Antecedents of burnout and turnover intentions during the COVID-19 pandemic in critical care nurses: A mediation study

Abstract

Background: Nurses working in critical care environments have experienced a great deal of psychological stress during the successive waves of the COVID-19 pandemic. Identifying factors which contribute to burnout and turnover intentions are important to retain intensive care unit (ICU) nurses.

Purpose: The purpose of this study is to identify factors that are directly and indirectly associated with burnout and turnover intentions in ICU nurses.

Methods: A cross-sectional design was used with survey data during the peak of the second wave of the COVID-19 pandemic. Data were collected through an online survey and analyzed using mediation analysis. A total of 236 ICU nurses across Canada participated in the study.

Results: The results indicate that burnout mediates the relationship between moral distress, organizational support, resilience, and turnover intentions. Moreover, 49% of the participants were considering leaving. The reasons were related to lack of administrative support, poor work environment and safety concerns.

Discussion: Organizational support and individual resilience can both play a role in turnover intentions through the prevention of burnout symptoms. Managers at all levels play an important role in mitigating the harmful effects of the pandemic.

Conclusion: The pandemic has had a serious psychological impact on ICU nurses. Targeted interventions are needed to support this group.

Implications for nurses

• Forty-nine percent (49%) of the participants indicated they were considering leaving their job.
• Moral distress, organizational support and resilience predicted intent to leave through burnout symptoms.
• Managers at all levels must provide support to ICU nurses by being visible and allowing nurses to participate in unit-based policies.
• Interventions to reduce moral distress must be implemented within critical care units.

Background and Purpose

            The COVID-19 pandemic has had a devasting effect on health care workers. In Canada, 20% of all COVID-19 infections have been found in individuals working in health care settings (Government of Canada, 2021). Furthermore, data from the International Council of Nurses (ICN) indicate that over 2,200 nurses have died from COVID-19 worldwide (ICN, 2021a). The pandemic has exacerbated the already existing stressful work environment of ICU nurses. ICU nurses are also at a higher risk of being infected with COVID-19 because of working with patients requiring mechanical ventilation and more invasive procedures (Mokhtari et al., 2020). Gaining a better understanding of the pathways leading to both burnout and turnover intentions in ICU nurses providing care to COVID-19 patients are essential in order to identify interventions mitigating the effects of the pandemic.

Literature review

            Pandemics and epidemics, such as SARS or Ebola, have put extraordinary pressure on health care workers as they deal with issues related to scarcity of resources, exposure, increased workloads, inadequate protective equipment, complex ethical dilemmas, and rapidly changing policies in relation to patient care (Liu et al., 2012).The 2003 SARS outbreak in Canada had a profound impact of front-line workers as over 40% of health care workers in the Toronto region were infected with SARS (Naylor, 2003). Similarly, nurses providing care to COVID-19 patients are experiencing unprecedented levels of psychological distress (Fernandez et al., 2020; Halcomb et al., 2020; Leng et al., 2020; Lorente et al., 2021; Nowicki et al., 2020). Thirty-eight percent (38%) of ICU nurses in British Columbia have experienced significant symptoms of PTSD, mild to severe depression (57%), anxiety (67%) and stress (54%) (Crowe et al., 2021). These rates are alarming and reflect similar trends in other countries (Shen et al., 2020). For instance, a cross-sectional study in Holland has shown that 19% to 27% of ICU nurses suffer from symptoms ranging from anxiety, depression to PTSD (Heesakkers et al., 2021).

            The stressful work environment of ICU nurses makes them more susceptible to burnout than other nurses in pre-pandemic times (Woo et al., 2020). Burnout is defined as an individual’s response to work-related stress which is not successfully managed (WHO, 2019).  ICU nurses are vulnerable to burnout because of several stressors unique to their work environment, such as high patient acuity, high levels of autonomy, caring for families in crisis and morally distressing situations (Epp, 2012). During the COVID-19 outbreak, two thirds of Belgium nurses working in ICU were at high risk of burnout symptoms associated with their working conditions (Bruyneel et al., 2021). Furthermore, ICU nurses were significantly more at risk of emotional exhaustion, a core component of burnout, than other nurses who were caring for COVID-19 patients (Buryneel & Smith, 2021). The authors of this study attribute these differences to the higher number of deaths and greater workload within critical care units.

