It has become vital for hospitals to create supportive and conducive working environments. With the reported adverse working conditions in public hospitals, it would be prudent to consider the stimulating factors of work engagement. This research suggests that personal resources such as resilience and emotional intelligence may cushion individuals from being disengaged by enabling them to manage job demands.
The study aimed to determine the extent to which a combination of positive aspects and resources of emotional intelligence and resilience may influence work engagement.
The study was inspired by Demerouti and Bakker who in 2011 signalled that employees become susceptible to health impairments when job and personal resources are likely to be limited. Expanding employee personal resources may thus effectively influence work engagement.
The study employed a cross-sectional quantitative survey by means of self-administered questionnaires. The sample consisted of 252 nurses from the Mangaung Metropolitan Municipality, South Africa. Data were analysed using the SmartPLS programme.
Emotional intelligence influences work engagement through resilience. The strong direct pathway between emotional intelligence and work engagement was noteworthy.
Managers may focus their attention on developing aspects of emotional intelligence and enhance resilience as a way of improving work engagement.
The findings add literature to the body of knowledge focusing on expanding personal resource as a way to enhance work engagement amongst nurses in public hospitals.
The work engagement of nurses in the public hospitals has become more critical than ever due to the pressure caused by the coronavirus disease, 2019 (COVID-19) pandemic (Giménez-Espert, Prado-Gascó, & Soto-Rubio,
Maphumulo and Bhengu (
Work engagement is identified as a key factor in achieving corporate success (Shuck & Herd,
In the light of improving efficiency and engagement amongst healthcare employees, Dewing and McCormack (
The study intended to determine whether emotional intelligence and resilience influence work engagement amongst nurses in public hospitals. The objectives were to:
determine the influence of emotional intelligence and resilience on work engagement
establish the influence of emotional intelligence on work engagement
determine the mediating role of resilience in the relationship between emotional intelligence and work engagement.
Work engagement is a unique phenomenon that has roused interest of researchers and practitioners because of its positive impact on competitive advantage and performance (Bailey et al., 2017). The concept has its roots in burnout literature and it emerged as an attempt to shift the focus from an employee’s ill-being to an employee’s well-being (Albrecht,
Work engagement has been linked with benefits for both individuals and organisations, it increases employee motivation and commitment (Bonner,
As indicated earlier, several personal resources have been recognised and empirically examined as antecedents of work engagement (Bjarnadotti,
Emotional intelligence is viewed as the ability to recognise and regulate emotions in oneself and in others to achieve successful work performance (Goleman,
Resilience is defined as an individual’s adaptive capacity; the concept is characterised by existential aloneness, perseverance, self-reliance, meaningfulness and equanimity (Wagnild & Young,
Pérez-Fuentes, Molero Jurado, Gázquez Linares and Oropesa Ruiz (
From the foregoing discussion, emotional intelligence is the point of entry on the proposed relationship (between emotional intelligence, resilience and work engagement). Magnano et al. (
The study used a quantitative approach, which is rooted in the positivist paradigm. As the study involved validation, hypothesis testing and describing associations between the predictors (resilience and emotional intelligence) and the outcome variable (work engagement), the quantitative approach was most appropriate. Specifically, the study employed a cross-sectional survey as the researcher wanted to get an overall picture of a phenomena at a particular point in time.
The study population was nurses in the Manguang Metropolitan Municipality’s district public hospitals. Nurses were selected from three hospitals in Mangaung Metro, namely Pelonomi, Botshabelo and National hospital with a total population of 938 nurses. Nurses who voluntarily accepted to participate in the study completed the questionnaires, thus the study employed a non-probability convenience sampling procedure. Considering the busy schedule of these nurses, voluntary participation was deemed suitable. The researcher approached the professional nurse in charge of the specific wards and asked for permission to distribute the questionnaires during their meetings amongst the nursing staff. Nurses who were available and willing to take part in the study including the professional nurses, enrolled nurses, staff nurses and assistant nurses completed the questionnaires. Thus, the participants consisted of professional nurses, assistant nurses, enrolled nurses and staff nurses.
