Study Results: Effect of Burnout on Clinical Lab Turnover Intention
June 2017 - Vol. 6 No. 5 - Page #14

Background

Despite the vital role clinical laboratory practice plays in patient care, the field is experiencing a shortage of qualified professionals. Many laboratories are experiencing an increase in voluntary staff turnover (ie, when employees choose to leave versus being asked to leave), yet research on factors affecting the turnover intentions of clinical laboratory employees is limited. The study described herein aims to examine the effect of burnout on the turnover intention of clinical laboratory employees in Florida.
Methods: For this quantitative study, data were collected using a cross-sectional, online survey comprising the Maslach Burnout Inventory – General Survey (MBI-GS) and a demographic questionnaire. The data were analyzed using linear regression and analysis of variance (ANOVA) in statistical package for the social sciences (SPSS) software.
Results: The sample encompassed 184 Florida state-licensed clinical laboratory employees out of 1,000 invited participants. Among clinical laboratory employees in Florida, the findings revealed significant predictive relationships among all three dimensions of burnout (emotional exhaustion, cynicism, and professional efficacy) and turnover intention.
Conclusion: These findings suggest emotional exhaustion and professional efficacy are the best predictors of turnover intention. In an effort to reduce turnover among their employees, clinical laboratory managers must create strategies that will reduce these factors.

Introduction

Job burnout as a cause of stress has garnered significant interest during the past few decades as the concept, and its negative effects, has become better understood.1 The concept of burnout was first introduced by psychologist Herbert J. Freudenburger in 1974.2 A well-known definition of burnout was introduced by Maslach and Jackson in 1981: “A syndrome of emotional exhaustion and cynicism that occurs frequently among individuals who do ‘people-work’ of some kind.”3 Further, burnout is described via three primary sub-constructs: emotional exhaustion, cynicism, and professional efficacy.3 Emotional exhaustion refers to employees lacking energy and feeling as though they can no longer give of themselves psychologically. Cynicism develops when employees begin to have negative and ambivalent attitudes toward the clients they serve. Professional efficacy suffers when employees have persistent feelings of negativity, unhappiness, and dissatisfaction with their own professional accomplishments.

Burnout is omnipresent among health care professionals, and this is generally understood to be due to the stressful nature of the work and the increasing demands being placed on health care workers.4 Other researchers have confirmed the correlation between burnout and turnover intention in the health care field among nurses, physicians, and other health care workers.5-7 Therefore, it is important to explore the concept of burnout and determine its influence on the turnover of laboratory employees.

Turnover of key laboratory talent not only affects health care quality, but is costly to the organization.8 The laboratory profession already is experiencing a shortage of qualified professionals, so health service organizations must work on retaining current employees, thus reducing voluntary turnover. The purpose of this study was to determine the influence job burnout has on the turnover intention of clinical laboratory employees in Florida. It was hypothesized that employees who report lower levels of burnout are less likely to have intentions to leave their current organization.

Methodology

Participants and Procedures

For the study’s quantitative, cross-sectional survey design, 1000 licensed clinical laboratory personnel were randomly selected from the total population of state-licensed clinical laboratory personnel in Florida (more than 10,000). Selected participants were required to have an active license from the Florida Department of Health (FDH) as a clinical laboratory director, clinical laboratory supervisor, clinical laboratory technologist, or clinical laboratory technician. Also, participants were required to have an email address on file with the FDH, which was used to send study invitations and explain the voluntarily nature of the study, including the protection of participant identities. Study invitation emails included a brief overview of the study, consent procedures, and a link to access the survey online. Participants were given a timeframe of 16 days to complete the survey, approval for which was gained through the institutional review board (IRB).

Instruments

Demographic Questionnaire

A demographic questionnaire for each participant asked for information on gender, age, education level, current job role, years of service at current organization, current work shift, and years of experience working as a clinical laboratory professional (see Table 1).

