|
| |
| ORIGINAL ARTICLE |
|
| Ahead of print publication |
|
|
A cross sectional study of quality of sleep, burnouts, anxiety and depression in rotatory shift workers of sir T hospital bhavnaga
Dimple Gupta1, Ashok U Vala2, Abhinav Ankur2, Chirag Ambaliya3, Krupa M Unadkat1, Bharat Panchal1
1 Department of Psychiatry, Hamdard Institute of Medical Sciences and Research, New Delhi, India
2 Department of Psychiatry, Government Medical College, Bhavnagar, Gujarat, India
3 Department of Psychiatry, Hospital for Mental Health, Jamnagar, Gujarat, India
| Date of Submission | 02-Nov-2022 |
| Date of Acceptance | 21-Jan-2023 |
| Date of Web Publication | 20-Feb-2023 |
Correspondence Address:
Dimple Gupta,
House No 86D/1, Lane No 3, Krishna Nagar, Safdarjung Enclave, New Delhi
India
 Source of Support: None, Conflict of Interest: None DOI: 10.4103/aihb.aihb_200_22
Introduction: Rotatory shift work is quite prevalent in the general population. The knowledge that effect does not depend on a single cause, but rather, diseases are multifactorial in origin, resulting in widespread interest towards the preventive aspect and focussing on the causative factors that directly or indirectly influence the health and well-being of shift workers. Materials and Methods: We analysed data from an observational, cross-sectional, single-centred, interview-based study of a total of 100 shift workers working in Sir T Hospital in Bhavnagar conducted from July 2020 to December 2021. The study was performed via face-to-face interviews using structured questionnaires. We used the Pittsburgh sleep quality index (PSQI) to evaluate sleep quality. To diagnose depression, anxiety and burnout, we used the Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A) and Copenhagen burnout inventory (CBI), respectively. Statistical data were analysed using R software version 4.0.5 (R Development Core Team, Vienna, Austria). Results: A total of 100 participants were interviewed. The respondents are almost symmetric in terms of male and female, married and unmarried and rural and urban residence. The mean age of our sample is 36.98 ± 9.37 years. Around 15% of participants showed moderate/severe levels of depression (18%) and moderate/severe levels of anxiety (9%) using HAM-D and HAM-A, respectively. Using CBI subscales, 27% of respondents showed personal burnout, 54% showed work-related burnout and 20% showed client-related burnout. Sleep quality was poor among shift workers (45%) using the PSQI scale. Significant positive correlations are found between HAM D and personal burnout (r = 0.206, P = 0.040), work burnout with personal burnout (r = 0.243, P = 0.015) and client burnout (r = 0.246, P = 0.013). Furthermore, personal and client burnout shows a positive correlation (r = 0.271, P = 0.006). Although these correlations are still significant, they indicate low positive nature of the relationship between such variables. Conclusion: The prevalence of depression, anxiety, burnout and poor sleep quality was high. The effect on shift work mental health is multifaceted, dealing with several aspects of personal characteristics and working and living conditions. Further research is needed to support the mental well-being of shift workers and minimise workplace-related psychiatric disorders by developing short- and long-term strategies.
