Abstract
Background
The recent coronavirus disease 2019 (COVID‐19) pandemic has imposed severe psychological pressure on nurses. Mindfulness has been shown to be effective in improving professional quality of life (ProQOL) and reducing psychological distress in a wide range of populations and contexts. However, its role in supporting critical care nurses during the outbreak of COVID‐19 has yet to be established.
Purpose
This study explores the relationship of mindfulness with negative emotional states and ProQOL among nurses working in critical care units during COVID‐19 pandemic.
Methods
A cross‐sectional descriptive correlational design was used. A sample of 156 critical care nurses completed self‐reported measures of mindfulness, ProQOL, and negative emotional states. Multiple regressions were used to address the study purpose.
Results
Overall, the participants had severe anxiety, moderate depression, moderate stress, moderate burnout, moderate secondary traumatic stress, and moderate compassion satisfaction. Mindfulness was significantly and negatively associated with stress (r = − 0.230, p = .004), depression (r = − 0.190, p = .018), burnout (r = − 0.218, p = .007), and secondary traumatic stress (r = − 0.168, p = .037). Mindfulness explained 3% of the variance in depression (B = −0.19, p = .018), 3.9% of variance in stress, (B = −0.201, p = .012), 4.2% of variance in BO (B = −0.206, p = .009), and 2.2% of the variance in secondary traumatic stress (B = −0.168, t = −2.104, p = .037), controlling for demographics.
Conclusions
The current study provides preliminary evidence that mindfulness can be helpful in reducing critical care nurses' psychological distress and promoting their ProQOL, and is worthy of further investigation in this population.
Keywords: anxiety, burnout (BO), compassion fatigue, compassion satisfaction, critical care unit, depression, mindfulness, nurse, professional quality of life (ProQOL), stress
1. BACKGROUND
The demands and responsibilities of working in the critical care unit impose a real‐life stressor that is hard to modify due to the nature of the work. 1 The recent coronavirus disease 2019 (COVID‐19) pandemic imposed additional stress and fear of the disease itself and its transmission to nurses or their beloved ones. 2 Nurses in the critical care units are particularly vulnerable to acquire the infection with the virus when there is a staff shortage, lack of personal protection equipment, and when the number of patients with COVID‐19 in the CCU suddenly increases. 3
Negative emotional states (i.e., anxiety, stress, and depression) are widespread among nurses employed in critical care units. 4 Previous research has shown that nurses employed in critical care units have emotional status problems including stress, anxiety, and depression. Stress and anxiety are closely connected, and anxiety alone is a vague discomfort and a sense of skepticism toward unknown situations. These uncomfortable feelings are associated with negative physiological and emotional consequences. Depression is a disorder that causes loss of interest in life, sadness, extreme fatigue, sleep disorders, reduced or increased appetite, unclear physical pain such as headaches, back pain, or digestive disorders, and impairment in social and personal relationships. 5 Anxiety and depression are caused by the stressors of life and they are related to previous, present, or future issues.
Exposure to a highly stressful work environment and providing care to patients with life‐threatening conditions could negatively influence caregivers' professional quality of life (ProQOL). 6 ProQOL refers to the quality care providers feel in relation to their job as helpers. 7 It has both positive (compassion satisfaction) and negative (compassion fatigue) aspects. Compassion satisfaction is related to the positive experience and the reward feelings of alleviation of patient suffering. Compassion fatigue has been described as a state of physical or emotional status in care providers that occurs as a result of providing care for needy individuals. Compassion fatigue includes two parts: burnout (BO) and secondary traumatic stress (STS). Burnout concerns things such as frustration, exhaustion, anger, and depression. Secondary Traumatic Stress is related to fear driven by work‐related trauma. 7
The current surrounding situations and context associated with the COVID‐19 pandemic (i.e rapid transmission, lack of knowledge about this new pandemic, and deficiency in medical equipment supply) could contribute to compassion fatigue among healthcare providers. 8 , 9 Such, there is a potential for the current situation to impact ProQOL among critical care nurses.
One of the suggested methods to support nurses employed in critical care units is mindfulness. 10 Recent research conducted in the CCU has shown that coping mechanisms have been significant indicators of compassion satisfaction and correlated with compassion fatigue. 11 However, the role of mindfulness in improving emotional states and ProQOL among nurses employed in the CCU has yet to be established.
