaviors occur. This questionnaire has two subscales: 1) circadian regularity factor: questions 1, 5, 6, and 8 (minimum and maximum score are 0 and 16); and 2) sleep continuity factor: questions 3 and 4 (minimum and maximum score are 0 and 8). This is concerning given the recent evidence suggesting the importance of sleep regularity above and beyond habitual sleep habits [26].

Statistical Analysis

Several steps were taken to analyze the data of this study. First, the data was cleaned and each variable was coded. Subsequently, the frequency and percentage were calculated for demographic indicators, and the subgroups of each were also reported. The mean, standard deviation, variance, minimum and maximum were calculated for each of the independent and dependent variables in this dataset. The Pearson correlation coefficient was first used to test the relationship between the variables. Because the dependent variables were continuous, linear regression was used for the association between independent and dependent variables. Finally, the SPSS Version 26 (IBM Corp., Armonk, NY, USA) was utilized for the data analysis.

RESULTS

The participants in this study were 661 healthcare professionals. Females consisted of 68.7% and males consisted of 31.3% of the population. The age range of the participants was between 20–65 years. Among the participants, 84.1% were working in public hospitals and 15.9% in private hospitals. Non-smokers were 77% of the participants, 9.7% former smokers, and 13.3% current smokers. Additionally, 87.7% of the participants had never consumed alcohol. In terms of body mass index, 4.8% were underweight (<18.5 kg/m2), 43.9% normal weight (18.5–24.9 kg/m2), 32.4% overweight (25–29.9 kg/m2), and 18.9% obese (≥30 kg/m2). Other details of the participants are listed in Table 1.
Table 2 shows the mean, standard deviation, and other descriptive indicators of each of the variables studied in this research including well-being, optimism, sleep health, sleep regularity, self-rated health, and sleep continuity.
To understand the relationship between research variables, Pearson correlation coefficient was used first. The correlation results among well-being, optimism, sleep health, sleep regularity, and self-rated health are shown in Table 3.
The Pearson correlation coefficient between each research variable showed that well-being, optimism, sleep health, and sleep circadian regularity have a significant positive correlation with self-rated health. The highest correlations were for well-being (r = 0.280), followed by optimism and sleep circadian regularity (r = 0.161 each), and sleep health (r = 0.118). This shows that higher levels of well-being and sleep health are associated with higher levels of self-rated health. Sleep continuity does not show a significant correlation with self-rated health (Supplementary Table 1 in the online-only Data Supplement).
Linear regression was used between self-rated health based on well-being, optimism, sleep regularity, and sleep health. The results are shown in Table 4. The results show that the regression model is significant, which suggests that some of the variables included in the model were able to predict self-rated health. The F test was equal to 15.099 and the level of significance was p < 0.001, indicating the significance of the model. The R2 coefficient shows that this model explains the 10% variance. From the total predictor variables included in the model, three variables were significant and were able to predict self-rated health, including well-being (p < 0.001), optimism (p = 0.004), and sleep circadian regularity (p = 0.009). Well-being and optimism are significant in men but not circadian regularity; well-being and circadian regularity are significant in women but not optimism.
A comparison was made between men and women in the studied variables including self-rated health, well-being, optimism, sleep regularity, sleep continuity, and sleep health. The results are listed in Table 5. The comparison of men and women in the studied variables showed that males had higher scores in well-being and sleep continuity compared to females. This suggests that males are healthier in terms of quality of life and sleep.