Keywords: Anxiety, burnouts, depression, quality of sleep, rotatory shiftwork
How to cite this URL:
Gupta D, Vala AU, Ankur A, Ambaliya C, Unadkat KM, Panchal B. A cross sectional study of quality of sleep, burnouts, anxiety and depression in rotatory shift workers of sir T hospital bhavnaga. Adv Hum Biol [Epub ahead of print] [cited 2023 Mar 31]. Available from: https://www.aihbonline.com/preprintarticle.asp?id=370026 |
| Introduction | |  |
Shift work is characterised as organising daily working hours in which different people work in succession to cover more than the usual 8-h day up to 24 h.[1] A recent study of representative workers in Taiwan indicated that the prevalence of non-standard shifts, including night shifts and rotating shifts, had increased considerably from 2001 to 2010, from 17% to 24% in men and 12% to 20.4% in women.[2] Shift work or work in unusual hours is more common in industries, transportation and services which require 24-h workforce, such as hospitals.[3] Mental health directly/indirectly influences the overall health of the individual. The socio-demographic variables, psychosocial environment and work–life balance influence it.[4],[5],[6]
Shift work affects mental health because it causes disruption of the sleep-wake cycle. The dis-accord between social time and the biological rhythm of the body in rotatory shift work results in a state when the body systems misalign the physiological norms, irregular meal time and hormonal balance essential to maintain homeostasis in the body. The fundamental pacemaker or the biological clock is the suprachiasmatic nucleus in the anterior hypothalamus. This endogenous clock controls sleep/wake rhythm in the human body.[7],[8],[9]
Shift workers have to work in rotation, disrupting the biological clock. On the one side, night shifts are known to impair melatonin secretion, increase stress hormones and cause disturbance in the functioning of the immune system, leading to impaired sleep quality and psychological well-being. On the other side, working odd hours also disrupt work–life balance and social communication, leading to greater mental distress.[10],[11],[12],[13]
Rosenberg found a 33% increased risk of depressive symptoms in shift workers, and it was also studied that there was an increased risk of anxiety; however, it was not statistically significant. Female shift workers were more likely to experience depressive symptoms than the females who did not work in shifts, and this difference was not seen among men.[14]
People facing prolonged stress may experience exhaustion of physical or emotional strength, termed burnout.[15] Health-care workers working in the rotatory shift are at greater risk of burnout. This may happen because their workspace involves taking decisions in emergencies, exposure to weak and ailing patients and a colossal workload.[16.17] The knowledge that effect does not depend on a single cause, but rather, diseases are multifactorial in origin, resulting in widespread interest towards the preventive aspect and focussing on the causative factors that directly or indirectly influence the health and well-being of shift workers. Scientific research has been trying to appreciate the measures to reach the goal of prevention rather than treatment. There is a growing concern about job-related health issues for an individual. The social environment of individual influence their sleep patterns and also have an effect on the daily activities during the light/dark cycle (Day/Night). In other words, it depicts the complexity of the current lifestyle, which is more heightened in rotating shift workers.[18]
It is considered that shift work forms the basis of giving 24-h care in hospitals; however, it also negatively affects the mental health of hospital workers. Despite the association between mental health and overall health, little is known about the effect of shift work on mental health in this population. It is essential to understand how shift work influences mental health so that we can improve their working environment. Our primary objective was to evaluate and describe the mental health status of Rotatory shift workers of Sir T hospital, Bhavnagar, for symptoms of sleep disturbance, depression, burnouts and anxiety while focussing on the impact the shift work has on psychological health during shift work and on overall mental health outcomes. The current study also explored the relationship among depression, anxiety, burnout and sleep disturbance. So far, no such study has been done in Bhavnagar. By studying the various psychiatric issues of rotatory shift workers, we can formulate new preventive strategies and formulate working schedules to minimise the hardship and get maximum output from shiftwork.
| Materials and Methods | | |
Study setting, design and period
We adopted a cross-sectional, observational, single-centre, interview-based study with a quantitative research approach. The study was conducted for 1 year at a selected hospital of Bhavnagar, Gujarat, India.
Study population
Rotatory shift workers working in different fields, including security guards, ward boys, staff nurses and casualty medical officers: all belonging to Sir Takhtasinhji (Sir T) Hospital, Bhavnagar, Gujarat, India. A total of 100 rotatory shift workers working in different fields in Sir. T. Hospital, Bhavnagar. The Institution's ethics committee approved the Study protocol (Institutional Review Board IRB/BRC2398). The sample size calculation was based on a cross-sectional design, and a prevalence of depression (60%), anxiety (49.78%), burnout (55.4%) and sleep disturbance (53.8%) which were chosen in the light of the studies on the health-care workers. We estimated that at least 100 participants (maximum sample size out of four parameters) were needed to achieve 90% power at a 5% significance level in detecting an association between shift work, sleep disturbance, depression, anxiety and burnout. A list of workers working in a rotatory shift is collected and compiled, and is arranged in alphabetical order and given a particular number. Using a random generator tool, 100 participants were selected randomly. If the participant selected is not willing to participate, then the participant corresponding to the next number is selected. Written informed consent from every participant was taken after explaining the purpose of the study. The anonymity and confidentiality of participants were maintained. The interview was taken in the participant's vernacular language (Gujarati, Hindi or English). Participants involved in rotatory shift work for more than 3 months were included in the study. Participants having any mental illness (mental illness will be considered if the patient has had a previous one visit to a psychiatrist before enrolling himself/herself in shift work) and workers having substance abuse (alcohol, charas, ganja, opium and smoking) were excluded from the study. Descriptive statistics were used for demographic data. The R software version 4.0.5 (R Development Core Team, Vienna, Austria) was used for the analysis. The study lasted for 12 months.