While mindfulness can reduce the burden of various negative symptoms, the mechanisms by which mindfulness helps manage stress‐related symptoms are less clear. 12 Recent theoretical perspectives and empirical research suggest that mindfulness helps people to deliberately accept the situation in the current moment and let go of thoughts or emotions they find maladaptive. 12 Mindfulness could act mainly on three systems, including emotional regulation, attention control, and self‐awareness. 13 Increased mindfulness is associated with lower reactivity to stress among nurses and nursing students as it would enhance the capacity to pay non‐judgmental acceptance of stressful situations in nursing education and practice. 14 A previous systematic review reported that mindfulness was effective at improving negative emotional states and compassion fatigue among nurses and health care providers. 15
While empathetic and compassionate care is at the core of the nursing role, there may be a cost to this empathetic and compassionate care that can contribute to compassion fatigue. Research has shown that the aptitude to be non‐judgmental, self‐compassionate, sensitive, and regardful toward oneself may be an important hindering factor of compassion fatigue among nurses. 15 , 16 Therefore, mindfulness may be an appropriate target variable to alleviate the overwhelming burden of caring for COVID‐19 patients in the critical care units and prevent or mitigate nurses' compassion fatigue and negative emotional states during the pandemic. Thus, this study is going to describe levels of ProQOL and negative emotional states and investigate the relationship between mindfulness and both negative emotional states and ProQOL among nurses employed in the CCU. This could provide new knowledge and direct future research to implement mindfulness‐based interventions to support CCU nurses during the COVID‐19 pandemic.
The study has the following objectives
To describe levels of ProQOL and negative emotional states among nurses working in critical care units.
To investigate the unique relationship between mindfulness and negative emotional states among nurses employed in critical care units, controlling for their demographics.
To investigate the unique relationship between mindfulness and ProQOL among nurses employed in critical care units, controlling for their demographics.
2. METHODOLOGY
A descriptive, correlational cross‐sectional design was used.
2.1. Sample and settings
The study population was all registered nurses working in critical units during COVID‐19 Pandemic. A multistage sampling technique was employed in sample selection. In the first stage, a list of the eight largest educational hospitals in the country was obtained and four of them were selected by simple random sampling technique, employing simple balloting. In the second stage, a convenience sampling technique was used to recruit the study participants from these four hospitals. The inclusion criteria were: (1) being a registered nurse with Bachelor's or Master's degree in nursing; (2) being employed in a critical care unit for at least six months during the COVID‐19 pandemic; and (3) working at bedside. Nurses with administrator positions and those with less than six months experience were excluded.
The required sample size was calculated using the G*Power program version 3.1.9.2. For multiple linear regression analysis, a medium effect size, a power = .80, α = .05, and 10 possible predictors, a minimum sample of 118 participants was needed. The sample size was increased to 154 to address the possibility of having incomplete questionnaires.
2.2. Procedure
After obtaining the IRB approval from the Ethical Committee *****, the researcher visited the hospitals where the data were collected. Because of the COVID‐19 pandemic and the recommendations from hospital administrators to do online data collection, and the strict roles of the Ministry of Health which prohibited the distribution of paper questionnaires, the author decided to collect data online. The online questionnaire was distributed to nurses working in the critical care units in one university hospital, two governmental teaching hospitals, and one private teaching hospital from April – May 2020. The potential respondents were assured that their participation in the study was voluntary and they could withdraw at any time. All collected data were confidential. In addition, all participants consented before participation in the study. The response rate was 98.7% (156 participants participated out of 158 invited).
2.3. Measures
2.3.1. The demographic questionnaire
This scale was developed by the researchers to collect data regarding the basic characteristics of the study participants including age, marital status, gender, level of education, years of experience, type of hospital, and clinical settings.
2.3.2. Depression Stress Anxiety Scale‐21 (DASS‐21)
DASS‐21 is a self‐reported measure of negative effects with three 7‐item subscales (depression, anxiety, and stress). The psychometric properties of the short version of DASS are well established. 17 The overall internal consistency of DASS‐21 (Arabic version) was found to be strong, giving a Cronbach's alpha of 0.86. 18 The DASS‐21 is widely used in Jordan to measure depression, anxiety, and stress in various populations. 19 , 20 , 21 The Cronbach's α of the Arabic version used in this study was .94.