            Many nurses are also experiencing moral distress while providing patient care to COVID-19 patients (Gebreheat et al., 2021; Lake et al., 2021; Silverman et al., 2021). Moral distress is described as painful feelings and psychological distress occurring when a person knows the right action to take but is constrained from taking action due to a variety of institutional or other barriers (Hamric, 2014). Health care workers are experiencing several different types of moral distress as a result of COVID-19 (Morley et al., 2020). Emerging studies on moral distress in nurses during the pandemic identify multiple sources of moral distress, such as watching patients die without family presence, working with limited resources, working beyond their scope of practice and concerns over transmission risk to own family (Cacchione, 2020; Lake et al., 2021; McKenna, 2020; Silverman et al., 2021; Sriharan et al., 2021). Causes of moral distress in ICU nurses during the pandemic are similar and related to end-of-life decisions, inappropriate care, availability, and management of resources (Falco-Pegueroles et al., 2020). Both burnout and moral distress are closely related concepts and, as such, have many of the same determinants and are associated with negative health outcomes (Fumis et al., 2017; Meltzer & Hackabay, 2004). Moral distress also predicts burnout symptoms (Fumis et al., 2017), while both moral distress and burnout individually predict turnover intentions (Karakachian & Colbert, 2019).

            Certain job resources (e.g., organizational support) and personal resources (e.g., resilience) can mitigate the harmful effects of burnout (Bakker et al., 2005; Schaufeli et al., 2014).  Organizational support is defined as the employees’ belief of the extent to which their organization values their contributions and cares about their well-being (Eisenbergen et al., 2002). Organizational support predicts several positive outcomes, such as quality of care and job satisfaction as well as psychological well-being (Pahlevan Sharif et al., 2018; Van Boageart et al., 2013). Organizational support also reduces turnover intentions (Li et al., 2020).

            Although organizations differ in the way they respond to natural disasters and pandemics (Mihalache & Mihalache, 2021), strong leadership and organizational support appear to have a buffering effect on the stress related to disasters (Veenema et al., 2017). Emerging COVID-19 studies support this view. Zhang et al. (2020) found that perceived organizational support reduced nurses’ fatigue through the mediating role of resilience in a sample of nurses caring for COVID-19 patients in China, while Labrague & de los Santos (2020) found that social support, organizational support, and resilience reduced anxiety related to COVID-19 in nurses. Unfortunately, many nurses perceive their managers as being unsupportive and unaware of their concerns over workplace issues during the pandemic (Falcó-Pegueroles et al., 2021; González-Gilet al, 2021; Halcomb et al., 2020; Moradi et al., 2021).

            Resilience, the ability to bounce back from stressful or traumatic events, has been the focus of an increasing number of studies in health care and shown to be negatively correlated to burnout among nurses (Garcia-Izquierdo et al., 2018; Guo et al., 2018; Yu & Lee, 2018). In a large-scale study of 904 nurses examining resilience in four countries (Japan, South Korea, Turkey, and the United-States), nurses who reported higher organizational support and who were involved in establishing COVID-19 unit-based policies had higher resilience levels (Jo et al., 2021). On the other hand, fear of being infected, intention to leave and a positive COVID-19 test were associated with negative resilience levels. Interestingly, nurses from the United-States had significantly higher resilience levels than nurses in other countries. Studies have also shown that resilience can help nurses cope with their stressful environment through the pandemic (Cooper et al., 2020; Labrague & de los Santo, 2020; Peñacoba et al., 2021). For this reason, many authors are calling for strategies to improve resilience during the COVID-19 pandemic (Labrague, 2021; Odom-Forren, 2020). 