Description of sample collection tool
Every participant's responses were recorded in a performance containing details of demographic details, The Hamilton Rating Scale for Depression, Hamilton Anxiety Rating Scale (HAM-A), Copenhagen Burnout Inventory (CBI) and Pittsburgh Sleep Quality Index (PSQI). Interviews with the participants were done in their vernacular language. The maintenance of anonymity and confidentiality of participants was ensured.
The Hamilton Depression Rating Scale, abbreviated HAM-D, is a 21 items questionnaire used to provide an indication of levels of depression. The scoring is based on the first 17 items 8 items are scored on a 5-point scale, ranging from 0 = not present to 4 = severe, and nine are scored from 0 to 2. A sum of the scores from the first 17 items was done. A score of 0–7 denotes normal; a score of 8–13 denotes mild depression. A score of 14–18 denotes moderate depression, a score of 19–22 denotes severe depression, and a score more than or equal to 23 denotes very severe depression. The HADS shows good internal reliability, concurrent validity, sensitivity and specificity.[19]
The HAM-A was one of the first rating scales developed to measure the severity of anxiety symptoms. The scale consists of 14 items, each defined by a series of symptoms, and measures both psychic anxiety (mental agitation and psychological distress) and somatic anxiety (physical complaints related to anxiety). This scale is a clinician-rated measure of anxiety comprising 14 items. Each item is scored from 0 (not present) to 4 (severe) with a total score range of 0–56 where a score <17 denotes mild severity, a score of 18–24 denotes moderate severity, a score of 25–30 denotes severe anxiety and score more than 30 denotes very severe anxiety. HAM-A validity and reliability has been satisfactory in the context of global anxiety in both adults and adolescents.[20],[21]
The CBI comprises three subscales: personal (six items), work burnout (seven items) and client burnout (six items). Twelve items have responses of frequency along a five-point Likert scale ranging from '100 (always), 75 (often), 50 (sometimes), 25 (seldom) and 0 (never/almost never). Seven items use response categories according to intensity ranging from a shallow degree' 'to a very high degree'. Typical items are: 'how often do you feel tired', 'do you feel burnt out because of your work' and 'do you find it hard to work with clients'. Scores of 50–74 are considered 'moderate', 75–99 are high and a score of 100 is considered severe burnout. All items are straightforward, positively skewed, relate to the relevant subscale and have high internal reliability.[22] The PSQI is a 19-item self-report questionnaire that assesses sleep quality over the past 1-month time interval. It consists of seven sections, each rated on a 0-3 scale and the overall score of PSQI ranges from 0 to 21. Higher scores signify poor sleep quality, i.e., ≥5 is considered undesirable. According to a study by Soleimany et al., the reliability and validity of the PSQI were found to be acceptable (0.89).[23]
Statistical analysis
We conducted statistical analyses using R software version 4.0.5 (R Development Core Team, Vienna, Austria). The quantitative variables are expressed as mean ± standard deviation and compared between groups using ANOVA/unpaired t-test. For Non-normal variables, the comparison is made using Kruskal–Wallis/Mann–Whitney test. Qualitative variables are compared between groups using the Chi-square exact test. Pearson's correlation coefficient is used to assess the extent of the linear relationship between two variables. A value of P < 0.05 is considered statistically significant.
| Results | | |
Demographic characteristics
The demographic characteristics of shift workers are shown in [Table 1]. Data are equally distributed amongst males and females. The respondents are almost symmetric in terms of married and unmarried as well as rural and urban residences. Most respondents (58%) belong to the Hindu religion and are either semi-professionals or professionals. Very few of them are Postgraduates, and our respondents' mean work duration is 14.4 ± 10 years. The mean age of our sample is 36.98 ± 9.37 years.
