You are currently viewing a new version of our website. To view the old version click .
MDPIMDPI
Search all articles
International Journal of Environmental Research and Public Health
Download PDF
  • Article
  • Open Access

26 August 2024

Exploring Risk Perception, Mental Health, Mental Fatigue, Stigma, and the Quality of Life among UAE Healthcare Workers during the COVID-19 Pandemic: A National Multicentric Cross-Sectional Study

,
,
,
,
,
,
,
,
and
1
School of Nursing, Faculty of Health Sciences, Higher Colleges of Technology, Abu Dhabi P.O. Box 25026, United Arab Emirates
2
Department of Mental Health, Medical Services Sector, Emirates Health Services, Dubai P.O. Box 2299, United Arab Emirates
3
Department of Community and Mental Health Nursing, Faculty of Nursing, WHO Collaborating Center, Jordan University of Science & Technology, Irbid 22110, Jordan
4
Department of Community and Mental Health Nursing, Faculty of Nursing, The Hashemite University, Zarqa P.O. Box 13115, Jordan
Int. J. Environ. Res. Public Health2024, 21(9), 1124;https://doi.org/10.3390/ijerph21091124
This article belongs to the Special Issue 2nd Edition: Public Health during and after the COVID-19 Pandemic
Version Notes
Order Reprints

Abstract

Globally, the COVID-19 pandemic has presented serious mental health challenges for healthcare professionals. This study investigated the mental health, mental fatigue, quality of life, and stigma of social discrimination among healthcare workers in the United Arab Emirates (UAE) during the COVID-19 pandemic. A correlational, cross-sectional, multi-centric design was employed to collect data from 1383 healthcare workers across various healthcare settings. Participants were recruited using combined cluster and purposive sampling techniques. Standardized questionnaires, including the COVID-19 Pandemic Mental Health Questionnaire (CoPaQ), the Mental Fatigue Scale (MFS), the Social Discrimination Scale-Stigma Subscale (SDS), and the WHO Quality of Life Questionnaire-Brief (WHOQOL-BREF), were administered to assess the study variables. The results indicated significant mental health impacts, with high average scores for post-traumatic stress disorder (PTSD) (9.37 ± 6.74) and positive coping by inner strengths (17.63 ± 5.72). Mental fatigue was prevalent (8.15 ± 8.62), and stigma of social discrimination scored notably (23.83 ± 7.46). Quality of life was the highest in the social domain (65.38 ± 24.58). Significant correlations were observed between mental health subscales, mental fatigue, and quality of life domains. These findings highlight the critical need for targeted mental health support programs, improved social support networks, and personalized interventions to mitigate the mental health challenges faced by healthcare workers. Healthcare organizations can guarantee a resilient workforce that can handle future health crises by giving mental health resources and support systems top priority.

1. Introduction

The Coronavirus disease 2019 (COVID-19) was declared a pandemic and a major public health crisis globally in March 2020 [,]. As of early August 2022, 581.8 million confirmed cases and 6.4 million deaths have been reported globally []. Healthcare workers were among the most vulnerable groups during the pandemic, facing occupational hazards, fear of transmitting the virus to family members, longer shifts, increased cases and death rates, lack of medical equipment, and isolation restrictions [,,,,,,]. These factors contributed to mental health issues such as fear, anxiety, stress, anger, and depression [,,,,,,,]. A recent study found that 61% of physicians experienced burnout, 57% reported anxiety, tearfulness, or anger, 46% experienced social isolation, and over 55% knew of a doctor who had attempted or committed suicide [].
Mental health disorders lead to a poor quality of life (QoL), mental fatigue, and stigmatization against those infected [,]. QoL is a multidimensional concept reflecting people’s perception of their culture and is influenced by various factors, including health status [,,]. Mental fatigue, characterized by lack of motivation and tiredness, affects cognitive performance, concentration, and planning, and is a symptom of psychiatric disorders like anxiety and depression [,,]. Health professionals experienced greater levels of mental fatigue, anxiety, and depression during COVID-19 [,].
Stigmatization, related to caring for patients with contagious diseases, contributed to uncertainty, stereotypes, and discrimination []. Social stigma in healthcare refers to the negative association with individuals who have a particular disease, leading to labeling and discrimination against those affected by COVID-19 [,]. This stigma can result in healthcare workers fearing virus contraction and feeling guilty about potentially spreading it to their families, ultimately affecting the quality of care provided [,,]. Stigmatization leads to reluctance in seeking healthcare, hampered pandemic control, and increased stress, anxiety, and burnout among healthcare professionals [,,].
As of 14 October 2023, the United Arab Emirates (UAE) reported 1,067,030 diagnosed COVID-19 cases with nearly 2349 deaths []. Despite the existing research on the mental and psychological impacts of COVID-19 in the UAE, there remains a significant gap in understanding the comprehensive effects on mental health, mental fatigue, social stigma, and quality of life (QoL) among healthcare workers during the pandemic. Our study aimed to address this gap by providing a detailed analysis of these factors within the unique healthcare environment of the UAE.

2. Materials and Methods

2.1. Enrolment and Data Collection

This national correlational, cross-sectional study was conducted in the United Arab Emirates to evaluate the risk perception, mental health, mental fatigue, quality of life, and stigma among healthcare frontliners during the COVID-19 pandemic. Participants were recruited using cluster and purposive sampling techniques from various healthcare settings, including those under the Ministry of Health and Prevention (MOHAP), Abu-Dhabi Health Services Company (SEHA), Sheikh Shakhbout Medical City (SSMC), and the private sector. The study received ethical approval from multiple research ethics committees: Higher Colleges of Technology (HCT) (REIC-06-2021), Ministry of Health and Prevention (MOHAP/DXB-REC/M.M.M/No.33/2022), SEHA Research Ethics Committee-SEHA Research Oversight Committee (HREC SEHA-IRB-42), and SSMC (SSMCREC-310). Data were collected in two phases between 18 March and 10 June 2022.

2.2. Pilot Phase

The pilot phase (18–24 March) tested the reliability and validity of the study instruments on 50 healthcare workers. The COVID-19 Pandemic Mental Health Questionnaire (CoPaQ), Mental Fatigue Scale (MFS), Social Discrimination Scale (SDS), and WHO Quality of Life Questionnaire-Brief (WHOQOL-BREF) were used, along with a Demographic Data Questionnaire. A priori criterion of Cronbach’s alpha ≥ 0.70 was used for adequate evidence of each scale and subscales reliability []. The pilot confirmed satisfactory internal consistency reliability (Cronbach’s alpha ≥ 0.70).