Burnout

The independent variable, burnout, was assessed using MBI-GS, a 16-item scale that measures three subscales of burnout, including emotional exhaustion, cynicism, and professional efficacy.9 The MBI-GS assesses burnout using a 7-point frequency rating scale from 0 to 6 in which 0 = never, 1 = a few times a year or less, 2 = once a month or less, 3 = a few times a month, 4 = once a week, 5 = a few times a week, and 6 = everyday. The three subscale scores on the MBI-GS are separate and distinct from one another and cannot be added together to form an overall scored of burnout. Therefore, each participant had three scores, one for each of the three subscales.

The emotional exhaustion subscale consists of 5 items describing feelings of being exhausted, the cynicism subscale consists of 5 items describing indifference or a distant attitude regarding one’s work, and the professional efficacy subscale contains 6 items describing general feelings of success, accomplishment, and competence in one’s work.9 Lower scores for professional efficacy along with higher scores for both emotional exhaustion and cynicism indicate higher degrees of burnout, whereas low scores on emotional exhaustion and cynicism along with higher professional efficacy scores indicate lower degrees of burnout.9-10

Turnover Intention

The dependent variable, organizational turnover intention, was measured using three items (reflective statements) adapted from the Michigan Organizational Assessment Questionnaire:11

  • I will likely actively look for a new job in the next year
  • I often think about quitting
  • I will probably look for a new job in the next year

The three items were rated on a 7-point Likert scale from (1) strongly agree to (7) strongly disagree. Responses to these three items were summed to create a total composite score. Higher turnover intention is indicated by a higher composite score and vice versa. The three items used to assess employees’ turnover intention were included in the demographics questionnaire.

Statistical Analysis

Data analysis was performed using SPSS version 21. Descriptive statistics were used to analyze demographic variables. Linear regression and multiple step-wise linear regression were used to see how each of the three dimensions of burnout (emotional exhaustion, cynicism, and professional efficacy) correlated with turnover intention.

Results

Demographic Characteristics of Participants

From the 1,000 laboratory professionals invited to participate in this study, 237 responses were received, of which 53 were excluded due to being incomplete. The 184 completed surveys yielded a useable response rate of 18.4%. Participant demographic data are shown in Table 1. Of the 184 participants, the majority were female (71.7%), were working as clinical laboratory technologists/technicians, worked first shift, were age 56 or older, held a bachelor’s degree, had worked at their current organization for 5-10 years, and had been in the clinical laboratory science field for more than 30 years.

Level of Burnout Among Participants

Table 2 shows the range (low, average, high) of experienced burnout for each of the three subscales. Based on the results, participants (N = 184) were found to be experiencing exhaustion (M = 3.00) at an average level, cynicism (M = 2.25) at a high level, and professional efficacy (M = 5.12) at a high level.

Descriptive statistics were performed to further examine the factors associated with burnout and to determine the extent to which the respondents were experiencing burnout. As shown in Table 3, respondents’ scores on the exhaustion subscale indicate that at the end of their work day, they feel moderately used up (M = 3.53; S.D. = 1.92). Cynicism scores indicate that respondents just want to do their job and not be bothered (M = 3.78; S.D. = 2.13). On the professional efficacy subscale, scores ranged from 4.42-5.80 and suggest that most respondents feel they are efficient at their job.

Correlation Between Burnout and Turnover Intention

To examine the relationship between burnout and turnover intention, the independent variables were established as the three dimensions of burnout: emotional exhaustion, professional efficacy, and cynicism. The dependent variable for this analysis was the turnover intention composite score (TIScore), obtained by finding the mean of the three turnover intention variables.

Linear regression analysis results indicate that the relationship between emotional exhaustion and turnover intention is statistically significant, F(1182) = 103.215, p < .001. Emotional exhaustion has a positive relationship with turnover intention (β = .602, p < .001). In addition, linear regression analysis indicates that the relationship between professional efficacy and turnover intention is statistically significant, F(1182) = 9.513, p = .002. Furthermore, professional efficacy has an inverse relationship with turnover intention (β = -.223, p = .002). The results of the linear regression analysis indicate that the relationship between cynicism and turnover intention is statistically significant: F(1182) = 49.877, p < .001. Cynicism has a positive relationship with turnover intention (β = .464, p = < .001).