Comparison of demographic variables with the severity of psychological traits
The association between demographic variables and psychological characteristics is shown in [Table 2] and [Table 3]. The variables associated with depression are age (P = 0.034) and duration of work (P = 0.045). While the severe depression patients are of the lowest age, 24.5 ± 0.71 years, the normal patients are of the highest age, i.e., 44.42 ± 11.06 years. In addition, the duration of work was lowest (2.00 ± 1.41 years) in the severe depression patients and highest in the normal patients (20.18 ± 1059). The duration of work appeared to be inversely correlated with the severity of depression, i.e., as the duration of work decreased, the severity of depression increased. Anxiety is also found to be correlated with age (P = 0.048). While mild anxiety patients reported the highest age of 37.73 ± 9.47 years, moderate have the second-highest age of 32.11 ± 5.84 years, with the lowest being 25.5 ± 2.12 years. Duration of work is also correlated with anxiety (P = 0.047), and the pattern is similar to an age where mild anxiety patients have the highest duration of work, followed by moderate and normal patients. Sleep quality is associated with education (P = 0.027), residence (P = 0.030) and duration of work (P = 0.033). While the majority of those with good sleep were graduates, the ones with poor sleep were primarily educated. The majority of respondents with good-quality sleep are urban residents, and those with poor-quality sleep are from rural areas. The average work experience for people with good sleep is 13.07 ± 1012 years which is significantly less than for those with poor sleep, which is 16.02 ± 9.7 years. Surprisingly, personal and client burnout is independent of socio-demographic variables, whereas work burnout is associated with gender only (P = 0.045). The majority of No or low work burnout respondents were females, while those with moderate work burnout were males. | Table 2: Comparison of demographic variables with depression, anxiety and quality of sleep
Click here to view |
[Table 4] calculates the extent of the linear relationship between all the psychological characteristics. Significant positive correlations are found between HAM D and personal burnout (r = 0.206, P = 0.040), work burnout with personal burnout (r = 0.243, P = 0.015) and client burnout (r = 0.246, P = 0.013). Furthermore, personal and client burnout shows a positive correlation (r = 0.271, P = 0.006), as shown in [Figure 1]. Although these correlations are significant still, they indicate low positive nature of the relationship between such variables. | Figure 1: Correlation between depression, anxiety, quality of sleep, and burnout. Values indicating Pearson coefficient (P value).
Click here to view |
 | Table 4: Correlation of depression, anxiety, sleep and burnout variables
Click here to view |
| Discussion | | |
In this study, shift workers reported varied degrees of depression (93%), which was higher than the prevalence reported by Korean nurses (64.80%),[24] and that reported by Luceño-Moreno et al. in Spain (46.0%),[25] and that reported by Awano et al. in Japan (34.90%).[26] In addition, shift work nurses reported varying degrees of anxiety. This prevalence was higher than health-care workers in a previous Chinese study (44.6%).[27] In this study, 9% of nurses showed moderate anxiety, which was comparatively less than that of Japanese nurses (11.10%).[26] These differences in the prevalence of depression and anxiety in shift workers might be due to differences in regional and social background. In the context of the role of shift workers during the COVID-19 pandemic, nurses in India had a heavier workload and increased levels of anxiety and depression during that period.
