ORIGINAL ARTICLE
The impact of emotional intelligence on work engagement of registered nurses: the mediating role of organisational justice Yun Zhu, Congcong Liu, Bingmei Guo, Lin Zhao and Fenglan Lou
Aims and objectives. To explore the impact of emotional intelligence and organisational justice on work engagement in Chinese nurses and to examine the mediating role of organisational justice to provide implications for promoting clinical nurses’ work engagement. Background. The importance of work engagement on nurses’ well-being and quality of care has been well documented. Work engagement is significantly predicted by job resources. However, little research has concentrated simultaneously on the influence of both personal and organisational resources on nurses’ work engagement. Design. A descriptive, cross-sectional design was employed. Methods. A total of 511 nurses from four public hospitals were enrolled by multistage sampling. Data collection was undertaken using the Wong and Law Emotional Intelligence Scale, the Organizational Justice questionnaire and the Utrecht Work Engagement Scale-9. We analysed the data using structural equation modelling. Results. Emotional intelligence and organisational justice were significant predictors and they accounted for 44% of the variance in nurses’ work engagement. Bootstrap estimation confirmed an indirect effect of emotional intelligence on work engagement via organisational justice. Conclusions. Emotional intelligence and organisational justice positively predict work engagement and organisational justice partially mediates the relationship between emotional intelligence and work engagement. Relevance to clinical practice. Our study supports the idea that enhancing organisational justice can increase the impact of emotional intelligence. Managers should take into account the importance of emotional intelligence and perceptions of organisational justice in human resources management and apply targeted interventions to foster work engagement.
What does this paper contribute to the wider global clinical community?
• This study reveals that emotional
•
•
intelligence and organisational justice significantly predict work engagement of clinical nurses. This study also finds that organisational justice plays a mediating role in the relationship between emotional intelligence and work engagement of clinical nurses. This study extends the Job Demands-Resources Model by examining the influence of personal resources and organisational resources simultaneously and provides support that changes are needed to be made to the organisational environment of clinical nurses to increase their work engagement.
Key words: emotional intelligence, nurses, organisational justice, public hospitals, work engagement Accepted for publication: 14 February 2015
Authors: Yun Zhu, RN, PhD Candidate, Associate Professor, School of Nursing, Shandong University, Jinan; Congcong Liu, RN, MMed Candidate, School of Nursing, Shandong University, Jinan; Bingmei Guo, RN, MMed Candidate, School of Nursing, Shandong University, Jinan; Lin Zhao, RN, MMed Candidate, School of Nursing, Shandong University, Jinan; Fenglan Lou, BMed, Professor, School of Nursing, Shandong University, Jinan, China
© 2015 John Wiley & Sons Ltd Journal of Clinical Nursing, 24, 2115–2124, doi: 10.1111/jocn.12807
Correspondence: Fenglan Lou, Professor, School of Nursing, Shandong University, No. 44, Wenhua Xi Road, Jinan, Shandong, 250012, China. Telephone: +86 531 88382003. E-mail: [email protected] The first and second authors contribute equally to this work.
2115
Y Zhu et al.