The total number of questionnaires distributed were 335 out of which only 282 were returned; of the 282 only 252 were eligible to be captured. Thus, the study had a response rate of 75.2%.
The data gathering tool had four sections. The first section (Section A) was a biographical questionnaire where respondents answered six items relating to age, category, area of speciality, length of service, highest qualification received and gender. The other sections consisted of pre-established scales, namely the Utrecht Work Engagement Scale (UWES) (Section B), Rahim Emotional Quotient Index (REQI) (Rahim et al.,
The 17 item, UWES by Schaufeli and Bakker (
The REQI (Rahim et al.,
Reliability estimates for the work engagement, emotional intelligence and resilience scale.
Scale | Number of items | Cronbach’s alpha |
---|---|---|
Vigour | 6 | 0.776 |
Dedication | 5 | 0.840 |
Absorption | 6 | 0.798 |
Self-awareness | 4 | 0.810 |
Self-regulation | 5 | 0.763 |
Empathy | 4 | 0.733 |
Motivation | 5 | 0.820 |
Social skills | 4 | 0.705 |
Note: The bold values indicate the reliability scores of the composite scales.
The resilience scale RS-14 (Wagnild & Young,
Tools such as the Statistical Package for the Social Sciences (SPSS) version 24, Lisrel 10.0 and SmartPLS were used to analyse the collected data. Descriptive and inferential statistics were used to summarise data and test research hypotheses. Cronbach’s alpha was used to assess the internal consistency reliability of the measuring instruments. A confirmatory factor analysis (CFA) through assessment of the goodness of fit statistics (comparative fit index [CFI], root mean square error of approximation [RMSEA], standardised root mean square residual [SRMR]) was used to determine the psychometric properties of the measuring instruments. Variance-based structural equation modelling (SEM) SmartPLS was used to test the model with direct and indirect links between emotional intelligence, resilience and work engagement.
The model was tested following a two-stage process, encompassing (1) the assessment of the measurement model, then (2) the assessment of the structural model.
Firstly, the outer model (i.e. measurement model) was evaluated in terms of internal consistency (composite reliability), convergent (average variance extracted [AVE] scores) and discriminant validity (heterotrait–monotrait [HTMT] values). The purpose of the outer model is to determine whether the measurements used to operationalise each of the latent variables are reliable and valid. The quality criteria associated with an acceptable outer model are: (1) AVE of 0.5 and higher, (2) composite reliability estimates of 0.7 and higher and (3) HTMT ratio of correlations cut-off score of 0.90 (Hair, Risher, Sarstedt, & Ringle,
Ethical clearance to conduct this study was obtained from the University of the Free State Health Sciences Research Ethics Committee (reference number: UFS-HSD2019/0077/2506). After permission was granted by the Free State Department of Health, questionnaires were distributed to the nurses in the public hospitals. Voluntary participation, anonymity and confidentiality were guaranteed.
Nurses between the ages of 41 and 50 years constituted the largest group within the sample (31.3%) and the majority of the nurses surveyed were females (80.2%). Most of the respondents were from the medical nursing department, constituting 28.6% of the sample. The highest level of academic study achieved by the nurses who participated was an advanced diploma (39.7%). Only a few nursing employees had undergraduate (5.6%) and postgraduate degree qualifications (15.1%). Most participants (23.8%) had been in the organisation for 6–10 years. In terms of nursing category, majority of the participants were enrolled nurses who made up 39.7% of the sample, followed by assistant nurses making up 29.6% and the least were the professional nurses, constituting 20.7% of the sample. The qualifications held by the different categories of nurses together with the nature of work the nurses perform were observed.
Confirmatory factor analysis through the goodness of fit statistics confirmed the distinctive validity of emotional intelligence, resilience and work engagement. Reliability of the measuring instruments was assessed using Cronbach’s alpha coefficient and composite reliability.
