key: cord-0728273-p32hnzg5 authors: Zhan, Yuxin; Liu, Yunfang; Liu, Huan; Li, Mei; Shen, Yue; Gui, Lingli; Zhang, Jun; Luo, Zhihua; Tao, Xiubin; Yu, Jiaohua title: Factors associated with insomnia among Chinese frontline nurses Fighting against COVID‐19 in Wuhan: A cross‐sectional survey date: 2020-07-13 journal: J Nurs Manag DOI: 10.1111/jonm.13094 sha: 359a26da491f4cc5d39de1e38fdbe9d51e4b66fe doc_id: 728273 cord_uid: p32hnzg5 AIM: To investigate the prevalence of insomnia among frontline nurses fighting against COVID‐19 in Wuhan, China and analyze its influencing factors. BACKGROUND: Insomnia is an important factor that can affect the health and work quality of nurses. However, There is a lack of big‐sample studies exploring factors that affect the insomnia of nurses fighting against COVID‐19. METHOD: This cross‐sectional study using the Ascension Insomnia Scale, Fatigue Scale‐14, and Perceived Stress Scale took place in March 2020. Participants were 1,794 frontline nurses from four tertiary‐level general hospitals. RESULTS: The prevalence of insomnia among participants was 52.8%. Insomnia was predicted by gender, working experience, chronic diseases, midday nap duration, direct participation in rescue of patients with COVID‐19, frequency of night shifts, professional psychological assistance during the pandemic, negative experiences (such as family, friends, or colleagues being seriously ill or dying due to COVID‐19), the degree of fear of COVID‐19, fatigue, and perceived stress. CONCLUSION: The level of insomnia among participants was higher than the normal level. Interventions based on influencing factors should be implemented to ensure nurses’ sleep quality. IMPLICATIONS FOR NURSING MANAGEMENT: An in‐depth understanding of the influencing factors of insomnia among frontline nurses can help nurse managers develop solutions to improve frontline nurses’ sleep quality, which will enhance the physical and mental conditions of nurses and promote the quality of care. previous studies have shown that insomnia would increase the turnover intention of nurses (Søbstad et al., 2020) . Therefore, it is extremely important to reduce the incidence of insomnia among nurses during the pandemic to promote personal development, relieve physical and mental disorders, ensure the quality of nursing, and stabilize the nursing team. Recently, nurses' insomnia has been increasingly studied, but the sample size of existing studies is small and the representativeness is limited. For example, Zdanowicz et al. (2020) selected 200 nurses from two hospitals to investigate the current situation of insomnia in Polish nurses, and Wu et al. (2020) selected 106 nurses to investigate the sleep quality and its influencing factors of frontline nurses fighting against COVID-19. In addition, most of the existing studies only report the current status, and a comprehensive analysis of the influencing factors of insomnia in nurses is still rare, which makes it difficult to make targeted interventions. However, researches on the influencing factors of insomnia in any group show that older adults, women (especially women before and after menopause), and those with a history of insomnia, a family history of insomnia, the tendency to be awakened easily, psychological diseases (such as depression, anxiety, post-traumatic stress disorder), chronic diseases (lung diseases, hypertension, diabetes and so on), nervous system diseases (such as Parkinson's), drugs, other sleep disorders (such as apnea syndrome) and central nervous system stimulants have an increased risk of insomnia (Drake et al., 2014; Drake et al., 2017; Jansen et al., 2019; Stein et al., 2018) . In addition, there is a correlation between insomnia and higher levels of job stress, effort-reward imbalance, high demand, heavy workload, and low social support (Yang et al., 2018) . Hence, insomnia is affected by a variety of factors, but the factors that affect insomnia of frontline nurses fighting against are currently unclear. The aim of this study was to investigate the prevalence of insomnia among Chinese frontline nurses fighting against COVID-19 in Wuhan, and to analyze its influencing factors. This article is protected by copyright. All rights reserved The design of the study was cross-sectional and descriptive. It was conducted in four public tertiary hospitals from March 3-10, 2020 in Wuhan, China. The convenience sampling method was used to obtain samples. The sample size should be 5 to 10 times the number of scale entries (DeVellis, 1991) . Furthermore, considering a sample dispersion rate of 20%, it was expected that at least 432 participants would be required. The inclusion criteria were as follows: (a) participant had a nurse's qualification certificate; (b) participant was based in Wuhan or came to Wuhan to provide medical assistance; (c) participant volunteered to take part in this study. The exclusion criteria were as follows: (a) internships in hospitals; (b) nurses who did not work continuously from January 