2.3. Data Collection

The main data collection phase began on 31 March and ended on 10 June 2022. Healthcare frontliners from the approved settings were invited to participate via institutional email. Inclusion and exclusion criteria were established to ensure a representative sample of healthcare workers for this study. Inclusion criteria were: (1) healthcare workers currently employed in the UAE, (2) adults aged 18 and above, (3) individuals who provided direct patient care during the COVID-19 pandemic, and (4) those who consented to participate in the study. Participation was voluntary, anonymous, and confidential. Out of 1443 invitations, 1383 participants completed the survey, forming the final sample.

2.4. Definitions of Key Terms

  • Risk Perception: Risk perception refers to an individual’s assessment of the likelihood and severity of a risk. In this study, it pertains to healthcare workers’ perceptions of their risk of contracting COVID-19 and the associated consequences.
  • Mental Health: Mental health encompasses emotional, psychological, and social well-being. It influences how individuals think, feel, and act, particularly under stress. In this study, mental health was assessed through symptoms of post-traumatic stress disorder (PTSD), anxiety, and general stress.
  • Mental Fatigue: Mental fatigue refers to the decline in cognitive performance and the feeling of exhaustion resulting from prolonged cognitive activity or stress. In this study, it was measured by assessing healthcare workers’ levels of cognitive and emotional exhaustion.
  • Stigma: Stigma refers to the negative attitudes and beliefs that lead to discrimination against individuals or groups. In this study, it pertains to the social discrimination experienced by healthcare workers due to their association with treating COVID-19 patients.
  • Quality of Life: Quality of life is a broad multidimensional concept that includes subjective evaluations of both positive and negative aspects of life. In this study, it was assessed in four domains: physical health, psychological state, social relationships, and environmental context.

2.5. Measurements

  • COVID-19 Pandemic Mental Health Questionnaire (CoPaQ): Participants’ risk perception, mental health impact, and positive coping were assessed using the COVID-19 Pandemic Mental Health Questionnaire (CoPaQ) []. The CoPaQ is a newly developed and highly comprehensive self-report measure of personal and social consequences of the COVID-19-pandemic with an application scope world-wide. The CoPaQ includes six sections with general questions as follows: general questions on the personal and social consequences of the COVID-19-pandemic (4 questions), general questions on the risk factors for a severe course of COVID-19 applied to participants (9 questions), general questions on the risk factors for a severe course of COVID-19 applied to participants the people living with participants in the same household (9 questions), 2 questions on the quarantine and work from home (WFH), nominal questions on previous diagnosis by a doctor or therapist with one or more of the psychological disorders (10 questions), and 1 question current receiving of psychotherapy. For the measurement of risk perception, mental health impact, and positive coping, 10 subscales were used as follows: COVID-19 contamination anxiety (9 questions), COVID-19 adherence measures (3 questions), COVID-19 mental health impact related to Post-Traumatic Stress Disorders (3 questions), COVID-19 mental health impact related to sleep disturbances (6 questions), COVID-19 mental health impact related to substance use (6 questions), COVID-19 mental health impact related to stress burdens (16 questions), COVID-19 positive coping by daytime structure (3 questions), COVID-19 positive coping by social contacts (4 questions), COVID-19 positive coping by inner strengths (7 questions), and COVID-19 stressor impact related to conspiracy beliefs (6 questions). Each subscale was measured on a Likert’s scale from 0 (not at all) to 4 (very much). Two scoring protocols were used for mental health impact subscales the continuous and the categorical scoring. For the continuous scoring, a sum score of all items pertaining to each subscale was calculated as an index of COVID-19-specific impact with higher scores indicating a greater stressor impact. For categorical scoring, using the total sum of all items, each subscale was categorized into 4 categories as follows: No Stressor Impact, Mild Stressor Impact, Moderate Stressor Impact, and Severe Stressor Impact. For mental health impact subscales, the continuous scoring protocol was used with higher scores indicating greater ability to cope with the COVID-19 stressors impact. In this study, the questionnaire demonstrated excellent internal consistency reliability with Cronbach’s alpha of 0.962.
  • Mental Fatigue Scale (MFS-14): Measured mental fatigue and related symptoms using 14 questions covering topics such as generalized fatigue, concentration, memory, slowness of thinking, stress sensitivity, and sleep problems. Each item had four response options: no (0), slight (1), fairly serious (2), and serious (3) problems. Scores above 10 indicated a problem with mental fatigue []. The MFS showed excellent internal consistency reliability (Cronbach’s alpha = 0.948).
  • Social Discrimination Scale-Stigma Subscale (SDS-12): Assessed stigma related to COVID-19 using 12 statements measuring personal and public perceptions of stigma. Participants rated each statement on a Likert scale from 1 (strongly disagree) to 4 (strongly agree). Higher scores indicated higher levels of stigma []. The SDS demonstrated excellent internal consistency reliability (Cronbach’s alpha = 0.901).
  • WHO Quality of Life Questionnaire (WHOQOL-BREF): Measured quality of life across four domains: Physical health, Psychological, Social relationships, and Environment. The questionnaire included 26 questions rated on a 1–5 Likert scale. Domain scores were scaled to a 0–100 scale for comparability []. The WHOQOL-BREF showed excellent internal consistency reliability (Cronbach’s alpha = 0.947).
  • Demographic Data Questionnaire: Collected social and demographic data from participants, including age, gender, nationality, educational level, occupational role, marital status, number of children, previous diagnosis of COVID-19, self-isolation, living conditions, and household status.

2.6. Data Analysis

Data were analyzed using SPSS (IBM SPSS Statistics, Version 29, 2022). Descriptive statistics were computed for continuous and categorical variables. The data was examined for statistical assumptions prior to each analysis. Independent samples t-tests and a one-way analysis of variance (ANOVA) were used to compare means across demographic and COVID-19-related variables. Pearson’s correlation coefficients assessed relationships between key study variables. Statistical significance was set at p < 0.05.

3. Results

3.1. Participants’ Demographics and COVID-19-Related Characteristics

Table 1 shows demographics and COVID-19-related characteristics. A total of 1383 healthcare workers were enrolled in the study. The participants’ mean age was 39.87 (SD = 8.76). The majority were females (75.1%), married (82%), non-Emirati (89.9%), had a diploma/bachelor’s degree (75.1%), employed (98.93%), nurses (75.6%), had more than ten years of experience (54.7%), with income less or equal to 10,000 Dirhams (60%), and either living or working in city of Sharjah (46%, 52.2%, respectively). Concerning COVID-19, 61.6% reported an ever-positive PCR test; however, only 12.4% reported COVID-19 symptoms, 5% were under quarantine, and 12.7% were working/studying remotely from their home.
Table 1. Participant demographics and COVID-19-related characteristics.

