research methodology of job satisfaction project

Improving Nurses’ Job Satisfaction: an Action Research Study

• Original Research
• Published: 03 February 2021
• Volume 35 , pages 15–32, ( 2022 )

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• Shahrzad Yektatalab 1 ,
• Marzieh Momennasab 2 ,
• Soroor Parvizy 3 &
• Noushin Mousazadeh 4  

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Despite the growing knowledge about job satisfaction, the improvement of it for healthcare providers has remained a challenge. The present study was conducted to identify the challenges to nurses' job satisfaction and improving it by an action research approach. The present study was conducted from 2016 to 2018. The participants were twenty-four nurses, head nurses, and academic researchers as facilitators. They worked through two cycles of reflection and action for change for 19 months. The data were collected and analyzed using the concurrent mixed-method approach. The findings of the quantitative data revealed that the score of nurses’ job satisfaction increased from 50.8 ± 8.34 to 59.88 ± 7.82 in pre and post measurements. Furthermore, reflection on actions in two cycles resulted in designing and implementing action plans for change, learning for both participants and facilitators, and improvement in nurses’ satisfaction with the new program. Some of the Nurses’ Job Satisfaction challenges can be decreased with their participation, they could establish the foundation of a sustainable job satisfaction program successfully. Also, implications introduced in this action research could be applicable for top managers and health system policymakers in a wider range of practice.

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Acknowledgements

Hereby, the researchers of this study wish to express their gratitude to the deputy of research at the Shiraz University of Medical Sciences for approving and providing financial support for this research project. They also would like to appreciate the nurses who participated in this study.

This work was supported by the Research Vice-chancellor of Shiraz University of Medical Sciences (Grant No.94.01.89.9155).

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Community Based Psychiatric Care Research Center, Department of Mental Health and Psychiatric Nursing, School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran

Shahrzad Yektatalab

Department of Nursing, School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran

Marzieh Momennasab

Department of Pediatric Nursing, Nursing and Midwifery Faculty, Center for Educational Research in Medical Sciences (CERMS), Iran University of Medical Sciences, Tehran, Iran

Soroor Parvizy

Amol Faculty of Nursing and Midwifery, Mazandaran University of Medical Science, Talebamoli Street, Fayyasbakhsh Alley, Sari, Iran

Noushin Mousazadeh

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All authors designed the study. Noushin mousazadeh gathered the data. Shahrzad Yektatalab, Marzieh Momennasab, Noushin mousazadeh and Soroor Parvizy interpreted and analyzed the data. Shahrzad ayaektatalab and Noushin Mousazadeh wrote and revised the manuscript.

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Yektatalab, S., Momennasab, M., Parvizy, S. et al. Improving Nurses’ Job Satisfaction: an Action Research Study. Syst Pract Action Res 35 , 15–32 (2022). https://doi.org/10.1007/s11213-021-09554-z

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Accepted : 01 January 2021

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DOI : https://doi.org/10.1007/s11213-021-09554-z

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An empirical study on the job satisfaction and turnover intention of health-care professionals: Moderated moderation approach

Ghulam muhammad kundi.

Department of Health Administration, College of Public Health and Health Informatics Qassim University, Al-Bukayriyah, Saudi Arabia

Yasir Hayat Mughal

Fahad albejaidi, syed arif pasha, associated data.

All data sets are available with authors and it will be produced on reasonable request.

The objective of this study was to investigate relationship between job satisfaction and turnover intention of health-care professionals using the moderated moderating approach.

Explanatory sequential research design was applied. Non-probability convenience sampling technique was used to determine the sample size using Weiers formula. Scales adopted in the current study were validated through exploratory and confirmatory factor analysis. To test the hypothesis correlation, the hierarchical multiple regression was used. In the second stage, semi-structured face-to-face interviews from 35 interviewees were conducted and transcribed in Nvivo.

Job descriptive index, cognitive style index (CSI), cognitive style indicator, and turnover intention scales were found to be reliable. Furthermore, correlation analysis shows that the factors of job satisfaction were significantly correlated with turnover intention. In addition, findings of the interviews highlighted the importance of cognitive styles for increasing the job satisfaction of health-care professionals.

Conclusions:

Study concludes that the involvement of health-care professionals in making health-care policies enhances their job satisfaction that also reflected on their performance. Moreover, it also reduces their turnover intention of workforce.

Introduction

Turnover intention is a mental process and it needs a lot of thinking for decision-making. The decision of whether to leave the job or to stay at a job is very difficult.[ 1 , 2 ] There are direct and indirect costs associated with turnover intention. For example, the recruitment and selection process, training, and development process need time and a lot of cost paid by organizations to train new employees.[ 3 ] Meanwhile, it brings a lot of burden to existing employees for replacing the previous employee.[ 4 ] Organizations, especially in health care, are very difficult to retain employee[ 5 ] as it embroils a lot of thinking and decision-making how to reduce turnover intention. Allinson and Hayes[ 4 ] have developed cognitive style index (CSI). They have divided human mind into two parts; one is called left brain it is also called analytical and second part is called intuition or right brain. People with analytical style tend to collect information first and then they make decisions while intuitive people make decision on basis of their experience, judgment, and feelings.[ 6 ] Later on, Cools and Broeck[ 7 ] developed cognitive style indicator (CoSI). She has divided analytical style into three more parts and named those constructs knowing, planning, and creating for making decisions. It is believed that decision-making plays very important role in reducing turnover intention and increasing job satisfaction. Hence, it was very crucial to use a well-reported and validated instrument for decision-making in this study. Job satisfaction is an international phenomenon,[ 8 ] in the 1960s, more than 4000 articles were published on job satisfaction. However, it gains popularity after the theories given by Herzberg two factor theory, Vroom’s[ 9 ] theory, McGregor Theory, Theory X and Theory Y, and job characteristics model by Hackman and Oldham[ 10 ] Spector theory of job satisfaction.[ 11 ] All these researchers confirmed that there are few attributes of job satisfaction that is held constant, for example, salary, supervisor, promotion, colleagues, work, work environment, and job security.[ 12 , 13 ] Later on, researchers added more variables in theories of job satisfaction but for this study, researchers have chosen the above-mentioned variables.[ 7 , 13 ] There is an American researcher named Judge, Klinger, and Simon[ 13 ] conducted and reported many articles on job satisfaction. From the findings of this study, it was indicated from the results that instrument was found reliable and valid.[ 14 , 15 ] CoSI was only related with job and supervisor while CSI was not significantly related with any factor of job satisfaction. In addition, there was moderated moderating effect on satisfaction and salary only but no moderated moderation effect on other variables.[ 16 , 17 ] Themes emerged from qualitative interviews and findings also supported the quantitative findings. Based on the above literature, we hypothesized proposed the following: H 1 : There is a negative relationship between predictors and criterion variables, that is, satisfaction, salary, supervision, promotion, coworkers, work environment, work itself, CSI and CoSI, and turnover intention. H 2 : There is a moderated moderating effect of CSI, CoSI on factors of job satisfaction, and turnover intention.

Explanatory sequential research design

There are six research designs for mixed methods research; however, in this study, explanatory sequential research design is adopted, it has two stages of research. In the first stage, quantitative data were collected and analyzed, while, in the second stage, interviews were conducted for qualitative study and analyzed. Qualitative data were used to supplement, support, and strengthen the quantitative results. For quantitative study, positivism philosophy was employed whereas, for a qualitative study, a phenomenological approach was adopted as recommended by Creswell,[ 18 ] Collis and Hussey.[ 19 ] Pragmatism considers the happening of events to the situation. In a mixed method, the researcher is capable to solve the problem using both methods that help researchers to go deep into the problem or the issue understudy. Smith et al .[ 20 ] suggested the use of at least 10 interviewees for the interpretative phenomenological approach (IPA), however, in the second stage of qualitative analyses, we have used 35 interviewees which is above the Smith threshold, that is, 10 participants. The majority of scientists and researchers have used survey questionnaires for the assessment of behaviors and attitudes of individuals and organizations.[ 21 ] Thus, the survey is a common, popular, and easy method that allows the researcher to collect a very big data in less time and cost, therefore, in this study, survey was employed to collect data.

Population and sampling

The population of the study consisted of health-care professionals in the Riyadh region of Saudi Arabia that included 124 administrative and 23,246 staff members, thus, N of the study was 23,370. Since the population was big so it was impossible to contact every member to obtain their responses, therefore, sampling was essential. Probability and non-probability sampling techniques are given by researchers in health care. Both have their strengths and weaknesses.