2.3.3. ProQOL version 5 (2009)
The ProQOL‐5 is a 30‐item measure used to assess CS (10 items) and CF (20 items). CF is categorized into two sub‐scales: BO (10 items) and STS (10 items). Items are assessed on a 5‐point Likert scale (from 1 = Never to 5 = Very Often). The alpha reliabilities for the scales have good to excellent reliability (CS α = .88; BO α = .75; and CF α = .81). 7 The tool is available for free on the ProQOL website. The ProQOL‐5 has been widely used to measure the ProQOL of clinical nurses during COVID‐19 pandemic. 22 , 23 , 24 Using the ProQOL was preferred in this study because it has been used in Jordan and found to have adequate validity and reliability. 11 The Arabic version of the tool was used. In this study, the scales had good to excellent internal consistency reliability (CS α = .90; BO α = .72; and CF α = .84).
2.3.4. The Mindful Attention Awareness Scale (MAAS)
The MAAS (15 items) measures mindfulness and focuses on awareness and attention to what is happening at this moment. Respondents are asked to rate items from 1 (almost always) to 6 (almost never) on a 6‐point scale. Cronbach's α values for the scale range from .80 to .87. 25 Data on construct validity was shown by positive interactions of mindfulness with personal well‐being, self‐esteem, optimism, and self‐actualization. 25 The MAAS is widely used in Jordan to measure mindfulness in various populations. 19 , 20 , 26 , 27 The Cronbach's α of the Arabic version used in this study was .94.
2.4. Data analysis
The IBM SPSS software was used to analyze data. Descriptive statistics (Frequency, percentages, mean, standard deviation, and minimum and maximum scores) were used to describe the sample characteristics and assess the levels of the main study variables (answer the first research question). One way analysis of variance was used to compare the scores of the main study variables based on hospital and department type separately. The Pearson product‐moment correlation was used to identify the correlation between the following continuous variables (i.e., age, total experience in nursing, total hospital experience, and total experience in the critical care unit) and the main study variables. Independent t‐test was used to compare the main study variables (i.e depression, anxiety, stress, CF, STS, CS, and mindfulness scores) according to gender, marital status, level of education, and type of shift. Hierarchical multiple regression analyses were used to assess the unique role of mindfulness in both professional QOL and negative emotional states among critical care nurses, controlling for their demographics.
3. RESULTS
3.1. Sample characteristics
Table 1 presents the demographic characteristics of the nurses who completed the study. A total of 154 participants completed the study including 84 (54.5%) males and 70 (45.5%) females. Regarding marital status, most of the participants (n = 118, 76.6%) were married, and 36 (23.4%) were unmarried. Most of the participants (n = 121, 78.6%) have a bachelor's degree, while the remaining 33 (21.4%) have a master's degree. Also, the majority of participants (n = 76, 49.4%) were employed at a university‐affiliated teaching hospital, 57 (37.0%) were employed at a governmental teaching hospital, and 21 (13.6%) were employed at a private teaching hospital. Regarding the type of department, most of the participants (n = 39, 25.3 %) were from cardiac units, 20 (20.8%) were from medical critical care units, 29 (18.8%) were from pediatric critical care units, 27 (17.5%) were from surgical critical care units, and 27(17.5%) were from general critical care units. Regarding the working shift, the majority of participants (n = 124, 80.5%) were working rotating shifts (A, B, and C shifts), and 30 (19.5%) were working day and night shifts. The participants' mean age was 33.03 years (SD = 5.08), ranging from 23 to 49 years. The participants' mean years of experience in nursing was 9.77 (SD = 5.34) ranging from 1 to 27 years. The participants' mean years of hospital experience was 8.48 (SD = 11.26) ranging from 1 to 33 years. The participants' mean years of experience in the critical care unit was 6.62 years (SD = 4.65) ranging from 1 to 20 years.
Table 1.
