Identifying key areas of worklife and their interactive effect in explaining Pakistani nurses' burnout

Qadeer, Faisal; Imtiaz, Amnah; Hameed, Imran Article Identifying key areas of worklife and their interactive effect in explaining Pakistani nurses' burnout Pakistan Journal of Commerce and Social Sciences (PJCSS) Provided in Cooperation with: Johar Education Society, Pakistan (JESPK) Suggested Citation: Qadeer, Faisal; Imtiaz, Amnah; Hameed, Imran (2017) : Identifying key areas of worklife and their interactive effect in explaining Pakistani nurses' burnout, Pakistan Journal of Commerce and Social Sciences (PJCSS), ISSN 2309-8619, Johar Education Society, Pakistan (JESPK), Lahore, Vol. 11, Iss. 3, pp. 737-752 This Version is available at: https://hdl.handle.net/10419/188314 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc/4.0/ Pakistan Journal of Commerce and Social Sciences 2017, Vol. 11 (3), 737-752 Pak J Commer Soc Sci Identifying Key Areas of Worklife and Their Interactive Effect in Explaining Pakistani Nurses’ Burnout Faisal Qadeer (Corresponding author) Lahore Business School, The University of Lahore, Pakistan Email: [email protected] Amnah Imtiaz The University of Texas, Rio Grande Valley, Edinburg, Texas, USA Email: [email protected] Imran Hameed Lahore Business School, The University of Lahore, Pakistan Email: [email protected] Abstract We examined the effect of incongruence in the areas of worklife (AWL) on burnout of nurses. Specifically, we were interested in identifying the most important AWL and interactions among AWL and psychological resilience in explaining nurses’ burnout. Incongruence in the worklife escalates burnout and resilience is a coping trait. The phenomenon needs to be studied in developing countries where entirely different health dilemmas exist. A cross sectional survey was conducted from 147 nurses. SEM through AMOS 21 and Process Macro of SPSS was used for data analysis. Two AWL namely control and reward, emerged out to be the most important factors in explaining burnout; community further mitigated reward-burnout relationship. Also, psychological resilience has a powerful independent explanatory role. Healthcare work environment must be equipped to minimize incongruence of the AWL. This congruence would need job redesigning to increase control of nurses over their jobs and reinforcement with all kinds of reward coupled with a supportive co-worker’s community. Keywords: areas of worklife, burnout, nurses, resilience, Pakistan 1. Introduction There has been a rising research interest in nurses’ burnout in health care professions (Chang & Chan, 2015; Elpert, & Wagner, 2017; Lu et al., 2015; Troppmann, & Troppmann, 2017; Wu et al., 2014), and it has become a worldwide barometer for understanding the phenomena of individual well-being. Burnout is an umbrella term composed of emotional exhaustion, cynicism, and inefficacy (Boamah & Laschinger, 2016). Occupational health studies are trying to unleash effects of occupational stress on health workforce experiences (Zhou & Gong, 2015) as working in a healthcare facility can be very stressful. Human resources in health care faces challenges with work demands (Zhou & Gong, 2015). A typical nurse is expected to work for long shifts and countless hours. They have to deal with stressful situations (death and emergencies), emotionally demanding patients and their relatives, the volume of patients supervised and caseloads. Key Areas of Worklife and Nurses’ Burnout 738 They often face diminished resources; administrative burdens work-life conflict, (Elpert, & Wagner, 2017; Lu et al., 2015; Potter et al., 2010; Troppmann & Troppmann, 2017; Zhou & Gong, 2015) and exposed to a stressful environment (Chang & Chan, 2015). These unmanageable work expectations relinquish the emotional capacity to perform any further (Howard & Johnson, 2004; Wu et al., 2014) leading to further stress and burnout for nurses. One of the most important themes of organizational psychology is to build interaction between the individual and work environment in the form of person-job fit and personorganization fit (Maslach et al., 2012). The two types of fits are often configured as areas of worklife initially theorized by Leiter and Maslach (1999) and are considered very important in explaining workers’ burnout. Many subsequent studies found the empirical support for this theory. However, not much is known about the comparative explanatory power of the various areas of worklife. In this study, we argue that in different contexts, the rank order of these areas regarding their variance explained may be very useful for decision makers. This rank ordering of the AWL would enable them to focus on two or three most critical areas. Likewise, we do not know enough about how these areas interact with each other to jointly explain burnout over and above the direct impacts. Further, we