In this study, researchers have used simple random stratified sampling, whereas, convenience sampling technique was applied to collect responses from the respondents. Weiers[ 22 ] has developed a statistical formula [SD 2 /((E 2 /Z 2 ) + (SD 2 /N))] for the finite population to determine sample size. Therefore, researchers have employed the Weiers formula. 95% confidence level is suggested by social scientists to determine the sample size for the finite population, which is equal to 1.96 z-value. Table 1 illuminates the procedure to determine the sample size of the study in hand.

Sample size

Measures and procedures

The job satisfaction instrument was adopted from Busari et al .[ 8 ] while turnover intention was taken Mughal et al. ,[ 4 ] and for CoSI, it was adopted from Cools and Broeck.[ 7 ] Therefore, the instrument developed by Cools and Broeck[ 7 ] was used in this study. The questionnaires were administered among administrators and staff. The questionnaire included four sections; first is about job satisfaction, second is about turnover intention, and the third is about the CoSI; all these sections were measured on a 5-point Likert scale. Job satisfaction has seven items, turnover has three items, and CoSI has 18 items, while the fourth section was demographic variables.

Data analysis

SPSS was used for quantitative data analysis. Exploratory factor analysis, bivariate correlation, and hierarchical multiple regression (HMR) were run to investigate the best fit model. Further for moderation, a procedure given by Aiken and West[ 23 ] is used. First, the variables were mean centered to reduce the multicollinearity problem. Then, interaction term was created to test moderation results. Thereafter, all variables were entered into HMR according to theoretical significance. Then, interaction plots were plotted one standard above the mean and one standard deviation below the mean. Nvivo 8 was used for qualitative data analysis; nodes were developed, where from themes emerged [Figures ​ [Figures11 11 and ​ and12]. 12 ]. Template analysis was used to analyze themes. Since, ideas and themes are parcel part of the respondents’ lives. Researchers also focus on the phenomenological flavor of themes. The current study was conducted in 2020.

Word cloud taken from NVIVO

Qualitative model taken from NVIVO

Work environment CoSI, CSI. CSI: Cognitive style index, CoSI: Cognitive style indicator

A total of 301 employees have participated in the current study. There were total 225 male participants, that is, 74.75%, 76 females have participated in the current study, that is, 25.2%. Majority of the participants belong to public sector health-care organization such as 198 (65.7%) while 34.2% belong to private sector organizations. Further analyses of results revealed that most of the professionals were foreigners and belong to India, Pakistan, Egypt, and Sudan, that is, 49% Indian, 33% Pakistani, 9.9% Egyptian, and remaining Sudan. In the first run of exploratory factor analysis, it is necessary to check the sample is adequate for EFA or not? This objective was accomplished by Kaiser-Meyer-Olkin (KMO) of all variables KMO for cognitive style was recorded KMO = 0.7 which is above 0.5 Hair et al .[ 24 ] for job satisfaction KMO = 0.775, for turnover intention KMO = 0.703. Bartlett’s’ test of sphericity for all variables was significant. Promax was used for rotation, as shown in Table 2 .

Factor loading pattern matrix

Table 3 presents the results of the correlation between predicting variables and the criterion variable. As expected, satisfaction is negatively related with turnover intention while positively but weakly related with CoSI and CSI, that is, r = 0.463, P < 0.05 and r = 0.91, r = 0.91, P > 0.05. Further examination of the relationship between salary and turnover intention is found moderate and negative but significant, that is r = −0.502, P < 0.05, but alary is not related to CoSI and CSI.

Correlation matrix

Further examination of results shows that promotion is negatively but significantly related with turnover intention, that is r = −0.332, P < 0.05, but promotion is negatively related with CoSI, that is r = −0.063, P > 0.05 while promotion is positively but insignificantly related with CSI, that is r = 0.028, P > 0.05. In the same way, further examination of correlation results shows that job/work is negative but significant related with turnover intention but also significant related with CoSI but weakly related with CSI, that is r = −0.412, P < 0.05; r = 0.134, P < 0.05; and r = 0.024, P > 0.05. Furthermore, examination revealed that coworkers/colleagues are also negative but significant related with turnover intention but weakly and positively insignificant with CoSI and CSI, that is r = −0.250, P < 0.05; r = 0.070, P > 0.05; and r = 0.050, P > 0.05.

Likewise, results revealed that supervisor is negative and significant but weak related with turnover intention also significant related with CoSI but insignificant related with CSI, that is r = −0.373, P < 0.05, r = 0.112, P = 0.05, and r = 0.012, P > 0.05. Furthermore, work environment is negative and significant with turnover intention but insignificant with CoSI and CSI, that is r = −0.304, P < 0.05; r = 0.105, P > 0.05; and r = 0.035, P > 0.05, so on the basis of discussion from correlation results, it is clear that our hypothesis 1 is substantiated and accepted. This means that there is a significant positive relationship between the predictors and criterion variables of the study, Table 3 .

There is different goodness of fit indices given by Hair et al . [ 24 ] for model fitness. Fit indices and their fitness range values are given in Table 5 .

Model fitness measurement model results

Table 4 and Figure 1 illustrate results for model 1 of the study. AMOS-SEM was used to develop a measurement model. In Figure 1 , measurement model is given. All the factor loadings are higher than 0.5 except one construct, that is, job it is 0.49, two constructs are deleted from analysis because of low factor loadings. All the goodness of fit index values met the required level, that is, Chi-square =2.847, RFI = 0.889, NFI=0.921, TLI = 0.925, CFI = 0.947, and IFI = 0.947, P < 0.01, all the values are in the specified range so the model if fit. Further analysis of results revealed construct reliabilities and average variance extracted values. Construct reliability for job satisfaction and CoSI is 0.786 and 0.706 while AVE value is 0.433 and 0.461 below 0.5 but construct reliability is met criteria, so reliability and validity are established.[ 25 ]

Measurement model. RMSEA: Root mean square error of approximation, GFI: Goodness of fit index, IFI: Incremental fit index, CFI: Comparative fit index, TLI: Tucker Lewis index, NFI: Normed fit index, RFI: Relative fit index. Chi-sq/df: Chi-square/Degree of freedom

Evaluating the model fit to fit before confirmatory factor analysis CFA

Figure 2 was developed for the structural model. In this model, job satisfaction is independent; cognitive style is also independent (moderator is considered independent) and turnover intention is criterion variable. Table 6 shows the goodness of fit indices. It is found that model is fit, and all the goodness of fit indices are in the specified range, that is, χ 2 = 2.847, RFI=0.889, NFI=0.921, TLI=0.925, CFI=0.947, IFI =0.947, and RMSEA=0.078. Further analysis of results revealed that correlation between job satisfaction and cognitive style is r = 0.17, P < 0.01, and impact of job satisfaction on turnover intention is beta β = −0.64, P < 0.05 and β = 0.20, P < 0.05 is also significant and R 2 = 0.41 it means that job satisfaction and cognitive style show variance on turnover intention 41%. It means that there is a negative impact of job satisfaction on turnover intention and the positive impact of cognitive style on turnover intention.

Structural model. RMSEA: Root mean square error of approximation, GFI: Goodness of fit index, IFI: Incremental fit index, CFI: Comparative fit index, TLI: Tucker Lewis index, NFI: Normed fit index, RFI; Relative fit index. Chi-sq/df: Chi-square/degree of freedom

Moderating effects of cognitive style on job satisfaction and turnover intention were also checked in AMOS-SEM. Results are highlighted in Figure 3 , it is found that job satisfaction has a negative impact on turnover intention, that is, β = −0.81, P < 0.05, while cognitive style has positive effect β = 0.10, P < 0.05, an interaction term was created by multiplying job satisfaction and cognitive style β = 0.24, P < 0.05, R 2 = 0.37 it means job satisfaction, cognitive style, and interaction term shows variance on turnover intention 37%. Next HMR is used for testing hypothesis 8, that is, there is moderated moderating effect of CoSI and CSI on job satisfaction factors and turnover intention. This moderated moderation results are also known as three-way interaction. All seven independent variables and their three-way interaction results are presented in Table 7 .

Moderation model

Moderated moderation results

In this study, CoSI is used as a moderator and the CSI is used as a moderated moderator. First examination of three-way interaction done with satisfaction CoSI and CSI and turnover intention. The results revealed that the interaction term is significant and ∆R 2 is also significant it means that there is moderated moderation and CSI does act as a moderated moderator on the CoSI, satisfaction, and turnover intention. Three-way interaction was conducted using the same procedure and found that CSI does not act as a moderated moderator on CoSI, coworkers, and turnover intention, there is no significant interaction term and ∆R 2 is also not significant although there is changed in ∆R 2 is recorded.