1, 2020 to the beginning of this study due to maternity or sick leave. After accounting for inclusion and exclusion criteria, a total of 1,886 online questionnaires were distributed, including 1,794 valid questionnaires. The effective response rate was 95.12%. The effective respondents of the four hospitals participanting in the study were 631, 491, 427, and 245, and the effective response rates were 95.75%, 95.16%, 94.89%, and 93.87%, respectively. The demographic information consisted of gender, age, working experience, professional title, highest educational level, the presence or absence of chronic diseases, midday nap duration, and frequency of exercise. The working status aspects consisted of the frequency of night shifts, whether the participant directly participated in the rescue of patients with COVID-19, whether the participant received the relevant professional occupational protection training, whether the participant received professional psychological assistance, whether occupational exposure had occurred, whether the participant had experienced negative events (such as family, This article is protected by copyright. All rights reserved friends, or colleagues being seriously ill or dying due to , and the degree of fear of COVID-19. The AIS was developed by the Department of Sleep Psychiatry, University of Athens Medical School, Greece, in 2000 (Soldatos et al., 2000) . It is a 8-item Likert-type scale, and each item is divided into four grades of 0-3 from none to severe, with a total score ranging from 0 to 32 points. Insomnia occurs when the score is 6 or more. It is easy to use and it has accurate measurement results. A Greek study (Kousloglou et al., 2014) showed that the scale's Cronbach's α was 0.91, and the Cronbach's α was 0.895 in our study. The FS-14 was developed by the Department of Psychological Medicine of King's College Hospital in the United Kingdom (Taylor-East et al., 2013) . The scale consists of 14 items, including physical fatigue (items 1 to 8) and mental fatigue (items 9 to 14). The total scores range from 0 to 14 points. Fatigue occurs when the score is 7 or more (Chalder et al., 1993) . The Cronbach's α of the two dimensions of the scale are 0.7449 and 0.7953, and the total Cronbach's α is 0.7725 (Morriss et al., 1998) . The Cronbach's α was 0.85 in our study. The Perceived Stress Scale is a widely recognized and internationally applied scale. This study used the Chinese version, which was revised by Yang et al. (2003) . It consists of 14 items, using a Likert 5-point scoring method of 0 to 4 points. The higher the overall score, the more stress the subject experiences. When the total score is higher than 25, it can be determined that the individual is in a risk of stress state. The Cronbach's α for the CPSS is 0.78, and the Cronbach's α was 0.814 in our study. The study was approved by the Medical Ethics Committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (NO.2020-0189). Before distributing the questionnaire, we contacted one of the directors of the nursing department of each hospital, and explained the purpose and procedures of this study in order to obtain their permission. Online questionnaires were distributed to frontline nurses in various departments of the four hospitals via WeChat (It is a cross-platform communication tool, a mobile application used by more than one billion people, which can send links, voices, pictures, videos, and text through the mobile phone network.), and respondents filled out the questionnaire and submitted it via their mobile phone or computer. In order to ensure the accuracy of the data, all items were set as required questions to ensure the completeness of the questionnaires, and the questionnaire filling method was set to limit each device to only submit once to avoid participants submitting their answers multiple times. All participants could withdraw from the study at any time without issue. Participants' privacy was strictly protected in this voluntary and confidential investigation. Statistical analyses were performed by SPSS 23.0 software. Count data was described by frequency and percentage, and measurement data is described by mean and standard deviation. Mann Whitney test and Kruskal Wallis test were used to analyze the insomnia status of nurses with different general data, working conditions, fatigue, and perceived pressure on insomnia among frontline nurses. Then, we took the insomnia score as the dependent variable and the single factor analysis as the independent variables, constructed a multiple linear regression equation, and analyzed the influencing factors of insomnia. All tests were conducted with α=0.05. Participant characteristics are presented in Table 1 . The majority of participants were women (97.0%), and 50.9% of participants were in the 26 to 35 year age group. In terms of working experience, 40% of the participants had no more than 5 years of working experience. This article is protected by copyright. All rights reserved 45.2% of the