Master’s programme Communication Science
Master’s Thesis
Job Demands, Communication-based Job Resources
and Work Exhaustion in the Education Sector
Differences between Millennials and Generation Xers
Author: Lisan Boerrigter 11384050 Supervisor: Iina Hellsten Date: 29 June 2017
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Abstract
The aim of this study was to investigate the relationships between certain job demands, communication-based job resources and work exhaustion, as proposed by the Job Demands-Resources Model. Moreover, this paper looks into differences between millennials (born between 1982 and 1999) and generation Xers (born between 1961 and 1981). A better understanding of the relationships can give us valuable insights into internal communication practices which can help different employees to cope with job demands that are related to work exhaustion. Since especially teachers suffer from burn-out symptoms in The Netherlands, the focus was on employees who are working in the education sector in The Netherlands. Respondents (N = 156) completed an online survey, in which they were asked questions regarding their experience of certain job demands (i.e., workload and emotional demands), communication-based job resources (i.e., social support, performance feedback and supervisory coaching) and work exhaustion. Results showed that, among these employees, workload and emotional demands are positively related to work exhaustion, especially for generation Xers. Moreover, although communication-based job resources do not have the capability of buffering the undesired impact of these job demands on work exhaustion for all employees, social support seems to be beneficial for generation Xers; social support helps generation Xers to deal with emotional demands in a way that it alleviates the impact of these demands on work exhaustion. In practice, these results have implications for HR departments or school management who could focus more on creating a social supportive environment by for example organizing interactive team-meetings where support can arise in order to diminish the effect of emotional demands on work exhaustion. The implications of the results are discussed in relation to current scientific literature, and guidelines for future research are provided.
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Introduction
In today’s workplace, more and more people suffer from stress. According to research carried out by Centraal Bureau voor de Statistiek (CBS) and Toegepast Natuurwetenschappelijk Onderzoek (TNO), work stress is the number one occupational disease in The Netherlands and more than one million people suffer from burn-out symptoms (CBS, 2014; TNO, 2014). On top of the disturbing impact on employee well-being, stress has a big impact on organizations: 36% of absenteeism is caused by stress. In 2012, this has cost employers in The Netherlands 1.8 milliard euros (TNO, 2014).
Examples of causes of work stress, as experienced by employees in The Netherlands, are emotionally demanding work and a high workload (CBS, 2014; TNO, 2014). According to the Job-Demands Resources Model (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001), the JD-R model, both are examples of job demands that exhaust employees mentally and are important predictors of negative job strain (Bakker, Demerouti, Taris, Schaufeli & Schreurs 2003; Bakker, Demerouti, & Verbeke, 2004). “Job demands refer to those physical, social or organizational aspects of the job that require sustained physical or mental effort and are therefore associated with certain physiological and/or psychological costs (e.g., exhaustion)” (Demerouti et al., 2001, p. 501).
About 3 million employees, particularly teachers, believe that relief measures or practices are needed to alleviate the experienced workload (i.e., deal with job demands) and prevent work stress (CBS, 2014; TNO, 2014). According to Elkin and Rosch (1990), the workplace is increasingly seen as an appropriate and logical setting for developing positive health practices, but Grawitch, Gottschalk and Munz (2006) state that the link between practices and employee outcomes is contingent on the effectiveness of communication within the organization. Thus, communication plays a significant and central role in a healthy
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workplace (Fitz-enz, 2000; Pfeffer, 1998). Therefore, it is interesting to gain insight into the role communication can play in the process of dealing with certain job demands by studying practices that are based on communication.
Social support and feedback can be seen as communication practices and have been proposed as possible practices that can help in the process of reducing stress (Elkin & Rosch, 1990). Both social support and feedback as well as supervisory coaching, another communication-based practice, are examples of job resources in the JD-R model:
Job resources refer to those physical, psychological, social or organizational aspects
of the job that may do any of the following: (a) be functional in achieving work goals; (b) reduce job demands at the associated physiological and psychological costs; (c) stimulate personal growth and development. (Demerouti et al., 2001, p. 501)
The JD-R model (Demerouti et al., 2001), proposes that job resources can buffer the relationships between job demands and exhaustion: employees who hold resources (e.g., social support) are more capable to deal with certain job demands and in turn experience lower levels of exhaustion. Different kinds of job demands and job resources may interact in predicting job strain (Bakker & Demerouti, 2007; Bakker, Demerouti & Euwema, 2005; Xanthopoulou, Bakker, Dollard, Demerouti, Schaufeli, Taris & Schreurs, 2007).
The first goal of this study is to gain insight into the relationships between certain job demands and work exhaustion as experienced by Dutch employees as well as to gain insight into the role communication can play in the process of dealing with certain job demands. The focus will be on employees who are working in the education sector in The Netherlands because, in comparison with other sectors, especially teachers suffer from burn-out symptoms and seven out of ten teachers believe that relief measures in organizations are needed (CBS, 2014; TNO, 2014). Thus, the study will contribute to literature by examining the relationships
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as proposed by the JD-R model in the Dutch context, specifically in the education sector where measurements are most needed (CBS, 2014). This study includes two main research questions:
RQ1: How are job demands (i.e., workload and emotional demands) related to work exhaustion among employees who are working in the education sector in The Netherlands?
RQ2: In what way can communication-based job resources (i.e., social support, performance feedback and supervisory coaching) buffer the relationships between job demands and work exhaustion?
The second goal of this study is to investigate possible differences between millennials (born between 1982 and 1999) and generation Xers (born between 1961 and 1981) in the relationships as proposed by the JD-R model. Millennials are an interesting generation to study: especially young employees between 25 and 35 years old, generally described as part of the millennial generation, suffer from burn-out symptoms (CBS, 2014; TNO, 2014). This is disturbing because in 2020 more than a third of the global workforce will consist of millennials (ManpowerGroup, 2016). Moreover, millennials are described as a generation growing up in supportive, nurturing environments who hold unique values, personality traits, and work attitudes that can impact today’s workplace (Hershatter & Epstein, 2010; Howe & Strauss, 2000; Myers & Sadaghiani, 2010; Ng, Schweitzer & Lyons, 2010; Twenge & Campbell, 2008).