Further examination of the results revealed that there is moderated moderation occurs on the relationship between CoSI, promotion, work, work environment, and supervisor because all interaction terms were insignificant and there is no significant change in recorded in ∆R 2 but when CSI is used with salary and turnover and CoSI it does acts as moderator because interaction term is significant and ∆R 2 is also significant so CSI acts as a moderated moderator on CoSI salary and turnover intention so our hypothesis 2 is partially accepted for satisfaction and salary. Table 7 highlights the moderated moderation result of this study.

To interpret the interactions, all three-way interactions were plotted, with cut values of one standard deviation below the mean and one standard deviation above the mean on each moderator variable. Examination of the first plot revealed that the CSI, that is, CSI is acting as a moderated moderator on CoSI, that is, COSI.

From the plot, it is also revealed that low CoSI and high CSI interact with high CoSI and high CSI. Hence, this plot [ Figure 4 ] is consistent with the results shown in Table 3 for satisfaction. Further analysis of results shows that low COSI and low CSI fully moderate the relationship between salary, turnover intention, and CoSI. Hence, this plot [ Figure 5 ] is consistent with the results shown in Table 7 for salary.

Satisfaction CoSI, CSI. CSI: Cognitive style index, CoSI: Cognitive style indicator

Salary CoSI, CSI. CSI: Cognitive style index, CoSI: Cognitive style indicator

Similarly, examination of the plot [ Figure 6 ] shows that CoSI and CSI interact with each other, but these two variables do not interact with coworker and turnover intention so three-way interaction does not exist in this Figure 6 . Further examination of plot [ Figure 7 ] indicated that high CoSI and high CSI and high CoSI and low CSI interact with promotion and turnover intention but low COSI and low CSI do not interact so there is no three-way interaction exists. Further examination of plots revealed that Figures ​ Figures8 8 - ​ -10 10 also consistent with regression results.

Coworkers CoSI, CSI. CSI: Cognitive style index, CoSI: Cognitive style indicator

Promotion CoSI, CSI. CSI: Cognitive style index, CoSI: Cognitive style indicator

Supervisor CoSI, CSI. CSI: Cognitive style index, CoSI: Cognitive style indicator

Work CoSI, CSI. CSI: Cognitive style index, CoSI: Cognitive style indicator

In this study, we have used 35 interviews, whereas Creswell[ 27 ] Smith et al .[ 29 ] suggested the use of at least 10 interviews for qualitative analysis. Furthermore, Silverman[ 25 ] suggested that in qualitative research, qualitative data must be natural. There should be no coding and the researcher is not allowed to minimize data. Semi-structured interviews are the best source for qualitative study as in this study researchers aimed to understand the phenomena in-depth, additionally; this method allows the interviewees to ponder freely on the issues. In the first instance, researchers got the consent of all the interviewees then an interview guide was provided to them as Rubin and Rubin[ 26 ] considered an interview guide as the scaffolding of the interview. The date and time for the interview were fixed mutually as practiced by Smith et al. ,[ 20 ] and interviews were recorded suggested by IPA. All interviews were transcribed verbatim. As asserted by Remenyi et al. ,[ 27 ] the researcher has read transcription thoroughly and made necessary corrections to make sense of it. Below is the narration and analyses of the interview data. Different questions were asked from interviewees about different attributes of their current job. Interviewees respond in the following manner: “Regarding salary my package is according to government rules and you know in public sector rules are already defined for each cadre and scale. So, salary is not an issue.” Another respondent explained “My package is attractive, and I am happy with this package, but I am not satisfied from the workload in this organization that is beyond the capacity, sometimes, I have to complete the work of my colleagues.” Other interviewees highlighted the issue of inter-relationships. Their concerns are as under “Relationships with colleagues are fine but my senior colleagues are not supportive. If I need equipment and consumable office supplies, I have to wait a few weeks or even a month. Although I know they have their limitations as they have to follow the rules, and they cannot buy from their own money since they have to ask the purchase department to make things available that is why it takes time. Efficiency of work is concerned, comparatively; the progress of work is slower than the private sector.” Other attributes of job satisfaction are highlighted in this way as under: “Work environment is good, yet promotion policies are inflexible, you know you have to fulfill the criteria for promotion, once you fulfill it, then you will get it” one of the respondents discussed about job security that “Job security in the public sector is very high since these are tenured jobs… you can easily work for whole life…. and nobody can disturb you if your conduct is aligning with the rules of business.” Responses of respondents regarding turnover are mentioned below. “I don’t have the intention to leave that job in future I am satisfied with my current job.” Other respondents highlighted their concerns in this way… “Since I am working in public sector organization so I have no intention to leave that job, however, if I get a better opportunity, then I could decide to move.” Cognitive style is used for making decisions. Different cognitive styles were used by researchers to know their role in decision-making, therefore, CSI and CoSI were used in this study. Respondents were of the view that: ”First I try to find the reason of problem… and it is better to know the history and background of the problem then you are better able to find the better solution, so I used to analyze the situation first as you know, we all are human beings and we have emotions and feelings so sometimes we cannot control our feelings and, in such situation, I use to make spontaneous decisions. However, I am intuitive by nature.” This study has some limitations which can affect some potential areas. First, the sample size of this study is small and collected from health-care organizations only and that to in Riyadh region, thus findings of this research could not be generalized to other sectors such as banks and universities, therefore, it will be better if future studies may use large sample size. Second, this study is quantitative; future studies can use mixed methods and longitudinal data for more thought provoking results. The third limitation is methodological limitations. This study has used two moderators, whereas, future studies can use multiple or series of mediators to come up with novel results and findings. Other dimensions of cognition such as feelings, emotions, and judgment can be used in future studies.[ 28 , 29 ]

Conclusions

It is imperative for the health-care organizations to enhance the satisfaction of their professionals by applying different strategies for involving them in decision-making policies, this not only increases their job satisfaction but also reduces turnover intention of workforce. Furthermore, management and leadership of the health-care professionals play very important role in increasing the job satisfaction of their professionals.

Authors’ Declaration Statements

Ethical approval.

The current study was carried out without receiving any funding and was approved by Qassim University Ethical Committee.

Data availability

Authors’ contributions.

G.M.K and Y.H.M participated in manuscript drafting, conceptualization, the idea of study design, and methodology. F.A and S.A.P.: Perform review, editing, formal data analysis, and validation. All authors have read and agreed to the published version of the manuscript.

Acknowledgments

Authors acknowledges to all study subjects for their active participation to complete the study.

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Research Project : Employee Job Satisfaction

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TEKLIT WELEGERGS

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This study was conducted to measure the impact of job stress on job satisfaction of managerial employees working in Domestic Commercial Banks. Job stress is considered as the harmful physical and emotional response that occurs when there is a poor match between job demands and capabilities, resources or needs of the employee. Job satisfaction describes how comfortable an individual is with own job. A self develop research model was tested where job stress is stated as the independent variable. All the branches of domestic commercial banks located in Colombo district were investigated and it was carried out on a sample of sixty branch managers. Simple random sampling was applied to select a representative sample. A self develop questionnaire was used to collect data. It was found that the measurement scales met the acceptable standards of validity and reliability analyses. Correlation analysis and regression analysis were used to test the research hypothesis. Researcher found that there is a high degree of job stress among branch managers of private commercial banks while having a moderate degree of job stress among branch managers of public banks. Findings revealed that women managers have a higher degree of job stress than male managers. Managers in public banks are highly satisfied while managers in private banks have either moderate or low level of job satisfaction. Women managers enjoy their jobs highly while male managers enjoy moderately. Study confirmed that job stress is significantly correlated with job satisfaction. Though job stress is a significant predictor of ICBI 2011 Faculty of Commerce and Management Studies 2 job satisfaction, it can be concluded that too little or too much of job stress leads to have low level of job satisfaction and moderate level of job stress leads to have high level of job satisfaction, in the tested domain.

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Apparel sector is the highest income generator of the country; it brings in an income of over USD 4.8 billion as per the Central Bank report, 2015. This is an industry that deals with 15% of the country’s labour force. In the apparel sector amount of automated processors are negligible therefore no matter what instruments, machinery and tools are brought in, it is the humans who will work on these and they are the ones who use these tools, machinery and instruments. As such performance of employees is one of the critical factors that the apparel company focuses on. Owners of these factories spend huge amount of time and money on machinery and tools to obtain maximum performance. But very little focus is given for psychological factors such as job satisfaction and behavioral factor such as leadership style. This research was done to find out the relationship of job satisfaction and leadership style on employee job performance of managerial and non-managerial employees at Sumithra Group of Companies in Sri Lanka. Five dimensions were selected for the Job Satisfaction namely works it-self, pay, supervision, co-workers and working conditions. Autocratic, democratic and laissez-faire were considered as the dimension of the leadership styles. The traits, behavior and results were the dimensions of the employee job performance. Out of the 4007 active employees at the time of the research 550 employees including all managers, supervisors and worker level employee were taken into the sample and 455 have responded to the self-administrated questioner given. This study indicated that 52% of the employee job performance in Sumithra Group is explained by the job satisfaction and the leadership style. The results showed that there is a positive significant correlation between job satisfaction and the job performance as well as there is a positive significant correlation between leadership style and job performance. The results showed that job satisfaction of the employees has more influence towards job performance than the leadership style. Findings of this study revealed that the democratic leadership style had the highest positive correlation towards the job performance than the other two leadership styles that were taken into this study. Supervision, working condition and the pay had the highest correlation value toward job performance out of the five dimensions of the Job satisfaction.

