Shift work sleep disorder and associated factors among healthcare professionals working at Jimma University Medical Center, Southwest Ethiopia, 2022: a cross-sectional study

Abstract

Objectives

Shift work sleep disorder is a circadian rhythm sleep-wake disorder characterised by insomnia and/or excessive sleepiness associated with a shift work schedule that overlaps with habitual sleep time. This study aimed to assess the prevalence of shift work sleep disorders and associated factors among healthcare professionals working at Jimma University Medical Center, Southwest Ethiopia.

Design

Institutional-based cross-sectional study.

Setting

Tertiary hospital in Southwest Ethiopia.

Participants

The data were collected using a self-administered questionnaire from health professionals recruited using a simple random sampling technique.

Outcome

Shift work-sleep disorder was assessed by the International Classification of Sleep Disorders, the Insomnia Severity Index and/or the Epworth Sleepiness Scale. A logistic regression analysis was conducted to determine the association between the predictor and the outcome variable. The ORs and 95% CIs were determined. Variables with a p value<0.05 were taken as statistically significant on multivariable analysis.

Result

370 participants were involved in the study, yielding a response rate of 97.6%. The prevalence of shift work sleep disorder was 35.9% (n=133). Working in three shifts (Adjusted OR (AOR) 3.25, 95% CI=1.92 to 5.57), more than 11-night shifts per month (AOR 2.83, 95% CI=1.49 to 5.37), absence of nap (AOR 2, 95% CI=1.14 to 3.52), stress (AOR 4.4, 95% CI=2.36 to 8.2), fatigue (AOR 2.7, 95% CI=1.26 to 3.73), alcohol (AOR 3.9, 95% CI=1.79 to 8.47) and khat (AOR 4.40, 95% CI=1.76 to 10.96) use in the last 3 months was significantly associated with shift work sleep disorder.

Conclusion

One in three healthcare professionals working at Jimma University Medical Center had a sleep disorder related to shift work. Working in three shifts per day, having more than 11-night shifts per month, lack of naps, presence of stress, fatigue and substance use were found to be associated with shift work sleep disorder.

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• It was not feasible to conduct clinical interviews, actigraphic assessments or administer sleep diaries to get a more accurate result in this study. Conducting our study in a single center could be another limitation of this paper.

• Underreporting sensitive issues such as substance use may result from social desirability bias.

• Since the study design is cross-sectional, it cannot assess a cause-and-effect relationship.

• The study involved different categories of professionals that could make the results appropriately represent shift work sleep disorder in all health professionals.

• There is limited evidence concerning the validation of the Chalder Fatigue Scale among healthcare professionals.

Introduction

Sleep is one of the most significant human behaviours, accounting for around one-third of an individual’s life.¹ Although the purpose of regular sleep is uncertain, most investigators conclude that sleep serves a restorative, homeostatic function and appears crucial for normal thermoregulation and energy conservation.^{1 2} The sleep pattern is influenced by the environment, circadian rhythms and time within the 24-hour framework.³

A circadian rhythm is an oscillating biological process that occurs every 24 hours, between sleep and alertness. It is affected by shift work, particularly night shift work, which is the most significant one.⁴ Shift work is a schedule that divides the 24 hours into roughly similar-sized periods. It involves long-term night shifts and work schedules in which employees rotate based on their shifts.^{5 6}

According to the International Classification of Sleep Disorders-2 (ICSD-2) and the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) definitions, shift work sleep disorder (SWSD) is a type of circadian rhythm sleep-wake disorder characterised by insomnia and/or excessive sleepiness associated with a prolonged shift work schedule that overlaps habitual sleep time. The diagnosis is primarily based on the history of the person who works frequently on shifts outside of the normal 8:00–18:00 hours daytime window (especially at night). The cause of SWSD is the inability to sleep due to an imbalance of the circadian rhythm and internal homeostatic sleep drives.⁷