Most research on millennials and millennials in the workplace has been carried out in the United States (see: Howe & Strauss, 2000; Kowske, Rasch & Wiley, 2010). According to the researcher’s knowledge, there is not much academic research on millennials in the workplace in The Netherlands while this knowledge is of great importance since especially young employees seem to suffer from burn-out symptoms (CBS, 2014; TNO, 2014). This
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study will make an effort to bridge this gap somewhat, by comparing the millennial group with generation Xers. Two sub-research questions are used:
Sub-RQ1: Are there differences between millennials and generation Xers in the relationships between job demands and work exhaustion?
Sub-RQ2: Are there differences between millennials and generation Xers in the possible buffer effects of communication-based job resources?
In practice, the JD-R Model (Demerouti et al., 2001) can be used as a tool for human resource management and has been applied within over 130 different organizations in The Netherlands (Bakker & Demerouti, 2007). A better understanding of generational differences in the possible buffering effect of different communication-based job resources can give us insights in the best practices or the best way to manage and communicate with different employees in order to cope with work exhaustion. In order to answer the research questions, an online survey was sent to employees in the education sector in The Netherlands.
Theoretical section
Job Demands-Resources Model
This study will be based on the JD-R Model (Demerouti et al., 2001). The JD-R Model follows two influential job stress models, namely the Demand-Control Model (Karasek, 1979) and the Effort-Reward Imbalance model (Siegrist, 1996). The basic assumption in these well-known models in health literature is that job strain is the result of an imbalance between the demands employees are experiencing and the resources they have at their disposal. In the Demand-Control Model (Karasek, 1979), job strain is the result of the combination of high job demands and low job control, whereas the Effort-Reward Imbalance model (Siegrist, 1996) assumes that job strain is the result of an imbalance between effort and reward.
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According to Bakker and Demerouti (2007), the simplicity of these models does no justice to the complex reality of organizations: the models include only a few variables (i.e., psychological and physical job demands, control, rewards, and autonomy) that may not be relevant for all job positions. Researchers have proposed other interesting job demands and job resources such as emotional demands, social support, supervisory support and performance feedback that are highly prevalent in the prediction of job strain (see; Bakker et al., 2005; Xanthopoulou et al., 2007). Especially the variable emotional demands is important in the teaching occupation. According to a study by Chang (2009), teachers may become emotionally exhausted due to the intensive emotional work and emotional labor required in teaching such as reform efforts, poor relationships and their engagement in maintaining student–teacher relationships.
Bakker and Demerouti (2007) state that the JD-R model is more flexible and encompasses and extends both models by including a variety of job demands and job resources. Point of departure in the JD-R model is that although every occupation may have its own specific work characteristics associated with job stress, these characteristics can always be classified in two general categories: job demands and job resources. In the JD-R model, job strain develops when (certain) job demands are high and when (certain) job resources are limited, irrespective of the type of occupation (Bakker & Demerouti. 2007). Thus, following the statements of Bakker and Demerouti (2007), the present study is based on the JD-R model, an overarching model that can be used for studying job strain in the teaching occupation. In the following sections, justifications for the choices in particular job demands and job resources in this study will be given.
Job demands: Workload and Emotional demands
The focus of this research will be on the job demands workload and emotional demands. Workload refers to quantitative, demanding aspects of the job (e.g., time pressure
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and working hard), whereas emotional demands refer to qualitative aspects of the job (e.g., how emotionally demanding the job is). Workload and emotional demands are among the most important job demands that have been found to be strong predictors of particularly the (emotional) exhaustion sub-dimension of burn-out (Bakker et al., 2003; Bakker et al., 2004; Bakker et al., 2005; Demerouti et al., 2001; Lee & Ashforth, 1996).
Different reports of Dutch institutes (CBS, 2014; TNO, 2014) show that workload and emotional demands are stated as the biggest causes of work stress or work exhaustion among employees in The Netherlands (CBS, 2014; TNO, 2014). Moreover, according to research by Chang (2009), teachers suffer from intensive emotional work and emotional labor required in teaching. One particular study by Bakker and colleagues (2005) was carried out among employees of a large institute for higher professional education in applied science in the Netherlands. According to human resource managers and employee representatives, work overload and emotional demands were among the four most important reported job demands in this educational institution in The Netherlands. Their results show that both work overload and emotional demands are strongly and positively related to exhaustion. This leads to the following hypothesis:
H1a: Among employees in the education sector in The Netherlands, high job demands (i.e., workload and emotional demands) are positively related to work exhaustion.
As stated before, young employees between 25 and 35 years old (millennials) suffer more from burn-out symptoms than employees of other ages (CBS, 2014; TNO, 2014). It is interesting to investigate what might contribute to these higher levels of exhaustion, such as the experience of higher job demands. Millennials strongly agree that they are pressured to do well and view themselves as high achieving (Hershatter & Epstein, 2010; Howe & Strauss, 2000; Myers & Sadaghiani, 2010). Because of this pressure and achievement focus, it can be
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expected that millennials feel more pressure to do well in their job and that the effect of job demands on work exhaustion will be stronger for millennials than for generation Xers.
H1b: The effect of job demands (i.e., workload and emotional demands) on work exhaustion will be stronger for millennials than for generation Xers.
Communication-based job resources: Social support, Performance feedback and Supervisory coaching
As stated before, in addition to the main effects of job demands on work exhaustion, the JD-R model proposes that job resources can buffer the relationships between job demands and exhaustion (Bakker & Demerouti, 2007). Social support is arguably the most well-known variable that has been researched as a potential buffer against job strain (see; Haines, Hurlbert, & Zimmer, 1991; Van der Doef & Maes, 1999). For example, support from colleagues can help to get the work done in time, and may therefore alleviate the impact of work overload on strain (Van der Doef & Maes, 1999). Other examples of potential buffers are: performance feedback and supervisory coaching (see; Bakker & Demerouti, 2007).