Zain Alshomaly

In today's increasing competitive environment, organizations recognize the internal human element as a fundamental source of improvement. On one hand, managers are concentrating on employees' wellbeing, wants, needs, personal goals and desires, to understand the job satisfaction. And on the other hand, managers take organizational decisions based on the employees' performance. The purpose of this study is to identify the factors influencing job satisfaction and the determinants of employee performance, and accordingly reviewing the relationship between them. This study is an interpretivist research that focuses on exploring the influence of job satisfaction on employee performance and vice, the influence of employee performance on job satisfaction. The study also examines the nature of the relationship between these two variables. The study reveals the dual direction of the relationship that composes a cycle cause and effect relationship, so satisfaction leads to performance and performance leads to satisfaction through number of mediating factors. Successful organizations are those who apply periodic satisfaction and performance measurement tests to track the level of these important variables and set the corrective actions.

IAEME Publication

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Md. Mostafizur Rahman

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Open Access

Peer-reviewed

Research Article

Professional quality of life in animal research personnel is linked to retention & job satisfaction: A mixed-methods cross-sectional survey on compassion fatigue in the USA

Roles Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Affiliations Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada, The 3Rs Collaborative, Denver, Colorado, United States of America

Roles Conceptualization, Writing – original draft, Writing – review & editing

Affiliation Consulting and Training in Animal Research, Berlin, Germany

Roles Validation, Writing – review & editing

Affiliation University of Georgia, Athens, Georgia, United States of America

Roles Conceptualization, Investigation, Project administration, Resources, Software, Supervision, Writing – review & editing

Affiliation Refinement and Enrichment Advancements Laboratory, Unit for Laboratory Animal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America

Roles Conceptualization, Funding acquisition, Supervision, Writing – original draft, Writing – review & editing

Affiliation Department of Environmental and Occupational Health Sciences, Office of Research, University of Washington, Seattle, WA, United States of America

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation The 3Rs Collaborative, Denver, Colorado, United States of America

• Lauren Young, 
• Fabienne Ferrara, 
• Lisa Kelly, 
• Tara Martin, 
• Sally Thompson-Iritani, 
• Megan R. LaFollette

• Published: April 16, 2024
• https://doi.org/10.1371/journal.pone.0298744
• Peer Review
• Reader Comments

Working with research animals can be both rewarding and challenging. The rewarding part of the work is associated with understanding the necessity for animal research to improve the health of humans and animals and the knowledge that one can provide care and compassion for the animals. Challenges with animal research include witnessing stress/pain in animals necessitated by scientific requirements, end of study euthanasia, and societal stigmatization about animal research. These challenges could be compounded with more general workplace stresses, in turn, impacting job retention and satisfaction. However, these factors have yet to be formally evaluated. Therefore, the purpose of this survey was to comprehensively evaluate professional quality of life’s correlation with key workplace metrics.

Six institutions were recruited to participate in a longitudinal intervention trial on compassion fatigue resiliency. This manuscript reports key baseline metrics from this survey. A cross-sectional mixed methods survey was developed to evaluate professional quality of life, job satisfaction, retention, and factors influencing compassion fatigue resiliency. Quantitative data were analyzed via general linear models and qualitative data were analyzed by theme.

Baseline data was collected from 198 participants. Personnel who reported higher compassion satisfaction also reported higher retention and job satisfaction. Conversely, personnel who reported higher burnout also reported lower job satisfaction. In response to open-ended questions, participants said their compassion fatigue was impacted by institutional culture (70% of participants), animal research (58%), general mental health (41%), and specific compassion fatigue support (24%).

Conclusions

In conclusion, these results show that professional quality of life is related to important operational metrics of job satisfaction and retention. Furthermore, compassion fatigue is impacted by factors beyond working with research animals, including institutional culture and general mental health support. Overall, this project provides rationale and insight for institutional support of compassion fatigue resiliency.

Citation: Young L, Ferrara F, Kelly L, Martin T, Thompson-Iritani S, LaFollette MR (2024) Professional quality of life in animal research personnel is linked to retention & job satisfaction: A mixed-methods cross-sectional survey on compassion fatigue in the USA. PLoS ONE 19(4): e0298744. https://doi.org/10.1371/journal.pone.0298744

Editor: Rosemary Frey, University of Auckland, NEW ZEALAND

Received: June 19, 2023; Accepted: January 29, 2024; Published: April 16, 2024

Copyright: © 2024 Young et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data supporting the findings of this study are available within the article and its supplementary information files. The dataset used in this study is available in the University of Michigan's Deep Blue Data repository, accessible at https://doi.org/10.7302/cdpa-qp43 .

Funding: MRL received funding for this project from the National Institute for Occupational Safety and Health (NIOSH) under Federal Training Grant T42OH008433. https://deohs.washington.edu/nwcohs/research/pilot-funding The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: All authors are employed by the institution noted in their affiliation except for Lauren Young who was a student during data collection and initial writing and then transitioned to a full-time role with the 3Rs Collaborative during manuscript revision. All authors are also members of the 3Rs Collaborative’s Compassion Fatigue Initiative. Elizabeth Nunamaker and Sally Thompson-Iritani also sat on the board of directors and leadership team of the 3Rs Collaborative during publication. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Introduction

Professionals that work with research animals can experience both distinct rewards and challenges due to the unique nature of their work. They contribute to critical scientific research that benefits the lives of people and animals such as through developing treatments for diseases and contributing to scientific breakthroughs. They often work in dynamic professional roles that help safeguard and enhance the lives of research animals themselves [ 1 , 2 ]. Both factors can provide great meaning for these professionals. Conversely, to accomplish these key scientific aims, it may be necessary to approve, view, or cause pain and/or distress to research animals as part of the experimental paradigm. This can lead to a sticky moral situation that we term the “Caring-Harming Paradox” and at the end of a study, although some animals may be rehomed or adopted, many are euthanized for reasons such as post-mortem scientific examinations or due to biohazard concerns [ 3 , 4 ]. Additionally, these professionals can experience negative social stigma for working with research animals which can be exacerbated by misrepresentation of animal research by some individuals or organizations [ 1 , 5 ]. Despite finding their work meaningful, these personnel may not feel as valued as other care workers [ 6 ].

Beyond the unique factors related to working with research animals, these professionals are also subject to general workplace factors that can influence burnout. As can occur in any field (although especially caring professions) staff may be asked to work long hours, feel unappreciated by other sectors of their institution, and face interpersonal conflicts with colleagues [ 6 , 7 ]. They may not fully understand their own or other key job responsibilities in the organization. Good work-life balances practices may not be promoted well in the face of organizational pressures. Furthermore, personal life and mental health challenges from outside of work can impact experiences at work [ 8 – 10 ].

Both the unique factors of working in animal research and typical workplace stressors can lead to decreased professional quality of life. Professional quality of life in caring professions can be segmented into compassion satisfaction (e.g., feeling good about their caring role) and compassion fatigue (e.g., feeling challenged by their caring role). Compassion fatigue is often described as being comprised of secondary traumatic stress (which is like post-traumatic stress disorder but caused by exposure to the stress of others) and burnout [ 11 , 12 ], considered by many as a manifestation of chronic psychological strain [ 13 ].

Research thus far has shown that compassion fatigue in animal research personnel is associated with several factors. One of the strongest findings is that personnel with less social support experience higher compassion fatigue [ 3 , 14 , 15 ] and evident by both quantitative and qualitative studies, seems to be a moderating factor for the development of psychological strain in the laboratory [ 13 ]. Animal-related findings include exposure to higher animal stress/pain [ 3 , 14 ], less enrichment frequency/diversity [ 3 ], physical euthanasia methods [ 3 , 13 ], close animal relationships [ 7 ], more euthanasia [ 16 ] less control over performing euthanasia [ 3 , 7 , 16 ] and internal conflicts between animal welfare and scientific needs [ 17 – 19 ]. General mental and physical factors are also associated with compassion fatigue such as poor mental or physical health as well as lower emotional stability, openness, and extraversion [ 7 ]. Finally, poor relationships with superiors and a lack of training and resources for coping with compassion fatigue have been identified as negative factors [ 7 ].

