Presenter Information

Elizabeth Ellis
Christopher Leone

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Faculty Sponsor

Dr. Christopher Leone

Faculty Sponsor College

College of Arts and Sciences

Faculty Sponsor Department

Psychology

Location

SOARS Virtual Conference

Presentation Website

https://unfsoars.domains.unf.edu/on-fire-or-burned-out-the-role-of-self-monitoring-on-burnout-in-the-workplace/

Keywords

SOARS (Conference) (2020 : University of North Florida) -- Posters. University of North Florida. Office of Undergraduate Research; University of North Florida. Graduate School; College students – Research -- Florida – Jacksonville -- Posters; University of North Florida – Graduate students – Research -- Posters; University of North Florida. Department of Psychology -- Research -- Posters. Social Sciences-- Research – Posters

Abstract

Workplace burnout (i.e., exhaustion, disengagement, lack of professional efficacy) produces turnover which, in turn, increases costs (personnel recruitment, selection, training) for businesses (Maslach et al., 2001). Job demands predict workplace exhaustion whereas job resources predict workplace disengagement (Demerouti et al., 2001). Burnout is also related to individual differences in personality (Alessandri et al., 2018). In the present study, we explore the potential mediating effect of demands and resources on the connection between self-monitoring (Fuglestad & Snyder, 2010; Wilmot et al., 2015) and burnout. Self-monitoring can be conceptualized as either a single, dichotomous variable (Snyder, 1974) or two, continuous variables: protective and acquisitive (Wilmot et al., 2015). Using Amazon’ s Mechanical Turk Participants System (MTurk), we recruited 109 employees from mid- to large-sized companies. Participants completed one measure of self-monitoring (Snyder, 1974), two measures of burnout (Kristensen, Borritz, Villadsen, & Christensen, 2005; Maslach et al., 2001), and one measure of job demands and resources (Bakker, 2014). Demographic variables such as age and sex were also assessed. Mediation was assessed using Hayes’ PROCESS model (Hayes, 2013). No direct relationship between self-monitoring (all types) and burnout was found. An indirect effect -mediated by job resources – was found for univariate as well as acquisitive self-monitoring and burnout . No indirect effects were found for protective self-monitoring and burnout. Results were replicated across both burnout measures. Our findings offer a theoretical and empirical addition to the literature on self-monitoring and the workplace (Day & Schleicher, 2006) as well as workplace burnout (Maslach et al., 2001).

Comments

Have you ever sat there at your job and thought, wow, I don’t think I can do this anymore. Well, you may have been experiencing burnout. Burnout has three components, exhaustion, cynicism, and lack of professional efficacy. Emotional exhaustion is based on emotional and cognitive withdrawal from the workplace. This is an active feeling of kind of a sadness or a desire to not engage with your work. Cynicism on the other hand is a more negative feeling and moving towards like this dis-compassionate feeling. It’s a feeling of depersonalization and cynical attitudes. So this is going to be when you might see coworkers lash out at one another or go against what is being asked of them. Finally, there’s lack of professional efficacy. This is a negative personal evaluation. So this is no longer a, there’s something wrong with the workplace, but more of a, maybe there’s something wrong with me.

Now, burnout has been linked to several different types of personality variables, but there hasn’t been as much research on the role of self-monitoring in the experience of burnout. So if monitoring has been linked to several other workplace correlates such as role conflict, role ambiguity, job performance, job satisfaction, um, and a couple of others. Therefore it’s actually very important to look at the role of self-monitoring on burnout. So if monitoring comes in two flavors, we’ve got univariate model and the bivariate model. Univariate model of self monitoring is the classical low versus high self-monitor. The low self-monitor, they want to be themselves no matter the situation. So they are cross situationally consistent. Um, the highest self-monitor on the other hand wants to be the right person for the right place at the right time. They are situationally specific. So a low self-monitor is going to be an introvert or an introverted.

No matter the situation, no matter who they’re with it. High self monitor on the other hand, may act introverted when they’re around other introverts or extroverted when they’re around other extroverts. It just depends on what the situation calls for. Now there’s the Bivariate model of self-monitoring, which is a reconceptualization and self-monitoring into two continuous variables. Those variables are acquisitive and protective self-monitoring, acquisitive self monitors want to achieve status and reward. So they want to, you know, be the best of the best. They are your prototypical high self-monitor from the univariate model. Protective self monitors are also high in self pondering, so they in those situationally specific attitudes, but it’s because they want to avoid status loss. So the acquisitive self-monitor is confident. Where is the protective self monitor is more anxious

now in terms of um, workplace correlates. Another known connection to burnout is job demands and resources. These are sources of burnout. So Job demands is sustained physical and mental effort that comes from the things that you have to do in your job. Whereas job resources can be either external or internal. External resources come from the organization and your social support. Internal resources are your stable cognitive features. So external resources might be something like a support group or your coworkers. While internal resources could be something like your ability to perform tasks such as do math or your ability to work quickly under pressure. Now for my thesis, we had a couple of different research questions. Our primary question was whether or not there was a direct connection between self-monitoring and burnout or if there was an indirect connection. So in this we were looking at a mediation model through the job demands resources model or a secondary question was, is there a difference between protective and inquisitive self-monitoring? Because if these two phenomenon are in fact individual differences, then they should show different patterns of results. All right. For our method, um, we had disciplines for participants. We had 109 participants, 46% female for mid to large size companies, recruited using Amazon’s mechanical Turk system. All of the participants had full time jobs and they held some sort of managerial or supervisory role.