Different researchers have studied job resources that can buffer the relationships between the job demands that will be used in this study (i.e., workload and emotional demands) and exhaustion. A number of 1012 employees of a large institute for higher education participated in the study of Bakker and colleagues (2005). They found that autonomy, social support from colleagues, high-quality relationship with the supervisor and performance feedback were capable of buffering the impact of work overload on exhaustion. A study by Xanthopoulou and colleagues (2007) focused on 747 employees at four home care organizations. They found that social support, performance feedback, and opportunities for professional development buffered the relationship between workload and exhaustion but
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only autonomy and support buffered the relationship between emotional demands and exhaustion.
Although autonomy and opportunities for professional development are proposed as possible ‘buffer’ job resources as well, the focus of this study will be on the communication-based resources: social support, performance feedback and supervisory coaching, because the goal of the study is to gain insight into the role communication can play in the process of dealing with certain job demands. Social support, performance feedback and supervisory coaching are, more than autonomy and opportunities for professional development, communication-based resources because they all depend on the way people communicate with each other. Performance feedback derives for example from the information someone gets, social support from the possibility to ask colleagues for help and supervisory coaching from the openness, friendly and supportive tone in the communication. Based on the two studies (Bakker et al., 2005; Xanthopoulou et al., 2007), it can be expected that all the communication-based job resources buffer the relationship between workload and work exhaustion but that only social support will buffer the relationship between emotional demands and work exhaustion.
H2a: Communication-based job resources (i.e., social support, performance feedback and supervisory coaching) buffer the relationship between workload and work exhaustion.
H2b: Only social support (and not performance feedback and supervisory coaching) buffers the relationship between emotional demands and work exhaustion.
The buffer effects of the communication-based job resources might be different for millennials than for generation Xers. According to the literature overview in Meyers and Sadaghiani (2010), millennials were indoctrinated from the beginning of their lives to seek approval and affirmation and are eager to develop close relationships with their supervisors
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whom many consider to be their workplace parents. In the workplace, this leads to a continuous seek for guidance and direction. Managers therefore often have to spend a lot of time managing these employees. Hershatter and Epstein (2010) described similar findings. In their study they reviewed current research on millennials in the workplace and described several case studies. According to them, millennials have been encouraged to have similarly close relationships with parents, teachers, mentors, and advisors throughout their lives and as a result they expect and want, more than generation Xers, that their supervisors take an interest in them (Epstein, nd). In the workplace, millennials seek lots of feedback from supervisors and the managers of millennials frequently describe their employees as ‘‘high-maintenance’’ or ‘‘needy.’’
Related to the high preference and need of close relationships with - and frequent feedback from supervisors (Hershatter & Epstein, 2010; Myers & Sadaghiani, 2010), we can expect that millennials might benefit more than generation Xers from the communication-based resources social support, performance feedback and supervisory coaching in order to buffer the effect of job demands on work exhaustion.
H2c: The buffer effect of social support, performance feedback and supervisory coaching on the relationships between job demands (i.e., workload and emotional demands) and work exhaustion is stronger for millennials than for generation Xers.
Following these hypotheses, the conceptual model of the present study is as follows, with job demands (i.e., workload and emotional demands) as independent variables, communication-based job resources (i.e., social support, performance feedback and supervisory coaching) as moderating variables, and exhaustion as the dependent variable (see;
figure 1). Moreover, as proposed in the sub-research questions, all main effects and
moderating effects will be compared between millennials and generation Xers (see; H1b, H2c).
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H2a,
H2b H1a
Figure 1: Conceptual model
Method
In this section, the sample and procedure of this study will be presented, the central variables will be described and an introduction of the analysis will be given. An overview of the variables is presented in table 1 (appendix A; table 1).
Sample and procedure
In this study, an online questionnaire (see: Appendix B) was sent by e-mail and text messages only to employees working in the education sector in The Netherlands. Respondents were recruited through the personal network of the researcher and through educational institutions such as the University of Amsterdam and Radboud University Nijmegen. Data was obtained individually through self-report in May 2017. A total of 200 respondents participated in the survey. However, 44 respondents were excluded from the analysis because they didn’t complete the questionnaire. Thus, the sample size consists of 156 respondents (N=156). First, respondents were asked to answer questions regarding their demographics. Then, respondents filled in questions related to their experience of different job demands, communication-based job resources and work exhaustion.
Job Demands - Workload - Emotional demands Communication-based Job Resources - Social Support - Performance feedback - Supervisory coaching -S o c i a l s u p p o r t -P e r f o r m a n c e f e e Work exhaustion
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The years of birth of the respondents ranges from 1945 to 1995 (M = 1973 SD = 12.29). Thus, in 2017, the average age of respondents is 44. Following Howe and Strauss (2000), people born between 1982 and 1999 are part of the millennial group and people born between 1961 and 1981 are part of generation X. In 2017, this means millennials are people between eighteen and 35 years old and Generation Xers between 36 and 56 years old. The sample consists of 50 millennials (32.1%), 73 generation Xers (46.8%), 32 respondents from other generations (20.5%) and one missing (0.6%) because one respondent did not fill in a correct year of birth.
A number of 60 respondents (38.5%) reported to be male, 95 respondents (60.9%) female, and one respondent (0.6%) reported to be neither male nor female (0.6%). All respondents in the present study are employees in the education sector in The Netherlands, 25 respondents (16%) work at an elementary school, 60 respondents (38.5%) at a high school, and 71 respondents (45.5%) at an institute for higher education or at a university. Also, 79 respondents (50.6%) reported working with people most of the time, seventeen respondents (10.9%) reported working with information most of the time and 60 respondents (38.5%) reported working with people and information equally.