Although previous literature has begun to establish associations between professional quality of life and potential risk factors, a few gaps remain. Although a few studies have connected professional quality of life to general workplace factors such as staffing and workplace relationships [ 7 ], no studies have yet connected professional quality of life to key factors of interest to workplace management such as retention and job satisfaction. Job satisfaction can be described as the feelings or attitudes an individual has in relation to their job and workplace [ 10 ]. Based on the literature, job satisfaction seems to be the most important factor for working motivation, performances and job retention [ 10 , 20 , 21 ], which is important to maintain an adequately qualified workforce and reduce turnover [ 22 ]. Thus far, most research has primarily used close-ended questions and limited free response, and there has been no extensive qualitative research on the subject to our knowledge.

Considering the gaps in previous research on workplace stress in research personnel, our objective in this survey was to explore associations between reported professional quality of life (i.e., compassion fatigue and satisfaction) and important workplace metrics (e.g., retention and satisfaction) and explore factors that individuals report as impacting their compassion fatigue resiliency. We hypothesized that higher compassion fatigue and lower compassion satisfaction would be associated with lower workplace satisfaction and retention. We also hypothesized that participants would cite key factors related to mental health support and working with research animals as impacting their compassion fatigue. With this knowledge, we hope to provide additional rationale and guidance for interventions promoting compassion fatigue resiliency for animal research personnel.

Materials and methods

All procedures and waived signed consent protocols were approved by University of Michigan’s Human Research Protection Program Institutional Review Board (IRB), protocol # HUM00207730. Participants provided waived signed consent via a yes or no question on the online survey platform after reading an informed consent document. No IACUC approval was sought as there were no interactions between the researchers or animals during this study.

Participants and procedures

Institutions were recruited to participate in this study via direct email or verbal communication with previously known contacts, presentations by members of the 3Rs Collaborative, and a request via the 3Rs Collaborative newsletter. Institutional inclusion criteria included being located in the USA or Canada, either not currently having a compassion fatigue resiliency program or having a newly established program, and be willing to work closely with the 3Rs Collaborative for recruitment and implementation of a program. In this manuscript, we present baseline data from a 2-year longitudinal study investigating the effectiveness of implementing institutional compassion fatigue resiliency programs.

Ultimately six institutions met inclusion criteria and were able to participate in the study. The institutions included one academic institution, three research institutes, and two large pharmaceutical companies. Institutions could choose to allow participation of only animal care staff or all related research personnel (e.g., researchers, IACUC members, etc.), based on the intended recipients of their individual planned compassion fatigue resiliency program. Each institution contained a possible sample size between 7 and 429 individuals. Altogether they represented approximately 723 eligible participants.

At each institution, one to three local contacts were identified to coordinate participation. These contacts were typically directors, managers, or supervisors with authority to coordinate compassion fatigue resiliency activities. These contacts recruited participants between Feb 11 and March 22, 2022, via three email contacts and one physical flyer. To compensate them for their time, participants were entered into a random drawing for a $25 visa gift card. Inclusion criteria for participants were being over the age of 18 and currently working at one of the included institutions; there were no exclusion criteria.

Following reading an informed consent document with the assurance that responses would be kept confidential, including from supervisors, participants confirmed documentation of waived signed consent. They then completed an online questionnaire estimated to take an average of 10 minutes via Qualtrics. Participants were informed that they could skip any question that made them feel uncomfortable. Although 3 of the authors had access to email addresses that could identify individual participants during data collection, during the data analysis phase the responses were de-identified with a participant and institutional code to ensure they were kept anonymous and confidential. Potentially identifiable information was only accessible to core research team members.

The 3Rs Collaborative’s Compassion Fatigue Resiliency committee created a mixed-method cross-sectional survey based on a review of the literature and consultations with experts in survey methodology and laboratory animal science. When possible, the survey contained validated survey instruments (e.g., professional quality of life scale [ 1 ]), but when such items did not exist similar survey scales were modified for purpose (e.g., modified nurse retention index, [ 2 ]) or created new for purpose. When new scales were created, they were reviewed by our team, piloted, and revised as necessary.

Overall, participants were asked 78 to 85 questions. The additional questions were asked only to personnel that worked with research animals in a hands-on role to attempt to determine if retention was unique for these types of roles. Questions were subdivided into 5 subsections as described below. All survey text and scoring can be found in S1 Table .

Demographics & work factors

After gaining documentation of waived signed consent, participants were asked their age for inclusion and their email to allow linking of responses across yearly surveys. Additional work and demographic factors were then asked including working role, years of work in the field, sex, average hours of work in a week, and highest education. Participants were also asked if they currently worked hands-on with research animals to allow for segmentation. Finally, they were asked to report the degree of stress/pain that most animals in their care experience based off the official United States Depart of Agriculture pain and distress categories for laboratory animal research [ 3 ] as this has previously been shown to impact professional quality of life [ 4 ].

Professional quality of life knowledge and experiences.

Participants were asked direct questions about their own self-reported compassion fatigue knowledge and experiences. They were first asked in close-ended questions of their familiarity with the definition of compassion fatigue, effective strategies to combat compassion fatigue, their own implementation of strategies to combat compassion fatigue, and whether they had experienced compassion fatigue in the past. Then, participants were asked to rate their level of compassion fatigue on a descriptive one to five scale. Finally, participants were asked two open-ended questions about what makes compassion fatigue worse or better for them personally.

Participants were then asked to complete the 30-question professional quality of life scale (PROQOL) to determine compassion fatigue (comprised of burnout and secondary traumatic stress) and compassion satisfaction [ 1 ]. The PROQOL is a widely used instrument to determine the positive and negative aspects of caring for others.

Job satisfaction & retention.

Participants then completed scales to assess job satisfaction and retention. For satisfaction, participants were asked to complete the seven item Brief Index of Affective Job Satisfaction Scale which includes 3 distractor questions [ 5 ]. It asks participants to evaluate how much they agreed or disagreed with four statements about their current job. The scale ranges from 4 being very low job satisfaction and 20 being high job satisfaction. Then participants were asked to complete a modified nurse retention index [ 2 ] where “nursing” was replaced with “Research animals”. The original MNRI has six questions including four positively worded questions and two negatively worded items. The scored scale ranges from 6 being very low planned retention to 48 being very high retention. Additionally, participants who worked hands-on with research animals were then asked a modified nurse retention index substituting “hands-on with research animal” where appropriate.

Institutional program.

To evaluate implementation of future institutional programs, participants were then asked two final questions about the program. First, participants were asked what they thought would be the most beneficial aspect of an institutional compassion fatigue resiliency program. Then, participants were asked which program components they planned to participate in.

Data analysis

Quantitative analysis..

Quantitative data were analyzed with descriptive statistics and general linear models. Continuous data are presented as mean and standard deviation (SD). Counts are presented as n and percent (%). Any duplicate responses were identified via matching email addresses; the most complete or recent response was retained. Only participants that answered questions through rating their level of compassion fatigue were included. For use in general linear models, categorical data with less than 20 responses were collapsed into larger categories. Additionally, summary scales were calculated according to instructions for each individual scale.

General linear mixed models were run to test associations between professional quality of life and both retention and job satisfaction. The dependent variables were retention and job satisfaction. The independent variables included compassion satisfaction, burnout, secondary traumatic stress, work factors (animal stress/pain, hands-on work, role, years of work, and hours per week), and demographics (highest education, age, sex). Institution was included as a random blocking factor. Significance level was set at p < 0.05. Results are presented as mean +- standard deviation. Effect sizes are reported using Cohen’s f 2 , where when f 2 > = 0.02, 0.15, and 0.35 indicating a small, medium, and large effect size, respectively [ 23 ].

This representative analysis was used: Retention = Compassion Satisfaction + Burnout + Secondary Traumatic Stress + Perceived Stress Scale + Animal Stress/Pain + Hands-On Work with Animals + Role + Years + Hours per Week + Highest Education + Sex + Institution

Qualitative analysis.

Open-ended questions were assessed using inductive, bottom-up, content analysis to derive themes from all respondent answers. This process resulted in the formation of a coding manual used to identify common themes. The complete manual is found in S2 Table . The same manual was created and used to code all open-ended qualitative questions. Microsoft Excel was used for manual creation and thematic analysis.