argue that the interaction of the areas of worklife for explaining burnout should be tested in the presence of psychological resilience of nurses – a heavily researched mechanism of reducing burnout. By advancing knowledge in these directions, we would be able to understand the variation in burnout more comprehensively, and can parsimoniously understand nurses’ burnout and suggest an actionable solution for the hospital administrator. Therefore, the study aimed to highlight which areas of worklife make Pakistani nurses more vulnerable to burnout. Specifically, the objectives were: a) to identify and rank the areas of worklife in term of their explanatory power to predict nurses’ burnout, thereby looking parsimonious understanding in this regard, and b) to examine the interaction of the areas of worklife that can further explain burnout. Keeping in view the extraordinary relevance of psychological resilience in burnout research, the examination of all possible interactions of the five areas would be in the presence of psychological resilience in the model. 2. Overview of the Literature 2.1 Areas of Worklife The areas of worklife are divided into six broad dimensions (Leiter & Maslach, 1999). We have used only five areas of worklife in this study, excluding ‘workload.' Keeping in view the Pakistan’s extremely worse nurses-to-the general population ratio (about 31 times more than the US), in coming years ‘the amount of work expected to be completed in each time’ is always likely to be high in the context of Pakistan. Hence workload is not a factor that could be possibly controlled by the hospital administrator, therefore not included in this study for the further examination. The remaining five areas of worklife include control, reward, community, fairness, and values. Control engages perceived capacity to influence decisions and gain access to the resources (Leiter et al., 2010). Reward demonstrates the usage of reinforcements to configure the behavior and facilitate learning and produce acceptable norms and values. Community captures work on social support and affective association of individuals with one another (Boamah & Laschinger, 2016). Fairness emerges on the pattern of justice, and equity and Values pick up how the organization’s mission, ethics, and goals are matched Qadeer et al. 739 with that of individuals (Boamah & Laschinger, 2016; Hendel & Kagan, 2014; Hunt, 2014; Leiter & Maslach, 2009). The genesis of areas of worklife model lays in its etiology of congruity or incongruity (Gascon et al., 2013). Matches in the worklife escalate constructive relationship with the work environment whereas mismatch leads to reduced involvement (Leiter & Maslach, 1999). Nature of the tipping points concerning the areas must be judged for nurses in their respective current conditions of the work environment (Potier, 2007). Burnout majorly stems from incongruence in the areas of worklife. Psychological distress and anxiousness are higher for employees who experience unfairness (Cole et al., 2010; Judge & Colquitt, 2004; Tepper et al., 2001). Insufficient rewards lead to feelings of inefficacy and a supportive social environment buffers the inequities at work and result in work engagement, whereas, value incongruence leads to inefficacy and exhaustion (Maslach et al., 2001; Truchot & Deregard, 2001). 2.2 Psychological Resilience Workplaces are traumatized by stressful events. Resilience is the act of fighting vulnerabilities and adversaries (Jackson et al., 2007). It is both a personality trait (Hart et al., 2014; Ong et al., 2004; Tusaie & Dyer, 2004) and a dynamic process (Hart et al., 2014; Jacelon, 1997). Individuals who possess this trait maintain a positive outlook and resourcefulness to take care of their emotional well-being whereas others languish in helplessness and hopelessness (Zellarsi et al., 2004). Workplace adversity has gained significant relevance in the international medical literature (Jackson et al., 2007). Hospital work settings contain occupational hardships for nurses (Vahey et al., 2004) such as workloads, lack of autonomy, bullying and restructuring (Demerouti et al., 2000; Hart et al., 2014). They are faced with challenges such as widespread shortages of experienced nurses, ageing workforce, increased use of casual staff in the nursing workforce, disruptive behaviors from colleagues, ethical dilemmas (Hart et al., 2014); organizational change and restructuring, health and safety issues (Gormley, 2011; Jackson et al., 2001; Strachota et al., 2003) etc. These problems create an impetus of cascading negative opinions about work place resulting in retention problems for a viable nursing workforce. This situation leads to turnover (Gormley, 2011) and burnout (McVicar, 2003; Strachota et al., 2003). On the other hand, nurses exhibiting resilience remains audacious against constraints (Ong et al., 2004) and ultimately exercise better coping mechanisms (Garcia & Calvo, 2012). Studies have found a strong link between resilience and burnout (Edward, 2005) that further leads to enhanced quality of life and work satisfaction (Hart et al., 2014). 