participants gained the professional title of nurse practitioner, and most participants had a bachelor's degree (78.3%). During work, 41.4% of the participants had a midday nap duration of 30 to 60 minutes per day. Most participants did not exercise more than once a week (79.8%). Additionally, most nurses did not have chronic diseases (91.2%). Regarding the frequency of night shifts, 32.5% and 30.3% of the participants have 0 and 2 night shifts per week, respectively. More than 70% of the participants did not directly participate in the rescue of patients with COVID-19. Furthermore, 93.5% of the participants received professional protection training, and more than 90% of the participants had no occupational exposure. Approximately 90% of participants did not receive professional psychological assistance. Only 78.8% participants did not have any experience of negative events. For the degree of fear with COVID-19, 39.2% was moderate and 28.7% was mild. As for fatigue and perceived stress, 66.1% of the nursing staff were not in a state of fatigue, and 56% of the nursing staff had no perceived stress. As the Table 2 shows, the average AIS score (Mean ± SD = 6.30 ± 4.61) of frontline nurses was higher than normal level, and 948 nurses (52.8%) had insomnia problems. The average FS-14 score (Mean ± SD = 5.20 ± 3.75) and average CPSS score (Mean ± SD = 22.35 ± 7.63) were within their normal range, and the mean sub-dimension scores of FS-14 for physical and mental fatigue were found as 3.39 (SD = 2.67) and 1.81 (SD = 1.67) respectively. There were 609 nurses (33.9%) and 789 nurses (44.0%) in fatigue and stress state respectively. As the Table 3 shows, female nurses had significantly higher mean AIS score than male nurses (z = -3.038, P = 0.002), and there were significant differences in the mean scores of AIS among nurses of different ages ( 2 = 13.306, P = 0.010). Nurses with more working experience had higher mean AIS scores ( 2 = 27.054, P = 0.000), and nurses' mean AIS This article is protected by copyright. All rights reserved scores decreased as midday nap duration time increased ( 2 = 28.253, P = 0.000). The mean AIS score of nurses who exercised no more than once a week was significantly higher than that of nurses who exercised 2 to 3 times and 4 times or more per week ( 2 = 29.622, P = 0.000). Nurses with chronic diseases had a higher mean AIS score than those without chronic diseases (z = -6.317, P = 0.000). Table 4 shows that the mean AIS scores of nurses who directly participated in the rescue of patients with COVID-19, or had occupational exposure during contagion rescue work, or experienced negative events during the rescue period were significantly higher (z = -7.322, P = 0.000; z = -3.935, P = 0.000; z = -7.897, P = 0.000). In addition, the mean AIS scores of nurses who had received professional protection training or professional psychological assistance were significantly lower (z = -2.752, P = 0.006; z = -4.424, P = 0.000). The more night shifts nurses had, the higher the mean AIS scores were ( 2 = 35.838, P = 0.000). Moreover, the more severe the nurse's fear of COVID-19, the higher the mean AIS scores were ( 2 = 217.159, P = 0.000). The result in Table 5 shows that FS-14 scores and CPSS scores were significantly related to the AIS scores of the frontline nurses (z = -22.856, P = 0.000; z = 16.194, P = 0.000). The variables that were found to have an effect on the insomnia score of frontline nurses were used as independent variables, and the insomnia scores were used as the dependent variables to construct a multiple linear regression equation. Table 6 shows the results of the multiple linear regression model, illustrating that frontline nurses' insomnia scores could be This article is protected by copyright. All rights reserved assistance (β = 0.063, P = 0.001), experience of negative events (β = -0.061, P = 0.002), the degree of fear of COVID-19 (β = 0.179, P = 0.000), fatigue (β = 0.379, P = 0.000), and perceived stress (β = 0.16, P = 0.000). The aim of this study was to investigate the prevalence of insomnia among Chinese frontline nurses fighting against COVID-19 in Wuhan and analyze its influencing factors. In this study, the mean score of AIS was 6.30 (SD = 4.61), which exceeded the critical value. The incidence of insomnia was 52.8%, which was consistent with the result of 51.7% reported by Qi et al. (2020) , but higher than the result 43.1% reported during a non-epidemic period in China (Lai et al., 2018) . The incidence rate of sleep disorders among nurses in Wuhan has been higher during the COVID-19 crisis. Due to its characteristics of high human to human transmission, being highly contagious, having a long incubation period, and sometimes resulting in fatality, COVID-19 has caused social panic to some extent (World Health Organization, 2020). At the beginning of the outbreak, nurses were faced with an unfamiliar viruses, high-intensity work, significant responsibilities, insufficient medical resources, and infected