Globally, 15–20% of people in industrial societies work in rotating shifts or carry out overnight duties, and more than 30% of the world population suffers from sleep disorders that are due to mental, psychological and physical diseases; working in different sectors on the same day and nocturnal work.^{8 9} Meta-analysis and systematic review studies conducted across the world found that one in four, or around 26.5%, of shift workers suffered from SWSD.¹⁰ In the Asian multiethnic population, a significantly higher prevalence of poor sleep quality was observed among shift workers compared with non-shift workers (54.8% vs 36.4%).¹¹ It has been documented that in different African countries, including Ethiopia, the magnitude of SWSD ranges from 25.6% to 49.6%.^{5 12 13}

Healthcare providers work in shifts to meet the needs of their patients. Consequently, ‘shift work’ disrupts the synchronous relationship between the health worker’s body’s internal clock and the environment.¹⁴

SWSD increases the likelihood of accidents and work-related errors, irritability or mood problems, poor coping skills, impaired social functioning and drug and alcohol dependency.¹⁵ The study found that men with SWSD have worse erectile function, with men who work night shifts having even poorer erectile function.¹⁶ The shift puts the professionals under stress and can cause their health, well-being and lifestyle to deteriorate. When shift work is scheduled on a 24-hour schedule and the shift itself is irregular, sleep disorders and burnout can affect job performance in terms of efficiency, productivity, task execution speed and supervision.¹⁷

To optimise patient care and professionals’ health, safety, wellness and retention, it is essential to assess and manage sleep difficulties.¹⁸ The quality of life for shift workers with SWSD was significantly poorer than that of shift workers without this disorder. Shift work is also associated with substantial neurocognitive impairment and reduced work efficiency. The costs associated with lost productivity and accidents due to shift work have a greater impact on economic burdens and consequences.¹⁹

The increasing demand for continuous 24-hour health service delivery in Ethiopian hospitals is associated with a rise in SWSD.^{12 20} However, there is a paucity of information regarding the prevalence of SWSD and its associated factors among healthcare professionals, particularly in Ethiopia. Moreover, variables such as feeling fatigued, total sleep duration before the night shift, stress, social support, presence of anxiety and depression regarding SWSD among health professionals were better addressed in the current study than in previous studies in Ethiopia. Therefore, this study aimed to fill the gaps by assessing the prevalence of SWSD and its associated factors among healthcare professionals working at Jimma University Medical Center (JUMC).

Methods and materials

Study area and period

The study was conducted at JUMC in Jimma town, Oromia Regional State, which is 352 km southwest of the capital city (Addis Ababa) of Ethiopia.

The town is located at 1500–2700 m above sea level. The study was carried out from 1 September to 30 October 2022. The JUMC provides healthcare services to more than 15 million people in the catchment area, with 1099 healthcare professionals.

The hospital has more than 800 beds and provides healthcare services in several units, including gynaecology and obstetrics, internal medicine, paediatrics, emergency care, radiology, surgery, psychiatry and other departments. The service in the hospital is being given in two or three shifts, depending on the nature of the departments and units.²¹

Study design

An institution-based cross-sectional study was conducted, and the Strengthening the Reporting of Observational Studies in Epidemiology guideline was used.²²

Source population

All healthcare professionals working at JUMC.

Study population

Randomly selected healthcare professionals who were available during the data collection and fulfilled the inclusion criteria.

Inclusion criteria

All healthcare professionals working in shift programmes who have greater than 3 months of work experience were included in this study.

Sample size determination

The sample size required for this study was calculated using a single population proportion formula, assuming that 33.67% of healthcare professionals have SWSD based on previously conducted research in Ethiopia.²⁰ A 5% margin and 95% CI have been considered. Accordingly, the final sample size was 379.

Sampling technique and procedures

The study population was proportionally allocated and categorised based on their profession, which includes physicians, nurses, midwives, pharmacists, medical laboratory technicians, mental health professionals, anaesthesiologists and radiologists. A lottery method was used to select individual participants from each profession, as well as units.

