Factors Associated With Poor Sleep Quality Among Primary Healthcare Workers During the SARS-CoV-2 Pandemic.

INTRODUCTION: Sleep is one of the most important activities for health and the processes related to the central nervous system. Healthcare workers commonly present alterations in the sleep-wake cycle due to complex work schedules because 24-hour attention to the population is required in public health institutions. The increase in care needs caused by the COVID-19 pandemic caused changes in work schedules; as in Mexico, the number of patients requiring consultation in all public health units increased. Chronic partial sleep deprivation (< 7 hours of sleep in the 24-hour cycle) is the most frequent sleep alteration in Mexican health workers. However, it has not been explored whether work modifications due to the pandemic had an impact on the sleep quality of workers. OBJECTIVE: We aimed to describe the prevalence of poor sleep quality and the associated factors in workers (clinical and non-clinical) of a primary care medical unit. MATERIAL AND METHODS: We conducted an analytical and cross-sectional study during November and December 2022. We used the following tools for studying clinical and non-clinical staff working at a family medicine primary care unit: Pittsburgh Sleep Quality Index, Hamilton Anxiety Scale, Beck Depression Inventory, Maslach Burnout Inventory, and Graffar-Méndez-Castellanos socioeconomic level scale, as well as a data collection sheet and a survey of workers' knowledge, attitudes, fears, and needs regarding COVID-19. RESULTS: A total of 233 workers were surveyed. The prevalence of poor sleep quality was 56.7%. A higher score on the Beck Depression Inventory (OR: 1.21, CI 95%: 1.13-1.29), being a doctor (OR: 3.48, CI 95%: 1.5-8.01), and frequent alcohol consumption (OR: 2.4, CI 95%: 1.13-5.2) were identified as risk factors for poor sleep quality. A lower score in the depersonalization dimension of the Maslach Burnout Inventory (OR: 0.5, CI 95%: 0.26-0.99) was identified as a protective factor for poor sleep quality. CONCLUSIONS: During the pandemic, the stress of health workers increased due to work alterations that were necessary to treat the greatest number of patients, so their quality of sleep decreased. Unfortunately, the mental health of healthcare workers is often under-assessed in many institutions. Thus, it is relevant to identify risk factors for alterations (especially those of sleep), since by identifying the target population, comprehensive interventions can be carried out, which can reduce the prevalence of burnout, anxiety, and depression, but if not addressed, the alterations can lead to inadequate care for users of health units.

Prevalence of poor sleep quality among physicians and nurses in a tertiary health care center.

Objectives: Sleep quality among tertiary healthcare professionals in KSA has not been well studied. Therefore, in this study, we aimed to assess sleep quality among physicians and nurses in a tertiary care center in Jeddah City and to identify the associated factors. Methods: In this quantitative, analytical, cross-sectional study, an online, self-administered questionnaire was distributed to all physicians and nurses working at King Abdulaziz University Hospital (KAUH). A total of 395 healthcare professionals participated in this study. The questionnaire included the participants' demographic characteristics and Pittsburgh Sleep Quality Index (PSQI) values. Results: The mean age and body mass index of the participating healthcare professionals were 37.74 ± 10.35 years and 26.32 ± 4.97 kg/m2, respectively. Most participants were women (70.4%) and expatriates (55.4%). The prevalence of poor sleep quality was high: 70.4% of the participants had a PSQI score >5. Several factors, such as female sex (adjusted odds ratio (AOR) = 2.03; 95% confidence interval (CI) = 1.11-3.74), shift work (AOR = 1.87; 95% CI = 1.01-3.45), physical inactivity (AOR = 2.43; 95% CI = 1.01-5.85), and current smoking (AOR = 4.64; 95% CI = 1.68-12.80), were associated with poor sleep quality among healthcare professionals. Conclusions: Our findings are consistent with those from previous studies indicating high prevalence of poor sleep quality among healthcare professionals. Furthermore, female sex, shift work, smoking, and physical inactivity were identified as risk factors for poor sleep quality.