DISCUSSION

The study examined the relationship between self-rated health and factors such as sleep health, well-being, and optimism among healthcare professionals in the UAE. Our results demonstrated that better sleep health, higher psychological well-being, and optimism positively correlate with self-rated health.
Prior studies have confirmed the correlation between sleep and health, whereby inadequate sleep is connected to many adverse health consequences such as depression, cardiovascular illnesses, and reduced life expectancy [27-29]. Our study found that higher levels of psychological well-being and optimism are associated with better self-rated health. Psychological well-being and optimism reduce common mental disorders and physical diseases, contributing to improved self-rated health [30-32]. The mechanisms include neuronal and immune system responses [33,34]. Additionally, well-being and optimism correlate with positive life outcomes, including longevity, academic success, and work productivity [35,36].
The study revealed gender disparities, as males reported superior well-being and sleep continuity. This aligns with studies indicating that women are more prone to inadequate sleep [37]. The higher vulnerability to psychiatric problems in women, such as depression and anxiety, may also contribute to these differences [38]. Longer working hours have been more associated with depressive symptoms in women than men [39]. Gender discrimination in the workplace can exacerbate job dissatisfaction and lower well-being among female healthcare professionals [40].
Although the study identified important factors that positively influence self-rated health, the amount of variation explained by these factors was quite small. The R2 value of 0.1 suggests that there are additional unmeasured factors that significantly influence self-rated health. In addition, the study found no significant link between sleep continuity and self-rated health, indicating that other factors of sleep, such as duration and quality, may have a greater impact. These findings emphasize the intricate nature of the factors that influence self-rated health and indicate that more research is necessary to uncover other determinants.
The strengths of our study are noteworthy. Firstly, its unique focus on healthcare professionals in the UAE provides valuable insights into a previously under-explored demographic. Secondly, the analysis of the interplay between sleep, well-being, and optimism offers an understanding of factors affecting self-rated health. Additionally, the statistical methods utilized in this study enhance the reliability of our findings. The study’s relatively diverse participant pool ensures broader applicability of the results, contributing significantly to the existing body of literature on healthcare professionals’ health and well-being.
The limitations of this study encompass its cross-sectional design and dependence on self-reported data, which could potentially induce bias. Notedly, the primary outcome, self-rated health, was based on a single self-rated item, resulting in potential subjective bias. As this study included mostly doctors and nurses in the UAE, the results may not be applicable to other populations. In order to establish causal links, future studies should utilize longitudinal designs and objective measurements of sleep and well-being. Furthermore, it is important to take into account aspects like as job satisfaction, levels of stress, and the existence of psychiatric or physical illnesses in order to have a more comprehensive understanding of the elements that influence an individual’s self-rated health.
Overall, this study highlights the significant importance of sleep health, well-being, and optimism in determining the self-rated health of healthcare professionals. The highest correlation with improved self-rated health was observed with higher levels of psychological well-being, followed by optimism and regularity in sleep patterns. Thus, the findings suggest that improved mental health in healthcare professionals can positively affect self-rated health, which can consequently enhance performance. Therefore, it is necessary to both screen for mental health and to identify the factors that have a wide impact on the mental health of healthcare professionals. Implementing focused treatments to strengthen these qualities can greatly improve their emotional and physical well-being, hence enhancing their performance and the quality of patient care. It is essential to acknowledge and tackle the distinct obstacles encountered by various genders in the healthcare sector in order to enhance their overall welfare.

Supplementary Materials

The online-only Data Supplement is available with this article at https://doi.org/10.17241/smr.2024.02257.
Supplementary Table 1.
Partial correlation coefficient by controlling sex, age, type of professional practice, length of night working hours per day in month
smr-2024-02257-Supplementary-Table-1.pdf

NOTES

Availability of Data and Material
The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.
Author Contributions
Conceptualization: Sohrab Amiri, Alexander Kieu, Moien A.B. Khan. Data curation: Sohrab Amiri, Moien A.B. Khan. Formal analysis: Sohrab Amiri. Methodology: Sohrab Amiri, Alexander Kieu, Moien A.B. Khan. Project administration: Alexander Kieu, Moien A.B. Khan. Software: Moien A.B. Khan. Supervision: Sohrab Amiri, Alexander Kieu. Validation: all authors. Writing—original draft: all authors. Writingr—eview & editing: all authors.
Conflicts of Interest
The authors have no potential conflicts of interest to disclose.
Funding Statement
None