2.3 Burnout Burnout is a psychological response to work related stressors in the form of exhaustion when people feel emotionally drained due to the lack of resources to deal with job-related demands and stressors. The lack of energy leads to maladaptive coping, known as cynicism, where individuals detach themselves from their jobs and colleagues, further leading to inefficacy. It is a physical, cognitive, and emotional deterioration of health as well as chronic long-term mental health impairment that builds strong with time (Demerouti et al., 2005). Burnout occurs as result of connections people associate with their jobs and the demanding workplaces (Leiter & Maslach, 2009). Exhaustion is the widely-reported dimension of burnout and results in cynicism and inefficacy (Maslach et Key Areas of Worklife and Nurses’ Burnout 740 al., 2001). Burnout has serious individual and organizational level consequences such as decreased productivity, absenteeism, turnover, reduced commitment (Cropanzano et al., 2003; Van der Colff & Rothmann, 2014) high neuroticism, less self-monitoring (Lewig et al., 2007). Burnout is heavily researched in preventive medicine and hospital management. Among all other medical deliverables, nurses face high rates of burnout; 40% of hospital nurses are victimized with this work place stress, and 40% report high burnout and 20% of them intent to leave within the first year of their employment (Aiken et al., 2001). An Australian study revealed that younger graduate nurses were most susceptible to burnout (SpoonerLane & Patton, 2007). A recent survey of 856 nurses from Shanghai reported a high level of burnout (Lu et al., 2015). Burnout was also reported by 818 nurses from seven provinces of South Africa (Van der Colff & Rothmann, 2014). The studies suggest that nurses are more traumatized due to burnout as compared to other health care workers. Lambert and Lambert (2001) in their systemic literature review report that only 9.5% of the studies on nurses’ stress/strain were from Asia, which is far less representation because about 60% of the world population resides in this continent. Their data may not surprise many that none of the studies were from a Muslim or South Asian country. Keeping in view their call for research ‘from around the world,' studied in countries like Pakistan are much needed because the situation has not changed much since then. 2.4 Nursing in Pakistan There is a worldwide shortage of nurses as reported by WHO (Boamah & Laschinger, 2016; Lu et al., 2015). In developed nations, nurses to the general population ratio range between 1:140 to 1:320 (Wu et al., 2014), whereas, in Pakistan, this ratio is 1:3175. Just to present a comparison, the ratio in the US is 1:102 (Ahmad, 2012). The WHO international standards require hospitals to comply with the ratio of 1:3 for doctors to nurses. However, this ratio is 3:1 in Pakistan (Akram & Khan, 2007) i.e. nine times more overloaded, which is perturbing. Pakistan’s health sector is in an abysmal condition and is obstructed by health workforce crisis. It falls on the list of 57 countries, against the World Health Organization (WHO) standards (Hafeez et al., 2010). Due to over population and burden to serve a greater number of patients, deficiency of nurses exists about patient care, creating an enormous pressure of decreased supply and increased demand for medical professionals. With the current population of 185M people and the rate expected to grow to 210M by 2020; the shortage of nurses is alarming. The plight of health structure has crippled down the patient care (Chauhan, 2014) by further exacerbating the likelihood of burnout in Pakistani nurses. 3. Research Method Self-administered, a cross sectional questionnaire survey was used for primary data collection. The ordinal data based on scaled items computed for the study variables served as a transformation onwards a continuous scale. These respondents were recruited through snowball sampling where waves of contacts were identified.The data were collected from November 2014 to January 2015 across nine different hospitals of Lahore, Pakistan. We determined sample size following Bartlett et al. (2001).The estimated target population size in the nine hospitals was 500 female nurses, with 0.3% margin of error and 0.01 Alppah level (t-value 2.58), our study, therefore, consisted of 147 female nurses. A total of 57.8% are married (n=85), the majority of them (55.8%) are permanently employed (n=82). About Qadeer et al. 741 42% of the participants (n=62) are aged above 30 and on the overwhelming majority (72.1 %, n=106) have hospital tenure of above one year. For