            This study was guided by the Burnout Syndrome Risk framework (Kerlin et al., 2020). According to this framework, a combination of personal characteristics (e.g., resilience) and organizational factors (e.g., support) can precipitate moral distress. These risk factors, in turn, may lead to burnout, and ultimately impact both patient and nurse outcomes (e.g., turnover).  The framework also places burnout as a mediator between risk factors and outcomes. The Burnout Syndrome Risk framework illustrates the complex relationships between burnout and its consequences (Kok et al., 2021).

            Although there are studies examining moral distress, burnout and turnover intentions within the nursing literature, there has been less consideration of complex models examining the interactions between antecedents of burnout and turnover intentions. Yet, complex models are needed to fully understand complex work environments, such as critical care units during the COVID-19 pandemic. The purpose of this study is to identify factors that are directly and indirectly associated with burnout and turnover intentions in ICU nurses. Identifying sources of burnout and turnover intentions are essential to establish strategies to reduce the psychological distress of ICU nurses during the pandemic. Figure 1 illustrates the proposed model. We propose the following hypotheses:

            Hypothesis 1: Burnout will mediate the relationship between moral distress and turnover intentions (moral distress → burnout → turnover intentions).

            Hypothesis 2: Burnout will mediate the relationship between organizational support and   turnover intentions (organizational support → burnout → turnover intentions).

            Hypothesis 3: Burnout will mediate the relationship between resilience and turnover         intentions (resilience → burnout → turnover intentions).

Figure 1

Conceptual diagram of hypothesized relations in mediation model

Methods and Procedures

Design and Sample

            This study is a concurrent mixed-methods study examining the impact of COVID-19 on nurses working in ICUs in Canada. We collected both quantitative and qualitative data. This paper mainly examines the quantitative data.  

Data collection

            We recruited a convenience sample of ICU nurses from the Canadian Association of Critical Care Nurses (CACCN).  Social media sites affiliated with the CACCN were also used to recruit ICU nurses. The CACCN sent an initial email request followed by two reminders at three-week intervals inviting members to respond to an online questionnaire. A total of 1,400 ICU nurses were asked to participate and, of these, 236 responded to the online survey and 108 responded to the qualitative component of the survey. The response rate was approximately eight percent. The researchers did not have any known relationships with the participants. G*Power was used to calculate the minimum sample size (Faul et al., 2009). For an effect size of .05, power of 95%, a sample size of 220 was required for chi square modelling. Our sample was therefore considered appropriate. The data was collected during the peak of the second wave over a three-month period from January 11 to March 2, 2021. The second wave in Canada began in September 2020, with a peak of 6,549 cases on November 9, 2020.

Measures

            Burnout was assessed using the Oldenburg Burnout Inventory (OBI) (Halbesleben et al., 2005). This OBI consists of a 16-item instrument with two subscales, that of emotional exhaustion and disengagement. A 4-point Likert scale was used to measure the dimensions of burnout, ranging from 1 (strongly agree) to 4 (strongly disagree). An example of an item from the emotional exhaustion subscale is ‘There are days when I feel tired before I arrive at work’, while an example of an item from the disengagement scale is ‘Over time, one can become disconnected from this type of work’. Higher scores indicated more severe burnout, furthermore, a cut-off score of 2.25 or higher on emotional exhaustion is considered as high, while a cut-off score of 2.1 or higher on disengagement is considered high. In our study, Cronbach’s alpha for the emotional exhaustion scale was .78, and the disengagement scale .79 and the entire questionnaire was .87.