Association Between Pittsburgh Sleep Quality Index and Depressive Symptoms in Chinese Resident Physicians.

Background: Previous studies have suggested that sleep quality is associated with depressive symptoms. However, associations between overall sleep quality and depressive symptoms in Chinese resident physicians remain unclear. Therefore, we aimed to determine whether overall sleep quality is associated with depressive symptoms in Chinese resident physicians. Methods: This cross-sectional study included 1,230 resident physicians. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). Logistic regression analysis was applied to estimate the associations between the PSQI and PHQ-9. Results: Among all participants, the prevalence of mild (PHQ-9 ≥ 5) and moderate or severe (PHQ-9 ≥ 10) depressive symptoms were 48.28 and 12.93%, respectively. PSQI score was positively associated with PHQ-9 score before and after adjustments of socio-demographic, behavioral, and psychologic confounding factors (all P < 0.0001). After adjustments, the regression coefficients (standard error) between PSQI scores and PHQ-9 scores were 0.95 (0.04), 0.88 (0.09), and 0.96 (0.05) in all participants, men, and women, respectively. Compared to physicians with good sleep quality (PSQI scores ≤ 5), the adjusted odds ratios (ORs) [95% confidence intervals (CIs)] for mild (PHQ-9 ≥ 5) and moderate or severe (PHQ-9 ≥ 10) depressive symptoms in physicians with poor sleep quality were 7.15 (5.44, 9.46) and 6.17 (4.03, 9.71) in all participants, respectively. Conclusions: Our findings suggest that poor sleep quality was associated with a higher prevalence of depressive symptoms in Chinese resident physicians.

Prevalence and Demographic Correlates of Poor Sleep Quality Among Frontline Health Professionals in Liaoning Province, China During the COVID-19 Outbreak.

BACKGROUND: Little empirical evidence is known about the sleep quality of frontline health professionals working in isolation units or hospitals during the novel coronavirus disease (COVID-19) outbreak in China. This study thus aimed to examine the prevalence of poor sleep quality and its demographic and correlates among frontline health professionals. METHODS: This is a multicenter, cross-sectional survey conducted in Liaoning province, China. Sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI). RESULTS: A total of 1,931 frontline health professionals were recruited. The prevalence of poor sleep quality was 18.4% (95%CI: 16.6%-20.11%). Multivariate logistic regression analysis found that older age (OR=1.043, 95%CI=1.026-1.061, P < 0.001), being nurse (OR=3.132, 95%CI=1.727-5.681, P < 0.001), and working in outer emergency medical team (OR=1.755, 95%CI=1.029-3.064, P=0.039) were positively associated with poor sleep quality. Participants who were familiar with crisis response knowledge were negatively associated with poor sleep quality (OR=0.70, 95%CI=0.516-0.949, P=0.021). CONCLUSION: The prevalence of poor sleep quality was relatively low among frontline health professionals during the COVID-19 epidemic. Considering the negative impact of poor sleep quality on health professionals' health outcomes and patient outcomes, regularly screening and timely treatments are warranted to reduce the likelihood of poor sleep quality in health professionals.

Sleep Disturbance and Psychological Profiles of Medical Staff and Non-Medical Staff During the Early Outbreak of COVID-19 in Hubei Province, China.

OBJECTIVE: The outbreak of coronavirus disease 2019 (COVID-19) has considerably burdened the healthcare system in the Hubei Province, the most severely affected region in China. The aim of our study was to assess the psychological effects of COVID-19 epidemic on the healthcare workers in Hubei. METHODS: A total of 2737 healthcare workers were sampled using a two-dimensional code shared online between Mar 4 and Mar 9, 2020. The questionnaires consisted of three elements: baseline characteristics, Pittsburgh Sleep Quality Index (PSQI), and Hospital Anxiety and Depression Scale (HADS). The primary outcome variables were PQSI, anxiety and depression scores of non-medical staff, non-frontline medical staff and frontline medical staff. Binary logistical regression analyses were used to compare between respondents with and without sleep disturbance. RESULTS: About 61.6% of the respondents reported sleep problems, 22.6% experienced anxiety, and 35% exhibited depressive symptoms. The prevalence of sleep disorders was higher among the frontline healthcare workers compared to the non-frontline and non-medical staff, while anxiety and depression were prevalent in the entire cohort. Logistic regression analysis identified medical occupation, family burden, bereavement, anxiety, and depression as significantly predictive of poor sleep quality. CONCLUSIONS: Frontline medical staff are more vulnerable to sleep disturbances. Psychosocial interventions are needed to help allied healthcare personnel to better respond to COVID-19 and future outbreaks.