Our procedure consists of giving out the 25 items, self-monitoring, scale, the mass like burnout, inventory, general survey, the Copenhagen burnout inventory, and the job demands/resources questionnaire. 25 items. Self-monitoring scale has, um, questions that in total makeup, the univariate self-monitoring scale and then certain questions that make up the bivariate self monitoring scales. Some, um, examples of questions might be, I find it hard to imitate the behavior of other people, meaning of low self-monitoring. All right. Answer. True. For this we mean low self-monitoring or I would make a good actor and the answer of true for this would be indicative of high self-monitoring. For the by various self-monitoring scale, we could say that I would make a good actor would be acquisitive self-monitoring. And even if I am not enjoying myself, I often pretend to be having a good time is indicative of protective laundering.

For the burnout inventories, the Maslach burnout inventory has three sub-scales, the emotional exhaustion, cynicism and professional efficacy scales. I feel emotionally drained by my work would be probably of emotional exhaustion. I just want to do my job and not be bothered who’d be cynicism and I can effectively resolve the problems that arise in my work would be professional efficacy. Now for the Copenhagen burnout inventory, they look at personal and work burnout. We wanted to see if there was a difference between the Maslach and the Copenhagen. The Copenhagen was, how often do you feel worn out would be just personal burnout because personal burnout is anything outside of work. So it’s just overall feeling. Whereas do you feel worn out at the end of the working day would be indicative of work burnout because it’s a more specific just to work issue. Finally we asked the job demands resources questionnaire, does your work require a lot of concentration, would be a demand and do you have control over how your work is carried out would be a resource for our findings.

What we found was that no matter the type of self-monitoring or the type of burnout, there was not a direct connection. However for um, or for the univariate model of self monitoring and for quizzed if self-monitoring. We did finding mediation through job resources. So self-monitoring was really to job resources and job resources really to burnout and that connection was significant. Now for protective self monitoring we didn’t find any connection at all, so there was nothing between self-monitoring in job demands or job resources. Now it’s important to note that for burnout, job demands and job resources were always related to the different kinds of burnout. So what we were really looking for was that connection from self-monitoring to the job demands resources model.

So some applications for these findings is that it helps me to roadmap for managers, it helps them see where people are going and what they should be concentrating on when it comes to helping their employees. So some other things about this is that there is implications for personality based burnout interventions and it helps expand the literature on burnout and self-monitoring. So some of the implications were personality based burnout intervention suggest that burnout intervention should be specialized to the employee’s personality. So there’s not just a one, you know, one fixed solution, some limitations to this study are your typical non experimental design limitations. So we have the directionality and third variable problems and it was also a self-report. Now for the third variable problems, we did find a confound between protective self-monitoring in age. And so therefore in the future, we should look at that connection. Some other future directions that we might be interested in are potential predictors such as extroversion and neuroticism. And this is because of the connection between protect, um, inquisitive and protective self-monitoring with extroversion and neuroticism. And some other potential media dues might be the areas of work, life role, conflict and ambiguity and work, family conflict. Given the role conflict is related to both self-monitoring and burnout. There’s good evidence that suggests that there would be a mediation through this pathway.

Alright, so this has been all about self monitoring and burnout in the workplace. Thank you.

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Apr 8th, 12:00 AM Apr 8th, 12:00 AM

On Fire or Burned Out?: The Role of Self-Monitoring on Burnout in the Workplace

SOARS Virtual Conference

Workplace burnout (i.e., exhaustion, disengagement, lack of professional efficacy) produces turnover which, in turn, increases costs (personnel recruitment, selection, training) for businesses (Maslach et al., 2001). Job demands predict workplace exhaustion whereas job resources predict workplace disengagement (Demerouti et al., 2001). Burnout is also related to individual differences in personality (Alessandri et al., 2018). In the present study, we explore the potential mediating effect of demands and resources on the connection between self-monitoring (Fuglestad & Snyder, 2010; Wilmot et al., 2015) and burnout. Self-monitoring can be conceptualized as either a single, dichotomous variable (Snyder, 1974) or two, continuous variables: protective and acquisitive (Wilmot et al., 2015). Using Amazon’ s Mechanical Turk Participants System (MTurk), we recruited 109 employees from mid- to large-sized companies. Participants completed one measure of self-monitoring (Snyder, 1974), two measures of burnout (Kristensen, Borritz, Villadsen, & Christensen, 2005; Maslach et al., 2001), and one measure of job demands and resources (Bakker, 2014). Demographic variables such as age and sex were also assessed. Mediation was assessed using Hayes’ PROCESS model (Hayes, 2013). No direct relationship between self-monitoring (all types) and burnout was found. An indirect effect -mediated by job resources – was found for univariate as well as acquisitive self-monitoring and burnout . No indirect effects were found for protective self-monitoring and burnout. Results were replicated across both burnout measures. Our findings offer a theoretical and empirical addition to the literature on self-monitoring and the workplace (Day & Schleicher, 2006) as well as workplace burnout (Maslach et al., 2001).

https://digitalcommons.unf.edu/soars/2020/spring_2020/23