Factors associated with Insomnia among Frontline nurses during COVID-19: A Cross-Sectional Survey

DOI: https://doi.org/10.21203/rs.3.rs-961040/v1


Background: Research predominantly suggests that nurses are at high risk of developing psychopathology. The empirical data show that the occurrence rate of problem-related sleep quality among clinical nurses is high. Therefore, this study was conducted to address the lack of information on the relationship between COVID-19 pandemic and Insomnia.

Methods: A convenience sample of nurses (n=680) completed an online survey that included the insomnia severity index, the COVID-19-related psychological distress scale, the general health questionnaire, neuroticism, dysfunctional beliefs and attitudes about sleep; and difficulties with emotional difficulties.

Results: Results showed that 35.8 % (n=253) of nurses were classified as individuals with moderate to severe clinical Insomnia. The results showed that the psychological distress generated by the COVID-19 predicted the insomnia (β=.47, SE= 0.02, P<.001, t=13.27, 95% CI 0.31-0.46). Also, this association mediated by the psychopathology vulnerabilities, emotion dysregulation, dysfunctional beliefs about sleep, and neuroticism. Moreover, female nurses exhibited higher levels of insomnia (Cohen’s d=.37), dysfunctional beliefs about sleep (Cohen’s d=.21), and neuroticism (Cohen’s d=.29), than males.

Conclusion: The findings make a significant contribution to the expanding literature on emotion dysregulation, beliefs, and psychopathology vulnerability on Insomnia. The findings suggest the potential influence of Cognitive behavioural therapy interventions for insomnia (CBT-I) and transdiagnostic integrated therapies that could be incorporated into therapeutic of programs designed to develop as a way of inhibiting or preventing insomnia among clinical nurses.


The outbreak coronavirus disease 2019 (COVID-19) is more than a medical disaster. Like biological and natural disasters, COVID-19 can increase the risk of psychopathology vulnerabilities and post-traumatic stress disorder [1], particularly among vulnerable groups. Healthcare staff are a professional group that is exposed to multiple traumatic conditions. Compared with the general population, Healthcare staff are remarkably (three times) more likely to be infected by a coronavirus [2]. Also, research predominantly suggests that HCWs are at high risk of developing psychopathology as first-line warriors against the pandemic [3–5]. The World Health Organization (WHO) early study authorities on the possibility of an increase in mental health problems among nurse staff. Medical personnel in public health situations suffer not only physical and psychological stress, but also the threat of prolonged exposure to infectious disease sources[6]. Following the COVID-19 epidemic, the demand for medical personnel surged considerably. The lack of healthcare workers has led to a dramatic increase in work overload for healthcare workers fighting COVID-19, as well as a great deal of anxieties and psychological distress among healthcare workers [7]. Exposure to a stressful situation, including actual or threatened death, can lead to sleep disorders. The qualitative and the cross-sectional data indicate that the occurrence rate of sleep disturbance among nurses is high [8, 9]. 

Sleep disorders

Sleep disorders are common and associated with considerable morbidity and functional impairment [10]. Insomnia is a prevalent sleep disturbance that refer to sleep symptoms such as difficulty initiating or staying asleep and irregular wake-sleep patterns, early morning awakening with non-resumption sleep [11]. Insomnia is a significant public health problem around the globe, with an estimated prevalence of 10%–50% in adults [12]. Insomnia is associated with remarkable medical, psychiatric[9], work place[13] and financial costs. In addition, Insomnia is associated with poor quality of life [14], significant burnout [15], cognition impairment, and psychosocial problems [16]. Insomnia is recognized as a causal factor of mental health problems and the core symptoms in psychiatric disorders, particularly depression and anxiety disorders. Clinical staff, especially shift workers, tend to be among the most affected by sleep disorders [17]. Regarding nursing, sleep disturbance negatively affects daily cognitive performance [18] and work productivity [19]. For instance, Insomnia may increase work-related accidents [20] and negatively affect patients' work productivity [21] and treatment processes [22].  