Measures
The variables in this study were operationalized in order to test the hypotheses and to contribute to the ability to answer the research questions regarding the relationships between job demands, communication-based job resources and work exhaustion as well as to investigate possible generational differences. Most variables, except from work exhaustion, were extracted from The Job Demands–Resources Questionnaire by Bakker (2014). The questionnaire does not include reversed items because the variables are based on existing scales in which no reversed items were used. Moreover, the questions are not sensitive and
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reversing items could lead to misinterpretation or confusion. The operationalization of the central variables is discussed below.
Workload. Workload was measured with the 4-item work-pressure scale, developed
by Bakker (2014). Sample questions are “Do you have to work at speed?” and “Do you work under time pressure?” Based on recommendations after pre-testing the questionnaire, the question: “Do you have to work at speed?” has been changed into “Do you have to work at a fast pace?” The questions were answered on a 5-item Likert-type scale ranging from 1 (never) to 5 (very often). A principal component analysis (PCA) shows that the four items form a single dimensional scale: only one component has an eigenvalue above 1 (eigenvalue 2.942) with an explained variance of 73.56 %. All items correlate positively and high with the first component (all the factor loadings are above 0.70). A reliability analysis shows that the scale is reliable (α = .88). Therefore, it appears the scale measures workload. The four items were calculated and computed into a new variable ‘workload’ (M = 3.12, SD = 0.88, Actual scores observed ranged from 1.25 to 5.00).
Emotional demands. Emotional demands were measured with the 6-item scale of
Bakker (2014). The scale includes questions such as “In your work, are you confronted with things that personally touch you” and “In your work, do you deal with clients who incessantly complain?” In the questions, the word ‘clients’ (that represents clients from the organization and internal clients like fellow colleagues) was replaced by the words ‘students, parents or colleagues’ because the sample consists of employees in the education sector whose clients are parents, students and colleagues. Moreover, based on recommendations after pre-testing the questionnaire, the word ‘touch’ in the question “In your work, are you confronted with things that personally touch you?” has been replaced by the word ‘affect’. Questions were answered on a 5-item Likert-type scale ranging from 1 (never) to 5 (very often). A factor analysis (PCA) shows that two components have an eigenvalue above 1 and that there are two
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double loaders with a difference below 0.20. Excluding these two items (“In your work, do you deal with students, parents or colleagues who incessantly complain?” and “Do you have to deal with students, parents or colleagues who do not treat you with the appropriate respect and politeness?”) in a second factor analysis, shows that the four remaining items form a single dimensional scale: only one component has an eigenvalue above 1 (eigenvalue 2.717) with an explained variance of 67.93 %. All items correlate positively and high with the first component (all the factor loadings are above 0.69). Moreover, reliability analyses shows that the scale that consists of four items is more reliable (α = .84) than the scale that consists of all six items (α = .82). Therefore, it appears the scale that consists of four items measures emotional demands better. Thus, two items were excluded and four out of six items were calculated and computed into a new variable ‘emotional demands’ (M = 2.58, SD = 0.76, actual scores observed ranged from 1.00 to 5.00).
Social support. Social support was measured with the 3-item scale of Bakker (2014).
The scale includes questions such as “If necessary, can you ask your colleagues for help?” and “Can you count on your colleagues to support you, if difficulties arise in your work?” The questions were answered on a 5-item Likert-type scale ranging from 1 (never) to 5 (very
often). The factor analysis (PCA) shows that only one component has an eigenvalue above 1
(eigenvalue 2.402) with an explained variance of 80.07 %. All items correlate positively and high with the first component (all the factor loadings are above 0.86) and a reliability analysis shows that the scale is reliable (α = .86). Therefore, the three items form a single dimensional scale that measures social support. The three items were calculated and computed into a new variable ‘social support’ (M = 3.65, SD = 0.92, actual scores observed ranged from 1.67 to 5.00).
Performance feedback. Performance feedback was measured with the 3-item scale of
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work objectives” and “My job offers me opportunities to find out how well I do my work” and respondents could answer from 1 (never) to 5 (very often). A principal component analysis (PCA) shows that the three items form a single dimensional scale: only one component has an eigenvalue above 1 (eigenvalue 2.386) with an explained variance of 79.54 %. All items correlate positively and high with the first component (all the factor loadings are above 0.85). Reliability of the scale is good (α = .87). Therefore, it appears the scale measures performance feedback. The three items were calculated and computed into a new variable ‘performance feedback’ (M = 2.79, SD = 0.79, actual scores observed ranged from 1.00 to 5.00).
Supervisory coaching. Supervisory coaching was measured with the 5-item scale,
developed by Bakker (2014). The scale includes items such as “My supervisor uses his/her influence to help me solve problems at work.” and “My supervisor is friendly and open to me” and respondents could answer from 1 (never) to 5 (very often). The factor analysis (PCA) shows that only one component has an eigenvalue above 1 (eigenvalue 3.823), with an explained variance of 76.45%. All items correlate positively and high with the first component (all the factor loadings are above 0.81) and a reliability analysis shows that the scale is reliable (α = .87). Thus, the scale measures supervisory coaching. The five items were calculated and computed into a new variable ‘supervisory coaching’ (M = 3.13, SD = 0.95, actual scores observed ranged from 1.20 to 5.00).