Coding manual creation involved an iterative and collaborative process with multiple steps and researchers. The goal was to extract all general themes from the open-ended survey question that respondents identified to create one coding manual. This began with one researcher (LEY) reading through all written responses and noting the themes within each question. These themes were compiled into a master list, and in collaboration with a second researcher (MRL), themes were discussed to look for similarities, differences, relationships between themes and overlap with the Culture of Care terminology. A preliminary manual was created by grouping the identified themes. The data was subsequently re-read and coded based on the preliminary manual. This process was repeated to refine the coding manual and ensure all themes in the data were represented in the final coding manual.

The coding process itself involved breaking down responses to identify themes to subsequently code. Each response was broken down into grammatical clauses and based on the theme in the coding manual it described, each clause was given a code. There was no limit to the number of codes a single response was given, and every clause was coded. For example, one respondent stated their compassion fatigue is made worse by “having to euthanize many animals on a single day”. This was coded as the theme Research Animals, and the subtheme ‘euthanasia’. When possible, responses were coded with a subtheme, to increase specificity. When a response did not clearly fall into a subtheme, they were coded only with the main theme. Non-comprehensive responses were coded as ambiguous.

Coding was performed by LEY and inter-rater reliability was assessed by having an additional individual, who was not involved in the manual creation process, code a random 20% of the data.

We calculated the prevalence of each theme by taking the number of participants whose response was coded with a particular theme/subtheme, divided by the total participants that responded to the survey. The formula used ensured each theme was only counted once per respondent, even if mentioned more than once across all qualitative questions.

Quantitative

Of the approximately 723 potentially eligible participants, a total of 302 survey responses were started, but only 198 individuals were included in the survey as they gave responses at least through the first block of questions through rating their level of compassion fatigue resiliency. From the total response pool, included participants results in a response rate of 27%. The number of participants per institution ranged from 9 to 54.

Complete demographics are reported in Table 1 . Participants were primarily animal caretakers (30%) and researchers (30%) although many other roles were represented. Most worked hands-on with animals (84%) and most worked with animals experiencing level 2 stress/pain (minor stress or pain of short duration, 51%). The majority of participants worked at research institutes (55%) or pharmaceutical organizations (39%). Most participants either had the highest degree of a bachelors (43%) or their veterinary or graduate degree (34%). Participants were age of 38 ± 12, primarily female (72%), worked 40 hours a week (57%), and just over half had worked in the field for 10 years or more (51%).

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https://doi.org/10.1371/journal.pone.0298744.t001

Research animal personnel reported about their compassion fatigue knowledge and experiences ( Fig 1 ). Most participants (87%) agreed that they were familiar with the definition and components of compassion fatigue. Most also agreed that they had experienced compassion fatigue in the past (70%). A little more than half agreed that they understood effective strategies for combatting compassion fatigue (58%). However, less than half (44%) agreed that they had implemented strategies to combat compassion fatigue.

Animal research personnel (N = 198) from 6 institutions across the USA answered questions about their understanding on compassion fatigue, whether they had experienced it, and whether they both understood/implemented strategies to combat compassion fatigue.

https://doi.org/10.1371/journal.pone.0298744.g001

Participants reported their compassion fatigue via a descriptive scale and the professional quality of life scale which are presented in categorized form in Table 2 . Based on a descriptive scale, most participants indicated they felt occasional burnout or stress but not compassion fatigue (64%), although a considerable portion felt they had symptoms of compassion fatigue (29%). Based on the PROQOL cutoff scores, no participants had low compassion satisfaction, high burnout, or high secondary traumatic stress. Based on continuous data ( Table 3 ), on average, participants experienced moderate compassion satisfaction, burnout, and secondary traumatic stress. On average, participants agreed with statements that they were satisfied with their job ( Table 3 ). Finally, participants reported higher planned retention to continue with their research animal career than to continue working hands-on with research animals ( Table 3 ).

https://doi.org/10.1371/journal.pone.0298744.t002

https://doi.org/10.1371/journal.pone.0298744.t003

Participants (n = 166) anticipated participating in the following components of a compassion fatigue program in decreasing order: webinar on overview of CFR (60%), webinar on culture of care (54%), webinar on mindfulness (52%), webinar on communication & trust in the workshop (51%), enrichment activities (50%), accessing independent activities (45%), accessing mindfulness or gratitude materials (42%), accessing reading materials on compassion fatigue (40%), in person activities (39%), poster viewing (36%), participating in group activities (36%), webinar on meaning making (30%), and memorial activities (26%).

Associations with job satisfaction, & retention.

In this survey, job satisfaction and retention were found to be associated with several factors ( Table 4 ). Research animal personnel who reported higher job satisfaction indicated less burnout (p < 0.0001, f 2 = 0.13) with a small effect size and higher compassion satisfaction (p < 0.0001, f 2 = 0.23) with medium effect size. Research personnel who reported higher general retention reported higher compassion satisfaction (p < 0.0001, f 2 = 0.16) with medium effect size. Research personnel who worked in hands-on roles with research animals who reported higher retention indicated compassion satisfaction (p < 0.0001, f 2 = 0.11) with small effect size and reported more average hours working per week (p < 0.0184, f 2 = 0.04) with a small effect size.

https://doi.org/10.1371/journal.pone.0298744.t004

Qualitative results.

A total of 85% (n = 167) participants responded to at least one open-ended, qualitative question. Participants responded to three questions: what makes your compassion fatigue worse (n = 160, 81%), what makes your compassion fatigue better (n = 156, 79%) and what would be most beneficial about a compassion resiliency program (n = 106, 54%). Theme prevalence is summarized across all three questions. Each subtheme’s name and response frequency are noted in paratheses. A detailed summary of qualitative results can be found in Fig 2 and S2 Table .

The percentage of research animal personnel (n = 167) whose responses included each of the themes (solid bars) and subthemes (hashed lines) created in qualitative coding of all responses. Each color represents a different thematic category.

https://doi.org/10.1371/journal.pone.0298744.g002

Theme 1: The culture of my institution contributes to my compassion fatigue.

Nearly three-quarters of participants (n = 118, 71%) indicated that something related to institutional culture or organization, unrelated to animal research, impacted their compassion fatigue. Specifically, participants mentioned work-life balance, staff interactions, feeling valued, general organization, training, or pay. One response that captures a number of these themes’ states, “our constant lack of adequate and reliable staff and the constantly growing list of things we as a department and I as a supervisor are behind on. Everyone is stressed, but when people snap at others, it doesn’t help the situation and makes me want to not assist other areas.”

Most often participants mentioned that maintaining a work-life balance, or lack thereof, is instrumental in their experience with compassion fatigue (subtheme = work-life balance , 44%). As one participant states, “lowering the expectations for scientists and allow[ing] them to create a healthy life-work balance” would be beneficial for compassion resiliency. Another emphasized the importance of “Vacations, mental health days, and coworkers who are willing to do some of the more stressful tasks when you are feeling burnt out.” Generally, participants indicated that it was important to spend time away from the workplace to cope with stress and burnout.

About a third of participants indicated that interactions with other staff members, whether positive or negative, can impact compassion fatigue (subtheme = interactions with staff , 30%). One participant stated that a “lack of understanding from other colleagues or managers of the workload/tasks I have been assigned” makes compassion fatigue worse. Additionally, a large proportion of these responses specifically mentioned something related to feeling valued (subtheme = feeling undervalued by staff , 17%). Feeling undervalued or underappreciated at work makes compassion fatigue worse, while recognition, especially by organizational leads, makes compassion fatigue better. As one participant states, their compassion fatigue is relieved by “receiving recognition, understanding, and help from higher-ups in the department (manager and veterinarians).”

About a fifth of respondents mention general institutional factors, as opposed to the specific factors represented by other subthemes (subthemes = general , 20%). For example, one participant states that “those who are not involved from an animal use perspective making decisions for animal staff” impacts their compassion fatigue. Others mention, “switching from my ex-vivo role and helping with in-vivo” and “the sense of knowing that tasks are completed”.

Although not a particularly common response, we note that a small proportion of respondents mentioned pay (subtheme = employee pay , 2%) or training (subtheme = employee training , 4%) as impactful to their compassion fatigue. Participants stated more pay and more training are needed to reduce compassion fatigue. For example, one participant stated, “I would like to see changes in the structure of operations. The issues that we run into usually stem from lack of training…”.

Theme 2: Working with research animals can be challenging or rewarding.

Over half of participants (n = 97, 58%) mentioned animal research-related factors that are inherent to their work as contributing to their compassion fatigue. Specifically, participants mentioned performing euthanasia, procedures, changes in animal welfare, research translatability, openness about research or the human-animal bond.

