Journal of Mental Health

ISSN: 0963-8237 (Print) 1360-0567 (Online) Journal homepage: http://www.tandfonline.com/loi/ijmh20

A non-linear relationship between the cumulative exposure to occupational stressors and nurses’ burnout and the potentially emotion regulation factors Ji-Wei Sun, Ping-Zhen Lin, Hui-Hui Zhang, Jia-Huan Li & Feng-Lin Cao To cite this article: Ji-Wei Sun, Ping-Zhen Lin, Hui-Hui Zhang, Jia-Huan Li & Feng-Lin Cao (2017): A non-linear relationship between the cumulative exposure to occupational stressors and nurses’ burnout and the potentially emotion regulation factors, Journal of Mental Health, DOI: 10.1080/09638237.2017.1385740 To link to this article: http://dx.doi.org/10.1080/09638237.2017.1385740

Published online: 08 Oct 2017.

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Date: 11 October 2017, At: 18:14

http://tandfonline.com/ijmh ISSN: 0963-8237 (print), 1360-0567 (electronic) J Ment Health, Early Online: 1–7 ß 2017 Informa UK Limited, trading as Taylor & Francis Group. DOI: 10.1080/09638237.2017.1385740

ORIGINAL ARTICLE

A non-linear relationship between the cumulative exposure to occupational stressors and nurses’ burnout and the potentially emotion regulation factors Downloaded by [UNIVERSITY OF ADELAIDE LIBRARIES] at 18:14 11 October 2017

Ji-Wei Sun, Ping-Zhen Lin, Hui-Hui Zhang, Jia-Huan Li, and Feng-Lin Cao School of Nursing, Shandong University, Jinan, China

Abstract

Keywords

Background: Stressful situations can increase the likelihood of nurses experiencing negative emotions, especially burnout. Aims: To explore the association of cumulative exposure to occupational stressors and emotion regulation strategies with nurses’ burnout. Methods: Participants were 602 nurses from three general hospitals in Jinan, China. Social demographic characteristics, occupational stress, burnout, and emotion regulation strategies (cognitive reappraisal, expressive suppression, and rumination), were assessed. Results: Nearly 70% of nurses reported that they were burnt out. Those with a moderate level and high level of stressors were 3.203 times and 26.444 times more likely to have burnout, respectively (2trend ¼ 62:732). Logistic regression revealed that nurses had higher cognitive reappraisal score (odds ratios (OR) ¼ 0.941), scored lower for burnout. Those who had higher expressive suppression score (OR ¼ 1.054), higher rumination score (OR ¼ 1.037), and a higher level of stressors (OR ¼ 2.779–18.259) scored higher for burnout. The results of sensitivity analysis were similar. Conclusions: A non-linear relationship exists between the cumulative exposure to occupational stressors and nurses’ burnout. Those who less frequently use cognitive reappraisal, more frequently use rumination and expressive suppression, and have a high level of stressors may be more likely to experience burnout.

Nurse, stress, burnout, emotion regulation

Introduction Stressful situations can increase the likelihood of experiencing negative emotions (Lazarus & Folkman, 1984). As we all know, chronic stress often results in burnout (Felton, 1998). Burnout ‘‘In March, 2016, Vivek Murthy, the US Surgeon General, declared that burnout among health-care workers was one of the two most pressing health problems in the nation to be addressed during the subsequent year’’ (Epstein & Privitera, 2017, p. 1398). Burnout is a significant psychological public health problem characterized by emotional exhaustion (EE), depersonalization (DP), and low personal accomplishment (PA) (Maslach & Leiter, 2008; Maslach et al., 1996, 2001), which occurs especially in nurses (Skinner et al., 2012). The prevalence of burnout was reported to be 32–54% among nurses in five different countries (Aiken et al., 2002; Kravits et al., 2010). The data from studies of health service providers (such as physicians and nurses) have shown that burnout has serious consequences that go beyond the negative effects experienced by the individual health care provider Correspondence: Feng-Lin Cao, School of Nursing, Shandong University, Jinan, China. E-mail: [email protected]

History Received 7 March 2017 Revised 29 July 2017 Accepted 20 August 2017 Published online 6 October 2017