The overall prevalence of burnout in this study was 20%–54%, which is comparable to the previous study by Peterson et al.[28] which reported a 33% prevalence of burnout, and a study was done by Aiken et al. in multisite depicted 33%–54%.[29] According to a study by Wisetborisut et al., the prevalence of burnout in shift workers was 25% compared with 15% in non-shift workers. The wide range of prevalence in detecting burnout may result from varied job scenarios and differences in workplace settings.[30]
This study showed poor sleep quality was found in 45% of participants, which was comparable to another study by Lajoie et al., conducted on hospital nurses in England (47.9%).[31] In another study by Thach et al., there was a significantly higher prevalence of poor sleep quality in shift workers compared to non-shift workers (54.8% vs. 36.4%).[32]
In a longitudinal study of UK households, Weston et al. discovered that shift work significantly correlated with depressive symptoms regardless of occupation, age or sex, whereas in our study, duration of work appeared to be inversely correlated with age and duration of work, i.e., severe depression was found in the patients of lowest age, and then as the duration of work decreased, the severity of depression increased.[33]
Anxiety is also found to be correlated with age (P = 0.048). While mild anxiety patients reported the highest age of 37.73 ± 9.47 years, moderate have the second-highest age of 32.11 ± 5.84 years, with the lowest being 25.5 ± 2.12 years. Duration of work is also correlated with anxiety (P = 0.047), and the pattern is similar to age, wherein mild anxiety patients have the highest duration of work, followed by moderate and normal patients, whereas in a study done by Picakciefe et al., anxiety scores of male health-care workers were found to be significantly higher than female workers' state anxiety scores. Compared with young workers, old workers reported higher levels of anxiety with the long duration of work, contrary to our results.[34]
Sleep quality was correlated with education, residence and average work experience in our study. The majority of those with good sleep was graduates. They were from urban residences with less average work experience (13.07 years) than the ones with poor sleep who were found to be primarily educated, the majority belonging to rural areas with more work experience (16.02 years). In another study, workers with poor sleep quality were older than those with good sleep quality (40.2 years vs. 38.4 years, P = 0.099), which is similar to our study; however, workers with poor sleep quality tended to have lower educational attainment (primary and secondary: 62.5% vs. 37.5; pre-college: 45.3% vs. 54.7%; college and above: 34.7% vs. 65.3%, P = 0.004.[32]
Personal and client burnout is independent of socio-demographic variables in our study, whereas work burnout is associated with gender only (P = 0.045). The majority of no or low work burnout respondents were females, while those with moderate work burnout were males in comparison to another study by Wisetborisut et al., where the prevalence of burnout was higher in females (24%) than males (13%). Furthermore, the mean age of participants with symptoms of burnout was significantly lower than those without; younger age, relationship status (single > married > divorced), higher income, higher education and occupation were all associated with burnout.[30] In another study on shift work and burnout and distress among 7798 blue-collar workers by Hulsegge et al., it was concluded that shift work was not associated with an increased risk of burnout and distress in the total population. However, shift workers who were dissatisfied with their schedule or who had experienced a high impact of their schedule on their private life had more distress and burnout complaints compared to non-shift workers.[35]
All the psychological parameters were correlated, and significant positive correlations were found between depression and personal burnout. Furthermore, personal and client burnout shows a positive correlation (r = 0.271, P = 0.006). Although there was a consistent correlation between personal burnout and symptoms of depression as indicated by the sense of physical and emotional exhaustion, it is still inconclusive if feelings of dissatisfaction towards work, frustrations for lack of control of situations and learned helplessness contribute simultaneously to burnout and depression.[36] It has been suggested that people whose profession involves repeated social contact tend to experience symptoms associated with mental exhaustion.[37] Rotatory shift workers use their mental well-being as a tool for handling work pressures, and accordingly, the vulnerability towards burnout appears high. Many studies relate high burnout to work involving massive human communications, situations demanding emotional balance and rotating shifts.[38],[39] However, the lack of a relationship between shift work and work burnout and client-related burnout in the present study might be due to the small sample size or the episodic nature of burnout. Furthermore, the workers who experience burnout and distress complaints are probably more likely to leave shift work than workers without burnout and distress complaints, which can cause a healthy worker effect. This common methodological problem of shift work research would have resulted in underestimating the association between shift work and burnout.[37]
Strengths of our study
The strength of the present study is the use of a homogeneous group, which minimises confounding related to differences across different workplaces, such as the division of tasks and the organisational culture of a particular setting. Clinician-rated scales were used in this study, and all the parameters were analysed through interviews in participants' vernacular language. Shift work schedule and shift work history were determined using objective registry data. So far, to the best of our knowledge and through surfing the search engines, no such study has been found including all these four parameters in rotatory shift work and their correlation.