Data collection procedures

Data were collected using a self-administered, structured questionnaire.

Sociodemographic and work-related factors

A questionnaire was designed to collect data on age, sex, marital status, profession, working unit, work experience and income.

Shift work sleep disorder

In this study, the three questions of the ICSD-3, which were developed to assess SWSD in epidemiologic studies, were used.²³ They are as follows: do you experience difficulties with sleeping or excessive sleepiness? Is the sleep or sleepiness problem related to a work schedule where you have to work when you would normally sleep? Has this insomnia or sleepiness problem related to your work schedule persisted for at least 3 months? The response to each of the three questions is either ‘yes’ or ‘no’. Participants who responded ‘Yes’ to all three questions were classified as having fully met the ICSD-3 criteria.²⁴ It was validated in India among 201 female nurses,²⁵ and its Cronbach’s alpha in the current study was 0.982.

Insomnia Severity Index

Additionally, the self-administered American Psychiatric Association DSM-IV, particularly the Insomnia Severity Index (ISI), was used to assess SWSD. The ISI examines the sleep patterns immediately preceding the administration of the test in the 2 weeks. Its rating is based on a scale from 0 (less severe) to 4 (more severe). The scores of the seven items are added to generate the total score, which can range from 0 to 28. Participants were categorised as having insomnia if they scored a total of ≥8. It was validated in Ethiopia and has good psychometric validity. The internal consistency of Cronbach’s alpha is 0.68 and 0.78.^{20 26} It is 0.90 in the current study.

Epworth Sleepiness Scale

The Epworth Sleepiness Scale (ESS) is an 8-item questionnaire that is used to assess the self-reported level of sleepiness. These eight items have a four-point scale, where ‘0’ indicates ‘would never nod off’, while ‘3’ indicates a strong chance of nodding off. The scale questions are applied to eight different situations encountered in daily life. The individual item scores are added to generate the ESS total score, which ranges from 0 to 24. The ESS score for a clinical cut-off ≥11 has been shown to allow distinctions to be made between patients with sleep disorders and healthy subjects. It was validated in Ethiopia with a Cronbach’s alpha of 0.75.²⁷ The Cronbach’s alpha in the current study was 0.88. Participants in this study were classified as having SWSD if they met the requirements of ICSD-3 and ISI and/or ESS.^{12 28}

Depression Anxiety Stress Scale (DASS-21)

The Depression Anxiety Stress Scale (DASS-21) is a widely used screening tool that can separately measure depression, anxiety and stress symptoms. It has been derived from the original 42-item DASS developed by Lovibond et al. It also has three subscales, namely the depression subscale, anxiety subscale and stress subscale. Each subscale comprises seven items, which are scored from 0 (did not apply to me at all) to 3 (applied to me very much or most of the time) to reflect severity in the week preceding the interview. The total score for each DASS-21 subscale ranges from 0 to 21. The items’ scores are added and multiplied by two to obtain the total score, which can be compared with the original DASS-42.²⁹ The studies conducted in Bangladesh, Ghana and Pakistan on the validation of the DASS-21 showed good validity and reliability of the screening tool for depression, anxiety and stress among healthcare workers. The internal consistency reliability, Cronbach’s Alpha, was 0.93 in the studies in Bangladesh and Ghana and 0.953 in the study in Pakistan.30,32