Insomnia risk factors

According to neurobiological and psychological views, individual [23], behavioural [24], cognitive [25], and emotional [26] variables have been implicated in the onset to maintenance of Insomnia. In addition to the theoretical frameworks conceptualized to address the insomnia pathophysiology (e.g., neurobiological, behavioral), the Insomnia etiology is significantly taught from a diathesis-stress perspective. The 3P (predisposing, precipitating, and perpetuating factors) model, proposed by Spielman et al,  [27], describe that how the interaction of different factors contribute to the initiation and persistence of acute insomnia. 

Stressful experience or situation is the most common precipitant factor of insomnia individual with problem related sleep recall the traumatic situation related with onset of insomnia.  It is posited that the joint effects of stressful life events[28, 29] and cognitive-emotional factors are central to the etiology of insomnia [30, 31]. Within The 3P model, suggests existing predisposing factors make individuals more vulnerable to insomnia than others. Individuals with predisposing traits (e.g., neuroticism) when faced with common, unexpected or traumatic precipitating events, experience stress related insomnia symptoms. The predisposing factors are interacted by precipitating factors (e.g., traumatic events), resulting in acute insomnia. The chronic course of insomnia is developed to acute insomnia by perpetuating cognitions (e.g., dysfunctional belief about the sleep) and sleep disrupting behaviours (e.g., emotion dysregulation) [32], after the severity of the precipitating stressor has lessened. 

Purpose of the current study 

The WHO has underscored the excessive burden on nurses, and called for immediate action to prevent a severe impact on the physical and mental health of nurses [33]. There is also a lack of empirical evidence on the preventive interventions during the current pandemic. Compared to individuals without Insomnia, the negative impacts of the pandemic are more severe in people with Insomnia. In addition to high prevalence, insomnia increases the risk of medical and psychological illnesses and   negatively impacts on cognitive and job performance [34]. While research predominantly concentrates on sociodemographic factors and prevalence of Insomnia. research on the relationship between factors associated with insomnia is extremely scarce.[35].  Identifying factors and mechanisms contributed in the development and persistence of Insomnia should be a priority in order to identify better strategies that improve prevention and treat Insomnia and its comorbid conditions. [35].  

Therefore, this study was conducted to address the lack of information on the relationship between COVID-19 pandemic and Insomnia. It was expected that psychological distress related COVID-19 directly predicted Insomnia symptoms. Also, it was hypothesized that dysfunctional beliefs about sleep, neuroticism, difficulties with emotion regulation, and psychopathology vulnerability would mediate association COVID-19 related psychological distress and Insomnia symptoms. More specifically, it was expected that psychological distress related COVID-19 indirectly influence insomnia through dysfunctional beliefs about sleep, neuroticism, difficulties with emotion regulation, and psychopathology vulnerability. 



The study sample comprised (N=680) nurses (55.7%, n=323 females) aged 23-45, enrolled via online survey. The participants' mean age was 32.85years (SD=7.09). Eligibility criteria included being (i) aged 18 years or above, (ii) able to read and complete an online consent form and survey, and (iii) not having COVID-19 or chronic disease (e.g., diabetes). Table 1 presents the overview of the sample’s demographic characteristics and group differences. The study applied a survey method for data collection, and the subjects obtained an informed consent before enrolment. The study was found to be in accordance to the ethical principles and the national norms per Helsinki Declaration, evaluated by Research Ethics Committees of Lorestan University of Medical Sciences

Table 1. Demographic characteristics of the sample (N=680)






Categorical variables

Gender, n (%)





257 (44.3)

χ² = 7.510a



323 (55.7)



ISI, n (%)




ISI <8

206 (30.3)



8≤ ISI <15

231 (33.9)

χ² =16


15≤ ISI <22

159 (23.4)



22≤ ISI 

84 (12.4)



Continuous variables M (SD)

Age (years)



t(1, 678)= -1.73





t(1, 678)= 4.50


Emotion Dysregulation



t(1, 678)= -2.35


Dysfunctional Belief



t(1, 678)= 1.65





t(1, 678)= 3.58


Psychopathology Vulnerability



t(1, 678)= 3.12


Fear anxiety COVID-19



t(1, 678)= 2.75


Note: n=frequency; M=mean; SD=standard deviation

t=independent t-test to compare  gender status


Insomnia symptoms: The Insomnia Severity Index (ISI) [36], a self-report brief  screening tool, was employed to assess the insomnia severity over the last month. The subjects rated a seven-item on a five-point Likert scale from Zero= no problem to; four = severe pain, with a total score ranging from 0 to 28. In the current study, a total score of ISI lower than 8 and a total score 8≤ ISI <15 were considered as a no clinically significant insomnia and sub-threshold of Insomnia, respectively. The ISI total score 15 to 21 and 22 to 28 were considered as moderate clinical Insomnia and severe clinical Insomnia, respectively. A high internal consistency coefficient was obtained for the current sample (Cronbach α = 0.88). 