colleagues, and the experienced tremendous psychological pressure. After the lockdown of the city, living materials were insufficient, separating from close relatives, while physical and mental needs could not be met, resulting in a series of traumatic stress, leading to sleep disorders and psychological disorders of medical staff (Xiao et al., As revealed in this study, females' insomnia level were higher than males', which was This article is protected by copyright. All rights reserved fluctuation of estrogen might affect the emotional regulation area in the brain, which made females more likely to sense pressure and have symptoms of depression and anxiety, which was also an important factor for insomnia. In addition, there were differences in the family responsibilities of women and men. Due to the sudden change in women's social roles, the conflict between work and family was exacerbated, and it was easy for female to feel guilty about the family, so the level of psychological distress was higher than that of men (Chandola et al., 2004) . The results also revealed that nurses with more working experience had higher mean AIS scores. The main reason was considered to be that nurses with more working experience had a higher ability to balance and deal with emergencies, but at the same time, their own standards and expectations for themselves were higher than nurses with less experience. They played an important role in the pandemic rescue work, constantly faced and adopted to different pressure challenges, and the higher levels of job stress made them more prone to insomnia (Yang et al., 2018) . The current study is the first to report the effect of working experience on insomnia. More attention should be paid to the mechanism of working experience affecting insomnia. Furthermore, the results of this study showed that nurses' mean AIS scores decreased as midday nap duration increased. Liao et al. (2018) also concluded in a study on athletes that a 60 minute nap was conducive to shortening the sleep latency at night and prolonging the length of deep sleep, but the study only compared the 60 minute nap with 120 minute nap. At present, there are few studies on the effects of midday nap duration on night sleep. However, previous studies have shown that 20-30 minutes of nap time can relieve fatigue and drowsiness, and improve reaction and cognitive ability, and reduce the incidence of obesity. If the nap time exceeds 30 minutes, the person would be prone to sleep inertia, and their alertness, calculation ability, reaction speed and short-term memory will be weakened in several minutes or even a few hours after awakening, and sometimes resulting in upset and depression (Trotti, 2017; Hilditch et al., 2016; Lovato & Lack, 2010) . Therefore, it is suggested that the time of midday nap duration on working days should be 20-30 minutes. This article is protected by copyright. All rights reserved With regard to chronic diseases, the findings found that nurses with chronic diseases were more likely to suffer from insomnia than those without chronic diseases, which was consistent with the results of Taylor et al (2007) . The chronic diseases related to insomnia include lung disease, diabetes, hypertension, and chronic pain (Taylor et al., 2007; Vgontzas et al., 2009; Tang et al., 2015) . In addition, insomnia can aggravate the condition of chronic diseases, which can creat a vicious circle. Therefore, nursing managers should pay more attention to nurses with chronic diseases. The results also revealed that the more night shifts nurses had, the higher the mean AIS scores were. Irregular shift work causes nurses' biological clocks to be disturbed, causing the body and mind to be in a state of stress, making them prone to shift work disorder, which is mainly manifested as insomnia and drowsiness (Ai & Guan, 2015) . It had also been pointed out that shift nurses tend to show low sleep quality, which has been shown to activate the hypothalamic pituitary adrenal axis and was related to sleep arousal (Tsai et al., 2019) . Previous research has shown that more than 5 night shifts per month and long working hours will seriously affect sleep quality. In reality, it was necessary to control night shift frequency and working hours and avoid overtime as much as possible (Li, 2019). In addition, individuals can try to go to bed at the same time every night when they are not on night shift to solve the sleep problem caused by night shifts (UpToDate, 2019). In our research results, nurses who directly participated in the rescue of patients with COVID-19, or experienced negative events, or had a high degree of fear of COVID-19 accompanied by higher insomnia scores. Events including directly participating in the rescue of patients with COVID-19 and experiencing negative events increased the emotional and psychological pressure of nurses' tension, sadness and fear. Perogamvros et al. (2020) reported that a real or individual perceived stress source can induce fear and stress