Chalder Fatigue Scale

The Chalder Fatigue Scale (CFS 11) allows the user to differentiate between fatigue ‘cases’ and ‘non-cases’. It contains 11 items, with each score ranging from 0 to 3, which are summed to a total score (0–33; 33 denotes maximum symptoms). It has two subscales: physical fatigue (seven items, range 0–21) and mental fatigue (four items, range 0–12). The CFS–11 items use an alternative scoring method called bimodal scoring, where each item’s response is categorised as 0 (scores of 0–1) or 1 (scores of 2–3), yielding a total score on a scale from 0 to 11. The case status (fatigued vs non-fatigued) was defined using this scale, with cut-off points ≥4 indicating the presence of fatigue.³³ In a study conducted in Brazil, the CFS-11 demonstrated good reliability and validity. The study was conducted with a rigorous translation and validation on the primary care attenders, and the Cronbach’s alpha of the CFS-11 was 0.88.³⁴

Oslo Social Support Scale

This is a 3-item brief assessment of social support that has been widely used by different studies and has good psychometric properties.³⁵

Study variables

The dependent variable was shift-work sleep disorder. The independent variables include sociodemographic-related factors (age, sex, marital status, profession, working unit, work experience and income); shift work-related factors (length of night shift, rotation time interval, number of shifts per day, number of night shifts per month, nap, interval day between night shifts and sleep duration before night shift); clinical factors (history of mental illness, chronic medical illness, current anxiety, current depression and stress); physical factors (fatigue); psychosocial factors (social support) and substance-related factors (alcohol, khat, tobacco, hashish and pethidine).

Data processing and analysis

After checking the data for completeness and consistency, the data were coded and entered into a computer using Epi-Data V.4.1. Then, the data were exported to SPSS V.25 for analysis. A χ² test was used to analyse the frequency distribution of the nominal variables. Frequencies, percentages and summary statistics were calculated. A bivariate logistic analysis was employed to determine the association between the outcome and each predictor variable. Variables that have a p value <0.25 were selected as candidates for multivariable logistic regression analysis. Then, the backward selection method was employed to identify predictors of SWSD at a p value <0.05. ORs and 95% CI were used to indicate the presence and strength of the association.

Data quality assurance

The questionnaire was translated into Amharic and Afaan Oromo versions and then back to English to ensure semantic equivalence. Language experts and mental health professionals participated in the translation of the questionnaires. A 1-day training was given for data collectors and supervisors. A pre-test was conducted on 5% of the total sample. The understandability of the questionnaires and the reliability of the instruments were checked. During data collection, the questionnaire was checked for completeness by the supervisor. Data quality was also ensured at the data entry, coding, cleaning and analysis levels.

Result

Sociodemographic characteristics of healthcare professionals

370 healthcare professionals completed the questionnaires, with a response rate of 97.6%. The mean age of the participants was 29.9±3.30 (with a range of 27–42). The respondents in this study consisted of 199 (53.38%) men. More than half, 209 (56.5%) of the respondents, were single. The majority of the professionals, 207 (55.9%), were nurses and 47 (12.7%) were physicians. Moreover, 37 (10%) and 51 (13.8%) of professionals were working in medical and surgical wards, respectively, and 187 (50.6%) of them had ≤4 years of working experience. The median income of the participants was 7701 Ethiopian birr (ETB), ranging from 4469 to 15 000 ETB (table 1).

Table 1. Sociodemographic characteristics of healthcare professionals working at Jimma University Medical Center, Southwest Ethiopia, 2022 (n=370).

Characteristics	Category	Frequency	Per cent
Age in years	≤29	211	57%
	30–34	120	32.4%
	≥35	39	10.6%
Sex	Male	199	53.8%
	Female	171	46.2%
Marital status	Single	209	56.5%
	Married	143	38.6%
	Others*	18	4.9%
Professions	Physician	47	12.7%
	Nurse	207	55.9%
	Midwives	30	8.1%
	Psychiatry professional	13	3.5%
	Pharmacy	31	8.4%
	Medical laboratory	32	8.6%
	Others†	10	2.8%
Working unit	Medical ward	37	10%
	Surgical ward	51	13.8%
	ICU/NICU	43	11.6%
	Orthopaedic ward	4	1.1%
	Gynaecology and obstetrics	36	9.7%
	Paediatric ward	13	3.5%
	Operation room	32	8.7%
	Others‡	154	41.6%
Work experience in years	≤4	187	50.6%
	5–9	167	45.1%
	≥10	16	4.3%
Monthly income in ETB	≤4999	7	1.9%
	5000–9999	290	78.4%
	10 000–14999	63	17%
	≥1 50 000	10	2.7%

^*Divorced, widowed and separated.