(depression, sleeplessness, and illness) (Ahola & Hakanen, 2007; Ahola et al., 2014; Bianchi et al., 2015, 2017; Wolfe, 1981). Public health significance of job-related distress is large and costly in both human and financial terms (Bianchi et al., 2017; Epstein & Privitera, 2017; Maslach & Leiter, 2017). With the worldwide shortage of nurses, nurse burnout is considered one of the main contributing factors and has been the focus of studies. For example, now that evidence suggests that burnout negatively affects medical personnel’s effectiveness and availability to patients, as well as patient safety, healthcare organizations and the public are justifiably worried about quality of patient care and the condition of healthcare institutions (Epstein & Privitera, 2016). According to the transactional stress theory, factors related to burnout are categorized as personal factors or environmental factors, which have been confirmed by empirical studies (Garrosa et al., 2008; Wang et al., 2015). Occupational stress Occupational stress is stress related to one’s job. Working in a hospital can be very stressful for nurses. Nurses face much occupational stress from exposure to pain and death, heavy workload, sensitive interpersonal relationships, lack of support from supervisors. A broad range of studies on nurses’

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occupational stress show that individuals with high levels of one or more burnout dimensions had higher average scores on perceived stress (Fernandez-Sanchez et al., 2017; Wang et al., 2015). Recent research indicates that there may be a relationship between occupational stressors and job burnout. Furthermore, any direct effect of occupational stress on burnout is not yet clear. Simultaneously, nurses exposed to long-term occupational stress may be more burnt out if their coping strategies are poor (Felton, 1998; Folkman & Greer, 2000). Thus, it becomes meaningful to explore whether an obvious dose– response relationship exists between occupational stressors and burnout, and the relevant factors influencing burnout in nursing professionals, to provide a new perspective of psychotherapy for nurses with burnout. To our knowledge, a factor that affects a person’s emotion can play a crucial role in burnout. How do nurses cope with burnout based on their emotion regulation strategies? Emotion regulation refers to the process of how individuals influence which emotions they have, when they have them, and how they experience and express them (Gross & John, 2003). The assessment of emotion regulation strategies can be a means to further characterize the control processes that are involved in burnout (Abler et al., 2007). Emotion regulation strategies According to their findings of the influence of emotion regulation, Aldao & Nolen-Hoeksema (2010) proposed that different emotion regulation strategies can be divided into adaptive and maladaptive strategies. According to Gross (1998), cognitive reappraisal and expressive suppression are the commonly used emotion regulation strategies. In addition, rumination is the most common maladaptive emotional regulation strategy. Thus, cognitive reappraisal, expressive suppression, and rumination were three emotion regulated strategies we explored. Cognitive reappraisal (CR) ‘‘Reappraisal refers to the reinterpretation of an emotional event with the goal of changing the subsequent emotion’’ (Giuliani & Gross, 2009, pp. 329–330). It can be seen as a form of cognitive change that is able to successfully reduce distress or negative future emotions by generating positive interpretations of a stressful situation (Koole, 2009; Lazarus & Alfert, 1964). Empirical evidence proves that cognitive reappraisal should be adaptive across a variety of contexts (Aldao & Nolen-Hoeksema, 2010; Aldao et al., 2010; Gross, 2015; Nolen-Hoeksema et al., 2008), and has a rather protective effect (Gross & John, 2003) concerning mood distress, which indicates that the use of adaptive emotion regulation strategies may be fostered by the ability to experience feelings consciously. Positive reappraisal as a cognitive emotion regulation strategy was found to significantly predict lower level of DP (Bamonti et al., 2017). Expressive suppression (ES) Expressive suppression is considered to involve the inhibition of ongoing emotion–expressive behavior (Gross & Levenson,

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1993; Lazarus & Alfert, 1964) and related to negative cognition and depression (Subic-Wrana et al., 2014). It is commonly associated with maladaptive psychological and social outcomes and less effective regulation (Aldao et al., 2010; Gross, 2015). Studies on the relationship between expressive suppression and burnout are scarce. Only one research showed that expressive suppression significantly moderates the relationship between positive experienced emotions and EE (Bassal et al., 2016). Rumination (R) Rumination is a sustaining cognitive process that involves being repetitively and unintentionally perseverative, passively focusing on negative emotions, which is seen as a maladaptive regulation strategy (Nolen-Hoeksema et al., 2008; Smith & Alloy, 2009; Treynor et al., 2003). Although rumination has been linked to various forms of psychopathology including depression (Malmberg & Larsen, 2015), anxiety, and alcohol misuse (Nolen-Hoeksema, 2012), one study indicated that rumination was positively related to EE and might be one of the psychological processes involved in EE (Donahue et al., 2012). Aims The aims of the study were to identify (1) whether a specific relationship exists between the cumulative exposure to occupational stressors and burnout; and (2) whether different emotion regulation strategies play different roles in nurses’ burnout.