The Cronbach’s alpha for the work engagement dimensions (measured by the UWES-17) may be regarded as good (vigour = 0.776, dedication = 0.840, absorption = 0.798). The internal consistency for emotional intelligence, consisting of five dimensions, is good, ranging from 0.820 for motivation to 0.705 for social awareness. Resilience observed a reliability score of α = 0.899, which is comparable to that of Wagnild and Collins (
On examining
Goodness of fit statistics.
Variable | S-B χ2 | df | CFI | RMSEA | SRMR | |
---|---|---|---|---|---|---|
WE | 273.765 | 116 | 0.930 | 0.132(0.121; 0.143) | 0.0718 | 0.0000 |
RES | 100.811 | 67 | 0.984 | 0.190 (0.176; 0.204) | 0.0919 | 0.0048 |
EI | 312.788 | 199 | 0.966 | 0.134 (0.126; 0.143) | 0.0863 | 0.0000 |
EI, emotional intelligence; RES, resilience; WE, work engagement; CFI, comparative fit index; RMSEA, root mean square error of approximation; SRMR, standardised root mean square residual.
For the goodness of fit results on work engagement, the following results are reported: CFI = 0.930, SRMR = 0.0718.
Goodness of fit indexes on resilience was reported as follows: CFI = 0.984, RMSEA = 0.190 and SRMR = 0.0919. The results of the CFI are comparable to those of previous studies, for example, Aiena, Baczwaski, Schulenberg and Buchanan (2015), who reported an acceptable but lower CFI than that of this study (CFI = 0.92). Damasio, Borsa and Da Silva (2011) reported a value of 0.056 for the RMSEA and this study reported a RMSEA = 0.190, which is indicative of poor fit. For the SRMR, Damasio et al. (2011) observed a value of 0.042 and the present study reported a higher value of 0.0929, which is a value larger than 0.08, but regarded as an acceptable fit (Kline,
Quality criteria of the measurement or outer model.
Variables | Cronbach’s alpha | rho_A | Composite reliability | AVE |
---|---|---|---|---|
EMOT_INTE | 0.900 | 0.905 | 0.926 | 0.715 |
RESILIENCE | 0.880 | 0.890 | 0.912 | 0.675 |
W_ENGAGE | 0.879 | 0.879 | 0.925 | 0.805 |
EMOT_INTE, emotional intelligence; W_ENGAGE, work engagement; AVE, average variance extracted.
Heterotrait–monotrait ratio.
Variables | EMOT_INTE | RESILIENCE | W_ENGAGE |
---|---|---|---|
EMOT_INTE | - | - | - |
RESILIENCE | 0.768 | - | - |
W_ENGAGE | 0.575 | 0.516 | - |
EMOT_INTE, emotional intelligence; W_ENGAGE, work engagement.
Outer loadings - loading of dimensions on the latent variable.
Dimensions | Factor loading | ||
---|---|---|---|
Absorption: WE | 0.906 | 57.792 | 0.000 |
Dedication: WE | 0.873 | 32.090 | 0.000 |
Empathy: EQI | 0.839 | 36.171 | 0.000 |
Equanimity: RES | 0.797 | 23.552 | 0.000 |
Existential aloneness: RES | 0.777 | 20.991 | 0.000 |
Meaningfulness: RES | 0.848 | 39.184 | 0.000 |
Motivation: EQI | 0.844 | 34.162 | 0.000 |
Perseverance: RES | 0.816 | 22.986 | 0.000 |
Self-awareness: EQI | 0.854 | 48.778 | 0.000 |
Self-regulation: EQI | 0.886 | 56.351 | 0.000 |
Self-reliance: RE | 0.866 | 52.122 | 0.000 |
Social skills: EQI | 0.872 | 45.705 | 0.000 |
Vigour: WE | 0.912 | 72.104 | 0.000 |
WE, work engagement; EQI, Emotional Quotient Index; RES, resilience.
,
Partial least squares path coefficient results.
Variables | Original sample (O) | Sample mean (M) | Standard deviation (SD) | ||
---|---|---|---|---|---|
EMOT_INTE ≥ RES | 0.692 | 0.695 | 0.034 | 20.121 | 0.000 |
EMOT_INTE ≥ W_ENG | 0.516 | 0.379 | 0.078 | 4.809 | 0.000 |
RESILIENCE ≥ W_ENG | 0.202 | 0.200 | 0.086 | 2.349 | 0.019 |
EMOT_INTE, Emotional intelligence; W_ENG, work engagement.