^†Anaesthesiology and medical radiology.

^‡Pharmacy Unit, laboratory unit, radiology unit, psychiatry ward, emergency ward, oncology unit, burn unit, stroke unit, ICU/NICU, ETB.

ETB, Ethiopian Birr; ICU, intensive care unit; NICU, neonatal ICU.

Shift work-related characteristics

Among the total respondents, 218 (58.9%) and 209 (56.6%) work in two shifts and stay on duty for ≤12 hours during the night shift, respectively. Most of the participants, 152 (41.1%), work <7-night shifts per month and about two-thirds, 247 (66.8%), of shift workers had the chance to take a nap during their night shift. Nearly two-thirds, 249 (67.3%) of the participants have ≤ four interval days between night shifts. The majority of shift workers, 255 (69%), slept 6–8 hours before the night shift (table 2).

Table 2. Shift work-related characteristics of healthcare professionals working at Jimma University Medical Center, Southwest Ethiopia, 2022 (n=370).

Characteristics	Category	Frequency	Per cent
Number of shifts per day	Two shifts	218	58.9%
	Three shifts	152	41.1%
Length of night shift time	≤12 hours	209	56.5%
	>12 hours	161	43.5%
Number of night shifts per month	≤ 7 days	152	41.1%
	8–11 days	115	31.1%
	>11 days	103	27.8%
Taking a nap	Yes	247	66.8%
	No	123	33.2%
Rotation time interval	≤10 hours	92	24.9%
	≥11 hours	278	75.1%
Interval day between night shifts	≤ 4 days	249	67.3%
	5–7 days	94	25.4%
	≥8 days	27	7.3%
Total sleep duration before night shift	3–5 hours	22	6%
	6–8 hours	255	69%
	>8 hours	93	25%

Clinical-related characteristics

Around one-third, 121 (32.7%) of the participants had current anxiety and 112 (30.3%) had current depression. On the other hand, 85 (23%), five (1.4%) and 11 (3%) of them had stress, a history of mental illness and a history of chronic medical illness, respectively.

Physical and psychosocial characteristics

139 (37.6%) and around half (181, 48.9%) of the healthcare professionals have fatigue and moderate social support, respectively.

Substance-related characteristics

In the last 3 months, alcohol, khat and tobacco were used by 39 (10.5%), 32 (8.7%) and 22 (6%) of the respondents, respectively.

Prevalence of shift-work sleep disorder

Overall, 133 (35.9%, 95% CI: 31% to 40%) of the healthcare professionals had SWSD.

Factors associated with SWSD

Being married, working in ICU/NICU, having ≥10 years of work experience, working in three shifts, working >11 night shifts per month, absence of nap opportunities during night shifts and ≤4 day interval between night shifts were found to be associated variables with SWSD in bivariate logistic regression at p value<0.25.

Current anxiety, current depression, stress, fatigue, poor social support, drinking alcohol and chewing khat in the last 3 months were the variables found to be associated in bivariable logistic regression with the SWSD at a p value<0.25 (online supplemental file 1).

Adjusting for potential confounders in multivariable logistic regression, frequency of shifts worked per day, number of night shifts per month, missing naps during the night shifts, stress, being fatigued, alcohol use and khat chewing in the last 3 months were associated with the SWSD at a p value <0.05 (online supplemental file 2).

Discussion

This study found that 35.9% of healthcare professionals working at JUMCre had SWSD, and frequency of rotation (number of shifts) per day, number of night shifts per month, missing naps, stress, being fatigued, alcohol use and khat chewing in the last 3 months were associated with the disorder.