A quarter of participants indicated that “having to euthanize animals” is a key contributor to their compassion fatigue (subtheme = euthanasia of animals , 25%). One participant stated, “I sometimes experience this now when working with the mice at my new job. For me, it’s hard to bring them in alive, put them under and then decapitate them. It feels like it goes against everything I have done/ stood for the last few years; saving lives instead of taking them.” Other participants indicated that performing procedures on animals can be challenging (subtheme = performing animal procedures , 7%). Examples include, “long, repeated procedures” and “large animals being dissected in the necroscopy room”. For some individuals, performing these types of procedures can contribute to compassion fatigue just as much as performing euthanasia.

A quarter of participants stated that witnessing animals with reduced welfare (e.g. in pain or suffering) impacts compassion fatigue (subtheme = animal welfare , 25%). As one participant stated, their compassion fatigue is worse “when a level of long-term pain or distress is necessary to meet the scientific requirements of a study”. In particular, participants indicated it was difficult to handle events described in their words as “repeated”, “high-intensity” or “unexpected”. Conversely, participants indicated that reducing the frequency of these negative events would make compassion fatigue better.

About a fifth of participants mentioned that knowing and thinking about the translatability, “the big picture”, and the “greater good” of animal research impacted compassion fatigue (subtheme = research translatability , 17%). These statements generally indicated that these thoughts made compassion fatigue better. As one participant stated, “[I] hope that my work with animals may one day produce a beneficial therapeutic that helps people manage disease and improve their lives.” Some participants indicate that learning about the specific research aims of their own lab is helpful, stating, “I try to remember the important work being accomplished by our researchers. I talk to the researchers about their studies so I can put the animals and the procedures into context.”

Another fifth of respondents mention general factors about working with research animals that impact compassion fatigue (subtheme = general , 16%). Some examples include “other people denying that animals feel pain” and “anything with the animals honestly”.

A small number of participants also mention that openness, or lack thereof, about their work with animals can impact compassion fatigue (subtheme = openness about animal research , 4%). As one participant stated, “feeling so responsible for the animals in my care and working so hard to make sure they have the best lives possible but still receiving public backlash/lack of understanding”.

Of note, a few participants state specific factors like “naming the animals”, “learning their behaviours” or “playing with them” contribute to compassion resiliency (subtheme = human-animal bond , 3%). As one participant stated, “short studies are easier to feel compassion fatigue since the animals are not around as long and there isn’t much of a bond between animals and handlers.”

Theme 3: My general mental health impacts my work life.

General mental health factors were commonly mentioned by participants when asked about compassion fatigue. A total of 38% of respondents (n = 64) made statements related to self-care, work stress, personal stress, talking about their mental health, or having a community.

Some participants mentioned using self-care practices (subtheme = self care , 17%) to help with compassion fatigue. Participants mentioned practices such as, “spending time with friends”, “exercising”, “thinking of happy thoughts”, “funny movies, trying to take a walk outside, watching funny videos of kids and pets online” and “adequate sleep.”

A portion of participants stated that their general mental health, or general stress levels were impacted (subtheme = general , 15%). Respondents make statements such as, “Heightened stress levels for prolonged periods” and “volume of stressful situations.” One participant specifically states, “if your mental health is not being taken care of outside of work then you will be even more affected at work and by the work that you do”, which emphasizes the importance of good mental health.

Respondents mentioned that talking to someone about their feelings, either a close colleague or a professional, can help their mental health, improving compassion resiliency (subtheme = talking about mental health , 8%). As one participant stated, it would be beneficial to “give employees an outlet to understand their feelings, talk about them and have them help makes changes as needed.”

Additional respondents indicated that when their personal lives were stressful then that made their compassion fatigue worse (subtheme = personal stress , 7%). For example, participants mentioned factors such as “pets or children [they] are responsible for” or “upsetting personal experiences”. One participant clearly described how work and personal stress can overlap stating, “deadlines, stresses when large experiments are coming up with heavy expectations. This can be made worse if my personal life is also heavy with stress or pain.”

Some participants mentioned that group events and creating a sense of community are important (subtheme = having a community , 6%). For example, one participant stated that it would be beneficial to have “a supportive community with regular gatherings”.

Theme 4: I need compassion-fatigue specific help.

Compassion fatigue specific factors and resources were mentioned by approximately a quarter of participants (n = 40, 24%). They indicated the importance of promoting awareness of compassion fatigue, resources to combat it, and talking to others with compassion fatigue.

Participants discussed that there can be lack of knowledge or even stigma around compassion fatigue–and that normalizing compassion fatigue would be beneficial (subtheme = normalize CF , 12%). As one participant states, “just acknowledging [compassion fatigue] is a huge first step.” Participants expressed a desire for compassion fatigue awareness to be widespread from upper management, to staff from other departments, and even the public. For example, one respondent stated it would be beneficial to “educating research staff on compassion fatigue and what care staff go through in a day.”

Other participants highlighted the need for more resources to combat or prevent compassion fatigue (subtheme = resources to combat CF , 11%). As a few participants state, “recognizing the signs would be beneficial” and “teaching employees coping mechanisms for combatting compassion fatigue before it gets serious”. One participant emphasizes that each individual may experience compassion fatigue in a unique manner, stating “there are many different factors that contribute to compassion fatigue, and not everyone will experience it in the same way…with a matter as serious as compassion fatigue, it is crucial to make sure that every individual does know how to have their needs with regards to receiving support met.”

A few participants mentioned that hearing real-world stories from those who have experienced compassion fatigue before is helpful (subtheme = talking to people with CF , 4%). As one participant states, “discussion/talks by real people sharing their experiences–it makes me feel less alone when I see others who feel the same way I do.” Some of these responses linked sharing experiences with normalizing compassion fatigue and therefore were coded in both categories. For example, as one participant states, “more discussion and sharing of personal experiences for the purposes of acknowledging this is a common and shared experience.”

A couple of participants mentioned general compassion fatigue-specific factors that did not align with any of our other subthemes (subtheme = general , 2%). One participant says, “having an organization/workplace that is very aware of compassion fatigue” makes their compassion fatigue better.

Of note, 4% of participants state they do not experience compassion fatigue, and 2% state that nothing impacts their compassion fatigue levels.

Themes by role.

Post hoc , we further investigated the percentage of respondents in each role who mentioned each theme ( Fig 3 ). We investigated this for animal caretakers and researchers; the two participant groups with a sufficient sample size to make accurate conclusions based on subsequent results. The majority of animal caretakers state that their institutional culture (n = 37, 74%) and working with research animals (n = 27, 54%) contributes to their compassion fatigue. In comparison, researchers more often mention research animals (n = 31, 66%), and discuss institutional culture slightly less (n = 28, 59%). Both roles equally mention the impact their general mental health has on their compassion fatigue. Finally, researchers mention compassion fatigue-specific factors (n = 14, 29%) more often than animal caretakers (n = 5, 10%).

The percentage of animal caretakers (n = 50) and researchers (n = 47) whose responses included each of the themes created in qualitative coding in at least one of their responses. Each color represents a different personnel role.

https://doi.org/10.1371/journal.pone.0298744.g003

To our knowledge, this is the first cross-sectional survey to find that professional quality of life in research animal personnel, including compassion satisfaction and burnout, is associated with retention and job satisfaction in animal research. Additionally, it is one of the first large qualitative surveys of compassion fatigue which found personnel reported the importance of institutional culture, factors unique to animal research, general mental health factors, and a desire for targeted resources. We successfully surveyed 198 individuals across 6 independent institutions and 9 unique sites.

Professional quality of life is linked to job satisfaction and retention

In this survey, compassion satisfaction was positively associated with both job satisfaction and retention with a medium effect size. That is, personnel who reported higher levels of compassion satisfaction also reported being more likely to be satisfied with, and stay in, their current jobs. Furthermore, this association was found regardless of whether individuals currently worked hands-on with research animals and when personnel who were currently working in a hands-on role were asked about staying in a hands-on role.

The link between compassion satisfaction, job satisfaction, and retention may be unsurprising, as compassion satisfaction could be considered a particular subtype of job satisfaction. Additionally, our findings mirror previous work, that faculty in higher education that reported higher compassion fatigue also reported less intended retention [ 24 ]. And in turn, past research has found that less burnout and higher job satisfaction is associated with higher retention of nurses [ 8 , 21 , 22 , 25 ]. This survey provides important evidence of this linkage in the research animal personnel field across roles using previously validated scales.

In this survey, burnout (as assessed as a key component of compassion fatigue through the professional quality of life scale) was negatively associated with job satisfaction. That is, personnel who reported higher levels of burnout also reported lower levels of job satisfaction. In the nursing field, a high quality of communication and information exchange between management and employees was negatively correlated with burnout [ 8 ] supporting the idea that as job satisfaction increases, burnout decreases.