Dysfunctional beliefs: Dysfunctional beliefs and attitudes about sleep (DBAS) [37] was  employed to measure unrealistic expectations and dysfunctional beliefs about sleep. Nurses rated each item on eleven Likert scales from Zero (strongly disagree) to ten (strongly agree). A higher score indicates a higher level of dysfunctional beliefs about sleep. This measure had high internal consistency in our sample (α = .83). 

Personality trait: The neuroticism subscale of the Big Five Inventory (BFI-44) [38] was used to access neuroticism. Nurses rated eight items on a five-point scale of 1 (disagree strongly) to 5 (agree strongly), with a total score of 8-40. A higher score was interpreted as a greater level of neuroticism. The scale reliability was very good in the present study (α=.80).

Psychopathology vulnerability: The General Health Questionnaire (GHQ-28) [39] was used to measure the severity of psychopathology in four domains (i.e., depression, anxiety, social dysfunction, and somatic symptoms) during the past few weeks in non-psychiatric settings. Nurses rated on a four-point scale ranging (0, 1, 2, 3). Higher scores indicate greater levels of psychopathology vulnerability. The scale reliability was very good in the present study (α=.83). 

Emotion dysregulation: Difficulties in Emotion Regulation Scale (DERS) [40]  was employed to measure emotion dysregulation. The nurses rated 18 items on a five-point scale from 1 (almost never) to 5 (almost always), with total scores ranging from 18-90. Higher scores were considered as the   greater levels of the difficulty in emotion regulation. The scale demonstrated perfect internal consistency in the present study (α=0.85). 

Psychological Distress: The COVID-19-Related Psychological Distress Scale (CORPDS) [41] is a specific self-report scale that assesses psychological distress in the context of COVID-19. Nurses scored the fourteen items on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Higher scores demonstrate severe significant distress. This instrument had acceptable internal consistency (α=0.87).


Participant Recruitment: Subjects’ recruitment efforts included advertisement, online postings, flyers, and Physician referrals. Study through the online professional health staff forums. Also, the forum members were requested to share the study invitation letter with other colleagues. The survey was administered online via convenience sampling.  Once the participants clicked on the distributed survey link, an informed consent page was opened. The informed consent was agreed upon before proceeding to the survey. Once the nurses who obtained an informed consent, they access the survey. The informed consent included information about the study’s objectives and confidentiality. 

Sample size: A priori power analysis was carried out using G-Power. The calculation  indicated a desired sample size of 647, considering  small effect size for multiple linear regression, power of 0.80, an alpha of .05, and five predictors [42]. 

Data Analysis

The statistical procedures were carried out using SPSS (Ver 25; Chicago, IL) and AMOS (Ver 24; IBM). The values for kurtosis and skewness (Values within <|1|) were examined to test the assumption of normal distribution—the variance inflation factor (VIF values < 5) was considered as the absence of the multicollinearity[43]. Pearson correlation coefficients (r) were evaluated to investigate the relationship between interested variables.

Multiple mediation analysis was conducted to investigate that the four mediators would mediate the association between psychological distress related COVID-19 (independent variable) with Insomnia symptoms (outcome variable), using structural equation modeling (SEM).   The goodness of fit of the model was evaluated according guideline proposed by Hu and Bentler [44]. An indirect effect was significant; if the calculated 95% bias-corrected confidence intervals (CI) were not included Zero. The 95% CI was generated by the bias-corrected method for the point estimate with 5,000 bootstrap samples[45].  The guideline proposed by Cohen[46] was considered to evaluate the effect size values (Cohen 2≥ 0.15: medium effect size;    Cohen 2≥ 0.35 large effect sizes).