In our study, the prevalence of SWSD was 35.9%, which is in line with a study conducted in Ethiopia that reported 33.67%²⁰ of the disorder among health professionals. This finding was also consistent with studies conducted in India, 39.9%,³⁶ China, 35.2% and 37.7%,³⁷ South Korea, 32.2%,³⁸ Finland, 33.5%,³⁹ and Norway 32.4%–37.6%²⁸ and 35.2%.⁴⁰

The prevalence of SWSD, however, was higher in this study than in studies in Ethiopia among nurses (25.6%),¹² India (15.8%)⁴¹ Japan (24.4%)⁴² and the USA (8.4%).⁴³

The prevalence of SWSD, however, was higher in this study than in studies in Ethiopia among nurses (25.6%),¹² India (15.8%,⁴¹ Japan (24.4%),⁴² and the USA (8.4%).⁴³

The difference between the previous study in Ethiopia¹² and our study was that the former involved only nurses, whereas the latter incorporated all healthcare professionals participating in shift work. The dissimilarity between our study and the study conducted in Japan may be due to time. In a study in Japan, almost half of shift workers spent a very short duration of time at work during the day and night, which is far different from the current finding, characterised by longer hours of shift work. Furthermore, the difference between the study in India (15.8%) and the current study might be explained by the study population. The former one involved only nurses and the current one involved all health professionals. The lower prevalence in India may also be attributed to the smaller sample size, as well as the workload at that tertiary centre. The study conducted in the USA defined SWSD as the presence of both excessive wake-time sleepiness and insomnia. However, the current study defines SWSD by the presence of either one or both symptom criteria. Additionally, the former study used a combined tool, the Insomnia Symptom Questionnaire and the ISI, to assess insomnia, while the current study used only the ISI to assess insomnia.

In contrast, the current finding is lower than the studies done in Nigeria,¹³ South India, 43.07%,⁴⁴ and China, 48.5%.²⁴

The difference in the prevalence of SWSD between the study conducted in Nigeria and our study could be due to the difference in the study settings. The research in Nigeria was conducted in a multicentre setting; ours was carried out in a single centre. On the other hand, the South Indian study comprised only female nurses. As supported by much literature, SWSD is more common in women than in men. It was also conducted among 130 participants, which was a smaller sample size than our study. In addition, the Indian study used the Standard Shift Work Index and Bergen Shift Work Sleep Questionnaire to assess SWSD, whereas this study used the ICSD-3, ISI and/or ESS to assess SWSD. Moreover, a study in China was carried out during the COVID-19 pandemic outbreak. So, the possible explanation for the high SWSD may be due to increased work overload, stress, anxiety and tension, which disturb normal sleep rhythms during the pandemic. Additionally, the former study was conducted in 14 hospitals, whereas our study was conducted in one hospital.

In this study, the frequency of rotation per day was significantly associated with SWSD. The shift workers who worked in three shifts had 3.25 times higher odds of SWSD than workers with two shifts. This is supported by studies done in Ethiopia^{12 20} and Norway.⁴⁵ A possible explanation might be that short rest periods between work shifts (quick returns) may cause circadian misalignment, which regularly interferes with the body’s natural rhythm of sleep and wakefulness. This causes a change in the secretion of the hormones melatonin and cortisol, which significantly affects sleep disturbance.^{45 46}

The odds of SWSD in individuals who work >11-night shifts per month are 2.83, much higher than in those who work ≤7-night shifts per month. This finding was in line with studies conducted in Ethiopia,^{12 20} Italy,⁴⁷ Norway⁴⁵ and southern India.⁴⁴ People who work at night often feel sleepy during their shift. This happens because their body rhythm (also called a circadian rhythm) tells them to be asleep at those times. Night workers must sleep during the day; nevertheless, their circadian rhythm is expected to be awakened. As a result, daytime sleep is short and feels ‘light’ or unsatisfying.⁴⁸ Often, night workers do not get enough sleep during the daytime to combat nighttime fatigue and sleepiness. As night work becomes more frequent, the resulting disruption increases, leading to SWSD.⁴⁹