3.2. Mental Health, Mental Fatigue, Stigma of Social Discrimination, and Quality of Life

Participants’ total scores of mental health impacts, mental fatigue, the stigma of social discrimination, and quality of life were reported in Table 2. Concerning mental health impacts for risk perception, while considering the number of response items, the highest average total score was COVID-19 mental health impact related to contamination anxiety (12.57 ± 9.14), followed by 19 mental health impact related to PTSD (9.37 ± 6.74). Furthermore, for COVID-19 positive coping, the highest average score was for COVID-19 positive coping by inner strengths (17.63 ± 5.72). The average total score of mental fatigue and stigma of social discrimination were 8.15 ± 8.62 and 23.83 ± 7.46, respectively. The highest reported quality of life score was for the social domain (65.38 ± 24.58), followed by the psychological domain (62.69 ± 20.30).
Table 2. Descriptive statistics for the continuous scoring of mental health, mental fatigue, stigma of social discrimination, and quality of life.

3.3. Levels of COVID-19 Contamination Anxiety, Stress Burden, and Mental Health Impacts

Table 3 presents the distribution of stressor impacts among healthcare workers for several key variables: COVID-19 contamination anxiety, COVID-19 mental health impacts (including PTSD, sleep disturbances, and substance use), and COVID-19 stress burden. Regarding COVID-19 contamination anxiety, the majority of participants reported no stressor impact (43.5%), while 31.4% experienced mild stressor impact. Moderate and severe stressor impacts were reported by 18.0% and 7.2% of participants, respectively. This distribution highlights that while a substantial portion of the healthcare workers experienced some level of anxiety related to contamination, a significant number reported only mild to no stressor impact. Similarly, most participants indicated no stressor impact related to PTSD (43.8%). Mild PTSD symptoms were reported by 34.9% of participants, with moderate and severe impacts observed in 16.0% and 5.3%, respectively. Regarding COVID-19 mental health impact related to sleep disturbances, the most frequent category was no stressor impact (64.3%), with mild disturbances reported by 18.9% of participants. Moderate and severe sleep disturbances were less common, affecting 12.9% and 3.9% of participants, respectively. These findings indicate that sleep disturbances were less prevalent compared to other mental health impacts. In contrast, a significant majority reported no stressor impact related to substance use (71.8%). Mild impacts were observed in 18.2% of participants, while moderate and severe impacts were reported by 8.5% and 1.4%, respectively. This indicates that substance use was relatively less of a concern compared to other stressors. Regarding COVID-19 stress burden, the distribution shows the varying levels of stress experienced by healthcare workers, with a notable portion reporting mild to moderate stress burdens.
Table 3. Descriptive statistics for categorical scoring of mental health, mental fatigue, stigma of social discrimination, and quality of life.

3.4. Inferential Analysis of Tested Variables on Participants’ Sociodemographic Variables

3.4.1. Independent Sample T-Test to Compare the Means of Tested Variables across Participants’ Sociodemographic Variables

Table 4 shows the means of total scores of scales and subscales of mental health impacts, mental fatigue, stigma of social discrimination, and quality of life across the participants’ sociodemographic. Compared with females, males reported a lower level of COVID-19 adherence measures (8.06 ± 2.83 vs. 8.50 ± 2.61, p = 0.009); however, males reported a higher level of COVID-19 stressor impact related to conspiracy beliefs (10.93 ± 5.45 vs. 10.20 ± 5.61, p = 0.037), physical (64.62 ± 21.84 vs. 59.82 ± 21.65, p ˂ 0.001), psychological (65.36 ± 20.52 vs. 61.80 ± 20.15, p = 0.005), social (68.07 ± 23.88 vs. 64.49 ± 24.75, p = 0.019), and environmental (65.67 ± 19.41 vs. 61.65 ± 19.98, p = 0.001) quality of life. The rest of the comparison for the significant differences in scales and subscales across the demographics and COVID-19 related characteristics were reported in Table 4. Furthermore, non-significant differences in outcome variables across the demographics were not reported in Table 4.
Table 4. Independent sample t-test of the tested variables on participants’ sociodemographic variables.

3.4.2. One-Way ANOVA to Compare the Means of Tested Variables across Participants’ Sociodemographic Characteristics

The one-way ANOVA test was performed to compare the differences in means of the total scores of tested variables across participants’ demographics, profession, city of residency, and city of employment (Table 5). Regarding COVID-19 adherence measures, significant differences were observed (F = 9.703, p < 0.001) among physicians, nurses, and others, indicating that adherence to COVID-19 measures varied by profession, with nurses showing different adherence patterns compared to physicians and other professionals. Furthermore, the results showed significant differences in impact of PTSD related to COVID-19 across the participants profession (F = 11.718, p < 0.001), with nurses experiencing more significant impacts compared to physicians and other professions. Similarly, a significant variation in stress burden related to COVID-19 (F = 8.004, p < 0.001) was found across professions, with nurses reporting higher stress levels. Regarding Quality-of-Life variables, significant differences were found in physical (F = 8.553, p < 0.001), psychological (F = 11.871, p < 0.001), social (F = 11.055, p < 0.001), and environmental (F = 21.742, p < 0.001) domains across the professions, suggesting that professionals experienced varied quality of life impacts based on their role, with significant differences in perceived quality across the various domains. On the other hand, significant differences in COVID-19 mental health impact related to PTSD (F = 3.034, p = 0.004), COVID-19 stress burden (F = 3.356, p = 0.001), COVID-19 positive coping (F = 2.398, p = 0.019), stigma of social discrimination (F = 3.036, p = 0.004) and QoL variables were found based on city of residency, indicating varied impacts among residents of different cities, with residents of certain cities reporting higher impacts. Similarly, the differences were noted in the tested variables based on the city of employment. For instance, significant differences in COVID-19 mental health impact related to PTSD (F = 2.266, p = 0.027) highlight that the impact of PTSD varied based on the city of employment, with some cities showing higher impacts. Furthermore, non-significant differences in outcome variables across the demographics were not reported in Table 5.
Table 5. One-way ANOVA of the tested variables on participants’ sociodemographic variables, profession, city of residency, and city of employment.