responses that cause acute insomnia symptoms. Physiological research has also found that in an environment with fear and stress, the awakening and high-frequency EEG power during non-rapid eye movement sleep increased, leading to the occurrence of short-term insomnia (Cano et al., 2008) . This article is protected by copyright. All rights reserved As revealed in our study, the mean score of nurses' who had received professional psychological assistance was lower, indicating that psychological support was of great importance to improving nurses' sleep. Chronic insomnia often coexists with mental illness. About half of patients with chronic insomnia suffer from mental illness, and most patients with mental illness have insomnia problems (Ohayon, 2002; Alvaro et al., 2013) . It is suggested that online psychological doctors should provide professional psychological support for nursing staff during the fight against COVID-19 at any time, thus reducing their mental pressure, preventing mental disorders and insomnia, and avoiding the development of chronic insomnia from short-term insomnia. The results of this study reported that the mean score of FS-14 was within normal levels, and fatigue rate was lower than the fatigue rate of Chinese nurses before the pandemic ( shifts, reasonable human resource allocation, clear core nursing care system, encouraging nurses to keep in touch with family and friends, providing additional salary subsidies, and publicizing the deeds of nurses to stimulate their sense of accomplishment. In the multiple linear regression model constructed in this study, fatigue was the most influential factor on nurses' insomnia. Skarpsno et al. (2019) found that work-related mental fatigue was an important risk factor for insomnia symptoms. Compared with patients without severe fatigue, insomnia patients with severe fatigue showed higher symptoms of insomnia, daytime sleepiness and longer habitual sleep duration (Kim, 2019). Hence, it is recommended that managers can use the above nursing management measures to try to minimize the fatigue of nurses. In regard to perceived stress, the result showed that the nurses' CPSS score in present This article is protected by copyright. All rights reserved study was slightly lower than normal level. It found that the greater the perceived stress, the higher the insomnia score. The interaction between stressors and sleep quality was complex, including direct and indirect effects, influenced by personality tendency, cognitive regulation, emotional regulation, and coping style (Yan et al., 2010) . Therefore, we suggest that nurses could be given a simple personality trait questionnaire evaluation, and experts could form assessment reports and recommendations based on the questionnaire, which would promote nurses to understand their own personality characteristics, control emotions in a targeted manner, and solve problems in a positive way. Wang and Zhou (2017) confirmed that mental decompression can also reduce the level of individual perceived stress, so as to improve sleep. The research has several limitations. First, its cross-sectional nature constrains the ability to interpret the causal relationships between the different variables in this study. Second, the self-reporting questionnaires used in the study may have introduced bias due to individual personal understanding and judgment of the survey items. Third, the convenience sampling method may lead to the limitation of the representativeness of the research sample and the generalization of the research conclusion. Future research requires more improved research design, including layered design, and comparative analysis of samples from different regions and different countries. Other studies using qualitative research should also be done to reveal more aspects of insomnia of frontline nurses fighting against COVID-19. Overall, there was a generally higher level of nurses' insomnia among Chinese frontline nurses who fought against COVID-19 in Wuhan. Fatigue, perceived stress, the degree of fear of COVID-19, working experience, and direct participation in rescue of patients with COVID-19 were the mainly predictive factors of insomnia in this study. Interventions should Accepted Article Sleep in Women Across the Life Span Failure of fear extinction in insomnia: An evolutionary perspective Insomnia as a Precipitating Factor in New Onset Mental Illness: a Systematic Review of Recent Findings The Evaluation of Sleep Disturbances for Chinese Frontline Medical Workers under the Outbreak of COVID-19 International classification of sleep disorders-third edition: highlights and modifications Work-Related Mental Fatigue, Physical Activity and Risk of Insomnia Symptoms: Longitudinal Data from the Norwegian HUNT Study Athens Insomnia Scale: validation of an instrument based on ICD-10 criteria Genome-wide analysis of insomnia disorder Predictors of turnover intention among Norwegian nurses: A cohort study. 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