Demographic characteristics of the participants (N = 154)
| Variable | Mean (SD) | N (%) |
|---|---|---|
| Age | 33.03 (5.08) | |
| Total experience in nursing | 9.77 (5.34) | |
| Total hospital experience | 8.48 (11.26) | |
| Total experience in the intensive care unit | 6.62 (4.65) | |
| Level of education | ||
| Bachelor degree | 121 (78.6%) | |
| Master degree | 33 (21.4%) | |
| Gender | ||
| Male | 84 (54.5%) | |
| Female | 70 (45.5%) | |
| Marital status | ||
| Unmarried | 36 (23.4%) | |
| Married | 118 (76.6%) | |
| Type of hospital | ||
| University‐affiliated teaching hospital | 76 (49.4%) | |
| Governmental teaching hospital | 57 (37.0%) | |
| Private teaching hospital | 21 (13.6%) | |
| Type of department | ||
| Medical intensive care unit | 32 (20.8%) | |
| Pediatric intensive care unit | 29(18.8%) | |
| Surgical intensive care unit | 27 (17.5%) | |
| General intensive care unit | 27 (17.5%) | |
| Cardiac care units | 39 (25.3 %) | |
| Working shift | ||
| A, B, C shift | 124 (80.5%) | |
| Day and night shift | 30 (19.5) |
3.2. The scores of depression, anxiety, stress, CS, STS, BO, and mindfulness
The participants' mean scores (SD) on depression, anxiety, stress, BO, STS, and CS, were17.65 (5.07), 15.92 (5.8), 21.81(6.16), 28.33 (5.74), 27.92 (7.35), and 35.72 (7.44), respectively. Overall, these mean scores can be interpreted as severe anxiety levels and moderate levels of stress, depression, BO, STS, and CS. The mean score of mindfulness was 2.70 (SD = 0.6) out of 6.
3.3. Differences in negative emotional states and ProQOL based on the categorical demographic variables
Table 2 presents the differences in the main study variables based on marital status, type of hospital, type of department, type of shift, gender, and level of education. As shown in Table 2, females had significantly higher stress scores than males (p = .049). In addition, nurses with a master's degree had significantly higher stress than those with a bachelor's degree (p = .043). Further, unmarried nurses had higher burnout levels than married nurses (p = .02). No other significant difference in the scores of the main study variables was noted based on the categorical demographic variables.
Table 2.
Differences in negative emotional states and ProQOL based on the categorical demographic variables
| Variable | Category | Anxiety | Depression | Stress | STS | BO | CS | Mindfulness |
|---|---|---|---|---|---|---|---|---|
| Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | ||
| Gender | Male | 14.76 (10.00) | 17.21 (9.80) | 20.33 (9.86) | 27.23 (7.76) | 28.50 (5.88) | 35.92 (8.37) | 3.77 (0.96) |
| Female | 17.31 (9.50) | 18.17 (10.45) | 23.57 (10.33) | 28.76 (6.80) | 28.14 (5.62) | 35.49 (8.59) | 3.62 (0.86) | |
| t | −1.61 | −0.59 | −1.99* | −1.29 | .38 | .31 | .98 | |
| p‐value | .109 | .559 | .049 | .199 | .702 | .754 | .331 | |
| Education | Bachelor's | 15.34 (9.91) | 17.34 (10.14) | 20.94 (10.07) | 27.42 (7.32) | 28.11 (5.54) | 36.20 (8.20) | 3.76 (0.925) |
| Master | 18.07 (9.35) | 18.79 (9.94) | 24.97 (10.04) | 29.76 (7.29) | 29.18 (6.48) | 33.97 (9.15) | 3.47 (0.89) | |
| t | −1.42 | −0.73 | −2.04* | −1.63 | −0.95 | 1.35 | 1.65 | |
| p‐value | .159 | .466 | .043 | .106 | .343 | .180 | .101 | |
| Marital status | Unmarried | 18.22 (9.54) | 18.89 (9.52) | 23.33 (8.83) | 29.78 (7.50) | 30.28 (5.39) | 33.53 (8.41) | 3.58 (0.92) |
| Married | 15.22 (9.83) | 17.27 (10.25) | 21.34 (10.63) | 27.36 (7.25) | 27.75 (5.74) | 36.39 (8.38) | 3.74 (0.92) | |
| t | 1.61 | 0.84 | 1.03 | 1.74 | 2.35* | −1.79 | −0.87 | |
| p‐value | .109 | .401 | .305 | .084 | .020 | .075 | .386 | |