Work exhaustion. Work exhaustion was measured with the 8-item sub-scale
‘emotional exhaustion’ of the MBI-NL ES instrument developed by Van Horn and Schaufeli (1998). The MBI-NL ES is a valid and reliable instrument for the study of burnout among Dutch teachers. The sub-scale ‘emotional exhaustion’ refers to a depletion of an individual’s emotional resources and the feeling that the individual has nothing left to give to others psychologically. Sample items of the sub-scale are “I feel like I’m at the end of my rope” and
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“I feel fatigued when I have to get up in the morning to face another day on the job”. Based on recommendations after pre-testing the questionnaire, the question “I feel like I’m at the end of my rope” was changed into “I feel worn out”. Moreover, the answering categories were changed from 0 (never) to 6 (always) into 1 (never) to 5 (very often), because the questionnaire would be more consistent and less confusing when the answering categories were consistent throughout the questionnaire. A principal component analysis (PCA) shows that the eight items form a single dimensional scale: only one component has an eigenvalue above 1 (eigenvalue 5.010) with an explained variance of 62.63 %. All items correlate positively and high with the first component (all the factor loadings are above 0.69). Reliability of the scale is very good (α = .91). Therefore, it appears the scale measures (emotional) work exhaustion. The eight items were calculated and computed into a new variable ‘work exhaustion’ (M = 2.10, SD = 0.76, actual scores observed ranged from 1.00 to 4.63).
Strategy of analysis
In order to test the hypotheses, multiple analyses have been conducted. First, a Chi-square test of independence was conducted in order to test if generation and the control variables gender, educational institution and nature of work are independent. Then, an independent samples t-test was used in order to compare generations on their average score on work exhaustion. For hypothesis 1a, a linear multiple regression analysis was conducted with work exhaustion as the dependent variable and workload and emotional demands as the independent variables. In order to compare millennials with generation Xers in hypothesis 1b the data was split by generation, and the same linear multiple regression as in hypothesis 1a was conducted in order to compare results.
In order to conduct moderation analysis as proposed by hypothesis 2a, 2b and 2c, the PROCESS tool (Hayes) was used. By using model 1 via PROCESS in SPSS, the dependent
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variable or outcome variable was work exhaustion and the independent variable was workload in hypothesis 2a and emotional demands in hypothesis 2b. Social support, performance feedback and supervisory coaching were used as moderator variables separately in every PROCESS analysis. For hypothesis 2c, the ‘select cases’ command was used to compare results of both generations.
Results
In this section, the results of the analyses that were conducted to test the hypotheses are presented. First, results regarding the control variables and results regarding the relationship of generation and work exhaustion will be presented. Then, results regarding job demands (i.e., workload and emotional demands) and work exhaustion will be reported including a comparison between generations. After, results of the PROCESS analyses regarding the moderating effects of communication-based job resources (i.e., social support, performance feedback and supervisory coaching) on the relationships between job demands and work exhaustion will be reported. Here, again, results between generations will be compared.
Control variables
In order to test if generation and the control variables: gender, educational institution and nature of work are independent, a Chi-square test for independence was conducted. Results show there are no significant interactions with gender (X² (1) = 2.22 p = .137), educational institution (X² (2) = 1.05 p = .592), and nature of work (X² (2) = 1.97, p = .373). Thus, the control variables and generation are independent. Therefore, there is no need to include these control variables in further analyses.
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Before reporting the results of the hypotheses, the relationship between generation and work exhaustion has been tested. According to research, as described in the introduction, especially young employees (millennials), suffer from burn-out symptoms (CBS, 2014; TNO, 2014). In order to be able to compare generations on their average score on work exhaustion, an independent samples t-test was conducted. Results show that the average score on work exhaustion of millennials (M = 2.09, SD = 0.58) does not differ significantly from the average score on work exhaustion of generation Xers, t (121) = 0.37, p = .712, 95% CI [-0.21, 0.31]. Thus, millennials are not more exhausted from work than generation Xers.
Job demands and work exhaustion
In hypothesis 1a, it was expected that job demands (i.e., workload and emotional demands) would have a positive effect on work exhaustion. The linear regression model with work exhaustion as dependent variable and workload and emotional demands as independent variables is significant, F (2, 153) = 51.70, p < .001 and the strength of the prediction is strong: 40 percent of the variation in work exhaustion can be predicted on the basis of workload and emotional demands (R²= .40). As presented in the first two rows in table 2
(Appendix A; table 2), both workload (b* = .44, t = 6.28, p <.001) and emotional demands (b*
= .30, t = 4.20, p <.001), show a significant, moderately strong association with work exhaustion. Thus, hypothesis 1a is accepted: Among employees in the education sector in The Netherlands, high job demands (i.e., workload and emotional demands) are indeed positively related to work exhaustion; the higher the scores on workload and emotional demands, the more exhausted employees are.
Generational comparison
In hypothesis 1b, it was expected that the effect of job demands (i.e., workload and emotional demands) on work exhaustion, would be stronger for millennials than for
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generation Xers. For millennials, the regression model with work exhaustion as dependent variable and workload and emotional demands as independent variables is significant, F (2, 47) = 5.35, p = .008, but the strength of the prediction is weak: only 19 percent of the variation in work exhaustion among millennials can be predicted on the basis of workload and emotional demands (R²= .19). Among millennials, workload (b* = .43, t = 2.84, p = .007), shows a significant, moderately strong association with work exhaustion but emotional demands (b* = .01, t = 0.07, p =.943) do not have a significant association with work exhaustion (see; Appendix A, table 2).
For generation Xers, the regression model with work exhaustion as dependent variable and workload and emotional demands as independent variables is significant, F (2, 70) = 37.00, p < .001 and the strength of the prediction is strong: 51 percent of the variation in work exhaustion among generation Xers can be predicted on the basis of workload and emotional demands (R²= .51). Among generation Xers, both workload (b* = .54, t = 5.81, p <.001) and emotional demands (b* = .30, t = 3.25, p =.002) show a significant, moderately strong association with work exhaustion (see; Appendix A, table 2).
Thus, the effect of workload on work exhaustion is significant for both generations but the effect is stronger for generation Xers (b* = .54), then for millennials (b* = .43). The effect of emotional demands on work exhaustion is only significant for generation Xers (b* = .30) but not for millennials. Therefore, hypothesis 1b is rejected: the effect of job demands (i.e., workload and emotional demands) on work exhaustion is not stronger for millennials than for generation Xers. The effects are actually stronger for generation Xers, especially regarding emotional demands.