Risk factors of SARS-CoV-2 infection in healthcare workers: a retrospective study of a nosocomial outbreak.

BACKGROUND: Healthcare workers (HCWs) are at the forefront of fighting against the COVID-19 pandemic. However, they are at high risk of acquiring the pathogen from infected patients and transmitting to other HCWs. We aimed to investigate risk factors for nosocomial COVID-19 infection among HCWs in a non-COVID-19 hospital yard. METHODS: Retrospective data collection on demographics, lifestyles, contact status with infected subjects for 118 HCWs (including 12 COVID-19 HCWs) at Union Hospital of Wuhan, China. Sleep quality and working pressure were evaluated by the Pittsburgh Sleep Quality Index (PSQI) and The Nurse Stress Index (NSI), respectively. The follow-up duration was from Dec 25, 2019, to Feb 15, 2020. RESULTS: A high proportion of COVID-19 HCWs had engaged in night shift-work (75.0% vs. 40.6%) and felt working under pressure (66.7% vs. 32.1%) than uninfected HCWs. SARS-CoV-2 infected HCWs had significantly higher scores of PSQI and NSI than uninfected HCWs (P < 0.001). Specifically, scores of 5 factors (sleep quality, sleep time, sleep efficiency, sleep disorder, and daytime dysfunction) in PSQI were higher among infected HCWs. For NSI, its 5 subscales (nursing profession and work, workload and time allocation, working environment and resources, patient care, management and interpersonal relations) were all higher in infected than uninfected nurse. Furthermore, total scores of PSQI (HR = 2.97, 95%CI = 1.86-4.76; P <0.001) and NSI (HR = 4.67, 95%CI = 1.42-15.45; P = 0.011) were both positively associated with the risk of SARS-CoV-2 infection. CONCLUSION: Our analysis shows that poor sleep quality and higher working pressure may increase the risk of nosocomial SARS-CoV-2 infection among HCWs.

To Assess Sleep Quality among Pakistani Junior Physicians (House Officers): A Cross-sectional Study.

BACKGROUND: Sleep deprivation among junior physicians (house officers) is of growing concern. In developed countries, duty hours are now mandated, but in developing countries, junior physicians are highly susceptible to develop sleep impairment due to long working hours, on-call duties and shift work schedule. AIM: We undertook the study to assess sleep quality among Pakistani junior physicians. SUBJECTS AND METHODS: A cross-sectional study was conducted at private and public hospitals in Karachi, Pakistan, from June 2012 to January 2013. The study population comprised of junior doctors (house physicians and house surgeons). A consecutive sample of 350 physicians was drawn from the above-mentioned study setting. The subject underwent two validated self-administered questionnaires, that is, Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS). RESULTS: A total of 334 physicians completely filled out the questionnaire with a response rate of 95.4% (334/350). Of 334 physicians, 36.8% (123/334) were classified as "poor sleepers" (global PSQI score > 5). Poor sleep quality was associated with female gender (P = 0.01), excessive daytime sleepiness (P < 0.01), lower total sleep time (P < 0.001), increased sleep onset latency (P < 0.001), and increased frequency of sleep disturbances (P < 0.001). Abnormal ESS scores (ESS > 10) were more prevalent among poor sleepers (P < 0.01) signifying increased level of daytime hypersomnolence. CONCLUSION: Sleep quality among Pakistani junior physicians is significantly poor. Efforts must be directed towards proper sleep hygiene education. Regulations regarding duty hour limitations need to be considered.