Descriptive Statistics

The data are reported as means (M) and standard deviations (SD) for continuous variables and as frequency (n) or percentages for categorical variables in Table 1. Of the 720 distributed web-based surveys, a total of 680 useable surveys were included in the final analysis. The generated VIF values and the calculated kurtosis and skewness showed no violation of the multicollinearity issue and normality (Table 2). Compared with males, females obtained higher neuroticism scores (t [678] =3.58, p<.01, Cohen’s d=.29) insomnia (t [678] =4.50, p<.001, Cohen’s d=.37, Fear anxiety COVID-19(t [678] =2.32, p<.01, Cohen’s d=.19), Psychopathology Vulnerability (t [678] =2.42, p<.01, Cohen’s d=.19). Males had significant higher scores Emotion Dysregulation the correlation analyses reported in Table 2.  Results also showed that 35.8 % (n=253) of nurses obtained an ISI score ≥ 15, which were classified as moderate severe clinical Insomnia. Female nurses reported significantly higher scores than males concerning emotion dysregulation (Cohen’s d=.29) and Insomnia. The experience was negatively correlated with insomnia (r= -.27; p<.001), dysfunctional belief (r= -.11; p=.002), and neuroticism (r= -.19; p<.001),

Table 2. Correlation Matrix and item analysis




















2-Emotion Dysregulation









3-Dysfunctional Belief


















5-Psychopathology Vulnerability



















Note: VIF=variance inflation factor. CORPD= COVID-19-Related Psychological distress

SK: skewness, Kur: Kurtosis; **Correlation significant at the P<.001 level (two-tailed).

Multiple mediation analysis

The predictive model is illustrated in Figure 1. The analysis produced excellent fit for model (χ2/df=1.42, CFI=.996, TLI: .995SRMR=.02, RMSEA=0.03, 90% CI 0.02- 0.05, R-squared= 0.73). While the total standardized effect of COVID-19 related psychological distress on Insomnia was statistically significant (β=.47, SE= 0.03, P<.001, t=13.77, 95% CI 0.39-0.54), with medium to large effect size (Cohen f = 0.29, P<.001). The analysis represented that COVID-19 related psychological distress directly predicted Insomnia, with small effect size (Cohen f = 0.06, P<.001). Also, that COVID-19 related psychological distress indirectly predicted Insomnia through  dysfunctional beliefs about sleep (β=.03, SE= 0.01, P=.001, t=3.29, 95% CI 0.01-0.05), neuroticism (β=.09, SE= 0.02, P<.001, t=4.39, 95% CI 0.05-0.13), difficulties with emotion regulation (β=.04, SE= 0.01, P<.001, t=4.10, 95% CI 0.02-0.06), and psychopathology vulnerability (β=.16, SE= 0.02, P<.001, t=9.12, 95% CI 0.13-0.19). Overall indirect effect of all mediators also was statistically significant (β=.32, SE= 0.03, P<.001, t=10.69, 95% CI 0.26-0.38). The associations between the variables are reported in table 3.

Table 3: the standardized effects and effect sizes of model path       






95%CIs b

Cohen 2

Direct  path


DBAS -> Insomnia








GHQ -> Insomnia








DER -> Insomnia








Neuroticism -> Insomnia
































CORPD-> Insomnia








CORPD-> Neuroticism







Beta: standardized path coefficient , CORPD=  COVID-19-Related Psychological Distress, 

DER= Difficulties in Emotion Regulation, GHQ=  The General Health Questionnaire

DBAS= Dysfunctional beliefs and attitudes about sleep , CIs b:confidence intervals


While nurses are affected by the pandemic, there is currently a lack of information regarding Understanding the pandemic­–related psychopathological development in nurses. It was expected that psychological distress related COVID-19 directly predicted Insomnia symptoms. Also, it was hypothesized that dysfunctional beliefs about sleep, neuroticism, emotion dysregulation, and psychopathology vulnerability would mediate association psychological distress related COVID-19 and Insomnia. Consistent with expectation and previous studies [5], [47]–[50]. COVID-19 psychological distress is associated with greater level of insomnia, with large effect size.  Also, the association is partially mediated by the interested variables, with small effect size, suggesting that traumatic life event is likely a unique factor for insomnia [47]. Research    indicates that individuals without sleep disturbance develop problem related-sleep subsequent to a significant stressful events.