Methods Design A cross-sectional study using a survey was conducted to examine job burnout among nurses experiencing occupational stressors, along with the relative impact of different emotion regulation strategies. Participants Participants included registered nurses from three hospitals in Jinan, Shandong Province, China. We selected six separate units (medical ward, surgical ward, obstetrics and gynecology ward, pediatric ward, emergency ward, and intensive care ward) in each hospital. A total of 633 nurses participated voluntarily in the study, with 602 returning the survey with usable data, for an effective return rate of 95.1%. The participants completed a battery of questionnaires in a fixed order (see below). Two assistants were always available to aid and to ensure the confidentiality and independence of the participants’ responses. Measures The nurses’ job stressor scale (NJSS) The NJSS (Xiaomei & Yanjun, 2000) examines potential stressors that may affect nurses. This scale is a wellestablished self-report measure of occupational stress among Chinese nurses (Li-hui et al., 2009). The participants were asked to rate each item using a five-point Likert scale ranging

Cumulative exposure of occupational stressors

DOI: 10.1080/09638237.2017.1385740

from 1 (not at all) to 4 (extremely strong). Adequate scale reliability was ensured for the present sample (Cronbach’s  ¼ 0.931). The total scale score was obtained by summing all the item scores. A higher score indicates a higher level of occupational stressors.

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The Maslach burnout inventory–human services survey (MBI–HSS) The Maslach burnout inventory–human services survey (MBI–HSS) (Leiter & Harvie, 1996) is a well-established measure of burnout that consists of 22 questions. It measures three aspects of burnout, and scores range from 0 (never) to 6 (everyday). The MBI–HSS evaluates the respondent’s level of EE, DP, and PA. Scores on each subscale are computed by summing the numeric responses. In this study, Cronbach’s  was 0.781 for the total scale, 0.842 for EE, 0.691 for DP, and 0.827 for PA. High burnout is characterized by high EE (27), high DP (8), and low PA scores (24) (Zhi-hong et al., 2008). The emotion regulation questionnaire (ERQ) The emotion regulation questionnaire (ERQ) (Gross & John, 2003) contains 10 items to assess emotion regulation strategies (expressive suppression and cognitive reappraisal). Participants answer on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree), and higher scores reflect more use of a certain strategy. The ERQ has been shown to be a reliable and valid measure of emotion regulation; Cronbach’s alpha in the present study was 0.877 for cognitive reappraisal and 0.695 for expressive suppression. The ruminative responses scale (RRS) The RRS (Nolen-Hoeksema & Morrow, 1991) is a 22-item self-report measure used to assess rumination. Using a 4-point Likert scale ranging from 1 (almost never) to 4 (almost always), participants indicate the extent to which they ruminate on negative content when feeling sad, blue, or depressed. A higher score on this scale indicates more rumination. This scale has good validity and a stable structure that supports the multidimensional nature of rumination (Schoofs et al., 2010). The Cronbach’s alpha of RRS in this study was 0.93 for the whole scale. Covariates Demographic characteristics, including age, gender, years of work, highest level of education, monthly salary, type of ward, beds/nurses (number of beds/nurses in a ward), were measured using a self-report questionnaire. Statistical analysis Statistical analyses were performed using the SPSS software (version 16.0; SPSS, Chicago, IL, USA). All reported p values are two-sided (with values less than 0.05 considered to indicate statistical significance). Missing data were replaced with the mean of nearby points. We divided burnout into binary data: ‘‘positive burnout group’’ coded 1 and ‘‘negative burnout group’’ coded 0. The data analysis was carried out using Student’s t-test,

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Chi-squared trend tests. Factors associated with a high risk of burnout were entered into a binary logistic regression model. (1) Frequencies and percentages were used to describe the distributions of participants according to age, gender, years of work, final education, monthly salary, allocation to clinical ward, beds/nurses, etc. (2) Student’s t-test was used to show the differences in occupational stressors and emotion regulation strategies between the positive burnout group and negative burnout group. (3) Chi-squared trend tests were used to access the trend of mild/moderate/high occupational stressors’ impact on nurses’ burnout. (4) Logistic regression analysis (forward selection) was used. Different levels of occupational stressors, emotion regulation strategies as predictors of high burnout while controlling the nurses’ characteristics (age, gender, final education, years of work, and allocation to clinical ward) and hospital variables (bed size). Odds ratios (OR) and 95% confidence intervals for risk were calculated on the basis of model-variable coefficients and standard errors, respectively. (5) We conducted a sensitivity analysis with linear regression and curvilinear regression to further explore the relationship between the cumulative exposure to occupational stressors and nurses’ burnout. The MBI–HSS total scores was dependent variable, each category of occupational stress was set dummy variable. Ethical considerations This study was approved by the ethics committee (ethical approval no. M2015039). All study participants provided written informed consent.