,
R-squared represents the proportion of the variance in work engagement that is explained by resilience and work engagement.
Variables | ||
---|---|---|
Resilience | 0.479 | 0.477 |
Work engagement | 0.288 | 0.282 |
To determine whether the relationship between emotional intelligence and work engagement is mediated by resilience, the specific indirect effects (see
Specific indirect effects.
Variables | Indirect effect | ||
---|---|---|---|
EMOT INTE ≥ RES ≥ W_ENGAGE | 0.145 | 1.419 | 0.157 |
EMOT INTE, emotional intelligence; RES, resilience; W_ENGAGE, work engagement.
From
The main objective of the study was to determine the influence of emotional intelligence and resilience on work engagement. It was hypothesised that the two constructs directly and indirectly influence work engagement and that emotional intelligence lays the foundation of the proposed relationship (from emotional intelligence to resilience and resilience to work engagement). This was based on the premise that emotional intelligence enables individuals to accurately assess their environment, express empathy, think according to the priority of problems and organise thoughts, which consequently increases resilience (Magnano et al.,
The two independent variables (emotional intelligence and resilience) had a significant effect on work engagement. It is argued that individuals who are highly emotionally intelligent show higher concentration in their professional activities are more energetic at work and show more enthusiasm, inspiration, pride and challenge for their work (Prins et al.,
Resilience, as a personal resource, has been argued to influence employees’ ability to cope with work-related stress factors and work engagement. It is claimed that resilient individuals appraise potential stressors as less threatening and consequently they feel that it is safe to engage (Sweetman & Luthans,
The findings demonstrate that emotional intelligence influences work engagement through resilience. The findings concur with Magnano et al. (
However, although an indirect link was observed, it is worth noting that the indirect effects of emotional intelligence were relatively smaller compared with the direct effects. A reasonable justification could be that the stronger direct relationship between emotional intelligence with resilience and work engagement decreased the amount of the variance of work engagement that could be accounted for by resilience. The findings are in line with Makikangas, Schaufeli, Tolvanen and Feldt (
In essence, the findings from the model demonstrate that emotional intelligence, through regulating and managing one’s emotions, fuels resilience, which then promotes higher levels of work engagement. Thus, the combined effect of emotional intelligence and resilience explains the 0.288 variance in work engagement. However, emotional intelligence had a stronger direct impact on work engagement. This suggests that emotional intelligence on its own can positively influence the work engagement levels of nursing employees. Thus, to boost nurses’ work engagement levels, interventions should be focused more on emotional intelligence training. As the literature reviewed indicated that work engagement has benefits for both the organisation and the individual, focusing on emotional intelligence to ensure higher levels of work engagement is crucial for public hospitals.
The results indicated that resilience and emotional intelligence explained only 28.8% variance in work engagement, which can be interpreted as moderate contribution. With more organisations desiring to achieve high levels of work engagement at the moment, the impact of COVID-19 however has affected the work context, especially the nurses’ working environment. In the context of the COVID-19 pandemic, it seems that nurses are overwhelmed with work and their engagement is both positively and negatively associated with health, well-being and work overload (Allande-Cussó et al.,
Although recent studies have shown that improving the level of work engagement of nurses increases their quality of work, job satisfaction and the sense of coherence and also their emotional well-being in the development of their profession, it is important to note that high levels of work engagement may result in promoting stress and work overload that characterises healthcare needs in the current COVID-19 conditions (Allande-Cussó et al.,
When interpreting the results from this study, the following limitations should be considered.