more details about the participants’ characteristics, please see Table 1. The measurements of these study variables are as under: 3.1 Areas of Worklife The Areas of Worklife Scale is a widely-used instrument for capturing nurses’ person-job fitness in the areas of worklife. We used 17 items adopted from Leiter and Maslach (2012) for measuring the five areas of worklife. Control and fairness were measured through 4 items each. The remaining areas of worklife (reward, community, and values) were measured through 3 items each. The scale used five points Likert scale as 1(strongly disagree) to 5(strongly agree). The alpha estimates for control, fairness, value, reward, and community were 0.79, 0.79, 0.64, 0.76 and 0.72 respectively. 3.2 Burnout The Maslach Burnout Inventory-General Survey (MBI-GS) (Schaufeli, Leiter, Maslach, & Jackson, 1996) scale measured burnout of the nurses on a seven-point Likert type scale (range from 0=never to 6= every day). We used two subscales, emotional exhaustion, and cynicism of burnout (Boamah & Laschinger, 2016) in this study. Emotional exhaustion was measured through 4 items same was the case for measuring cynicism. In this study, alpha estimates for emotional exhaustion and cynicism were 0.80 and .70 respectively. 3.3 Psychological Resilience The Connor–Davidson Resilience Scale (Campbell-Sills & Stein, 2007) is a ten items instrument measured using a 5-point Likert scale ranging from 1 (not true at all) to 5 (nearly always true). We adopted five items in our survey. Participants were asked to respond the questions keeping in mind a prior month. The alpha value for this scale was 0.75. Table 1: Demographic Characteristics of Nurses (n=147) Age n (%) Under 30 85 (57.8) 31-40 44 (29.9) 41-50 8 (5.4) Above 50 10 (6.8) Marital Status Single 52 (35.4) Married 85 (57.8) Divorced 8 (5.4) Widow 2 (1.4) Employment Status Permanent 82 (55.8) Contractual 65 (44.2) The Hospital Tenure < 1 years 41 (27.9) 1-2 years 29 (19.7) 2-5 years 49 (33.3) 5-10 years 18 (12.2) > 10 years 10 (6.8) Key Areas of Worklife and Nurses’ Burnout 742 4. Data Analysis and Results Statistical package for social sciences 21 with Amos program included was used for analyzing the data. In the first step, aberrant values, missing values, and data normality were checked for all the variables of interests. In next step, descriptive statistics and product moment correlation analyses were performed. We followed the guidelines of Jackson (2009) for interpreting correlations results. He states that the absolute value of r =0.70 or higher shows string correlation, while the absolute value of r between 0.30 and 0.69 shows moderate level and the value of r below 0.30 shows a weak relationship, with the level of significance p< 0.05. The results of the correlation analysis are presented in Table 2. Table 2: Inter-correlations Among Variables Variables Control Fairness Value Reward Community PR Control 1 Fairness 0.40*** 1 Value 0.48*** 0.54*** 1 Reward 0.25** 0.31*** 0.25** 1 Community 0.33*** 0.30*** 0.30*** 0.15 1 PR 0.23** 0.27** 0.09 0.14 -0.04 1 BO -0.41** -0.31*** -0.21** -0.32*** -0.25** -0.41*** Note. PR = Psychological Resilience; BO = Burnout; *** p <0.001; ** p<0.01, * p<0.05 These results show that five areas of work life (i.e. control, fairness, value, reward, and community) negatively correlate with burnout. More specifically, prominent level of control, reward and community showed stronger negative correlation with burnout as compared to fairness and value. Psychological resilience also exhibited significant negative correlation with burnout. Further, a careful analysis of the absolute values of skewness and kurtosis of hypothesized constructs indicated the normal distribution of data i.e. the absolute values of skewness and kurtosis were in normal range (below |1|) (Table 3) (Tabachnick & Fidell, 2013). Table 3: Descriptive Statistics of the Hypothesized Constructs Variables Mean SD Skewness Kurtosis Control 3.20 0.91 -0.42 0.20 -0.21 0.40 Fairness 2.69 0.93 -0.09 0.20 -0.85 0.40 Value 3.00 0.82 -0.53 0.20 -0.14 0.40 Reward 3.14 1.03 -0.15 0.20 -0.77 0.40 Community 3.42 0.86 -0.55 0.20 -0.03 0.40 PR 3.36 0.84 -0.51 0.20 -0.30 0.40 Burnout 2.46 1.24 0.42 0.20 -0.71 0.40 Note. PR = Psychological Resilience These results built the basis for formal testing of hypotheses and aims of the study. In further analysis, first, we performed confirmatory factor analysis (Model 1 for five areas of work life and Model 2 for psychological resilience and burnout; Table 4). Then the hypotheses were tested using structural regression model (Model 3 and Model 4 in Table 4). For analyzing the interaction effects, we used the Process Macro of Hayes (2013) in SPSS. Qadeer et al. 743 4.1 Confirmatory Factor Analysis Confirmatory factor analysis (CFA) was conducted using AMOS 21 for the validity of measures in the research context. Following