Results Descriptive statistics for demographic characteristics The study participants included 602 nurses in three hospitals. The mean age of all participants was 28.54 years (SD 5.53 years). The maximum year as a registered nurse was 32 years. Most nurses were women (97%) and most had a bachelor degree (75.9%). The proportion of nurses working in the medical, surgical, obstetrics and gynecology, pediatric, emergency, and intensive care wards was 29.5%, 32.9%, 10.5%, 8.5%, 7.7%, and 10.9% respectively (Table 1). Burnout Of the nurses, 34.4% met the threshold for high EE (27), 42.2% for high DP (8), and 26.1% for low PA (24) (Zhi-hong et al., 2008). Overall, 63.8% had at least one aspect on burnout and 36.2% did not. Independent sample t-tests were conducted to identify the differences between the positive burnout group and negative burnout group. In this study, the occupational stressors scores, cognitive reappraisal, expressive suppression, and rumination showed significant differences in these two groups (Table 1). There were significant differences between the two burnout groups in the different clinical wards (2 ¼ 11.785) (Table 1).

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Table 1. Descriptive statistics of demographic characteristics and variables (n ¼ 602).

Age 20–29 years 30–39 years 40 years Years as a RN Beds/nurses Gender Male Female Final education Below college College and above Monthly salary (dollar)a 5290 290–435 435–580 580–725 725–870 Departmentsa MW SW OGW PW EW ICU Occupational stressors score Emotion regulation strategies Cognitive reappraisal Expressive suppression Rumination

n

M  SD

602 448 131 23 602 602

28.54  5.53 25.79  2.23 35.08  2.58 44.70  3.55 6.45  6.16 3.22  2.07

Percentage/ positive rate

Positive burnout group (n¼ 384)

Negative burnout group (n ¼ 218)

28.41  5.19

28.76  6.08

2/t

p

0.708

0.479

3.069

0.087

0.024

0.876

8.262

0.082

74.4% 21.8% 3.8%

18 584

3% 97%

15 (83.3%) 369 (63.2%)

3 (16.7%) 215 (36.8%)

143 459

23.8% 76.2%

51 (35.7%) 167 (36.4%)

92 (64.3%) 292 (63.6%)

107 127 136 106 123

17.8% 21.1% 22.6% 17.6% 20.4%

177 197 63 51 46 65 602

29.5% 32.9% 10.5% 8.5% 7.7% 10.9%

602 602 602

60 86 87 77 73

(56.1%) (67.7%) (64.0%) (72.6%) (59.3%)

47 41 49 29 50

(43.9%) (32.3%) (36.0%) (27.4%) (40.7%)

104 (58.8%) 130 (66.0%) 33 (52.4%) 37 (72.5%) 36 (78.3%) 42 (64.6%) 68.22  12.43

11.785

0.038

75.40  15.19

73 (41.2%) 67 (34.0%) 30 (47.6%) 14 (27.5%) 10 (21.7%) 23 (35.4%) 79.48  15.12

9.868

50.001

30.42  6.43 15.47  4.58 43.10  10.02

29.59  6.39 15.86  4.47 45.03  10.29

31.87  6.26 14.77  4.69 39.71  8.54

4.222 2.817 6.463

50.001 0.005 50.001

RN: registered nurse; MW: medical ward; SW: surgical ward; OGW: obstetrics and gynecology ward; PW: pediatric ward; EW: emergency ward; ICU: intensive care unit.

Table 2. The relationship between occupational stressors and burnout (n ¼ 602).

Occupational stressors High stress Moderate stress Mild stress

Positive burnout group (n)

Negative burnout group (n)

OR (95% CI)

84 273 27

6 161 51

26.444 (10.221, 68.416) 3.203 (1.932, 5.310) 1.000

Table 3. The independence analysis of risk factors for nurses’ burnout: forward analysis of the odds ratio value. Occupational stressors

2trend ¼ 62.732, p50.001.