Taken together, these findings provide a good rationale for institutions to promote professional quality of life. Not only are decreasing burnout and increasing compassion satisfaction good for personnel individually, both may also help prevent expensive and time-consuming employee turnover.

It is more than just research animals: Culture and mental health matter

In this survey, we asked participants open-ended questions about what makes their compassion fatigue better and worse, as well as what they believed would be beneficial in a compassion fatigue resiliency program. Through analyzing the responses of 167 personnel across roles (including both caretakers and researchers), we were able to gain new insights into what factors may matter most in promoting professional quality of life in this field.

Significantly, the most common response given by participants was that factors related to institutional culture were important in their professional quality of life. In this way, the people working with research animals are just like any other employee in any other workplace. They want to feel supported in their home life, have positive interactions with other staff that lead them to feeling valued, and receive adequate training and pay. In fact, previous research has found increased compassion fatigue is linked to understaffing, feeling valued, long working hours, poor relationships/communication with superiors, and a generally poor work environment [ 3 , 6 , 7 , 16 ]. Similarly, in a systematic review of emergency healthcare workers many typical work- and job-related factors were found to lead to burnout [ 8 ]. These factors include interpersonal conflict and lack of supervisory support [ 26 , 27 ], quality of staff communication [ 28 ], adequate staffing [ 29 ], and workload [ 27 ].

Similarly, in our qualitative responses, participants often stated that their general mental health impacts their compassion fatigue. Again, just as in any other workplace, personnel discussed the importance of self-care and community, the ability to talk with others about their mental health, and stressors in their personal lives. Similarly, three previous studies have found worse compassion fatigue in animal research personnel who reported less social support or increased loneliness [ 3 , 14 , 15 ], while social support [ 13 ] and promoting mental well-being is suggested as an important component to building compassion-fatigue resiliency in an animal facility [ 30 ]. Additionally, previous work has found that poor personal mental health contributes to worse compassion fatigue, while talking to others is a good coping strategy [ 7 ]. Finally, a recent investigation found that high levels of mental well-being are positively associated with compassion satisfaction [ 14 ].

Together, these two findings highlight the ways that working in animal research has similarities to other jobs. These findings could be considered quite positive as they indicate that general strategies and workplace wellness programs designed for general institutional staff could also benefit animal research personnel’s professional quality of life, and, in turn, retention. Furthermore, these findings point to potentially solvable problems, despite some of the inherent challenges of working with research animals.

Working with research animals is uniquely rewarding and challenging

Despite our findings of the similar concerns of animal research personnel to other workplaces, there are still unique aspects of animal research that impact compassion fatigue. On the one hand, our participants state that it can be rewarding to contribute scientific advances, bond with research animals and promote research animal welfare. These results are supported by previous findings that higher enrichment levels are associated with less burnout [ 3 ] and involvement and insight into research are relevant to psychological strain [ 13 ]. It is therefore possible that ensuring and communicating translational studies, promoting good relationships with animals, and generally promoting animal welfare could increase compassion satisfaction. In turn, retention may also be increased.

Conversely, our participants discussed the challenges of performing euthanasia, stressful procedures, witnessing an animal with reduced welfare, and societal stigma contributing to worsened compassion fatigue. Again, these findings are supported by previous research that worse compassion fatigue is associated with personnel reporting increased animal stress and pain, less control of euthanasia, physical methods, and greater euthanasia distress [ 3 , 6 , 15 ]. These factors align with research suggesting that unique aspects of the research animal environment can contribute to compassion fatigue [ 31 , 32 ]. Interestingly, our quantitative analysis didn’t reveal a direct association between either animal stress/pain or hands-on animal work with retention or job satisfaction.

Post hoc , we were able to investigate similarities and differences between two roles distinct to the animal research setting: animal caretakers and researchers. Although with a small sample size and unable to investigate this for all the research animal personnel surveyed, this suggests different roles within the animal research setting may be impacted uniquely. Further research is needed to adequately investigate this topic.

Compassion-fatigue specific resources are beneficial

Finally, our survey results suggest that the provision of specific resources may help alleviate compassion fatigue. Participants discussed the importance of compassion fatigue-specific support which included normalizing and reducing stigma with compassion fatigue, talking to others with compassion fatigue and having targeted resources and strategies to combat it. Indeed, previous research has found that providing training and resources for coping with compassion fatigue is linked to improved compassion fatigue [ 6 , 7 ].

Investigations of healthcare professionals during the COVID-19 pandemic found that social stigma was associated with increased compassion fatigue and decreased compassion satisfaction [ 33 ]. This is especially pertinent to research animal professionals experiencing compassion fatigue, as there is the negative stigma generally associated with animal care workers combined with the ongoing stigma surrounding mental health [ 34 , 35 ]. Lastly, numerous studies support the notion that talking to others is helpful through talk therapy [ 36 ] and specifically talking to others with a shared experience through group therapy [ 37 , 38 ].

Specific resources for compassion fatigue may include educating staff on what compassion fatigue is, recognizing its signs, and outlining the steps for prevention or mitigation. Additionally, programs may attempt to normalize and decrease the stigma surrounding compassion fatigue. To our knowledge, two institutions have published about their compassion fatigue programs: University of Washington [ 39 ] and Ohio Status University [ 16 ]. Additional institutions, such as the University of Michigan, also provide online resources detailing their programs. These programs could be used as models of institutional programs. Providing specific resources to promote professional quality of life has the potential to increase job satisfaction and retention in research animal personnel.

Limitations & generalizability

This survey includes key limitations that are important to acknowledge. As this was a cross-sectional survey, it is not possible to determine the causation, if any, of determined associations. That is, it’s possible that rather than poor professional quality of life causing decreased job retention that instead individuals who do not plan to stay in their job experience poor professional quality of life due to that choice. A randomized empirical intervention trial would be necessary to determine any direction of causation. However, this survey still provides further rationale for the importance of institutional compassion fatigue resiliency programs for animal research personnel and provides guidance for future research.

Additionally, this survey was limited as we might have failed to capture information from personnel currently experiencing compassion fatigue and by design would have missed information from those who have already left the field. Individuals with high levels of compassion fatigue may have been less likely to respond to this survey due to workplace withdrawal and decreased motivation. Individuals that already left the field would not have been reached due to distribution being through current workplace emails and networks. If anything, these limitations may cause our findings to be stronger than what was found here. It is also important to note that although we surveyed research personnel at 6 institutions, this was not a representative sample of all personnel working in animal research across the United States. Therefore, our results may not be generalizable beyond this particular sample. Despite these limitations, our findings still provide insight into the lives of those currently working in the research field in the United States.

In conclusion, these results show that research animal personnel professional quality of life is linked to two critical workplace factors: job satisfaction and retention. Furthermore, research animal personnel in the United States are impacted not only by the work they do with research animals and whether they have been provided compassion fatigue specific resources, but also by their general institutional culture and mental health support. These results suggest that institutions that focus on improving compassion satisfaction and decreasing compassion fatigue could improve employee satisfaction and retention. To accomplish these aims, institutions may benefit from improving workplace culture, improving specific animal research factors, providing general mental health support, and providing compassion fatigue specific resources. Ultimately these results provide insight and rationale for improving the professional lives of a critical sector of our society that conducts animal research.

Supporting information

S1 table. survey text and coding scheme..

The question text and answers shown to participants as well as the corresponding variable name, scale, and coded value of each answer.

https://doi.org/10.1371/journal.pone.0298744.s001

S2 Table. Qualitative coding manual, results, and descriptions.

The name of each thematic code, a generalized participant response created by the researchers, subtheme response % and n, main theme response % and n, description of each category, key phrases, and representative quotes.

https://doi.org/10.1371/journal.pone.0298744.s002

Acknowledgments

We gratefully acknowledge the institutions and research animal personnel who took the time to participate in and promote this survey. We also thank the 3Rs Collaborative’s staff, volunteers, and members for making this research possible. We appreciate all research animal personnel who have worked to promote institutional compassion fatigue resiliency. Finally, we thank all research animals currently being used in science.

The authors would first like to thank the institutions who chose to participate in this pilot study, especially for the individual champions who helped coordinate distribution of the survey. We also wish to thank all the research personnel who took the time to participate in this survey and provide useful insight, also acknowledging those who champion compassion fatigue resiliency efforts. We wish to thank that research animals used in research worldwide. Lastly, we would like to thank the 3Rs Collaborative staff, volunteers, and sponsors for making this research possible, and the participation from the entire compassion fatigue resiliency initiative on this project.

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