3.5. Pearsons’ Correlation Analysis for the Relationships between the Outcome Variables

Table 6 presents the bivariate relationships between COVID-19 mental health impacts, mental fatigue, stigma of social discrimination, and quality of life. Also, age and number of internet hours were included in this table. Age exhibited several statistically significant correlations. Specifically, it negatively correlated with contamination anxiety, sleep disturbances, substance use, stress burden, and mental fatigue, suggesting that older participants reported lower levels of these stressors. Conversely, age was positively correlated with daytime structure and social contact, indicating that older individuals might have better-organized daily routines and more social interactions. Furthermore, contamination anxiety showed a strong positive correlation with PTSD (r = 0.544, p < 0.01), sleep disturbances (r = 0.551, p < 0.01), and substance use (r = 0.543, p < 0.01), highlighting the significant impact of contamination anxiety on various mental health aspects. Contamination anxiety also had notable positive correlations with stress burden (r = 0.633, p < 0.01) and stigma of social discrimination (SSD) (r = 0.180, p < 0.01). Additionally, adherence to measures was positively correlated with contamination anxiety (r = 0.222, p < 0.01) and had moderate correlations with PTSD (r = 0.277, p < 0.01) and stress burden (r = 0.222, p < 0.01). This suggests that adherence measures are associated with higher levels of anxiety and stress but show weaker relationships with other variables. PTSD was strongly correlated with sleep disturbances (r = 0.686, p < 0.01), and substance use (r = 0.686, p < 0.01). The strong associations indicate that PTSD symptoms are prevalent among those experiencing high levels of anxiety, sleep issues, and substance use. Sleep disturbances was positively correlated with PTSD (r = 0.693, p < 0.01), substance use (r = 0.837, p < 0.01), and stress burden (r = 0.680, p < 0.01), suggesting that individuals with sleep disturbances experience significant stress and increased substance use. Stress burden showed strong correlations with PTSD (r = 0.681, p < 0.01), sleep disturbances (r = 0.680, p < 0.01), and substance use (r = 0.739, p < 0.01), indicating a robust relationship between perceived stress and other mental health issues. Regarding Quality of Life (QoL) variables, All QoL subscales (physical, psychological, social, environmental) showed negative correlations with mental health stressors such as contamination anxiety, PTSD, and stress burden. For instance, QoL Physical (QOL-PH) was negatively correlated with contamination anxiety (r = −0.326, p < 0.01), PTSD (r = −0.302, p < 0.01), and stress burden (r = −0.422, p < 0.01), indicating that higher levels of anxiety and stress are associated with poorer quality of life. Mental fatigue exhibited significant positive correlations with contamination anxiety (r = 0.434, p < 0.01), PTSD (r = 0.381, p < 0.01), sleep disturbances (r = 0.545, p < 0.01), and substance use (r = 0.491, p < 0.01). These correlations suggest that increased levels of mental fatigue are strongly associated with higher levels of anxiety, PTSD symptoms, sleep issues, and substance use. Additionally, mental fatigue showed moderate positive correlations with stress burden (r = 0.479, p < 0.01) and a weaker but still significant correlation with stigma of social discrimination (r = 0.186, p < 0.01), indicating that mental fatigue is linked to perceived stress and stigma but to a lesser extent. Regarding stigma of social discrimination (SSD), there was a weak correlation with mental fatigue (r = 0.186, p < 0.01) and was negatively correlated with several QoL variables, including physical (r = −0.355, p < 0.01) and psychological (r = −0.424, p < 0.01), indicating that higher stigma is associated with a lower quality of life across different domains.
Table 6. Correlation matrix of mental health, mental fatigue, stigma of the social discrimination, and quality of life (n = 1383).

4. Discussion

This study aimed to investigate the mental health, mental fatigue, quality of life and stigma of social discrimination among healthcare workers during the COVID-19 pandemic in United Arab Emirates. The study enrolled a total of 1383 healthcare workers of them, 61.6% had tested positive for the virus at some point during the outbreak of the pandemic. The results of our study revealed noteworthy effects on the mental health of healthcare professionals. Among these effects, the COVID-19 mental health impact associated with PTSD had the highest average score. This finding is consistent with earlier research reporting that healthcare workers experienced higher levels of PTSD symptoms during the pandemic [,]. Local studies in the UAE have also reported similar trends. For instance, Al Dhaheri et al. (2020) found high levels of psychological distress, including PTSD, among healthcare professionals in Abu Dhabi []. Additionally, a study by Cheikh Ismail et al. (2021) highlighted significant levels of anxiety and depression among healthcare workers in the UAE during the pandemic, reinforcing our findings on mental health impacts []. Furthermore, the high average score for positive coping by inner strengths indicates a resilient response from the participants, which has also been observed in studies highlighting the crucial role of positive coping mechanisms [,]. The study results show that healthcare workers face significant challenges related to mental fatigue and social discrimination. These findings align with other studies that emphasize the dual burden healthcare workers endure [,]. For example, a study by Saddik et al. (2021) on healthcare workers in Dubai reported significant levels of mental fatigue and social discrimination, similar to our findings []. According to quality-of-life scores in this study, the psychological domain scored lower than the social domain. This is consistent with other research demonstrating the critical role social and psychological support networks play in preserving quality of life when facing major stressors [,].
A significant proportion of participants in our study reported experiencing moderate to severe impacts from various COVID-19-related stressors, notably contamination anxiety, PTSD, and general stress burdens. These results are consistent with earlier studies that showed the pandemic had a significant psychological toll on healthcare workers [,,]. Interestingly, our study found that relatively fewer participants reported moderate to severe impacts from sleep disturbances and substance use. This indicates that while some aspects of mental health are significantly affected by the pandemic, others may show greater variation [].
In our study, the independent t-tests and one-way ANOVA analyses showed notable variations in the effects of mental health and quality of life among different demographic groups. For example, men reported a better quality of life in all domains and lower levels of COVID-19 adherence measures, but higher levels of stressor impacts related to conspiracy beliefs. Specifically, men had higher scores in physical, psychological, social, and environmental domains compared to women, who had lower scores in all these domains. However, men reported higher stressor impacts related to conspiracy beliefs, with an average score of compared to in women. These gender differences are consistent with earlier research showing that men and women react to pandemic-related stressors differently [,]. Furthermore, our study revealed notable variations among occupations and places of employment, indicating that the professional role and workplace atmosphere have a substantial impact on mental health and overall well-being []. Specifically, nurses reported higher levels of mental fatigue and social discrimination compared to physicians, who had lower scores in these areas. Similarly, healthcare workers in high-risk areas such as emergency departments and COVID-19 wards reported higher PTSD scores compared to those in low-risk areas. Therefore, understanding these variations is pivotal to putting in place support networks and interventions that are specifically designed to meet the needs of every healthcare subgroup.
The correlation analysis found multiple significant correlations shedding light on the interconnected nature of mental health issues and quality of life domains among healthcare workers. Notably, the strong correlation between mental health impacts related to sleep disturbances and substance use is consistent with earlier study indicating that individuals experiencing sleep disturbances may be more susceptible to substance use as a coping mechanism [,,]. Additionally, we found a strong correlation between the environmental and physical quality of life domains, demonstrating how these domains are interrelated in determining overall well-being [,].
As we outlined above, while many findings in our study align with existing literature, several unique insights emerged that contribute to the scientific understanding of healthcare workers’ experiences during the pandemic. For instance, our study found that nurses, especially those from high-risk regions were reported to have higher levels of mental fatigue and social discrimination compared to physicians. This clearly indicates that there is an urgent need for specialized mental health treatments for nurses working under pressure. Furthermore, our research identified gender-based stressor effects whereby males had greater levels of tension than their female counterparts owing to conspiracy belief-related issues. This finding about behavioral variations between the genders regarding stress responses indicates how crucial it is when developing programs aimed at improving mental wellbeing across genders.
The study’s strengths include its comprehensive evaluation of multiple mental health and quality of life domains in addition to its large sample size. The findings’ generalizability is further improved by the participation of a diverse range of healthcare professionals from various cities and units. Moreover, the data reported in this study could be a good comparable source for other researchers and future studies that aim to study such a large number of variables simultaneously. However, the study does have certain limitations. Inferring causality between variables is limited by the cross-sectional design. Due to participant under- or overreporting of symptoms and experiences, self-reported data may introduce bias. Furthermore, there may be limited generalizability to other regions due to the study’s execution within a particular cultural and geographical context.
The findings of our study have significant implications for post-COVID situations and future healthcare crises. First, the high levels of mental fatigue and social discrimination reported by healthcare workers, particularly nurses in high-risk areas, suggest that ongoing mental health support and interventions will be crucial even after the immediate threat of the pandemic has subsided. Establishing long-term mental health programs that address these specific stressors can help mitigate the prolonged impact on healthcare workers’ well-being. Moreover, the gender-specific differences in stressor impacts indicate that mental health interventions should be tailored to address the unique needs of different demographic groups. Our study also highlights the importance of strengthening social support networks within healthcare settings. Enhanced peer support programs, resilience training, and opportunities for professional development can help create a more supportive work environment that can buffer against the negative impacts of high-stress situations.
The results of the study recommend that specific mental health support programs for healthcare workers that address stress management, PTSD, and fatigue reduction are imperative. In healthcare settings, social support networks should be strengthened in order to reduce feelings of isolation and enhance mental health. Positive coping strategies like mindfulness and resilience training can also be promoted. Furthermore, customized interventions that cater to the particular requirements of various professional and demographic groups are advised. For instance, targeted support for nurses in high-risk areas who experience higher levels of mental fatigue and social discrimination, and tailored programs for men who report higher stressor impacts related to conspiracy beliefs, could be beneficial. In order to maintain a robust and efficient healthcare workforce that is able to handle both present and future health crises, policymakers and administrators must prioritize mental health resources and support networks. These actions have a substantial impact on healthcare policy and practice.