            Moral distress was evaluated using the Modified Moral Distress Scale (MDS-11) (Badolamenti et al., 2017).  This questionnaire was based on the Corley’s Moral Distress Scale (MDS), which measured the frequency and intensity of events. This scale has two dimensions (futility and potential damage) and contains 11 items with a 5-point Likert scale ranging from never (1) to always (5) for the frequency of moral distress events, and from never (1) to a lot of (5) for the intensity of events. Higher scores suggest extreme moral distress. An example of an item is the following: “Witness health care providers giving ‘false hope’ to a patient or family”. The MDS-11 has good psychometric properties, with a Cronbach alpha of .84 for futility, while the potential damage scale was somewhat lower with a score of .64. The entire questionnaire had an alpha of .82.

            A subscale measuring organizational support from Halcomb et al.’s (2020) questionnaire on front-line nurses’ experiences during COVID-19 was used to evaluate the knowledge offront-line nurses during the pandemic. The complete questionnaire contains 14 items with a 5-point Likert scale, ranging from 1 (strongly agree) to 5 (strongly disagree). The tool was created by a research team and validated by six clinicians, policy experts and academics. It has not undergone any other psychometric tests.  We therefore examined the dimensions of the questionnaire through exploratory factor analysis (EFA) with maximum likelihood estimator and promax oblique rotation. Bartlett’s sphericity test and the Keiser-Meyer-Olkin indicator were used to confirm the factor assumptions prior to EFA.  Results indicated two dominant factor loadings (> .30), that of organizational support and knowledge. Further reliability testing indicated a Cronbach’s alpha score of .85 for the organizational support subscale. An example of an item from this subscale is “I feel well supported in my clinical role by my employer.”

            Nurses’ ability to bounce back from distressing situations during the pandemic was measured with the Brief Resilience Scale (Smith et al., 2008). The scale contains six items on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). An example of an item is ‘It does not take me long to recover from a stressful event’. The scores can be interpreted as follows: 1.00-2.99, low resilience, 3-4.30, normal resilience and 4.31-5.00, high resilience. The scale, which has been used widely in research, has excellent psychometric ratings (Windle et al., 2011). Cronbach’s alpha coefficient for the current study was .91.

            Intent to leave was measured using a dichotomous measure by Halcomb et al. (2020). The question was the following: “Have you considered leaving your employment as a result of COVID-19?” Following this, there was a choice of five different reasons: concern for personal physical safety, concern for psychological safety, concern for family safety, carer responsibilities or other. Those that indicated other were asked to specify the reasons they considered leaving.

            The following socio-demographic variables were examined: age, gender, occupational status (full time, part time), years of experience as a registered nurse, years of experience in ICU, number of beds in unit, hospital size (i.e., 1 to 199 beds was designated as small hospital), and province where the participant worked).

Data analysis

            Initial data analysis was performed with SPSS version 27.  Data were examined for normality by evaluating skewness and kurtosis.  Afterwards, descriptive statistics were performed on the sociodemographic data. In relation to the main variables, means, standard deviations and reliability scores (Cronbach’s alpha) were calculated, followed by correlations between main variables and key sociodemographic variables.  Once the preliminary analyses were done, we transferred the data to Mplus version 8 for mediation analysis (Muthén & Muthén, 1998–2017). Full-information maximum likelihood (FIML) was used to estimate missing values in this study. Model fit was evaluated using the following indices: the chi-square fit statistics, the root mean square error of approximation (RSMEA), the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the standard root mean square residual (SRMR) (Hu & Bentler, 1999). A bootstrapping procedure of 5,000 iterations was run to estimate the 95% confidence intervals. Standardized regression estimate scores (Beta) were calculated to interpret the results of the mediation analysis. The qualitative component of the intent to leave question (the reason participants considered leaving) was analyzed using thematic analysis (Braun & Clarke, 2006). Initially, each answer was read to gain a better understanding of the meaning. Initial codes were attributed to the text and afterwards, similar codes were grouped together into broader themes. The themes were reviewed and refined. A second member of the team also created the initial codes and themes. Afterwards, team members validated the three major themes emerging from participant answers.