The results empirically revealed that four mediators significantly mediated the association between the COVID-19 psychological distresses with insomnia. COVID-19 psychological distresses predicts higher levels of neuroticism. The neuroticism is salient risk factor for insomnia. The findings provide evidence that neurotic nurses exhibit higher level of Insomnia[51, 52] . The vulnerability or risk model hypothesizes that pre-existing personality traits (e.g., neuroticism) predispose an individual to develop sleep disorders [53]. Study’s findings extend prior findings that neuroticism strongly predicts lower subjective sleep quality[54]. Also, Individuals high in neuroticism exhibit lower sleep quality and frequently report unwanted wakefulness after sleep onset [55, 56]. Vulnerability to psychological disorder is key to understanding differential stress responses to severe life events[57–59]. Depression are also one of the common causes of sleep disorders, with depressive symptoms accounting for more than 40% of insomnia cases[60]. More than one-fifth of health-care workers suffers from anxiety and depression, and over two-fifths suffer from sleeplessness, according to the prevalence rates of insomnia, anxiety, and depression among health-care workers  [61]. 

Regarding the association between difficulties in emotion regulation and insomnia, growing evidence supports that the link is bidirectional [62, 63]. Compared with good sleepers, individual with insomnia significantly utilize the maladaptive emotion regulation strategies such as suppression, avoidance[64]. Neuroimaging investigations also provides to support the existence of the association between emotion regulation and sleep quality. The prefrontal cortex (i.e., principal brain regions responsible for cognitive control emotion regulation) is sensitive to sleep deprivation [65]. Compared  to the healthy sample., an experimental research reveals that the individual with problem- related sleep presented an impaired functional connectivity between prefrontal cortex and amygdala (i.e., brain region responsible for emotional responses) [66]. The prefrontal cortex (i.e., principal brain regions responsible for cognitive control emotion regulation) is sensitive to sleep deprivation [67].   Compared   to the healthy sample., an experimental research reveals that the individual with problem- related sleep presented an impaired functional connectivity between prefrontal cortex and amygdala (i.e., brain region responsible for emotional responses) [68].

Unrealistic and erroneous cognitions significantly predict Insomnia, with moderate effect size. The study’s finding highlights the role of cognitions in higher levels of insomnia Dysfunctional beliefs and attitudes about the nature of sleep can lead to that a course of the chronic form of insomnia is persistent [69]. In line with pervious literature and cognitive models of insomnia [67–69], this perpetuating factor disrupts sleep in two ways [70-73].  It triggers arousal and distress, increasing selective attention and monitor toward sleep-related threat cues, resulting in an overestimation sleep deficit. Second, negatively toned cognitive activity provokes safety behaviors, which develop dysfunctional beliefs about sleep [74]. 

The study’s findings reveal the small associations between age and insomnia (i.e., younger participants had higher Insomnia.). Also, higher experience levels were negatively associated with Insomnia, emotion dysregulation, neuroticism.  Nurses can adjust to the stressful working environment regulate to demanding working environment. There is general agreement that females are more vulnerable to problem-, related sleep more [75]. Similarly with broad range of literature, females also report higher levels of psychopathology vulnerabilities during the pandemic[76, 77]. Compared with males, psychological distress and emotional pain were perceived more by females. 

Practical implication

The findings also hold practical implications in intervention design in primary and secondary intervention. In terms of primary intervention, administration, policymakers, and healthcare providers must plan and implement appropriate programs and interventions to support nurses in overcoming sleep issues. The etiology of Insomnia is multidimensional; the treatment is also a multi-component treatment American Academy of Physicians recommended CBT-I as first-line therapy for Insomnia, which is as multi-component non-pharmacological treatment. There is also extensive research demonstrating the effectiveness of CBT-I in the context of comorbid conditions[78]. In addition, CBT-I covers a broad range of psychological aspects ranging from changing cognitive thoughts to a reduction of psychiatric symptoms[78, 79]. For example, evidence indicates that depression symptoms improve following CBT-I. Regarding the high prevalence of sleep disturbance, high comorbidities with depression, economic and social burden emotional problems across nurses, the application of CBT-I could be beneficial through targeting comorbid conditions reducing the risk of depression[80, 81]. Also, the relationship between sleep disturbances and psychological distress provides empirical evidence that healthcare providers should undertake sleep problems and psychological distress. Subsequently, psychological distress can be diminished when an individual's sleep is improved (and vice versa).  