Introduction and background Burnout is a typical syndrome among health care professionals and has been studied extensively during the past few decades. Recently, however, there has been a shift towards the perspectives of positive psychology and positive organisational behaviour and researchers are now more focused on work engagement, which is the opposite of burnout (Bakker & Demerouti 2008, Maslach & Leiter 2008). Work engagement is a positive, fulfilling workrelated state that is characterised by vigour, dedication and absorption (Schaufeli et al. 2002). Rather than a specific and momentary state, work engagement is a more pervasive and persistent affective–cognitive state (Schaufeli et al. 2006). With the rapid ageing of populations and the global shortage of nurses, work engagement has become strategically important, because engaged employees are energised, dedicated and engrossed to persevere and complete their work (Schaufeli et al. 2002). A large body of literature has confirmed the contributory role of nurses’ work engagement to both organisational and personal outcomes, including care quality (Freeney & Fellenz 2013), extra-role performance (Salanova et al. 2011) and job satisfaction (Giallonardo et al. 2010). Nevertheless, nurses report lower levels of work engagement than other health care professionals (Huang et al. 2012), which increases the need to identify the potential facilitators of their work engagement. Emerging research on the antecedents of work engagement has concentrated more on job resources (Garrosa et al. 2011) and little attention has been paid to the impact of personal and organisational resources. Nursing is a people-oriented helping profession and nurses’ emotional intelligence is of great importance. Emotional intelligence is ‘the ability to monitor one’s own and other’s feelings and emotions, to discriminate among them and to use this information to guide one’s thinking and actions’ (Salovey & Mayer 1990, p. 190). Emotional intelligence is a personal psychological resource that can be predictive of human performance. In addition to technical skills, current nursing practice also involves holistic care that addresses patients’ emotional, social and spiritual needs (Fernandez et al. 2012). To provide holistic care, nurses have an obligation to empathise with patients, to be appropriately responsive to their suffering and to show empathetic concern (McQueen 2004). Therefore, the ability to manage one’s own emotions while interpreting others’ becomes a prerequisite skill for nursing profession. Previous studies have demonstrated the positive effect of nurses’ emotional intelligence on quality of care (Adams & Iseler 2014), psychological ownership
2116
(Kaur et al. 2013) and well-being (Karimi et al. 2014). Research in nonhealth care fields has also shown the influence of emotional intelligence on work engagement. It was reported that emotional intelligence led to employee engagement through the mediating roles of job satisfaction and well-being with 193 police officers as participants (Brunetto et al. 2012). Similarly, prior study found that teachers’ emotional intelligence was linked to high levels of engagement as well (Garrido & Pacheco 2012). Yet the contribution of emotional intelligence in explaining nurses’ work engagement remains inadequately understood. In collectivism-oriented Asian countries, fairness of an organisation is highly valued. Organisational justice refers to one’s perceptions of the fairness of decisions and decision-making process within an organisation and how the fairness perceptions influence one’s behaviour (Lavelle et al. 2007). According to social exchange theory, obligations between parties are generated through a series of interactions based on the rules of reciprocity. When employees perceive high levels of organisational justice, they feel obliged to exhibit greater levels of performance. Conversely, if they perceive a fairness imbalance, feelings of anger or bitterness may arise. High levels of organisational justice strengthen identification with the organisation and increase employees’ sense of belonging. Employees will be engaged only when they feel that they are treated fairly (Macey et al. 2009). Nevertheless, the impact of organisational justice on nurses’ engagement remains ill-understood. Moreover, as perceptions of organisational justice are subjective, they can be influenced by an individual’s characteristics. Emotionally intelligent individuals have better emotional perception and regulation capacity and are capable of successfully handling negative feelings such as unfairness (Di Fabio & Palazzeschi 2012). Until now, no study has simultaneously explored the influences of emotional intelligence and organisational justice on work engagement in clinical nurses.
Aims The goal of the current study was to create and test a model of how personal resources and organisational resources predict work engagement among nurses. Specifically, we intend to test three hypotheses: (1) there is a positive relationship between emotional intelligence and work engagement; (2) there is a positive relationship between organisational justice and work engagement; (3) organisational justice mediates the relationship between emotional intelligence and work engagement. The hypothesised model is illustrated in Fig. 1. © 2015 John Wiley & Sons Ltd Journal of Clinical Nursing, 24, 2115–2124
Original article
Resources and work engagement
Figure 1 Measurement and structural components of the hypothesised model. SEA: selfemotional appraisal; ROE: regulation of emotion; UOE: use of emotion; OEA: other’s emotion appraisal; PJ: procedural justice: DJ: distributive justice; IJ1: interpersonal justice; IJ2: informational justice.
Methods Design and data collection A nonexperimental, cross-sectional descriptive design was used. Participants were registered nurses selected from four tertiary first-class hospitals in Jinan city, China using multistage sampling. In the first stage, four hospitals were selected from tertiary first class hospitals in this city by simple random sampling. In the second stage, eligible nurses were selected from chosen hospitals by cluster sampling. Inclusion criteria were: (1) nurses who had been working in the current department for over six months and (2) nurses who agreed to participate in the survey. A total of 565 nurses from the medical department, surgical department and intensive care unit were enrolled. Data were collected using a self-report questionnaire during April 2014–June 2014. Permission from nurse administrators and participant written informed consent were obtained. Anonymous questionnaires with a cover page introducing the study purpose were distributed and collected by researchers. Finally, 511 complete questionnaires were returned, resulting in a response rate of 904%.