Ethics

            The study obtained approval from the ethics committee was obtained through a university in eastern Canada prior to data collection (approval number 2021-024). A cover letter explaining the nature of the study was included with the survey guaranteeing the anonymity and confidentiality of the participants. Participants were provided with several resources, both online and in-person, in the event that answering the survey caused distress.

Results

            Table 1 shows the demographic profile of the participants. As can be seen, the average age of participants was 36 years old, and the majority were women (91.9%, n = 159). Seventy-eight of participants worked full time (78.3%) and the average number of years working in ICU was 11.  Most participants worked in medium sized (37.9%) or large hospitals (46.7%). The participants were largely from the following provinces: Ontario (32.7%, n = 56), British Columbia (19.9%, n = 34), New Brunswick (17%, n = 29) and Alberta (13.5%, n = 23).

Table 1

Socio-demographic characteristics of sample

Note. SD = standard deviation

            Forty-nine percent (48.9%, n = 87) of the participants considered leaving their jobs.  The two main reasons for considering leaving were psychological safety (30.3%, n= 27) and physical safety (13.5%, n = 12). Fifty percent (49.4%, n = 44) of the participants indicated other reasons. Three main causes emerged from these qualitative responses: 1) lack of administrative support, 2) poor work environment and 3) safety issues. Table 2 shows verbatims corresponding to each category. In relation to the first category (administrative support), participants described a lack of support, understanding and respect from management. The participants did not differentiate between the front-line managers or middle management. The second category, work environment, included issues such as the lack of staff, resources and a general disregard for meeting basic needs of nurses when working. The last category, safety issues, included concerns about both patient care and nurse safety. A few participants expressed non-specific reasons for considering leaving, often related to a sense of weariness with workplace issues. The following excerpt from a nurse summarizes this sentiment, “…the never-ending changes.  I think of quitting daily. It’s time for this to end” (participant 121).

            Table 3 presents the mean, standard deviation, reliability coefficient and correlation of the main variables.  Nurses reported moderately high levels of burnout (   = 2.77, SD = .42), with subscale dimensions for emotional exhaustion (  = 2.89, SD = .43) higher than that of depersonalization (  = 2.64, SD = .49). Nurses had moderate levels of organizational support (  = 3.13, SD = .92) and normal levels of resilience (   = 3.47, SD = .73).  Mean overall moral distress scores were 20.00 (SD = 8.51), the futility subscale was 13.48 (SD = 5.06) and the potential damage subscale was 7.08 (SD = 4.00). The highest mean score was 17.88 (SD = 6.33) in relation to medical futility. The item was: “Follow the family’s wishes to continue life support even though I believe it is not in the best interest of the patient”. On the other hand, the lowest score was related to potential damage with a low of 4.31 (SD = 3.21). The item was: “Avoid taking action when I learn that a physician or nurse colleague has made a medical error and does not report it.” Significant negative correlations were found between burnout and organizational support (r = -.49, p = .000), intent to leave (r = -.58, p = .000) and resilience (r = -.31, p = .000). On the other hand, burnout also had a positive significant relationship with moral distress (r = .43, p = .000).

Table 3

Mean, Standard Deviations, Reliability Coefficient and Correlation between Study Variables

  Note. ^*p <  .01, ^**p <  .001

            Our hypothesized model has very good fit indices (χ² = .007, df = 1, p = .934, RMSEA = 0.000, CFI = 1.000, TLI = 1.072).  The model explained 39% of the variance of burnout and 40% of the variance of intent to leave. Figure 2 shows the coefficients for each direct path within this five-factor model. Moral distress is positively related to burnout (β = .261, p =.000) but not to turnover intentions (β = .129, p =.113). Hypothesis 1 stated that burnout will mediate the relationship between moral distress and turnover intentions (moral distress → burnout → turnover intentions). The indirect effect of moral distress on turnover intentions through burnout was negative and significant (β = -.153, p =.001, 95% CI [-.238, -.081]), indicating full mediation as the indirect path is significant, but the direct path became nonsignificant when combined with the direct path. Hypothesis 1 is supported. Table 4 shows the parameter estimates of the indirect effects of the main study variables.