A multiple step-wise linear regression analysis was then conducted to determine which combination of burnout predictor variables (exhaustion, professional efficacy, and cynicism) would best predict turnover intention among clinical laboratory employees in Florida. Results of this analysis between the independent variables and the dependent variable showed a prediction model that was statistically significant: F(2,181) = 57.623, p < .001. The model revealed that exhaustion has a positive relationship with turnover intention (β = .585, p = <.001) and professional efficacy has an inverse relationship with turnover intention (β = -.166, p =.005). The model excluded cynicism, as it was not a significant predictor of turnover intention.

Discussion

The results of this study were consistent with other research studies from the literature that found a high correlation between burnout and turnover intention among healthcare professionals.7,12 Based on the study results, clinical laboratory employees in Florida are experiencing burnout.

Results of this study support the concept that as burned out employees start to feel emotionally exhausted, they will begin to look for ways to reduce that exhaustion, perhaps by leaving their current job. Further, as laboratory employees become burned out, they may begin to develop increased levels of cynicism and a lackadaisical attitude toward their job. Emotional exhaustion and professional efficacy were found to be the best predictors of turnover intention among this group of health care workers and thus should be the focus of efforts to reduce burnout among lab employees.

Limitations and Future Work

There were several limitations with this study. First, a cross-sectional design was used, meaning no firm conclusions regarding causation can be made. Future studies can utilize a longitudinal design. Second, this study only focused on one geographic location, Florida. Future studies can expand this study and apply it to a much larger population. Additionally, although the response rate for this study was satisfactory, it was somewhat lower than expected. Nonetheless, the study sample was representative of the whole population of clinical laboratory workers regarding gender and age based on data reported in the 2015 Medical Laboratory Observer (MLO) Annual Salary Survey.

Conclusions

This study investigating the role that job burnout plays in the decision of clinical laboratory workers to leave their job reveals a strong correlation between burnout and turnover intention. Given this, laboratory leadership teams must work on methods to decrease burnout among employees by reducing emotional exhaustion and increasing the sense of professional efficacy. Hopefully, these findings clearly delineate the effects of job burnout among laboratory personnel and encourage laboratory leadership to work on strategies to decrease burnout and turnover among their employees.

References

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9. Maslach C, Jackson SE, Leiter MP. Maslach burnout inventory manual, 3rd ed. Consulting Psychologists Press: California. 1996

10. Amigo I, Asensio E, Menéndez I, Redondo S, Ledesma J. Working in direct contact with the public as a predictor of burnout in the banking sector. Psicothema. 2014; 26(2): 222-226.

11. Cammann C, Fichman M, Jenkins GD, Klesh JR. Assessing the attitudes and perceptions of organizational members. In Seashore SE, Lawler EE, Mirvis PH, Cammann C (Eds). Assessing Organizational Change: A Guide to Methods, Measures, and Practices. Wiley: New York. pp 71-138, 1983

12. Zhang Y, Feng X. The relationship between job satisfaction, burnout, and turnover intention among physicians from urban state-owned medical institutions in Hubei, China: a cross-sectional study. BMC Health Serv Res. 2011; 11: 235.


Tasia Hilton, PhD, MLS(ASCP)CM is assistant professor of health care administration at Saint Leo University in Savannah, Georgia. She also is a medical technologist at Liberty Regional Medical Center in Hinesville, Georgia. Tasia received a BS in chemistry from the University of South Carolina, a BS in medical laboratory science from Armstrong Atlantic State University, a Master of Healthcare Administration from Ashford University, and a PhD in Health Services - Healthcare Administration from Walden University. Tasia’s 10+ years of clinical laboratory experience include positions in general core laboratory departments, toxicology, and health information technology.

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