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The PROCESS tool was used to investigate the hypotheses that communication-based job resources (i.e., social support, performance feedback and supervisory coaching) moderate the effect of job demands (i.e., workload and emotional demands) on work exhaustion. The effects were tested using a bootstrap estimation approach with 5000 samples. All Beta coefficients (b*) of the interactive effects are shown in table 3 (Appendix A; table 3).
First, results regarding the moderating effect of the communication-based job resources on the relationship between workload and work exhaustion are presented. The results of a moderation test regarding the job resource social support, reveal that the interactive effect of workload with social support is not significant (b* = .06, SE = .06, t = -1.11, p = .268), the R² does not change significantly when interaction is added. The interactive effect of workload with performance feedback (b* = -.08, SE = .06, t = -1.34, p = .183) and the interactive effect of workload with supervisory coaching (b* = -.05, SE = .06, t = -0.83, p = .410) are also not significant. Thus, social support, performance feedback and supervisory coaching do not buffer the relationship between workload and work exhaustion, hypothesis 2a is rejected.
Next, for hypothesis 2b, results regarding the moderating effect of the communication-based job resources on the relationship between emotional demands and work exhaustion will be presented. The results of a moderation test regarding the job resource social support, reveal that the interactive effect of emotional demands with social support is not significant (b* = -.10, SE = .06, t = -1.72, p = .087). The R² does not change significantly when interaction is added. Again, same results were found regarding the job resources performance feedback and supervisory coaching: the interactive effect of emotional demands with performance feedback (b* = -.13, SE = .09, t = -1.44, p = .151) and the interactive effect of emotional demands with supervisory coaching (b* = -.07, SE = .09, t = -0.70, p = .486) are not significant. Thus,
22
social, support, performance feedback and supervisory coaching do not buffer the relationship between emotional demands and work exhaustion, hypothesis 2b is rejected.
Generational comparison
In hypothesis 2c, it was expected that the moderating effects of social support, performance feedback and supervisory coaching on the relationships between job demands (i.e., workload and emotional demands) and work exhaustion, would be stronger for millennials than for generation Xers.
First, generational results regarding the moderating effect of the communication-based job resources on the relationship between workload and work exhaustion are presented. As shown in table 3 (Appendix A; table 3), not one of the interaction effects of the moderator’s; social support (b* = .02, SE = .11, t = 0.15, p = .881), performance feedback (b* = -.09, SE = .10, t = 0.88, p = .384) and supervisory coaching (b* = -.08, SE = .09, t = -0.92, p = .363), is significant for millennials. Similar results were found for generation Xers: not one of the interaction effects of the moderator’s; social support (b* = -.05, SE = .07, t = -0.70, p = .488), performance feedback (b* = -.04, SE = .09, t = -0.40, p = .693) and supervisory coaching (b* = -.04, SE = .06, t = -0.66, p = .509), is significant. Thus, for both generations, no significant interaction effects of communication-based job resources on the relationship between workload and work exhaustion were found.
Next, generational results regarding the moderating effect of the communication-based job resources on the relationship between emotional demands and work exhaustion are described. As shown in table 3 (Appendix A; table 3) again, not one of the interaction effects of the moderator’s social support (b* = .10, SE = .16, t = 0.65, p = .522), performance feedback (b* = -.19, SE = .12, t = -1.55, p = .129) and supervisory coaching (b* = .04, SE = .21, t = -0.21, p = .835) is significant for millennials. For generation Xers, the interaction
23
effect of the moderator’s; performance feedback (b* = -.10, SE = .28, t = -0.37, p = .714) and supervisory coaching (b* = -.13, SE = .16, t = -0.77, p = .440) are not significant, but the interaction effect of the moderator social support (b* = -.18, SE = .08, t = -2.13, p = .036) is significant. For generation Xers it seems that, on the lowest level of social support, the effect of emotional demands on work exhaustion is stronger than on the middle or the higher level of social support. Thus, for millennials there are no significant interaction effects of communication-based job resources on the relationship between emotional demands and work exhaustion, but for generation Xers the interaction effect of social support is significant.
In total, the moderating effects of social support, performance feedback and supervisory coaching on the relationships between job demands (i.e., workload and emotional demands) and work exhaustion, is not stronger for millennials than for generation Xers. Therefore, hypothesis 2c is rejected. Nevertheless, social support seems to have a moderating effect on the relationship between emotional demands and work exhaustion, but only for generation Xers.
Discussion
The aim of this study was to investigate the relationships between certain job demands and work exhaustion as experienced by employees working in the education sector in The Netherlands as well as to gain insight into the role communication can play in the process of dealing with certain job demands. Moreover, the researcher was interested in possible differences between millennials and generation Xers in these relationships.
Regarding the first main research question about the relationships between job demands and work exhaustion, the results of the present study demonstrated that both job demands (i.e., workload and emotional demands) are highly related to work exhaustion. This is in line with findings in previous research on the Job-Demands Resources Model
24
(Demerouti et al., 2001) in which workload and emotional demands have been found to be strong predictors of particularly the (emotional) exhaustion sub-dimension of burn-out (Bakker et al., 2003; Bakker et al., 2004; Bakker et al., 2005; Demerouti et al., 2001; Lee & Ashforth, 1996). Although this study only focused on the education sector, results regarding the relationships between job demands and work exhaustion or burn-out symptoms seem to be similar to general findings on employees in The Netherlands as reported by Dutch institutes (CBS, 2014; TNO, 2014).
The second main research question was focused on the way communication-based job resources (i.e., social support, performance feedback and supervisory coaching) could buffer the relationships between job demands and work exhaustion. Results in this study have shown that social support, performance feedback and supervisory coaching were not able to buffer the relationships between job demands (workload and emotional demands) and work exhaustion. This is inconsistent with the findings of Bakker and colleagues (2005) and Xanthopoulou and colleagues (2007), who studied the JD-R model in the Dutch context and have found that several job resources were capable of diminishing the impact of job demands on work exhaustion. The unexpected nonsignificant interaction effects in the current study could be attributable to the specific demands and resources that were included. Also, several studies on different stress models such as the Demand-Control Model (Karasek, 1979) have similarly failed to report significant interaction results (see; Schreurs & Taris, 1998; Van der Doef & Maes, 1999). Thus, it seems that the communication-based job resources: social support, performance feedback and supervisory coaching only have limited capability of buffering the undesired impact of certain job demands on work exhaustion.