Figure 2

Final mediation model

Table 4

Parameter estimates of indirect paths with burnout as mediator

Note. TI = turnover intentions

            Hypothesis 2 proposed that burnout will mediate the relationship between organizational support and turnover intentions (organizational support → burnout → turnover intentions). Organizational support is negatively related to burnout (β = -.374, p =.000) and but not related to turnover intentions (β = .150, p =.077). The indirect effect of organizational support on turnover intentions through burnout was significant (β = .219, p =.000, 95% CI [.148, .296]) while the direct path became nonsignificant. Once again, this indicated full mediation.

            Lastly, hypothesis 3 proposed that burnout will mediate the relationship between resilience and turnover intentions (resilience → burnout → turnover intentions). Resilience was negatively related to burnout (β = -.167, p =.027) but not to turnover intentions (β = .014, p =.844). The indirect effect of resilience on turnover intentions through burnout was significant (β = .098, p =.029, 95% CI [.024, .172]) and the direct path was not significant, indicating full mediation. Age was not significantly related to burnout (β = -.106, p = .108)

Discussion

            The purpose of this study was to gain a better understanding of the pathways leading to both burnout and turnover intentions among ICU nurses during the second wave of the pandemic. We found that burnout mediated the relationship between turnover intentions and three predictors, that of organizational support, moral distress, and resilience. In other words, nurses who received more organizational support and were resilient had reduced burnout symptoms and as a result, were less inclined to consider leaving. On the other hand, high levels of moral distress increased turnover intentions through burnout symptoms. These results lend support to the Burnout Syndrome Risk framework (Kerlin et al., 2020). The findings also support past research on the mediating role of burnout, linking work-related stressors and occupational outcomes, such as turnover intentions (Leiter & Maslach, 2005).

            The pandemic has taken a serious toll on ICU nurses (Mokhtari et al., 2020; Crowe et al., 2021; Bruyneel et al., 2021). The participants in our study had high levels of moral distress and reasonably high levels of futility, a component of moral distress. Moral distress is common in ICU nurses (Dodek et al., 2016; Browning, 2013; Mealer & Moss, 2016) and often related to end-of-life issues, such as futility of care (Wiegand, et al., 2012; Dodek et al., 2016; Lluch-Canut et al., 2020). According to Hamric (2014), moral distress is characterized by feelings of powerlessness and the inability of being heard. During the pandemic, factors beyond nurses’ control were often the most difficult to deal with (Cacchione, 2020). Our findings support this literature, as the highest moral distress scores were related to situations beyond nurses’ control, unable to advocate for their patients whose lives were prolonged with questionable benefits.

            The participants also had reasonably high levels of futility, a component of moral distress. Futile care is defined as the aggressive treatment of patients, who are at the final stages of life and will not benefit from them (Rostami et al., 2019). It includes troubling situations such as being involved in the administration of aggressive treatments or observing physicians giving painful treatments to seriously ill patients with questionable outcomes (Heland, 2006). ICU nurses may experience increased moral distress due to futile situations because they spend more time with patients and are more aware of patient suffering than other health care professionals (Neville et al., 2015).   

            Our results also show that burnout fully mediated the relationship between moral distress and turnover intentions (moral distress → burnout → turnover intentions). Thus, moral distress has far reaching consequences on ICU nurses, leading to burnout and considerations of leaving. These findings are in line with other studies examining the consequences of moral distress and burnout on nurses (Fumis et al., 2017; Kok et al., 2021; Burston & Tuckett, 2013). As well, our findings are consistent with previous studies showing that moral distress is a significant predictor of turnover intentions (Karakachian & Colbert, 2019; Lusignami et al., 2017; Sheppard et al., 2022). Unfortunately, there are few studies examining the long-term effects of moral distress during the pandemic as most studies examining psychological distress in nurses during the pandemic are cross-sectional. An exception is Wilson et al.’s (2021) study measuring moral distress on a weekly basis for 23 weeks in 771 health care workers, 12% being nurses. The results showed that moral distress had a cumulative effect and predicted increased mental health distress and burnout each week over the study period. Although not longitudinal, Lake et al.’s (2021) study also sheds light on the effects of moral distress on the mental health of nurses in the United-States five months after the peak of the first wave. Both effective communication and access to PPE decreased moral distress, while moral distress was the only variable predicting long-term psychological distress.