5. Conclusions

This national study sheds light on the significant mental health challenges faced by healthcare workers during the COVID-19 pandemic, focusing on mental health, mental fatigue, quality of life and social discrimination. Despite showing resilience through positive coping strategies, healthcare workers are still prone to experiencing high levels of stress, anxiety, and other mental health and mental fatigue issues. The study stresses the importance of addressing these challenges through targeted support programs, improved social support networks, and personalized interventions tailored to the unique needs of different groups within the healthcare workforce. By prioritizing mental health resources and support systems, healthcare organizations can better care for their employees, ensuring their well-being and ability to effectively handle current and future health emergencies.

Author Contributions

Conceptualization, Y.M.A., H.F.D. and H.A.-O.; methodology, Y.M.A., N.G., H.F.D., N.A.M., S.A., H.A.-O. and S.R.S.; software, Y.M.A., A.M.A.-B., A.G. and O.A.; validation, Y.M.A., A.M.A.-B., H.Y.G. and S.R.S.; formal analysis, Y.M.A., H.F.D., A.M.A.-B., A.G. and H.A.-O.; investigation, Y.M.A., N.G., H.F.D., N.A.M., S.A., H.A.-O. and S.R.S.; resources, Y.M.A., H.F.D., H.A.-O., S.A., N.A.M. and G.L.B.; data curation, Y.M.A., A.M.A.-B., A.G., H.Y.G., N.G. and O.A.; writing—original draft preparation, Y.M.A., A.M.A.-B., N.G., S.A., N.A.M., S.R.S., H.Y.G., A.G. and O.A. writing—review and editing, N.G., N.A.M., A.G. and H.Y.G.; visualization, Y.M.A., A.M.A.-B. and O.A.; supervision, Y.M.A., N.G., H.F.D. and G.L.B.; project administration, Y.M.A., N.G., H.F.D. and G.L.B.; funding acquisition, Y.M.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the World Health Organization (WHO), grant number (AP21-00546).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of Research Integrity and Ethics Committee (RIEC) at the Higher Colleges of Technology (HCT) (REIC-06-2021), the Research Ethics Committee at the Ministry of Health and Prevention (MOHAP/DXB-REC/M.M.M/no. 33/2022), the Research Ethics and Oversight Committee at Abu-Dhabi Health Services Company (SEHA) (HREC SEHA-IRB-42), and by the Research Ethics Committee at Sheikh Shakhbout Medical City (SSMC) (SSMCREC-310).