| Unit | general ICU | 14.22 (9.97) | 17.78 (9.97) | 19.93 (10.21) | 26.74 (7.06) | 28.89 (4.99) | 34.00 (8.29) | 3.91(0.99) |
| Surgical ICU | 14.59 (9.70) | 15.93 (8.62) | 20.81 | 27.26 (7.90) | 28.56 (5.51) | 32.96 (10.23) | 3.56(0.85) | |
| medical ICU | 16.56 (9.18) | 19.81 (11.06) | 24.50 (9.68) | 28.97 (7.23) | 28.97 (5.77) | 35.81 (8.19) | 3.67(1.02) | |
| Picu | 16.21 (10.64) | 17.17 (10.72 | 22.41 (10.79) | 29.00 (6.51) | 27.24 (6.12) | 39.03 (8.79) | 3.49 (0.83) | |
| cardiac unit | 17.28 (9.93) | 17.33 (10.37) | 21.13 (10.66) | 27.59 (7.99) | 28.10 (6.23) | 36.28 (6.38) | 3.84 (0.89) | |
| F | 0.55 | 0.59 | 0.92 | 0.57 | 0.44 | 2.23 | 1.10 | |
| p‐value | .702 | .673 | .452 | .687 | .778 | .069 | .354 | |
| Type of Hospital | Governmental | 18.04 (10.57) | 19.51 (11.29) | 23.09 (11.02) | 28.89 (7.37) | 28.26 (6.12) | 36.35 (8.26) | 3.70 (0.94) |
| University | 14.16 (8.83) | 15.71 (8.96) | 20.55 (9.44) | 26.93 (7.05 | 28.08 (5.59) | 35.53 (8.35) | 3.64 (0.83) | |
| Private | 16.57 (10.36) | 19.62 (9.54) | 22.86 (10.23) | 28.86 (8.25) | 29.48 (5.37) | 34.71 (9.56) | 3.90 (1.16) | |
| F | 2.64 | 2.84 | 1.14 | 1.36 | 0.49 | 0.32 | .540 | |
| p‐value | .074 | .061 | .321 | .260 | .613 | .723 | .619 | |
| Shift | A,B,C | 16.35 (10.01) | 17.83 (10.18) | 22.16 (10.21) | 28.04 (7.39) | 28.57 (5.78) | 35.12 (8.54) | 3.69 (0.88) |
| day, night | 14.13 (8.97) | 16.87 (9.77) | 20.33 (10.02) | 27.43 (7.33) | 27.40 (5.59) | 37.97 (7.79) | 3.76 (1.09) | |
| t | 1.11 | .47 | .88 | .40 | 1.00 | −1.63 | −.39 | |
| p‐value | .268 | .637 | .379 | .268 | .637 | .379 | .268 |
Abbreviation: ProQOL, professional quality of life.
p < .05
p < .01.
3.4. The relationship of the continuous variables with negative emotional states and ProQOL
As shown in Table 3, none of the continuous demographic variables (i.e., age, years of nursing experience, years of hospital experience, and years of experience in the critical care unit) was significantly associated with the main study variables (p > .05 for all of them). Regarding the relationship between mindfulness and negative emotional states, there were significant negative correlations between mindfulness and both stress (r = − 0.230, p = .004) and depression (r = − 0.190, p = .018). Although mindfulness was negatively associated with anxiety, this relation was not significant (r = −0.156, p = .054). Regarding the relationship between mindfulness and the ProQOL, mindfulness was significantly and negatively associated with burnout (r = − 0.218, p = .007) and STS (r = − 0.168, p = .037). Although mindfulness was positively associated with CS, this relation was not significant (r = .047, p = .0563).
Table 3.
The relationship of the continuous demographic variables with negative emotional states and ProQOL
| Variable | Anxiety | Depression | Stress | STS | BO | CS | |
|---|---|---|---|---|---|---|---|
| Age | r | −0.115 | −0.037 | −.100 | −.097 | −.080 | .076 |
| p | .156 | .653 | .217 | .231 | .324 | .348 | |
| Experience in nursing | R | −0.107 | −.034 | −.075 | −.147 | −.066 | .013 |
| p | .188 | .677 | .356 | .069 | .419 | .868 | |
| Hospital experience | R | −0.108 | −.006 | −.085 | −.057 | −.043 | .043 |
| p | .181 | .937 | .293 | .484 | .596 | .593 | |
| Experience in the ICU | R | −0.072 | −.093 | −.078 | −.087 | −.086 | .084 |
| p | .377 | .249 | .336 | .285 | .291 | .303 | |
| Mindfulness | R | −0.156 | −.190* | −.230** | −.168* | −.218** | .047 |
| p | .054 | .018 | .004 | .037 | .007 | .563 |
Abbreviations: BO, burnout; ICU, intensive care unit; ProQOL, professional quality of life; STS, secondary traumatic stress.