Generational comparison
Before including job demands in the discussion about the generational comparison, results on employees’ scores on work exhaustion will be discussed. It appears that in the
25
sample in this study, millennials are not more exhausted by their work than generation Xers although this was expected based on findings in Dutch reports (CBS, 2014; TNO, 2014). These Dutch reports have shown that young employees between 25 and 35 years old suffer more from burn-out symptoms than employees of other ages. Differences between this study and the Dutch reports could be explained by the fact that the current study only investigated the ‘emotional exhaustion’ sub-dimension of burn-out while the Dutch reports could also have been focused on the two other dimensions of burn-out: depersonalization and diminished personal accomplishment on which millennials could have scored higher. In fact, in the current study, the average score of employees of all generations on work exhaustion is below average. Thus, employees of all generations in the sample used in this study are in general not that exhausted by work. In future research, it could be interesting to use all the dimensions of the burn-out scales (Van Horn & Schaufeli, 1998) in order to test burn-out in general and compare generations on different dimensions. Moreover, future research could include a control variable about working hours in order to compare work exhaustion as experienced by employees who work on project basis or part-time with employees who work full-time.
Turning to the generational comparison of the relationships between job demands and work exhaustion, as proposed by the first sub-research question, interesting results were found. Unexpectedly, the effects of workload and emotional demands on work exhaustion seem to be stronger for generation Xers than for millennials. It appeared that there was not an effect of emotional demands on work exhaustion among millennials. Since the effect of both demands on work exhaustion is stronger for generation Xers than millennials, while on average they do not differ in their scores on work exhaustion, a possible explanation could be that millennials experience certain other job demands in a more negative way than generation Xers. In this study, only workload and emotional demands were used as job demands while there are other demands that could be (even more) strongly related to work exhaustion, which
26
could be more relevant for millennials. For example, millennials place a great importance on rapid advancement and the development of new skills, while also ensuring a meaningful and satisfying life outside of work (Ng et al., 2010). In that sense, millennials might suffer more from the absence of these elements (i.e., job demands like career stagnation or home-work interface) than from the job demands workload and emotional demands. Especially for research in the education sector, where it could be relatively hard to climb the ladder and separate work from private life, it is interesting to include job demands such as career stagnation in order to investigate how strongly certain job demands are related to work exhaustion or burn-out and how this might differ per generation.
As described before, it seems that communication-based job resources such as social support, performance feedback and supervisory coaching only have limited capability of buffering the undesired impact of certain job demands on work exhaustion. Nevertheless, when comparing generations as proposed by the second sub-research question, something interesting happens. It seems that, in the current study, social support is actually able to buffer the relationship between emotional demands and work exhaustion, but only for generation Xers. It is not surprising that the buffering effect of social support only exists among generation Xers since there was not even an effect of emotional demands on work exhaustion among millennials. Still, this finding contradicts the expectation that millennials might benefit more than generation Xers from communication-based job resources such as social support. This expectation was based on research in which millennials are described as a generation growing up in supportive, nurturing environments where they developed high preferences and a high need for close relationships, open communication and frequent feedback (Hershatter & Epstein, 2010; Myers & Sadaghiani, 2010). This general view is mostly based on the American culture and nation but it might be that the Dutch millennials in the current study differ from the millennial group as described in scientific literature carried out in The United
27
States. In future research, it will be interesting to compare the preferences and needs of millennials in The Netherlands with millennials from different countries such as The United States in order to see if they meet the stereotypical image about millennials. Then, better explanations regarding generational differences in the JD-R model can be given.
Limitations and future research
The current study had several limitations. First and foremost, the study is unable to draw causal claims, as it relied on cross-sectional data. This limitation could be addressed in future research by running longitudinal studies. Secondly, to be able to ascribe generational differences to the characteristics of the generations and not on the age of the respondents, a cohort study should be used in future research. In the current cross-sectional study, differences between generations could have been solely linked to the age of the respondents. For example, results in the present study show that the effects of workload and emotional demands on work exhaustions are stronger for generation Xers than for millennials but it is not clear if millennials would have reported similar results if they would have had the same age as generation Xers. A cohort study, in which the same individuals are observed over a long period of time, is able to control for age effects and therefore to investigate the characteristics of generational differences more precisely. Thirdly, in the present study, the gender question did not include an ‘other’ category. In future research this category should be included in order to be able to include respondents who do not describe themselves as male or female. Lastly, in future research, it would be helpful to enlarge the sample size in order to ensure the studies will have sufficient power to find significant (moderating) results. This is especially relevant when comparing groups (e.g., generations) where data of smaller groups (and thus a smaller n) will be compared.
Despite these limitations, the study had two main strengths. First, the scales used in this study were all highly reliable. Second, the fact that the sample consisted of employees
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from different areas in The Netherlands and different educational institutions, including elementary schools, high schools and institutes for higher education such as universities, increased the generalizability of the present study’s findings.
Conclusion and implications
In conclusion, the current study shows that, among employees who are working in the education sector in The Netherlands, workload and emotional demands are positively related to work exhaustion, especially for generation Xers. Moreover, although communication-based job resources do not have the capability of buffering the undesired impact of these job demands on work exhaustion for all employees, social support seems to be beneficial for generation Xers; social support helps generation Xers to deal with emotional demands in a way that it alleviates the impact of these demands on work exhaustion.