ACKNOWLEDGEMENTS

None

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Table 1.
Demographic descriptions of the participants
Characteristic Value (n = 661)
Age (yr)
 20–30 354 (53.5)
 31–40 191 (28.9)
 41–50 78 (11.8)
 51–65 38 (5.8)
Type of professional practice
 Doctor 472 (71.4)
 Nurse 183 (27.7)
 Allies health care professionals 6 (0.9)
Length of night working in last month (h/day)
 0 104 (15.7)
 1–6 44 (6.7)
 8 185 (28.0)
 ≥12 328 (49.6)

Values are presented as n (%).

Table 2.
Descriptive statistics for self-rated health, well-being, optimism, sleep health, and sleep regularity (n = 661)
Self-rated parameter Scores
Mean ± SD Range (min–max)
Self-rated health 71.30 ± 21.52 0–100
WHO well-being 50.68 ± 20.44 0–100
Optimism 13.86 ± 3.54 0–24
Sleep health 5.31 ± 2.19 0–10
Sleep circadian regularity 7.41 ± 3.90 0–16
Sleep continuity 3.68 ± 2.24 0–8

SD, standard deviation.

Table 3.
Pearson correlation coefficients (r) for well-being, optimism, sleep health, sleep regularity with self-rated health (n = 661)
Self-rated parameter Self-rated health WHO well-being Optimism Sleep health Sleep circadian regularity
Self-rated health -
WHO well-being 0.280** -
Optimism 0.161** 0.167** -
Sleep health 0.118** 0.261** 0.039 -
Sleep circadian regularity 0.161** 0.238** 0.050 0.444** -
Sleep continuity 0.044 0.152** -0.088* 0.249** 0.583**

* p < 0.05;

** p < 0.01.

Table 4.
Linear regression for self-rated health based on well-being, optimism, sleep regularity and sleep health
Predictors Overall
p-value R2
Unstandardized coefficients
Standardized coefficients
B Std. Error Beta
WHO well-being 0.25 0.041 0.24 <0.001 0.103
Optimism 0.66 0.231 0.11 0.004
Sleep circadian regularity 0.72 0.274 0.13 0.009
Sleep continuity -0.58 0.443 -0.06 0.188
Sleep health 0.09 0.413 0.01 0.832
Predictors Female
p-value R2
Unstandardized coefficients
Standardized coefficients
B Std. Error Beta
WHO well-being 0.30 0.048 0.29 <0.001 0.113
Optimism 0.32 0.271 0.05 0.236
Sleep circadian regularity 0.81 0.324 0.15 0.013
Sleep continuity -0.85 0.529 -0.09 0.110
Sleep health -0.40 0.493 -0.04 0.417
Predictors Male
p-value R2
Unstandardized coefficients
Standardized coefficients
B Std. Error Beta
WHO well-being 0.165 0.081 0.14 0.041 0.132
Optimism 1.36 0.438 0.21 0.002
Sleep circadian regularity 0.39 0.508 0.07 0.438
Sleep continuity 0.52 0.823 0.48 0.531
Sleep health 0.98 0.854 0.100 0.196
Table 5.
Comparison between male and female in self-rated health, well-being, optimism, sleep regularity and sleep health
Self-rated parameter Scores (mean ± SD)
Mean difference p-value
Male Female
Self-rated health 70.05 ± 22.21 71.87 ± 21.19 -1.82 0.313
WHO well-being 54.87 ± 19.33 48.76 ± 20.66 6.11 <0.001
Optimism 13.75 ± 3.47 13.91 ± 3.56 -0.16 0.589
Sleep circadian regularity 7.78 ± 3.76 7.24 ± 3.95 0.54 0.096
Sleep continuity 4.12 ± 2.08 3.48 ± 2.28 0.64 <0.001
Sleep health 5.36 ± 2.26 5.28 ± 2.15 -0.08 0.662

SD, standard deviation.