3.5. The unique relationship between mindfulness and negative emotional states
The regression analysis which was conducted to examine the unique predictors of depression is shown in Table 4. Based on the previous analysis, mindfulness was significantly associated with depression. However, none of the demographic variables was correlated with depression. Therefore, only mindfulness was entered into the regression analysis. The overall regression model was statistically significant, F (1, 152) = 5.70, p < .05, R = 0.19, R square = 0.036, adjusted R square = 0.03. The model explained 3% of the variance in depression. The model shows that when mindfulness increases by one standard deviation, depression will decrease by .19 standard deviations (β = −0.19, t = −2.388, p = .018).
Table 4.
The unique relationship between mindfulness and the main study variables
| Mindfulness and depression | ||||||
|---|---|---|---|---|---|---|
| Model | B | Std. Error | β | t | p‐value | |
| 1 | (Constant) | 25.339 | 3.318 | 7.636 | .000 | |
| Mindfulness | −2.078 | 0.870 | −.190 | −2.388 | .018 | |
| Mindfulness and Stress | ||||||
| 1 | (Constant) | 12.205 | 3.435 | 3.553 | .001 | |
| Gender | 3.238 | 1.613 | .159 | 2.007 | .046 | |
| Education | 4.028 | 1.957 | .163 | 2.058 | .041 | |
| 2 | (Constant) | 21.666 | 5.017 | 4.319 | .000 | |
| Gender | 2.915 | 1.590 | .143 | 1.834 | .069 | |
| Education | 3.369 | 1.940 | .136 | 1.736 | .085 | |
| Mindfulness | −2.214 | 0.869 | −.201 | −2.549 | .012 | |
| Mindfulness and STS | ||||||
| 1 | (Constant) | 32.887 | 2.432 | 13.525 | .000 | |
| Mindfulness | −1.342 | 0.638 | −.168 | −2.104 | .037 | |
| Mindfulness and Burnout | ||||||
| 1 | (Constant) | 32.810 | 1.959 | 16.749 | .000 | |
| Marital status | −2.532 | 1.079 | −.187 | −2.348 | .020 | |
| 2 | (Constant) | 37.213 | 2.550 | 14.595 | .000 | |
| Marital status | −2.336 | 1.061 | −.173 | −2.202 | .029 | |
| Mindfulness | −1.284 | 0.488 | −.206 | −2.628 | .009 | |
The regression analysis which was conducted to examine the unique predictors of stress is shown in Table 4. Based on the previous analysis, three variables were correlated with stress including gender, education, and mindfulness. Gender and education were entered into the first model, while mindfulness was entered into the second model. The two models were statistically significant, Model 1: F (2, 151) = 4.132, p = .018, R = 0.228, R square = 0.052, adjusted R square = 0.039. The model explained 3.9% of the variance in stress. For Model 2: F (3, 150) = 5.020, p = .002, R = 0.302, R square = 0.091, adjusted R square= 0.073, R square change = 0.039. Thus, mindfulness explained 3.9% of the variance in stress above and beyond the variance explained by participants' demographics. Notably, in the second model, only mindfulness has a significant contribution in the model (t = −2.549, β = −0.201, p = .012). The model shows that when mindfulness increases by one standard deviation, stress will decrease by −.201 standard deviations (β = −0.19, t = −2.549, p = .012).
3.6. The unique relationship between mindfulness and ProQOL
The regression analysis which was conducted to examine the unique predictors of STS is shown in Table 4. Based on the previous analysis, only mindfulness was significantly associated with STS. Therefore, only mindfulness was entered into the regression analysis. The overall regression model was statistically significant, F (1, 152) = 4.426, p < .05, R = 0.168, R square= 0.028, adjusted R square = 0.022 (Table 4). The model explained 2.2% of the variance in STS. The model shows that when mindfulness increases by one standard deviation, STS will decrease by .168 standard deviations (β = −0.168, t = −2.104, p = .037).