Limitations of the study
Although we have used validated scales of assessment, our study has some limitations, such as its small sample size, being a cross-sectional study and the lack of knowledge on the relevance of the observed differences, cause–effect or temporal association cannot be established. The period of this study coincided with COVID-19 pandemic. Further larger sample sizes, multi-centric studies and in a non-pandemic period studies are recommended to have further insight into this subject.
| Conclusion | | |
The prevalence of depression, anxiety, poor sleep and personal burnout in rotatory shift workers was high. The participants' responses are strong predictors of mental health distress faced by shift workers. Our study underlines the importance of finding adequate strategies to prevent and combat psychiatric disorders in shift workers. We recommend future longitudinal studies to evaluate detailed aspects of job-related factors in shift workers and to explore their relationship with the larger organisational context of the work settings. This would not only prevent much unnecessary suffering for the individual shift worker but also benefit the entire work organisation can be addressed in future policies and practices.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Costa G. Shift work and occupational medicine: An overview. Occup Med (Lond) 2003;53:83-8.  |
| 2. | Cheng Y, Chen IS, Burr H, Chen CJ, Chiang TL. Changes in psychosocial work conditions in Taiwanese employees by gender and age from 2001 to 2010. J Occup Health 2014;55:323-32. |
| 3. | Alterman T, Luckhaupt SE, Dahlhamer JM, Ward BW, Calvert GM. Prevalence rates of work organization characteristics among workers in the U.S.: Data from the 2010 National Health Interview Survey. Am J Ind Med 2013;56:647-59. |
| 4. | Driesen K, Jansen NW, Kant I, Mohren DC, van Amelsvoort LG. Depressed mood in the working population: Associations with work schedules and working hours. Chronobiol Int 2010;27:1062-79. |
| 5. | Zhao Y, Richardson A, Poyser C, Butterworth P, Strazdins L, Leach LS. Shift work and mental health: A systematic review and meta-analysis. Int Arch Occup Environ Health 2019;92:763-93. |
| 6. | Scott AJ. Shift work and health. Prim Care 2000;27:1057-79. |
| 7. | Wyse CA, Celis Morales CA, Graham N, Fan Y, Ward J, Curtis AM, et al. Adverse metabolic and mental health outcomes associated with shiftwork in a population-based study of 277,168 workers in UK Biobank. Ann Med 2017;49:411-20. |
| 8. | Torquati L, Mielke GI, Brown WJ, Kolbe-Alexander T. Shift work and the risk of cardiovascular disease. A systematic review and meta-analysis including dose-response relationship. Scand J Work Environ Health 2018;44:229-38. |
| 9. | Vogel M, Braungardt T, Meyer W, Schneider W. The effects of shift work on physical and mental health. J Neural Transm (Vienna) 2012;119:1121-32. |
| 10. | Ding JM, Chen D, Weber ET, Faiman LE, Rea MA, Gillette MU. Resetting the biological clock: Mediation of nocturnal circadian shifts by glutamate and NO. Science 1994;266:1713-7. |
| 11. | West AC, Bechtold DA. The cost of circadian desynchrony: Evidence, insights and open questions. Bioessays 2015;37:777-88. |
| 12. | Dijk DJ, Lockley SW. Integration of human sleep-wake regulation and circadian rhythmicity. J Appl Physiol (1985) 2002;92:852-62. |
| 13. | Mohawk JA, Green CB, Takahashi JS. Central and peripheral circadian clocks in mammals. Annu Rev Neurosci 2012;35:445-62. |
| 14. | Rosenberg K. Shift work adversely affects mental health. Am J Nurs 2020;120:67. |
| 15. | Felton JS. Burnout as a clinical entity – Its importance in health care workers. Occup Med (Lond) 1998;48:237-50. |
| 16. | Wu S, Zhu W, Wang Z, Wang M, Lan Y. Relationship between burnout and occupational stress among nurses in China. J Adv Nurs 2007;59:233-9.9. |
| 17. | Demerouti E, Bakker AB, Nachreiner F, Schaufeli WB. A model of burnout and life satisfaction amongst nurses. J Adv Nurs 2000;32:454-64. |