            Our study also extends knowledge of the pathway in relation to organizational support, burnout, and turnover intentions (organizational support → reduced burnout → decreased turnover intentions). Burnout fully mediated the relationship between organizational support and intent to leave. Thus, when ICU nurses perceive they have organizational support, they will be less likely to suffer from burnout symptoms leading to turnover intentions. These findings demonstrate the important ramifications of workplace support. In a broader sense, they corroborate the literature on the relationship between healthy workplace environments (e.g., supportive management) and positive nurse-related outcomes (Wei et al., 2018). Organizational support can take on many different forms, some are more structural, such as offering flexible schedules to help with the demands of home and work, while others are more supportive, such as acknowledging the challenges that employees are facing and showing appreciation of their efforts (Mihalache & Mihalache, 2021). Regardless of the form, organizational support may be viewed as a strategy for reducing the negative outcomes of pandemics, such as SARS or COVID-19 (Marjanovic et al., 2007). Unfortunately, not all nurses have felt supported by their managers during the pandemic (González-Gil et al., 2021 Rhéaume et al., 2021; Moradi et al., 2021). For many nurses, the COVID-19 pandemic has exacerbated the psychosocial risk factors for health care workers such as high demands, lack of control over work environment and poor organizational support (Theorell, 2020). These, in turn, create the underlying conditions for depression and burnout.   

            Thoughts about leaving a job, and subsequently leaving may be considered the cumulative end result of a cascade of events occurring within the workplace. Fifty percent of our participants were considering leaving. Qualitative results indicate that lack of organizational support, poor work environment and safety issues were driving nurses to consider leaving their employment. According to the ICN, 20% of the National Nursing Associations have reported their nurses leaving the profession at an increased rate (ICN, 2021b). Moreover, the existing global nurse shortage could increase to 13 million once the pandemic is over. The effect of the pandemic is considered as a “mass traumatisation of the nursing workforce” related to increased risk of infection at work, ongoing high demands, inadequate staffing to respond to the pandemic. A recent study in Québec indicates that 30% of the nursing staff reported high intent to leave their current position, while 22% intended to leave the profession (Lavoie-Temblay et al., 2021). Falatah’s (2021) review of 43 studies on turnover intention suggests that reasons for leaving pre-pandemic and post-pandemic are different. While the determinants of turnover intention pre-pandemic were mainly related to job satisfaction, organizational commitment and leadership, post-pandemic the turnover intention predictors were fear of disease, stress, and anxiety. The authors conclude that COVID-19 has had an alarming impact on the rate and predictors of turnover in nurses.

             Lastly, burnout also mediates the relationships between resilience and turnover intentions (resilience → burnout → turnover intentions), albeit the relationship was weaker when compared to the two other predictors (moral distress and organizational support). These results were surprising given the amount of evidence on the buffering effects of resilience on psychological distress in health care workers (Labrague & de los Santos, 2020). We attribute this to the stronger impact of both moral distress and organizational support on health outcomes in our sample during a chaotic and stressful time frame. There is, nonetheless, mounting evidence that personal resilience may help nurses deal with the stress incurred by the pandemic (Labrague, 2021; Foster et al., 2020). There is less known about whether nurses’ ability to bounce back from stressful events lasting over successive waves of the pandemic, with ongoing difficult working conditions, high number of complex patients and corresponding deaths. Resilience, as a personal resource, may be useful in mitigating some of the negative effects of stress during events such as pandemics, even so, other factors within the environment should not be ignored. Focusing uniquely on strategies promoting individual resilience can be counterproductive if promoting healthier work environments are set aside across Canada.