In practice, these results give us better insights in internal communication practices that can help different employees to cope with job demands that are related to work exhaustion. Based on the results, HR departments or school management could focus more on creating a social supportive environment by stimulating and organizing team-meetings where difficulties can be discussed and employees can interact with- and support each other. Still, since measurements are especially needed in the education sector, future research should extend the findings of the current study in bigger samples in longitudinal cohort studies and include other job demands, (communication-based) job resources and dimensions of burn-out in order to further contribute to the knowledge of possible effective practices or measures that can reduce work exhaustion.
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Appendices
Appendix A: TABLE 1 Descriptives variables N Range Mean SD Generation Year of birth Control variables Gender Educational institution Nature of work Independent variables Workload Emotional demands Moderators Social support Performance feedback Supervisory coaching Dependent variable Work exhaustion 155 155 156 156 156 156 156 156 156 156 1945-1995 1-2 1-3 1-3 1-5 1-5 1-5 1-5 1-5 1-5 1973.08 1.61 2.29 1.88 3.16 2.58 3.65 2.79 3.13 2.10 12.29 0.49 0.73 0.94 0.88 0.76 0.92 0.79 0.95 0.7634 TABLE 2
Summary regression analyses for job demands (workload and emotional demands) predicting work exhaustion, divided by generation (all generations, millennials and generation Xers)
Generation Variable B SE B b* t p 95% CI
All generations Workload 0.38 0.06 .44 6.28 .000 [0.62, 0.50] Emotional demands 0.30 0.07 .30 4.20 .000 [0.16, 0.44] Millennials Workload 0.29 0.10 .43 2.84 .007 [0.08, 0.49] Emotional demands 0.01 0.14 .01 0.07 .943 [-0.28, 0.30] Generation Xers Workload 0.44 0.08 .54 5.81 .000 [0.29, 0.59] Emotional demands 0.28 0.09 .30 3.25 .002 [0.11, 0.44]
35 TABLE 3
Summary interaction terms of PROCESS moderating analyses, divided by generation (all generations, millennials and generation Xers)
Generation Independent variable Moderator b* All generations Workload Social Support -.06
Performance feedback -.08 Supervisory Coaching -.05
Emotional Demands Social Support -.10
Performance feedback -.13 Supervisory Coaching -.07
Millennials Workload Social Support .02
Performance feedback -.09 Supervisory Coaching -.08
Emotional Demands Social Support .10
Performance feedback -.19 Supervisory Coaching .04
Generation Xers Workload Social Support -.05 Performance feedback -.04 Supervisory Coaching -.04
Emotional Demands Social Support -.18*
Performance feedback -.10 Supervisory Coaching -.13
36 Appendix B
Questionnaire Work Exhaustion
Thank you for participating in this study on work exhaustion! The questionnaire is anonymous so you don’t have to fill in your name and answers will be dealt with
confidentially. The questions that follow concern your own work situation. For the realization of this research it is very important that you fill out all the questions. There are no right or wrong answers. Please provide the answer that you think that suits you best. Completing the questionnaire will take approximately 10 minutes. In case there are any questions or remarks regarding this questionnaire please contact me, I will be happy to answer your
questions (lisan.boerrigter@live.nl).
Demographics
First of all, I would like to ask you to fill in the following information about yourself: Q1: What is your gender? *
Male Female
Q2: What is your year of birth? (for example: 1993) …………
*Note; after receiving feedback from one respondent who didn’t want to be described as female or male, a neither/both category has been included in another questionnaire and data from this respondent was added to the main dataset. In the main dataset, the neither/both category regarding the gender variable has been included as a missing.
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Q3: In what kind of educational institution do you work? Elementary school
High school
Higher education/University Other ____________________
Q4: Could you state the nature of your work?
Most of the time, I work with people (students, parents)
Most of the time, I work with information (like research, administration, preparation) I work with people and with information equally
Work
The following questions or statements refer to your personal work situation and your
experience of related aspects. For each question, please choose the answer that best describes your situation.
Q5: Work situation. The following questions refer to your personal work situation and your experience of it.
Never Sometimes Regularly Often Very
often Do you have to work at a fast pace?
Do you have too much work to do? How often do you have to work extra hard in order to reach a deadline? Do you work under time pressure?
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Q6: Emotions at work. The following questions are about your emotions during your work.
Never Sometimes Regularly Often Very
often Is your work emotionally demanding?
In your work, are you confronted with things that personally affect you? Do you face emotionally charged situations in your work?
In your work, do you deal with students, parents or colleagues who incessantly complain?
In your work, do you have to deal with demanding students, parents or
colleagues?
Do you have to deal with students, parents or colleagues who do not treat you with the appropriate respect and politeness?
39
Q7: Collaboration. The following questions concern the collaboration with your colleagues.
Never Sometimes Regularly Often Very
often If necessary, can you ask your colleagues
for help?
Can you count on your colleagues to support you, if difficulties arise in your work?
In your work, do you feel valued by your colleagues?
Q8: Feedback. The following questions concern the feedback that you receive about your work.
Never Sometimes Regularly Often Very
often I receive sufficient information about my
work objectives.
My job offers me opportunities to find out how well I do my work.
I receive sufficient information about the results of my work.
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Q9 Supervisor. The following questions are about your supervisor.
Never Sometimes Regularly Often Very
often My supervisor informs me whether he/she
is satisfied with my work.
My supervisor shows consideration for my problems and desires regarding my work.
I feel valued by my supervisor.
My supervisor uses his/her influence to help me solve problems at work.
My supervisor is friendly and open to me.
Q10 Feelings regarding work experience. The following statements relate to the way you experience your work and how you feel about it. Please explain how often each statement applies to you.
Never Sometimes Regularly Often Very
often I feel emotionally drained by my work.
I feel used up at the end of the day. I feel fatigued when I have to get up in the morning to face another day on the
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job.
Working with people all day is really a strain for me.
I feel ‘burned out’ from my work. I feel frustrated by my job.
I feel I’m working too hard in my job. I feel worn out.
That was the last question. Please click on the 'next' button to save your answers. Thank you very much for your participation!