The regression analysis which was conducted to examine the unique predictors of BO is shown in Table 4. Based on the previous analysis, two variables were correlated with STS including marital status and mindfulness. Marital status was entered into the first model, while mindfulness was entered into the second model. The two models were statistically significant, Model 1: F (1, 151) = 5.511, p = .020, R = 0.187, R square = 0.035, adjusted R square = 0.029. The model explained 2.9% of the variance in BO. For Model 2: F (2, 151) = 6.316, p = .002, R = 0.278, R square = 0.077, adjusted R square = 0.065, R square change = 0.042. Thus, mindfulness explained 4.2% of variance in BO above and beyond the variance explained by marital status. Notably, in the second model, both marital status and mindfulness had significant contributions in the model (p < .05). The model shows that when mindfulness increases by one standard deviation, BO will decrease by .206 standard deviations (β = −0.206, t = −2.628, p = .009).
4. DISCUSSION
In our analysis, the participants had severe anxiety levels and moderate levels of stress and depression. The scores of stress and depression were consistent with the scores reported by Alharbi and Alshehry 28 who showed that the CCU nurses had moderate perceived levels of stress. Besides, a previous research study 29 found that 43% of nurses in the CCU had moderate to severe levels of stress, 82% had moderate to very severe levels of anxiety and 40% had moderate to severe levels of depression. In a study conducted with a sample of critical care nurses during the COVID‐19 pandemic, 48.5% of nurses had severe or extremely severe stress levels, 62% had severe levels of anxiety, and 34.5% had moderate levels of depression. 30
The study participants had moderate levels of burnout, secondary traumatic stress, and compassion satisfaction. This finding in general indicates somewhat higher anxiety scores than a previous study conducted before COVID‐19 pandemic which showed that CCU nurses had low‐to‐average burnout and secondary traumatic stress levels. 11 The results of the current study are also consistent with the previous research on the professional quality of life during disasters and pandemics. For example, in a study 31 conducted in China, there was an elevated risk for the development of compassion fatigue among rescuers and healthcare providers following the Yushu earthquake in 2010. Also, the study results are in line with the results of a recent study, which found moderate levels of CS, burnout, and STS among frontline nurses during COVID‐19 pandemic. 32
Our analysis shows that females had significantly higher stress scores than males. This result is consistent with a previous study conducted in Chinese CCU nurses which shows that female CCU nurses had more psychological disorders than male nurses. 33 Besides, our results are consistent with a previous study which showed that female nurses had higher scores in terms of stress, anxiety, and depression than their male counterparts. 34 Nurses with master's degree had significantly higher stress than those with bachelor's degree. Previous studies showed the opposite of this result. Hegney and colleagues 34 found that a higher educational degree among nurses was associated with lower depression levels. Unmarried nurses had higher levels of burnout than married nurses. This outcome is consistent with previous literature which showed that married professionals had lower burnout levels than those who are unmarried. 35 In the current study, age, gender, and working area were not associated with ProQOL scores. These outcomes contradict the outcomes of a previous study 34 which found that older age was correlated with lower burnout scores and men were more likely than women to have higher burnout scores. Furthermore, in that study, female nurses reported better compassion satisfaction compared with male nurses. The study of Al Barmawi and colleagues 11 also contradicts our finding as it revealed that nurses working in medical CCUs had higher levels of compassion satisfaction than nurses from other units.
Regarding the relationship between mindfulness and negative emotional states, there were significant negative correlations between mindfulness and both stress and depression. This finding is consistent with the previous research which showed that mindfulness has the potential to enhance the psychological well‐being of nurses working with COVID‐19 patients. 36 Heard and colleagues 37 noted that awareness and mindfulness were negatively correlated with depression and anxiety and the facet of consciousness behavior was strongly correlated with all negative measures of depression. These outcomes are in line with the theoretical perspectives and empirical research that support the neural, cognitive, emotional, sensory, and self‐processing networks through which mindfulness can help improve coping and reduce negative emotional states. 38 , 39
Mindfulness was negatively and significantly associated with STS and burnout. These results are consistent with a previous study conducted in South India among nurses in emergency and CCU that showed a decrease in the mean score of BO and STS and an increase in CS in nurses who received an intervention program with mindfulness components. 40 Also, a previous intervention study confirmed the effectiveness of mindfulness intervention for nurses to reduce burnout. 41 These results are also consistent with a previous research study 42 which reported that mindfulness significantly predicts burnout and STS among nurses.