The relationship between the cumulative exposure to occupational stressors and burnout The total occupational stressors scores were 75.40  15.19. We classified the occupational stressors scores into ‘‘mild occupational stressors’’ for scores that were less than mean 1 SD (N ¼ 78), ‘‘high occupational stressors’’ for scores that were more than mean þ1 SD (N ¼ 90), and ‘‘moderate occupational stressors’’ for scores that were between mean 1 SD and mean þ1 SD (N ¼ 434) to examine the relationship between levels of occupational stressors and burnout. The results indicated that nurses exposed to a moderate level of occupational stressors were 3.203 times more likely to have burnout symptoms than nurses exposed to a mild level of occupational stressors, while those exposed to a high level of occupational stressors were 26.444 times more likely to have burnout than those exposed to a mild level of stressors (2trend ¼ 62.732) (Table 2).

Model 1 Model 2 Model 3

Emotion regulation strategies

High

Moderate

CR

ES

R

26.444*** 16.204*** 18.259***

3.203*** 2.723*** 2.779***

0.936*** 0.941***

1.054* 1.054*

1.037** 1.037**

*p50.05. **p50.01. ***p50.001. Model 1: Mild/moderate/high level of occupational stressors. Model 2: Model 1 þ emotion regulation strategies (CR, ES, R). Model 3: Model 2 þ other covariables. CR: cognitive reappraisal; ES: expressive suppression; R: Rumination.

We tested three models in this study (Table 3). Model 1 included mild/moderate/high level of occupational stressors; Model 2 included Model 1 þ emotion regulation strategies (CR, ES, and R); Model 3 included Model 2 þ other covariables. We adopted logistic regression analysis (forward selection) for the independence analysis. Exposed to higher level of occupational stressors is still significant for burnout, which can prove the independence, when model 2–3 included emotion regulation strategies and other covariables. Logistic regression revealed that nurses who had a higher level of stressors (OR ¼ 2.779–18.259) scored higher for burnout after controlling covariables (model 3, Table 3).

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DOI: 10.1080/09638237.2017.1385740

Figure 1. A non-linear relationship between occupational stressors and burnout. Note: ‘‘Mild Occupational Stressors’’: scores that were less than mean 1 SD (N ¼ 78), ‘‘High Occupational Stressors’’: scores that were more than mean þ1 SD (N ¼ 90), ‘‘Moderate Occupational Stressors’’: scores that were between mean 1 SD and mean þ1 SD (N ¼ 434).

Additionally, the results of sensitivity analysis similarly showed that it is improper to describe it as linear relationship. Thus, there exists a non-linear relationship between burnout and occupational stressors (Figure 1). The relationships between emotion regulation strategies and burnout For the three emotion regulation strategies, the mean scores (and SDs) for cognitive reappraisal, expressive suppression, and rumination were 30.42 (6.43), 15.47 (4.58), and 43.10 (10.02), respectively. Logistic regression revealed that nurses with higher cognitive reappraisal subscale scores (OR ¼ 0.939), scored lower for burnout. Those who had higher expressive suppression subscale scores (OR ¼ 1.054), and higher rumination scores (OR ¼ 1.037) scored higher for burnout when controlling covariables (Table 3).

Discussion In this study, we found that (1) a non-linear relationship exists between the cumulative exposure to occupational stressors and burnout. Exposure to a high level of stressors increased the risk of burnout among nurses, and was nearly 20 times as high when controlling confounding factors; and (2) Expression suppression and rumination positively predicted burnout, while cognitive reappraisal negatively predicted burnout. Consistent with previous studies (Wang et al., 2015), we observed that occupational stressors could positively predict burnout. Nurses with a perception of excessive workload can experience physical and mental exhaustion, which can lead to burnout. To our surprise, there is an obvious non-linear relationship that verifies the cumulative effect of occupational stressors on burnout. The impact of high occupational stressors on burnout is much higher than that of moderate stressors, so that it can reach 26.444 times when compared to mild stressors. These results suggest that exposure to a high