The absence of nap opportunities during the night shift was positively associated with SWSD. This is in line with studies done in Ethiopia,^{12 20} Japan⁴² and Italy.⁴⁷ The similarity could be due to a characteristic of nighttime naps that can result in considerably deeper sleep, as indicated by a lower body temperature, much like slow-wave sleep. Night-time naps prevented a reduction in alertness and performance and reduced sleepiness during the period following waking from a night-time nap.⁵⁰

According to the findings of this study, stress is significantly associated with SWSD. This is consistent with studies done in Switzerland,⁵¹ Italy¹⁷ and China.²⁴ One of the factors that causes sleep disturbances is stress. Both stress and wake trigger the activity of the hypothalamic-pituitary-adrenal axis (HPA), causing the awakening. During sleep, the activity of the HPA axis decreases; conversely, stress activates the HPA axis in response to distressing situations.⁵²

In this study, the odds of SWSD in fatigued participants were 2.7 times higher than those without fatigue. This finding is in line with studies in Sweden,⁵³ China²⁴ and Finland.³⁹ This might be due to a lack of energy in fatigued individuals, subsequently leading to reduced physical activity and prolonged daytime napping, which can, in turn, perpetuate sleep disturbances such as insomnia.⁵⁴

Participants who used alcohol in the last 3 months were 3.90 times more likely to develop SWSD than those who abstained. It was supported by a study done in Ethiopia.²⁰ Alcohol consumption has been linked to abnormalities of the circadian rhythm and decreased melatonin hormone production by the pineal gland, which is responsible for the onset of sleep and is strongly associated with SWSD. Alcohol use has also been associated with sleep disturbances. Use of alcohol decreasesRapid Eye Movement (REM) duration, especially in the second half of the night.⁵⁵

This study also showed that the odds of SWSD were 4.40 times higher among individuals who chewed khat in the past 3 months, which is consistent with previous studies in Ethiopia.²⁰ The presence of cathinone and cathine in khat shares structural similarities with amphetamine and causes the release of dopamine and serotonin. Both enhance alertness and decrease fatigue. These stimulants may lead to disturbed sleep patterns.⁵⁶

As one of the methodological limitations of the study, the social desirability bias was believed to lead the participants to underreport sensitive issues such as substance use in this study. However, the data collectors tried to collect the data regarding substance use in culturally sensitive ways and with a good approach to the participants. Additionally, there are limited validation studies on the CFS-11) among healthcare professionals. We also recommend considering the validation of CFS 11 among health professionals for the researchers. Clinical interviews, actigraphic evaluations and the administration of sleep diaries were not incorporated into this study to obtain more precise results.

The study’s single-centre nature can be another limitation for generalisability; however, the authors have included various categories of health professionals, such as nurses, physicians, anaesthesiologists and psychiatrists, to address concerns about the involvement of the different categories of health professionals in the study. As a strength, this study assessed the association of variables such as feeling fatigued, total sleep duration before the night shift, stress, social support, presence of anxiety and depression with SWSD among health professionals, which was better addressed in the current study than in previous studies in Ethiopia.

Conclusion and recommendation

This study revealed that more than one in three health professionals working at JUMC had SWSD, suggesting the importance of preventing and treating the disorder in these individuals. The increased number of shifts per day, more night shifts in a month, missing a nap, presence of stress, fatigue, alcohol and khat use in the last 3 months were significantly associated with SWSD. Therefore, it is better to reduce the frequency of rotating shifts in a day, which may, in turn, reduce the number of night shifts in a month. Focusing on decreasing fatigue, substance use and stress among health professionals is also a crucial issue.

Data availability statement

Data are available upon reasonable request.