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

The authors would like to express their gratitude to the Institutional Research Department at the Higher Colleges of Technology for their invaluable technical support during data collection and project administration. Their assistance was instrumental in the successful completion of this research.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. AlGhufli, F.; AlMulla, R.; Alyedi, O.; Zain AlAbdin, S.; Nakhal, M.M. Investigating the impact of COVID-19 pandemic on mental health status and factors influencing negative mental health among health-care workers in Dubai, United Arab Emirates. Dubai Med. J. 2021, 4, 301–309. [Google Scholar] [CrossRef]
  2. Li, Q.; Guan, X.; Wu, P.; Wang, X.; Zhou, L.; Tong, Y.; Ren, R.; Leung, K.S.M.; Lau, E.H.Y.; Wong, J.Y.; et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. N. Engl. J. Med. 2020, 382, 1199–1207. [Google Scholar] [CrossRef]
  3. World Health Organization. Weekly Epidemiological Update on COVID-19—10 August 2022. 2022. Available online: https://www.who.int/publications/m/item/weekly-epidemiological-update-on-COVID-19---10-august-2022 (accessed on 5 August 2024).
  4. Adams, J.G.; Walls, R.M. Supporting the Health Care Workforce During the COVID-19 Global Epidemic. JAMA 2020, 323, 1439–1440. [Google Scholar] [CrossRef]
  5. Elbay, R.Y.; Kurtulmuş, A.; Arpacıoğlu, S.; Karadere, E. Depression, anxiety, stress levels of physicians and associated factors in COVID-19 pandemics. Psychiatry Res. 2020, 290, 113130. [Google Scholar] [CrossRef]
  6. Korkmaz, S.; Kazgan, A.; Çekiç, S.; Tartar, A.S.; Balcı, H.N.; Atmaca, M. The anxiety levels, quality of sleep and life and problem-solving skills in healthcare workers employed in COVID-19 services. J. Clin. Neurosci. Off. J. Neurosurg. Soc. Australas. 2020, 80, 131–136. [Google Scholar] [CrossRef] [PubMed]
  7. Pierce, M.; Hope, H.; Ford, T.; Hatch, S.; Hotopf, M.; John, A.; Kontopantelis, E.; Webb, R.; Wessely, S.; McManus, S.; et al. Mental health before and during the COVID-19 pandemic: A longitudinal probability sample survey of the UK population. Lancet Psychiatry 2020, 7, 883–892. [Google Scholar] [CrossRef]
  8. Rania, N.; Coppola, I.; Brucci, M. Mental health and quality of professional life of healthcare workers: One year after the outbreak of the COVID-19 pandemic. Sustainability 2023, 15, 2977. [Google Scholar] [CrossRef]
  9. Sasangohar, F.; Jones, S.L.; Masud, F.N.; Vahidy, F.S.; Kash, B.A. Provider Burnout and Fatigue During the COVID-19 Pandemic: Lessons Learned from a High-Volume Intensive Care Unit. Anesth. Analg. 2020, 131, 106–111. [Google Scholar] [CrossRef] [PubMed]
  10. Barello, S.; Palamenghi, L.; Graffigna, G. Burnout and somatic symptoms among frontline healthcare professionals at the peak of the Italian COVID-19 pandemic. Psychiatry Res. 2020, 290, 113129. [Google Scholar] [CrossRef]
  11. Giusti, E.M.; Pedroli, E.; D’Aniello, G.E.; Stramba Badiale, C.; Pietrabissa, G.; Manna, C.; Stramba Badiale, M.; Riva, G.; Castelnuovo, G.; Molinari, E. The Psychological Impact of the COVID-19 Outbreak on Health Professionals: A Cross-Sectional Study. Front. Psychol. 2020, 11, 1684. [Google Scholar] [CrossRef]
  12. Huo, L.; Zhou, Y.; Li, S.; Ning, Y.; Zeng, L.; Liu, Z.; Qian, W.; Yang, J.; Zhou, X.; Liu, T.; et al. Burnout and Its Relationship With Depressive Symptoms in Medical Staff during the COVID-19 Epidemic in China. Front. Psychol. 2021, 12, 616369. [Google Scholar] [CrossRef]
  13. Lai, J.; Ma, S.; Wang, Y.; Cai, Z.; Hu, J.; Wei, N.; Wu, J.; Du, H.; Chen, T.; Li, R.; et al. Factors Associated with Mental Health Outcomes among Health Care Workers Exposed to Coronavirus Disease 2019. JAMA Netw. Open 2020, 3, e203976. [Google Scholar] [CrossRef]
  14. Marcotrigiano, V.; Pattavina, F.; Blangiardi, L.; Salerno, G.; Dalena, A.; Del Bianco, F.; Di Fant, M.; Fabbro, A.; Forgiarini, M.; Lanzilotti, C.; et al. The Preventive Health Professions in Italy: The Efficient Use of Resources, Skills and Best Practice during the Pandemic. Healthcare 2022, 10, 1906. [Google Scholar] [CrossRef]
  15. Matsuo, T.; Kobayashi, D.; Taki, F.; Sakamoto, F.; Uehara, Y.; Mori, N.; Fukui, T. Prevalence of Health Care Worker Burnout during the Coronavirus Disease 2019 (COVID-19) Pandemic in Japan. JAMA Netw. Open 2020, 3, e2017271. [Google Scholar] [CrossRef]
  16. Philip, J.; Cherian, V. Factors Affecting the Psychological Well-being of Health Care Workers during an Epidemic: A Thematic Review. Indian J. Psychol. Med. 2020, 42, 323–333. [Google Scholar] [CrossRef]
  17. Savitsky, B.; Radomislensky, I.; Hendel, T. Nurses’ occupational satisfaction during COVID-19 pandemic. Appl. Nurs. Res. ANR 2021, 59, 151416. [Google Scholar] [CrossRef]
  18. Physicians Foundation. 2021 Survey of America’s Physicians. COVID-19 Impact Edition: A Year Later. 2021. Available online: https://physiciansfoundation.org/wp-content/uploads/2021/08/2021-Survey-Of-Americas-Physicians-COVID-19-Impact-Edition-A-Year-Later.pdf (accessed on 5 August 2024).
  19. Young, K.P.; Kolcz, D.L.; O’Sullivan, D.M.; Ferrand, J.; Fried, J.; Robinson, K. Health Care Workers’ Mental Health and Quality of Life during COVID-19: Results from a Mid-Pandemic, National Survey. Psychiatr. Serv. 2021, 72, 122–128. [Google Scholar] [CrossRef]
  20. Haraldstad, K.; Wahl, A.; Andenæs, R.; Andersen, J.R.; Andersen, M.H.; Beisland, E.; Borge, C.R.; Engebretsen, E.; Eisemann, M.; Halvorsrud, L.; et al. A systematic review of quality of life research in medicine and health sciences. Qual. Life Res. Int. J. Qual. Life Asp. Treat. Care Rehabil. 2019, 28, 2641–2650. [Google Scholar] [CrossRef]