Measures Demographic characteristics Demographic characteristics included age, gender, marital status, length of working experience, education level, professional rank, employment status and department. Emotional intelligence Emotional intelligence was measured using the Wong and Law Emotional Intelligence Scale (WLEIS) (Law et al. 2004). WLEIS is a 16-item scale consisting of four dimensions: (1) Self Emotion Appraisal (SEA); (2) Regulation of Emotion (ROE); (3) Use of Emotion (UOE) and (4) Other’s © 2015 John Wiley & Sons Ltd Journal of Clinical Nursing, 24, 2115–2124
Emotion Appraisal (OEA), with four items for each dimension. The response format is a five-point Likert-type scale ranging from ‘strongly disagree’ to ‘strongly agree’ with high scores representative of high emotional intelligence. The internal consistency reliability for the four dimensions ranged from 083–090. In the present study, the Cronbach’s a coefficient for the total scale was 093 and subscales ranged from 075–087. Organisational justice Organisational justice was assessed with the Organizational Justice questionnaire (Colquitt 2001). This scale contains 20 items along four dimensions: (1) procedural justice (perceived fairness of the decision-making process within an organisation, seven items); (2) distributive justice (fairness in allocating resources, four items); (3) interpersonal justice (the extent to which individuals feel they are treated with dignity and respect when decisions are made, four items); and (4) informational justice (the extent to which individuals feel they receive adequate and timely information about how decisions related to them are made, five items). All items were evaluated on a five-point Likert scale ranging from ‘totally disagree’ to ‘totally agree’. Each dimension was averaged to yield a total score of 1–5 with high scores indicative of better perceived fairness. In our study, the Cronbach’s a coefficient for the total scale was 094 and subscales ranged from 085–090. Work engagement Work engagement was measured with the shortened version of the Utrecht Work Engagement Scale (UWES-9), which correlated highly with the original longer counterparts (Schaufeli et al. 2006). The UWES-9 contains three subscales based on the components of work engagement: vigour, dedication and absorption with three items for each subscale. All items are rated on a seven-point frequency scale ranging from ‘never’ to ‘always’. The three subscales
2117
Y Zhu et al.
were averaged to produce a total score range of 0–6 with high scores signifying greater work engagement. In this study, the Cronbach’s a coefficient for the total scale was 092 and the three subscales ranged from 071–089.
Ethical considerations This research was approved by the Ethical Board of Shandong University School of Nursing (ethical approval number: 00140918). In addition, permission to perform the study was obtained from the hospital ethics committees. All participants were ensured that the participation was voluntary and that the data were anonymous and confidential.
Data analysis Data were analysed using SPSS version 17.0 software (Statistical Package for Social Sciences, Inc., Chicago, IL, USA) and AMOS version 21.0 (IBM SPSS Inc.). Due to the selfreported data collection method used, common method variance (CMV) may be introduced (Podsakoff et al. 2003). In accordance with Podsakoff et al. (2003) and previous research (Salanova et al. 2011), Harman’s single-factor test with Confirmatory Factor Analyses (CFA), a widely used technique, was applied to test the extent to which CMV may be a problem. Then, descriptive statistics were used to characterise participants’ socio-demographic and general study variables. Pearson’s correlation analyses were conducted to examine the relations between emotional intelligence, organisational justice and work engagement. Finally, we performed structural equation modelling (SEM) analysis to test whether organisational justice mediated the relationship between emotional intelligence and work engagement. Maximum likelihood (ML) estimation methods were used and absolute indices and relative indices were calculated to evaluate the goodness-of-fit of the model. Absolute indices included: (1) normed chi-square (v2/df); (2) the goodnessof-fit index (GFI); (3) the adjusted goodness-of-fit index (AGFI); and (4) the root mean square error of approximation (RMESA). The relative indices included (1) incremental fit index (IFI) and (2) comparative fit index (CFI). Values of v2/df