In terms of secondary intervention, personality traits have been considered stable and inflexible across time (American Psychiatric Association, 2013), but growing evidence suggests that neuroticism may be more malleable than originally believed. In line with previous research [83], COVID-19 distress was associated with greater neuroticism level. Neuroticism is recognized as a key etiology mechanism, which is shared by  psychological  disorders [84, 85]. Nurses  experience high rates of negative emotions related to fear or anxiety generated by COVID-19 [86].  Emotional dysregulation also play a crucial role in the treatment of complex cases, diagnoses with comorbidities and psychological risk factors [87]. These mechanisms can be crucial in initiating, increasing or maintaining emotional disorders and insomnia. In terms of secondary prevention, targeting of the disorders’ risk factors prior to the acute form of the disorder potentially improve prevention and treat Insomnia and its co-existing conditions. 

Understanding the contribution or co-existence of these risk factors has implications for insomnia assessment and treatment.  Given the high prevalence of insomnia  and its comorbidity with mental health problem, disorder-specific protocols could be difficult to justify when the comorbidities are the norm [88] and clinical reality is complex are suspected to be effective in cases of comorbidity [89]. Transdiagnostic and integrated therapies target identified group of underlying core processes and can be potentially served as a promising intervention [90].  Because they tackle multiple problems,  provide a more parsimonious, and arguably more practical approach [91]. The transdiagnostic interventions (e.g., TranS-C) comprise core and optional modules, which provide the treatment sessions to be more personalized to the specific sleep problem [92]. The Unified Protocol, a manualized transdiagnostic treatment for emotional disorders [93] – represents an intervention explicitly developed to address temperamental vulnerabilities, in this case neuroticism, associated with comorbidity conditions. 


The present study suffers from limitations – most notably related to the participants’ enrolment and information collection. The current research was carried out during the COVID-19 pandemic. Therefore, to follow pandemic instruction, data is collected online instead method. This meant that nurses without internet access could not participate. Subsequently, the collected data do not represent such groups’ considerations and influences the study's generalizability. Also, the self-report data were subject to common methods biases. Finally, the study was cross-sectional. Therefore, causality between the study’s variables cannot be determined. 


Overall, the present study contribute to understand the role of predisposing, precipitating, and perpetuating factors in the development of insomnia across nurses. The findings make a significant contribution to the expanding literature on emotion dysregulation, beliefs, and psychopathology vulnerability on Insomnia. The findings suggest the influence of CBT-I, transdiagnostic, and integrated therapies that could be incorporated into therapeutic of programs designed to develop as a way of inhibiting or preventing insomnia among clinical nurses. Based findings here, Special interventions (e.g., transdiagnostic interventions) must be immediately implemented to promote mental health of nurses exposed to COVID-19. Female nurse’s frontline must receive particular attention.


Cognitive behavioural therapy interventions for insomnia =CBT-I

Structural equation modeling =SEM

VIF=variance inflation factor. 

CORPD= COVID-19-Related Psychological Distress Scale

Insomnia Severity Index=ISI 

Dysfunctional beliefs and attitudes about sleep=DBAS

 Difficulties in Emotion Regulation Scale=DERS 

General Health Questionnaire= GHQ-28


Ethics approval and consent to participate 

The study was carried out in accordance with the Declaration of Helsinki and was approved and registered by the ethical and research committees from the following collaborating canters. The first author’s Institutional Review Board approved the research, prospectively. All participants provided signed written consent. 

Competing interests

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this paper.


The authors received no financial support for the research, authorship, and/or publication of this paper.

Availability of data and material

The data that support the findings of this study are available on request from the corresponding author. 

Authors' Contributions

N.N had significant contribution in Conceptualization, Methodology, and Writing- Original draft preparation: MS had significant contribution in Methodology Supervision. Validation. Supervision.

AA: had significant contribution in Data curation, software Writing- revision draft preparation.

VS had significant contribution in Writing- Original draft preparation, all authors Writing- Reviewing and Editing.




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