  21. Singh, R.; Subedi, M. COVID-19 and stigma: Social discrimination towards frontline healthcare providers and COVID-19 recovered patients in Nepal. Asian J. Psychiatry 2020, 53, 102222. [Google Scholar] [CrossRef]
  22. Villa, S.; Jaramillo, E.; Mangioni, D.; Bandera, A.; Gori, A.; Raviglione, M.C. Stigma at the time of the COVID-19 pandemic. Clin. Microbiol. Infect. Off. Publ. Eur. Soc. Clin. Microbiol. Infect. Dis. 2020, 26, 1450–1452. [Google Scholar] [CrossRef]
  23. Mozuraityte, K.; Stanyte, A.; Fineberg, N.A.; Serretti, A.; Gecaite-Stonciene, J.; Burkauskas, J. Mental fatigue in individuals with psychiatric disorders: A scoping review. Int. J. Psychiatry Clin. Pract. 2023, 27, 186–195. [Google Scholar] [CrossRef]
  24. Morgul, E.; Bener, A.; Atak, M.; Akyel, S.; Aktaş, S.; Bhugra, D.; Ventriglio, A.; Jordan, T.R. COVID-19 pandemic and psychological fatigue in Turkey. Int. J. Soc. Psychiatry 2021, 67, 128–135. [Google Scholar] [CrossRef]
  25. Torrente, F.; Yoris, A.; Low, D.; Lopez, P.; Bekinschtein, P.; Vázquez, G.H.; Manes, F.; Cetkovich, M. Psychological symptoms, mental fatigue and behavioural adherence after 72 continuous days of strict lockdown during the COVID-19 pandemic in Argentina. BJPsych Open 2021, 8, e10. [Google Scholar] [CrossRef]
  26. Teng, Z.; Wei, Z.; Qiu, Y.; Tan, Y.; Chen, J.; Tang, H.; Wu, H.; Wu, R.; Huang, J. Psychological status and fatigue of frontline staff two months after the COVID-19 pandemic outbreak in China: A cross-sectional study. J. Affect. Disord. 2020, 275, 247–252. [Google Scholar] [CrossRef]
  27. Zhan, Y.X.; Zhao, S.Y.; Yuan, J.; Liu, H.; Liu, Y.F.; Gui, L.L.; Zheng, H.; Zhou, Y.M.; Qiu, L.H.; Chen, J.H.; et al. Prevalence and Influencing Factors on Fatigue of First-line Nurses Combating with COVID-19 in China: A Descriptive Cross-Sectional Study. Curr. Med. Sci. 2020, 40, 625–635. [Google Scholar] [CrossRef]
  28. Ramaci, T.; Barattucci, M.; Ledda, C.; Rapisarda, V. Social stigma during COVID-19 and its impact on HCWs outcomes. Sustainability 2020, 12, 3834. [Google Scholar] [CrossRef]
  29. Link, B.G.; Phelan, J.C. Conceptualizing stigma. Annu. Rev. Sociol. 2001, 27, 363–385. [Google Scholar] [CrossRef]
  30. Parker, R.; Aggleton, P. HIV and AIDS-related stigma and discrimination: A conceptual framework and implications for action. Soc. Sci. Med. 1982 2003, 57, 13–24. [Google Scholar] [CrossRef]
  31. Cavalera, C. COVID-19 Psychological Implications: The Role of Shame and Guilt. Front. Psychol. 2020, 11, 571828. [Google Scholar] [CrossRef]
  32. Raza, A.; Matloob, S.; Abdul Rahim, N.F.; Abdul Halim, H.; Khattak, A.; Ahmed, N.H.; Nayab, D.E.; Hakeem, A.; Zubair, M. Factors Impeding Health-Care Professionals to Effectively Treat Coronavirus Disease 2019 Patients in Pakistan: A Qualitative Investigation. Front. Psychol. 2020, 11, 572450. [Google Scholar] [CrossRef]
  33. Cannizzaro, E.; Cirrincione, L.; Mazzucco, W.; Scorciapino, A.; Catalano, C.; Ramaci, T.; Ledda, C.; Plescia, F. Night-time shift work and related stress responses: A study on security guards. Int. J. Environ. Res. Public Health 2020, 17, 562. [Google Scholar] [CrossRef] [PubMed]
  34. Ramaci, T.; Barattucci, M.; Vella, F.; Senia, P.; Cannizzaro, E.; Scorciapino, A.; Ledda, C.; De Giorgio, A.; Rapisarda, V. Straining at Work and Its Relationship with Personality Profiles and Individual Consequences in Healthcare Workers (HCWs). Int. J. Environ. Res. Public Health 2020, 17, 610. [Google Scholar] [CrossRef]
  35. Santarelli, L.; Rapisarda, V.; Fago, L.; Vella, F.; Ramaci, T.; Ledda, C.; Bracci, M. Relation between psychosomatic disturbances and job stress in video display unit operators. Work 2019, 64, 303–310. [Google Scholar] [CrossRef]
  36. National Emergency Crisis and Disaster Management Authority. 2023, UAE Coronavirus (COVID-19) Updates. Available online: https://covid19.ncema.gov.ae/en (accessed on 3 August 2024).
  37. DeVellis, R.F.; Thorpe, C.T. Scale Development: Theory and Applications; Sage Publications: Thousand Oaks, CA, USA, 2021. [Google Scholar]
  38. Rek, S.V.; Bühner, M.; Reinhard, M.A.; Freeman, D.; Keeser, D.; Adorjan, K.; Falkai, P.; Padberg, F. The COVID-19 Pandemic Mental Health Questionnaire (CoPaQ): Psychometric evaluation and compliance with countermeasures in psychiatric inpatients and non-clinical individuals. BMC Psychiatry 2021, 21, 426. [Google Scholar] [CrossRef] [PubMed]
  39. Johansson, B.; Ronnback, L. Evaluation of the Mental fatigue scale and its relation to cognitive, social and emotional functioning after a TBI or stroke. Int. J. Phys. Med. Rehabil. 2014, 28, 572–573. [Google Scholar] [CrossRef]
  40. Dinos, S.; Stevens, S.; Serfaty, M.; Weich, S.; King, M. Stigma: The feelings and experiences of 46 people with mental illness. Qualitative study. Br. J. Psychiatry J. Ment. Sci. 2004, 184, 176–181. [Google Scholar] [CrossRef]
  41. Skevington, S.M.; Lotfy, M.; O’Connell, K.A.; WHOQOL Group. The World Health Organization’s WHOQOL-BREF quality of life assessment: Psychometric properties and results of the international field trial. A report from the WHOQOL group. Qual. Life Res. Int. J. Qual. Life Asp. Treat. Care Rehabil. 2004, 13, 299–310. [Google Scholar] [CrossRef]
  42. Pappa, S.; Ntella, V.; Giannakas, T.; Giannakoulis, V.G.; Papoutsi, E.; Katsaounou, P. Prevalence of depression, anxiety, and insomnia among healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis. Brain Behav. Immun. 2020, 88, 901–907. [Google Scholar] [CrossRef]