The impact of emotional intelligence on work engagement of registered nurses: the mediating role of organisational justice Yun Zhu, Congcong Liu, Bingmei Guo, Lin Zhao and Fenglan Lou
Aims and objectives. To explore the impact of emotional intelligence and organisational justice on work engagement in Chinese nurses and to examine the mediating role of organisational justice to provide implications for promoting clinical nurses’ work engagement. Background. The importance of work engagement on nurses’ well-being and quality of care has been well documented. Work engagement is significantly predicted by job resources. However, little research has concentrated simultaneously on the influence of both personal and organisational resources on nurses’ work engagement. Design. A descriptive, cross-sectional design was employed. Methods. A total of 511 nurses from four public hospitals were enrolled by multistage sampling. Data collection was undertaken using the Wong and Law Emotional Intelligence Scale, the Organizational Justice questionnaire and the Utrecht Work Engagement Scale-9. We analysed the data using structural equation modelling. Results. Emotional intelligence and organisational justice were significant predictors and they accounted for 44% of the variance in nurses’ work engagement. Bootstrap estimation confirmed an indirect effect of emotional intelligence on work engagement via organisational justice. Conclusions. Emotional intelligence and organisational justice positively predict work engagement and organisational justice partially mediates the relationship between emotional intelligence and work engagement. Relevance to clinical practice. Our study supports the idea that enhancing organisational justice can increase the impact of emotional intelligence. Managers should take into account the importance of emotional intelligence and perceptions of organisational justice in human resources management and apply targeted interventions to foster work engagement.
What does this paper contribute to the wider global clinical community?
• This study reveals that emotional
•
•
intelligence and organisational justice significantly predict work engagement of clinical nurses. This study also finds that organisational justice plays a mediating role in the relationship between emotional intelligence and work engagement of clinical nurses. This study extends the Job Demands-Resources Model by examining the influence of personal resources and organisational resources simultaneously and provides support that changes are needed to be made to the organisational environment of clinical nurses to increase their work engagement.
Key words: emotional intelligence, nurses, organisational justice, public hospitals, work engagement Accepted for publication: 14 February 2015
Authors: Yun Zhu, RN, PhD Candidate, Associate Professor, School of Nursing, Shandong University, Jinan; Congcong Liu, RN, MMed Candidate, School of Nursing, Shandong University, Jinan; Bingmei Guo, RN, MMed Candidate, School of Nursing, Shandong University, Jinan; Lin Zhao, RN, MMed Candidate, School of Nursing, Shandong University, Jinan; Fenglan Lou, BMed, Professor, School of Nursing, Shandong University, Jinan, China
© 2015 John Wiley & Sons Ltd Journal of Clinical Nursing, 24, 2115–2124, doi: 10.1111/jocn.12807
Correspondence: Fenglan Lou, Professor, School of Nursing, Shandong University, No. 44, Wenhua Xi Road, Jinan, Shandong, 250012, China. Telephone: +86 531 88382003. E-mail: [email protected] The first and second authors contribute equally to this work.
2115
Y Zhu et al.