Cumulative exposure of occupational stressors

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level of occupational stressors may be more explanatory of burnout. An alternative explanation is that it is a set of psychological responses to the job burnout in relation to cumulative occupational stressors, especially among nurses. Therefore, our results suggest a need to pay special attention to nurses’ occupational stressors. Earlier studies (Ko & KiserLarson, 2016; Wang et al., 2015) have shown that professional and career issues, workload, time pressure, resource and environmental problems, patient care and interaction, and interpersonal relationship and management issues are the major occupational stressors occurring among nurses that can contribute to the risk of developing burnout. Likewise, good stress management has important implications for nurses’ burnout and retention (Pipe et al., 2009). The logistic regression revealed that nurses with higher cognitive reappraisal subscale scores, scored lower for burnout. Those who had higher expressive suppression subscale scores, higher rumination scores, and a higher level of stress scored higher for burnout. Occupational stressors, cognitive reappraisal, expressive suppression, rumination, and age were independent predictors of burnout. In our study, 524 nurses were exposed to moderate to high levels of occupational stressors, but only 357 of these nurses experienced burnout. Thus, burnout developed in many nurses exposed to a moderate to high level of occupational stressors. Many studies focus on nurses’ use of effective coping strategies to prevent or manage occupational stressors in the case of suffering from burnout (Ko & Kiser-Larson, 2016) but there has been little specific attention paid to the roles of different emotion regulation strategies. In our study, as we expected, efficient cognitive appraisal led to better results, such as less job burnout, than expression suppression and rumination because maladaptive emotion regulation strategies result in more job burnout. For example, cognitive reappraisal as an adaptive emotion regulation strategy is related to less self-reported negative affect (Aldao et al., 2010); when individuals use more cognitive reappraisal, they evaluate the difficulties from a positive perspective and find more valuable and meaningful aspects, which contributes to reducing the amount of burnout on some level. On the contrary, when more frequent expression suppression and rumination are used, nurses suppress their negative emotion and continue to think about their work, ruminate about work-related problems, or reflect on their leader’s demands, and consequently deplete their energy level after regular work hours. When staying psychologically attached to their work during evening hours and weekends, individuals may not fully benefit from their time off work and eventually may come to experience EE (Donahue et al., 2012). Several studies have implied that meditation has an effect on brain areas associated with emotion regulation (Chiesa et al., 2013) and improves emotional adaptation through keeping attention (Desbordes et al., 2012). One study (Duarte & Pinto-Gouveia, 2016) about the effectiveness of a mindfulness-based intervention on oncology nurses’ burnout showed that interventions may play a role in reducing oncology nurses’ psychological symptoms and burnout and improving their overall well-being; thus, longitudinal studies are needed in future to explore the effects of interventions on the relationships between the cumulative exposure to

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occupational stress, emotion regulation strategies (cognitive reappraisal, expressive suppression, and rumination), and burnout among nurses.

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Limitations A few limitations of the study should be noted. Firstly, a cross-sectional design limits our ability to infer specific causal relationships. However, plenty of studies have identified burnout as an outcome of job stress (Garrosa et al., 2008; Wang et al., 2015). Secondly, we did not explore the effect of occupational stressors and emotion regulation strategies separately on EE, DP, and low PA. However, we did divide burnout into two groups that were based on the positive state of those three dimensions. Thirdly, there is a lack of data from psychiatry wards because it was not feasible to obtain this data in general hospitals, although we had a sizable sample. It has been argued that ‘‘the domain of psychiatry within which nurses work could influence burnout’’ (McTiernan & McDonald, 2015); however, we did not explore this possibility in the present study. Fourthly, the study was limited by lack of objective measures of ‘‘actual’’ stress, but a subjective measure of perceived events and their impact on the person. Finally, most of our participants were women, which also limits the generalizability of our findings. However, the present sample does reflect general gender distributions within the nursing field.

Conclusions The impact of occupational stressors on nurses’ job burnout is significant, and it is necessary to explore the cumulative effect of occupational stressors on burnout. Early identification of this emotional slippage is needed to prevent the DP of the nurse–patient relationship. In our sizable sample, we found that those who less frequently use cognitive reappraisal, more frequently use rumination and expressive suppression, and have a high level of stress may be more likely to experience burnout. Occupational stressors were the biggest factor predicting nurses’ burnout: the higher the level of stress, the higher the level of burnout. Burnout is an occupational disease of health care professionals that must be recognized early and explored in further research.

Declaration of interest No potential conflict of interest was reported by the authors.

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[Treatment of Kienböck's disease using a pyrocarbon implant: case report].

We report on two patients with advanced Kienböck's disease (Lichtman IIIa and IIIb) who underwent surgical treatment in which the lunate was replaced ...
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