Limitations

            There are several limitations to this study. First, we measured organizational support through a larger questionnaire on nurses’ experiences during the pandemic. In hindsight, it would have been preferrable to use a comprehensive questionnaire targeting organizational support and examining different levels of support in the organizations, from front-line managers to upper-level management. Second, exploring front-line managers’ perspectives would have also given us a more complete picture of the situation on critical care units. Although we have nurses’ perspectives, we cannot begin to fully understand the pressures that front-line managers confronted, given their limited span of control within health care organizations (Fallman et al., 2019). Lastly, although we had representation from most provinces, we would have preferred to have a larger sample with representation from all regions of the country to better understand the work environment of ICU nurses.

Clinical implications

            The results of this study provide more evidence of ongoing psychological distress seen in front-line nurses providing care to COVID-19 patients. Critical care nurses work in chaotic environments and, as such, are used to providing care to complex patients. The unique characteristics of providing care to patients during the pandemic has exacerbated the already stressful working environment and increased the moral distress risks of these nurses. Our study suggests that organizational support is key to reducing both burnout and intent to leave in ICU nurses. How do we support ICU nurses? Firstly, managers at all levels must be visible to answer questions and listen to staff concerns (Moore, 2020). Supporting nurses through access to counselling and participation in unit management decisions will give them a greater sense of control of their work environment. Strategies can be as informal as daily team huddles, or more formal, such as unit-based meetings to increase nurses’ sense of control and decision making in relation to policies affecting them.  As well, a comprehensive communication strategy must be implemented with the input of all staff allowing them to understand decisions that are made as well as their rationale. There are many excellent guidelines on supporting nurses and other health care workers through the pandemic that can be used in ICU settings (Hossain & Clatty, 2021; Muller et al., 2020; Wright et al., 2020). These guidelines should be used with the input of nurses.

            Interventions to reduce moral distress are also essential. In a commentary on the moral obligation of nurse leaders, Prestia (2020) calls for transparent communication, mindful communication and truth telling in order to minimize the moral distress of staff. This kind of communication appeared to be lacking within the work environment of our participants.  Another way of responding to moral distress is by ‘recognizing and naming it’, which can then lead to discussion, advocacy and protocols that guide nurses through ethically challenging situations (Silverman et al., 2021). Target interventions to build moral resilience and providing nurses with a safe space at work are important steps which may mitigate some of the difficult situations ICU nurses have faced throughout the pandemic.  

Conclusion

            We finished our analyses during the fourth wave of the pandemic as health care officials discuss the possibility of a fifth wave. Uncertainty remains as to how many more waves we will go through, and, in terms of the future, what the next epidemic or pandemic will look like.  Although our understanding of the impact the pandemic has on ICU nurses has increased, there is still little known about the cumulative effects of each wave on nurses. Logic dictates that the psychological distress will amplify over time if the work environment does not change. This is frightening as ICU nurses are an essential part of our health care system. We must protect and maintain this essential group of health care workers.

Author Notes

Ann Rhéaume, PhD, Professor, School of Nursing, Université de Moncton

Myriam Breau, MScN, PhD candidate, Professor, School of Nursing, Université de Moncton

Address for correspondence:   Ann Rhéaume, PhD, Professor, School of Nursing, 51 Antonine-Maillet avenue, Université de Moncton, Moncton, New Brunswick, Canada E1A 3E9

Telephone:  506-858-4268, Email:  Ann.rheaume-bruning@umoncton.ca.

Acknowledgments

The authors would like to thank Canadian Association of Critical Care Nurses (CACCN) and the ICU nurses that have taken their precious time to participate in the study.

Funding and Conflict of Interest

Funding for this research was provided by the Université de Moncton.  The authors have no conflict of interest to disclose.

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