fit indices were used to assess model adequacy (Byrne, 2001), namely Tucker–Lewis Index (TLI), Comparative Fit Index (CFI), and RootMean Square Error of Approximation (RMSEA). CFI and TLI values above 0.90 and RMSEA scores below 0.08 represent a good model fit (Hair, Black, Babin, & Anderson, 2010; Kline, 2011). The model 1 was tested for the 5 areas of work life which showed good fit to data (x2= (94, n=147) = 145.43, CFI = 0.93; TLI = 0.91, RMSEA = 0.06). CFA model 2 was tested for psychological resilience and burnout which also showed acceptable fit to the data (x2= (51, n=147) = 76.59, CFI = 0.95; TLI = 0.93, RMSEA = 0.06). Therefore, we used these models as bases for testing the structural regression model. Table 4: Summary of Data Model Fit Statistics Standardised Coefficients and Fit Indices Model 1a Model 2b Model 3c Model 4d Chi-square 145.43 76.60 345.04 191.17 Df 94 51 235 125 RMSEA 0.06 0.06 0.06 0.06 CFI 0.93 0.95 0.90 0.92 TLI 0.91 0.93 0.87 0.90 Model R-square (%) 48.6 46.9 43.7 53.7 Note. CFI = Comparative Fit Index; Df = Degree of Freedom; RMSEA = Root-Mean Square Error of Approximation; TLI = Tucker–Lewis Index a Measurement model for Areas of Worklife (AWL) Scale. b Measurement model for Burnout and Psychological Resilience. c Structural regression model through which hypotheses are tested. 4.2 Structural Model We built a structural regression model (i.e. Model 3) by combining the two CFA models and added the regression lines for the hypothesized relationships. The model fit indices for this model were not acceptable (x2= (235, n=147) = 345.04, CFI = 0.90; TLI = 0.89, RMSEA = 0.06). Upon examining the results, it reveals that three areas of work life (i.e. fairness, value, and community) exhibited an insignificant effect on burnout (i.e. p > .05). Then after removing the insignificant paths, we tested the model 4 for which the fit indices were acceptable (x2= (125, n=147) = 191.17, CFI = 0.92; TLI = 0.90, RMSEA = 0.06). These results highlighted that two areas of work life (i.e. control and reward) and psychological resilience have significant negative impact on burnout. The variance explained for the tested models ranged from 44% to 54%. 4.3 Interaction Effect For testing the possible interactions between areas of work life for predicting burnout, we used Process Macro of SPSS. Multiple models were tested, but the only significant interaction effect was reported for community on the negative relationship between reward and burnout (Table 5). Which highlight that high level of rewards could decrease the degree of burnout. However, this effect can be more effective when high congruence with community is available. Therefore, these two areas together can play a more effective role in reducing the level of burnout (Figure 1 & Figure 2). Key Areas of Worklife and Nurses’ Burnout 744 Table 5: Moderation of Community on Reward-Burnout Relationship Variables Point of estimate S.E. BC 95% CI Lower Upper Reward -0.3477*** 0.0951 -0.5313 -0.1641 Community -0.2969** 0.0929 -0.5170 -0.0768 Reward x Community -0.1963* 0.1113 -0.3888 -0.0037 *** p <0.001; ** p<0.01, * p<0.05 5. Discussion The relative importance of individual areas of work life has not been studied so far to the best of our knowledge in nursing context. Rather than focusing on determining the most critical areas of the worklife, there is a general tendency to sum ‘mean of each subscale’ and ‘produce a measure of the overall degree of the match in the areas of worklife’ (Boamah & Laschinger, 2016). We argue that focusing on all areas might not be actionable in many parts of the world. For example, when a shortage of nurses is felt even in US (Juraschek, Zhang, Ranganathan, & Lin, 2012) that is far better on nurses to general population ratio, then how countries like Pakistan can deal with ‘unmanageable workload’ of nurses. Further, many studies ‘frequently’ show a strong relationship between workload and burnout (Boamah & Laschinger, 2016; Lu et al., 2015). Thus its importance is beyond any doubt. The developing countries might not be able to overcome the shortage of trained nurses, due to severe budget constraints. Therefore, there are hardly any chances left for them to deal with workload generated burnout. From among the remaining areas of worklife, the study finds three areas more important. Figure1: Explaining burnout through PR and Areas of Worklife Note. PR = Psychological Resilience; ** p < .01, * p < .05 This paper attempts to discover most important factors among the areas of worklife to explain nurses’ burnout and interaction among these areas. The paper demonstrated that two areas of worklife, control, and reward remain significant along with psychological PR Burnout Reward Control Community -0.37** -0.41** -0.24* -0.20* Qadeer et al. 751 Laschinger, H. K. S., & Grau, A. (2012). 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