| 18. | Richter KD, Acker J, Scholz F, Niklewski G. Health promotion and work: Prevention of shift work disorders in companies. EPMA J 2010;1:611-8. |
| 19. | |
| 20. | Clark DB, Donovan JE. Reliability and validity of the Hamilton anxiety rating scale in an adolescent sample. J Am Acad Child Adolesc Psychiatry 1994;33:354-60. |
| 21. | Hamilton M. The assessment of anxiety states by rating. Br J Med Psychol 1959;32:50-5. |
| 22. | Kristensen TS, Borritz M, Villadsen E, Christensen KB. The Copenhagen burnout inventory: A new tool for the assessment of burnout. Work Stress 2005;19:192-207. |
| 23. | Soleimany M, Masoodi R, Sadeghi T, Bahrami N, Ghorban M, Hassanpoor A. General health and its association with sleep quality in two groups of nurses with and without shift working in educational centers of Iran university of medical sciences IUMS. J Shahrekord Univ Med Sci 2008;10:70-5. |
| 24. | Lee HY, Kim MS, Kim O, Lee IH, Kim HK. Association between shift work and severity of depressive symptoms among female nurses: The Korea nurses' health study. J Nurs Manag 2016;24:192-200. |
| 25. | Luceño-Moreno L, Talavera-Velasco B, García-Albuerne Y, Martín-García J. Symptoms of posttraumatic stress, anxiety, depression, levels of resilience and burnout in Spanish health personnel during the COVID-19 pandemic. Int J Environ Res Public Health 2020;17:5514. |
| 26. | Awano N, Oyama N, Akiyama K, Inomata M, Kuse N, Tone M, et al. Anxiety, depression, and resilience of healthcare workers in Japan during the coronavirus disease 2019 outbreak. Intern Med 2020;59:2693-9. |
| 27. | Lai J, Ma S, Wang Y, Cai Z, Hu J, Wei N, et al. Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA Netw Open 2020;3:e203976. |
| 28. | Peterson U, Demerouti E, Bergström G, Samuelsson M, Asberg M, Nygren A. Burnout and physical and mental health among Swedish healthcare workers. J Adv Nurs 2008;62:84-95. |
| 29. | Aiken LH, Clarke SP, Sloane DM. Hospital staffing, organization, and quality of care: Cross-national findings. Nurs Outlook 2002;50:187-94. |
| 30. | Wisetborisut A, Angkurawaranon C, Jiraporncharoen W, Uaphanthasath R, Wiwatanadate P. Shift work and burnout among health care workers. Occup Med (Lond) 2014;64:279-86. |
| 31. | Lajoie P, Aronson KJ, Day A, Tranmer J. A cross-sectional study of shift work, sleep quality and cardiometabolic risk in female hospital employees. BMJ Open 2015;5:e007327. |
| 32. | Thach TQ, Mahirah D, Dunleavy G, Zhang Y, Nazeha N, Rykov Y, et al. Association between shift work and poor sleep quality in an Asian multi-ethnic working population: A cross-sectional study. PLoS One 2020;15:e0229693. |
| 33. | Weston G, Zilanawala A, Webb E, Carvalho LA, McMunn A. Long work hours, weekend working and depressive symptoms in men and women: Findings from a UK population-based study. J Epidemiol Community Health 2019;73:465-74. |
| 34. | Picakciefe M, Turgut A, Igneci E, Cayli F, Deveci A. Relationship between socio-demographic features, work-related conditions, and level of anxiety among Turkish primary health care workers. Workplace Health Saf 2015;63:502-11. |
| 35. | Hulsegge G, van Mechelen W, Proper KI, Paagman H, Anema JR. Shift work, and burnout and distress among 7798 blue-collar workers. Int Arch Occup Environ Health 2020;93:955-63. |
| 36. | Creedy DK, Sidebotham M, Gamble J, Pallant J, Fenwick J. Prevalence of burnout, depression, anxiety and stress in Australian midwives: A cross-sectional survey. BMC Pregnancy Childbirth 2017;17:13. |
| 37. | Maslach C, Jackson SE. The measurement of experienced burnout. J Organ Behav 1981;2:99-113. |
| 38. | Leiter MP, Maslach C. The impact of interpersonal environment on burnout and organizational commitment. J Organ Behav 1988;9:297-308. |
| 39. | Kandolin I. Burnout of female and male nurses in shiftwork. Ergonomics 1993;36:141-7. |
[Figure 1]
[Table 1], [Table 2], [Table 3], [Table 4]
|