The participants were made up of different categories of nurses (professional nurses, enrolled nurses, assistant nurses) exposed to different training and different job demands, which might have different influence on how they manage their emotions, acquire more personal resources and eventually become more engaged. The differences in the work context of these categories include the degree of autonomy, interaction with patients, working hours, role overload, lack of professional experience for some assistant nurses and closeness to recurring death situations may play a significant role in the interplay between the three variables under study. It is especially striking how nursing graduates (professional nurses ) along with nurses who have achieved an advanced diploma (enrolled nurses) may find it less difficult to bounce back, manage their emotions and eventually offer the highest work engagement scores compared with the assistant nurses who do not have adequate training and autonomy to their work. Having an adequate sample from one category of nurses would provide more consistent findings.
As the study involved only professional nurses, assistant and enrolled nurses, results should only be generalised specifically to these categories of nurses. Also, because of the possibility of sampling error and lack of representation as the study used convenience sampling results were generalised to nurses who participated in the study and those with the same characteristics as them.
Some of the categories of nurses investigated have limited scope of practice (assistant nurses), perform elementary and basic tasks and they work under instruction from the professional nurse, this influences their resilience and emotional intelligence because full responsibility for patient care lies with the professional nurse. Thus, it might be difficult to engage nurses whose duties are delegated by others.
The study relied on a cross-sectional survey design, making it difficult to prove causal relationships between the variables.
The study used self-administered questionnaires. Self-reported questionnaires could affect the trustworthiness and rigour (validity and reliability) of the findings as they can lead to response biases, such as social desirability bias. The use of paper-based copies of the questionnaire may give rise to impression management, which can be seen as a weakness of self-administered questionnaires.
The questionnaire was only provided in English. Some of the Afrikaans and Sesotho-speaking nurses found some of the items difficult to understand, especially words such as ‘immersed’ and ‘determined’ in the UWES and resilience (RES).
Despite these limitations, the results of this study may be useful in an analysis of the relationship between emotional intelligence, resilience and engagement of employees in the public hospitals.
The findings inform leaders and human resource practitioners of the dynamics between emotional intelligence, resilience and work engagement and help them design more effective employee–work engagement strategies. Considering that COVID-19 may affect nurses emotionally, assessing the way the nurses manage their emotions as a coping skill may shine a light on the initiatives designed to assist frontline workers during a pandemic. The results reveal that human resource practitioners need to consider the relationship between emotional intelligence, resilience and work engagement but mainly that between work engagement and emotional intelligence. The study observed that individuals with highly emotionally intelligent and resilient experience high levels of work engagement. However, a very strong link was observed between emotional intelligence and work engagement. In the light of these findings, organisations should try to develop organisational work environments that promote emotional intelligence, thereby boosting work engagement. Interventions aimed at raising awareness regarding these constructs and how to foster greater emotional intelligence and work engagement would lead to positive organisational outcomes.
The study demonstrated that further research into the relationship between emotional intelligence, resilience and work engagement is necessary especially with homogenous groups of nurses. The study was conducted amongst 252 nurses, predominantly women, from three selected public hospitals in the Mangaung Metropolitan Municipality, South Africa. Future research should use a randomised sampling process with larger samples and include more male nurses. Future research should also employ a longitudinal design in order to gain insight into the constructs that influence work engagement. Future studies should focus on studying the mediating effects of other positive psychology variables.
The main aim of this study was to determine the influence of emotional intelligence and resilience on work engagement and to determine the levels of work engagement, resilience and emotional intelligence of the nurses. The empirical statistical effect of emotional intelligence and resilience on work engagement observed in the study provided new understanding with respect to the engagement of employees. It also contributed to the development of a model for the facilitation of work engagement. This study concludes that both emotional intelligence and resilience play important roles in explaining employees’ vigour, absorption and dedication in the workplace. However, the strong direct link between emotional intelligence and the dependent variable work engagement is very interesting. This strongly suggests that emotional intelligence should be the main focus in the promotion of work engagement in the workplace.
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
P.C. developed the research idea and designed the study and was responsible for literature review, collected and analysed the data then compiled the manuscript. M.H. supervised the research done by P.C., reviewed the data analysed and was responsible for final integration of the research findings and assisted in compiling and proofreading the compiled manuscript.
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Data can be made available by the first author, P.C. (chikopardonjd@gmail.com), upon reasonable request.
The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors, and the publisher/s.