Introduction and background Burnout is a typical syndrome among health care professionals and has been studied extensively during the past few decades. Recently, however, there has been a shift towards the perspectives of positive psychology and positive organisational behaviour and researchers are now more focused on work engagement, which is the opposite of burnout (Bakker & Demerouti 2008, Maslach & Leiter 2008). Work engagement is a positive, fulfilling workrelated state that is characterised by vigour, dedication and absorption (Schaufeli et al. 2002). Rather than a specific and momentary state, work engagement is a more pervasive and persistent affective–cognitive state (Schaufeli et al. 2006). With the rapid ageing of populations and the global shortage of nurses, work engagement has become strategically important, because engaged employees are energised, dedicated and engrossed to persevere and complete their work (Schaufeli et al. 2002). A large body of literature has confirmed the contributory role of nurses’ work engagement to both organisational and personal outcomes, including care quality (Freeney & Fellenz 2013), extra-role performance (Salanova et al. 2011) and job satisfaction (Giallonardo et al. 2010). Nevertheless, nurses report lower levels of work engagement than other health care professionals (Huang et al. 2012), which increases the need to identify the potential facilitators of their work engagement. Emerging research on the antecedents of work engagement has concentrated more on job resources (Garrosa et al. 2011) and little attention has been paid to the impact of personal and organisational resources. Nursing is a people-oriented helping profession and nurses’ emotional intelligence is of great importance. Emotional intelligence is ‘the ability to monitor one’s own and other’s feelings and emotions, to discriminate among them and to use this information to guide one’s thinking and actions’ (Salovey & Mayer 1990, p. 190). Emotional intelligence is a personal psychological resource that can be predictive of human performance. In addition to technical skills, current nursing practice also involves holistic care that addresses patients’ emotional, social and spiritual needs (Fernandez et al. 2012). To provide holistic care, nurses have an obligation to empathise with patients, to be appropriately responsive to their suffering and to show empathetic concern (McQueen 2004). Therefore, the ability to manage one’s own emotions while interpreting others’ becomes a prerequisite skill for nursing profession. Previous studies have demonstrated the positive effect of nurses’ emotional intelligence on quality of care (Adams & Iseler 2014), psychological ownership
2116
(Kaur et al. 2013) and well-being (Karimi et al. 2014). Research in nonhealth care fields has also shown the influence of emotional intelligence on work engagement. It was reported that emotional intelligence led to employee engagement through the mediating roles of job satisfaction and well-being with 193 police officers as participants (Brunetto et al. 2012). Similarly, prior study found that teachers’ emotional intelligence was linked to high levels of engagement as well (Garrido & Pacheco 2012). Yet the contribution of emotional intelligence in explaining nurses’ work engagement remains inadequately understood. In collectivism-oriented Asian countries, fairness of an organisation is highly valued. Organisational justice refers to one’s perceptions of the fairness of decisions and decision-making process within an organisation and how the fairness perceptions influence one’s behaviour (Lavelle et al. 2007). According to social exchange theory, obligations between parties are generated through a series of interactions based on the rules of reciprocity. When employees perceive high levels of organisational justice, they feel obliged to exhibit greater levels of performance. Conversely, if they perceive a fairness imbalance, feelings of anger or bitterness may arise. High levels of organisational justice strengthen identification with the organisation and increase employees’ sense of belonging. Employees will be engaged only when they feel that they are treated fairly (Macey et al. 2009). Nevertheless, the impact of organisational justice on nurses’ engagement remains ill-understood. Moreover, as perceptions of organisational justice are subjective, they can be influenced by an individual’s characteristics. Emotionally intelligent individuals have better emotional perception and regulation capacity and are capable of successfully handling negative feelings such as unfairness (Di Fabio & Palazzeschi 2012). Until now, no study has simultaneously explored the influences of emotional intelligence and organisational justice on work engagement in clinical nurses.
Aims The goal of the current study was to create and test a model of how personal resources and organisational resources predict work engagement among nurses. Specifically, we intend to test three hypotheses: (1) there is a positive relationship between emotional intelligence and work engagement; (2) there is a positive relationship between organisational justice and work engagement; (3) organisational justice mediates the relationship between emotional intelligence and work engagement. The hypothesised model is illustrated in Fig. 1. © 2015 John Wiley & Sons Ltd Journal of Clinical Nursing, 24, 2115–2124
Original article
Resources and work engagement
Figure 1 Measurement and structural components of the hypothesised model. SEA: selfemotional appraisal; ROE: regulation of emotion; UOE: use of emotion; OEA: other’s emotion appraisal; PJ: procedural justice: DJ: distributive justice; IJ1: interpersonal justice; IJ2: informational justice.
Methods Design and data collection A nonexperimental, cross-sectional descriptive design was used. Participants were registered nurses selected from four tertiary first-class hospitals in Jinan city, China using multistage sampling. In the first stage, four hospitals were selected from tertiary first class hospitals in this city by simple random sampling. In the second stage, eligible nurses were selected from chosen hospitals by cluster sampling. Inclusion criteria were: (1) nurses who had been working in the current department for over six months and (2) nurses who agreed to participate in the survey. A total of 565 nurses from the medical department, surgical department and intensive care unit were enrolled. Data were collected using a self-report questionnaire during April 2014–June 2014. Permission from nurse administrators and participant written informed consent were obtained. Anonymous questionnaires with a cover page introducing the study purpose were distributed and collected by researchers. Finally, 511 complete questionnaires were returned, resulting in a response rate of 904%.