It is noteworthy to mention that, in the current study, mindfulness had very low predictive power on professional quality of life and negative emotional states among critical care nurses. However, we cannot state that mindfulness‐based interventions would be ineffective in helping these nurses. The low predictive power of mindfulness in this study could be due to the characteristics of the sample which included a homogeneous group of participants with severe anxiety levels (M = 15.92, SD = 5.8) and low mindfulness scores (M = 2.70, SD = 0.6). Thus, mindfulness could have had a better predictive power on the study variables if there was more variability in mindfulness scores. Research has shown that the combination of low mindfulness and high anxiety is associated with deficits in attentional network, cognitive inhibition, and reduction in visual working memory capacity. 43 In addition, high anxiety is associated with low acceptance and mindfulness skills. 44 This suggests a need to conduct mindfulness training for the study participants to increasing their mindfulness, which could show a better predictive power on professional quality of life and negative emotional states among the study participants.
5. STUDY RECOMMENDATIONS AND IMPLICATIONS
Anxiety, depression, stress, and compassion fatigue pose a significant threat to the health and safety of critical care nurses and patients alike. The need for effective interventions or strategies that mitigate the harmful effects of negative emotional states and compassion fatigue has become more apparent. Using mindfulness as a coping strategy may help critical care nurses reduce negative emotional states and compassion fatigue during the pandemic.
Future intervention studies are necessary to ensure proper mindfulness‐based programs to enhance CS and reduce negative emotional states and compassion fatigue in the workplace. Conducting research studies to identify current occupational risks affecting nurses in the CCU is also important to develop possible strategies that can help reduce these risks in hospitals.
The negative emotional states of CCU nurses need to be addressed from a systematic, organizational, and holistic approach. Nurse leaders and policymakers should be encouraged to take action to improve nurses' working conditions while maintaining attention to the emotional responses of nurses who provide care for patients with life‐threatening conditions. Reducing burnout and keeping experienced nurses in the profession should be a priority for nursing administrators. Also, nursing administrators need to develop effective policies to reduce stressors at work. Future training on basic mindfulness skills for nurses should be considered a priority to better cope with stressors, particularly during periods of pandemics.
Involvement of the continuous education department to introduce in‐service education programs related to mindfulness training programs could be needed to enhance the awareness of nurses about mindfulness and its benefits. Nursing educators may want to enroll their students in mindfulness‐based stress reduction (MBSR) programs to acquire basic mindfulness knowledge and skills, which can then be disseminated to their patients.
6. CONCLUSION
Improving the psychological health of nurses, reducing their anxiety, stress, and depression levels, improving their professional quality of life, and developing a strategy to support them during the COVID‐19 pandemic are of utmost importance in the CCU. It was found that mindfulness and negative emotional states were significantly and negatively correlated. As well, mindfulness was significantly and negatively associated with BO and STS. Considering the outcomes of the current study, it can be concluded that mindfulness is one of the important coping strategies that have the possibility to support CCU nurses, reduces their negative emotional states, and improves their ProQOL during the COVID‐19 pandemic. Therefore, mindfulness can be used as a helpful strategy for reducing nurses' negative emotional states and improving their ProQOL in high‐strain work environments.
CONFLICTS OF INTEREST
The authors declare no conflicts of interest.
ETHICS STATEMENT
The IRB was obtained for this research (IRB number: 122020). The research conforms to the provisions of the Declaration of Helsinki (as revised in Brazil 2013). All participants gave informed consent for the research, and their anonymity was preserved.
Abu‐Horirrah HA, Rayan AH, Eshah NF, ALBashtawy MS, Masa'deh R. The association of mindfulness with professional quality of life and negative emotional states among critical care nurses during COVID‐19 pandemic. Nurs Forum. 2022;57:1381‐1389. 10.1111/nuf.12828
DATA AVAILABILITY STATEMENT
The data sets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data sets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.