  43. Marvaldi, M.; Mallet, J.; Dubertret, C.; Moro, M.R.; Guessoum, S.B. Anxiety, depression, trauma-related, and sleep disorders among healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis. Neurosci. Biobehav. Rev. 2021, 126, 252–264. [Google Scholar] [CrossRef]
  44. Al Dhaheri, A.S.; Bataineh, M.A.; Mohamad, M.N.; Ajab, A.; Al Marzouqi, A.; Jarrar, A.H.; Habib-Mourad, C.; Abu Jamous, D.O.; Ali, H.I.; Al Sabbah, H.; et al. Impact of COVID-19 on mental health and quality of life: Is there any effect? A cross-sectional study of the MENA region. PLoS ONE 2021, 16, e0249107. [Google Scholar] [CrossRef]
  45. Cheikh Ismail, L.; Mohamad, M.N.; Bataineh, M.A.; Ajab, A.; Al-Marzouqi, A.M.; Jarrar, A.H.; Abu Jamous, D.O.; Ali, H.I.; Al Sabbah, H.; Hasan, H.; et al. Impact of the coronavirus pandemic (COVID-19) lockdown on mental health and well-being in the United Arab Emirates. Front. Psychiatry 2021, 12, 633230. [Google Scholar] [CrossRef]
  46. Labrague, L.J.; de Los Santos, J.A.A. Fear of COVID-19, psychological distress, work satisfaction and turnover intention among frontline nurses. J. Nurs. Manag. 2021, 29, 395–403. [Google Scholar] [CrossRef]
  47. De Brier, N.; Stroobants, S.; Vandekerckhove, P.; De Buck, E. Factors affecting mental health of health care workers during coronavirus disease outbreaks (SARS, MERS & COVID-19): A rapid systematic review. PLoS ONE 2020, 15, e0244052. [Google Scholar] [CrossRef]
  48. Saddik, B.; Elbarazi, I.; Temsah, M.H.; Saheb Sharif-Askari, F.; Kheder, W.; Hussein, A.; Najim, H.; Bendardaf, R.; Hamid, Q.; Halwani, R. Psychological distress and anxiety levels among health care workers at the height of the COVID-19 pandemic in the United Arab Emirates. Int. J. Public Health 2021, 66, 1604369. [Google Scholar] [CrossRef]
  49. Søvold, L.E.; Naslund, J.A.; Kousoulis, A.A.; Saxena, S.; Qoronfleh, M.W.; Grobler, C.; Münter, L. Prioritizing the Mental Health and Well-Being of Healthcare Workers: An Urgent Global Public Health Priority. Front. Public Health 2021, 9, 679397. [Google Scholar] [CrossRef]
  50. Pollock, A.; Campbell, P.; Cheyne, J.; Cowie, J.; Davis, B.; McCallum, J.; McGill, K.; Elders, A.; Hagen, S.; McClurg, D.; et al. Interventions to support the resilience and mental health of frontline health and social care professionals during and after a disease outbreak, epidemic or pandemic: A mixed methods systematic review. Cochrane Database Syst. Rev. 2020, 11, CD013779. [Google Scholar] [CrossRef]
  51. Shechter, A.; Diaz, F.; Moise, N.; Anstey, D.E.; Ye, S.; Agarwal, S.; Birk, J.L.; Brodie, D.; Cannone, D.E.; Chang, B.; et al. Psychological distress, coping behaviors, and preferences for support among New York healthcare workers during the COVID-19 pandemic. Gen. Hosp. Psychiatry 2020, 66, 1–8. [Google Scholar] [CrossRef]
  52. Rossi, R.; Socci, V.; Talevi, D.; Mensi, S.; Niolu, C.; Pacitti, F.; Di Marco, A.; Rossi, A.; Siracusano, A.; Di Lorenzo, G. COVID-19 Pandemic and Lockdown Measures Impact on Mental Health among the General Population in Italy. Front. Psychiatry 2020, 11, 790. [Google Scholar] [CrossRef]
  53. Salari, N.; Khazaie, H.; Hosseinian-Far, A.; Khaledi-Paveh, B.; Kazeminia, M.; Mohammadi, M.; Shohaimi, S.; Daneshkhah, A.; Eskandari, S. The prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients: A systematic review and meta-regression. Hum. Resour. Health 2020, 18, 100. [Google Scholar] [CrossRef]
  54. Fitzpatrick, K.M.; Harris, C.; Drawve, G. Fear of COVID-19 and the mental health consequences in America. Psychol. Trauma Theory Res. Pract. Policy 2020, 12, S17–S21. [Google Scholar] [CrossRef]
  55. Lu, W.; Wang, H.; Lin, Y.; Li, L. Psychological status of medical workforce during the COVID-19 pandemic: A cross-sectional study. Psychiatry Res. 2020, 288, 112936. [Google Scholar] [CrossRef] [PubMed]
  56. Liu, Y.; Zhang, Q.; Jiang, F.; Zhong, H.; Huang, L.; Zhang, Y.; Chen, H. Association between sleep disturbance and mental health of healthcare workers: A systematic review and meta-analysis. Front. Psychiatry 2022, 13, 919176. [Google Scholar] [CrossRef]
  57. Lu, M.Y.; Ahorsu, D.K.; Kukreti, S.; Strong, C.; Lin, Y.H.; Kuo, Y.J.; Chen, Y.P.; Lin, C.Y.; Chen, P.L.; Ko, N.Y.; et al. The Prevalence of Post-traumatic Stress Disorder Symptoms, Sleep Problems, and Psychological Distress Among COVID-19 Frontline Healthcare Workers in Taiwan. Front. Psychiatry 2021, 12, 705657. [Google Scholar] [CrossRef] [PubMed]
  58. Alimoradi, Z.; Broström, A.; Tsang HW, H.; Griffiths, M.D.; Haghayegh, S.; Ohayon, M.M.; Lin, C.Y.; Pakpour, A.H. Sleep problems during COVID-19 pandemic and its’ association to psychological distress: A systematic review and meta-analysis. eClinicalMedicine 2021, 36, 100916. [Google Scholar] [CrossRef]
  59. Woon, L.S.; Mansor, N.S.; Mohamad, M.A.; Teoh, S.H.; Leong Bin Abdullah, M.F.I. Quality of Life and Its Predictive Factors among Healthcare Workers after the End of a Movement Lockdown: The Salient Roles of COVID-19 Stressors, Psychological Experience, and Social Support. Front. Psychol. 2021, 12, 652326. [Google Scholar] [CrossRef]
  60. Sharma, S.K.; Mudgal, S.K.; Thakur, K.; Parihar, A.; Chundawat, D.S.; Joshi, J. Anxiety, depression and quality of life (QOL) related to COVID-19 among frontline health care professionals: A multicentric cross-sectional survey. J. Fam. Med. Prim. Care 2021, 10, 1383–1389. [Google Scholar] [CrossRef] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Journal Statistics
Multiple requests from the same IP address are counted as one view.
Download PDF
Leisure Screen Time and Food Consumption among Brazilian Adults
Previous
Betrayed, Beaten, Banished: The Stigma of Being a Rural Tongqi in China
Next