Measures Demographic characteristics Demographic characteristics included age, gender, marital status, length of working experience, education level, professional rank, employment status and department. Emotional intelligence Emotional intelligence was measured using the Wong and Law Emotional Intelligence Scale (WLEIS) (Law et al. 2004). WLEIS is a 16-item scale consisting of four dimensions: (1) Self Emotion Appraisal (SEA); (2) Regulation of Emotion (ROE); (3) Use of Emotion (UOE) and (4) Other’s © 2015 John Wiley & Sons Ltd Journal of Clinical Nursing, 24, 2115–2124
Emotion Appraisal (OEA), with four items for each dimension. The response format is a five-point Likert-type scale ranging from ‘strongly disagree’ to ‘strongly agree’ with high scores representative of high emotional intelligence. The internal consistency reliability for the four dimensions ranged from 083–090. In the present study, the Cronbach’s a coefficient for the total scale was 093 and subscales ranged from 075–087. Organisational justice Organisational justice was assessed with the Organizational Justice questionnaire (Colquitt 2001). This scale contains 20 items along four dimensions: (1) procedural justice (perceived fairness of the decision-making process within an organisation, seven items); (2) distributive justice (fairness in allocating resources, four items); (3) interpersonal justice (the extent to which individuals feel they are treated with dignity and respect when decisions are made, four items); and (4) informational justice (the extent to which individuals feel they receive adequate and timely information about how decisions related to them are made, five items). All items were evaluated on a five-point Likert scale ranging from ‘totally disagree’ to ‘totally agree’. Each dimension was averaged to yield a total score of 1–5 with high scores indicative of better perceived fairness. In our study, the Cronbach’s a coefficient for the total scale was 094 and subscales ranged from 085–090. Work engagement Work engagement was measured with the shortened version of the Utrecht Work Engagement Scale (UWES-9), which correlated highly with the original longer counterparts (Schaufeli et al. 2006). The UWES-9 contains three subscales based on the components of work engagement: vigour, dedication and absorption with three items for each subscale. All items are rated on a seven-point frequency scale ranging from ‘never’ to ‘always’. The three subscales
2117
Y Zhu et al.
were averaged to produce a total score range of 0–6 with high scores signifying greater work engagement. In this study, the Cronbach’s a coefficient for the total scale was 092 and the three subscales ranged from 071–089.
Ethical considerations This research was approved by the Ethical Board of Shandong University School of Nursing (ethical approval number: 00140918). In addition, permission to perform the study was obtained from the hospital ethics committees. All participants were ensured that the participation was voluntary and that the data were anonymous and confidential.
Data analysis Data were analysed using SPSS version 17.0 software (Statistical Package for Social Sciences, Inc., Chicago, IL, USA) and AMOS version 21.0 (IBM SPSS Inc.). Due to the selfreported data collection method used, common method variance (CMV) may be introduced (Podsakoff et al. 2003). In accordance with Podsakoff et al. (2003) and previous research (Salanova et al. 2011), Harman’s single-factor test with Confirmatory Factor Analyses (CFA), a widely used technique, was applied to test the extent to which CMV may be a problem. Then, descriptive statistics were used to characterise participants’ socio-demographic and general study variables. Pearson’s correlation analyses were conducted to examine the relations between emotional intelligence, organisational justice and work engagement. Finally, we performed structural equation modelling (SEM) analysis to test whether organisational justice mediated the relationship between emotional intelligence and work engagement. Maximum likelihood (ML) estimation methods were used and absolute indices and relative indices were calculated to evaluate the goodness-of-fit of the model. Absolute indices included: (1) normed chi-square (v2/df); (2) the goodnessof-fit index (GFI); (3) the adjusted goodness-of-fit index (AGFI); and (4) the root mean square error of approximation (RMESA). The relative indices included (1) incremental fit index (IFI) and (2) comparative fit index (CFI). Values of v2/df
