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. Author manuscript; available in PMC: 2014 Apr 9.
Published in final edited form as: Adm Policy Ment Health. 2013 Mar;40(2):69–75. doi: 10.1007/s10488-011-0375-7

Job satisfaction and burnout among VA and community mental health workers

Michelle P Salyers 1, Angela L Rollins 2, Yu-Fan Kelly 3, Paul Lysaker 4, Jane R Williams 5
PMCID: PMC3980458  NIHMSID: NIHMS569226  PMID: 21972060

Abstract

Building on two independent studies, we compared burnout and job satisfaction of 66 VA staff and 86 community mental health center staff in the same city. VA staff reported significantly greater job satisfaction and accomplishment, less emotional exhaustion and lower likelihood of leaving their job. Sources of work satisfaction were similar (primarily working with clients, helping/witnessing change). VA staff reported fewer challenges with job-related aspects (e.g., flexibility, pay) but more challenges with administration. Community mental health administrators and policymakers may need to address job-related concerns (e.g., pay) whereas VA administrators may focus on reducing, and helping workers navigate, administrative policies.

Keywords: Staff, job satisfaction, burnout, community mental health

Introduction

Burnout, characterized by high levels of emotional exhaustion, depersonalization, and a diminished sense of personal achievement in the work place (Maslach, 1993) is very common among mental health providers and administrators. Depending on the sample and methods used, 21–67% of mental health workers are reported to experience high levels of burnout at any given time (Oddie & Ousley, 2007; Rohland, 2000; Siebert, 2005; Webster & Hackett, 1999). Burnout is associated with a number of problems not only for individual mental health workers, but also for their employer organizations, consumers, and the nation’s mental health system as a whole.

At the individual level, burnout is associated with poor physical and mental health (Lee & Ashforth, 1996; Rohland, 2000). At the organization and system levels, problems include lower productivity, higher absenteeism and costs, and a failure to retain trained and qualified professionals (Burke & Richardsen, 1993; Cropanzano et al., 2003). Although the existing empirical data is limited, burnout is believed to negatively affect the quality of mental health services. Not surprisingly, given cynical and negative attitudes that comprise burnout’s depersonalization component, burnout has been associated with negative feelings about mental health consumers (Holmqvist & Jeanneau, 2006). Negative staff attitudes, in turn, have been linked with poorer outcomes among consumers with severe mental illness (Gowdy et al., 2003). In addition, burnout and staff turnover are believed to disrupt the continuity of mental health care (Boyer & Bond, 1999) and to undermine the quality of services provided (Carney et al., 1993; Hoge et al., 2007; Maslach & Pines, 1979).

One theory of burnout that has received attention and research has been the conservation of resources model (Stalker & Harvey, 2002), which postulates that stress occurs when: (a) demands exceed or threaten resources, (b) resources are lost, and/or (c) individuals do not receive expected rewards for the investment of personal resources in their job (Halbesleben & Buckley, 2004; Hobfoll, 1989; Stalker & Harvey, 2002). While initial threats and demands are experienced as stress, ongoing threat or the loss of resources (especially after a worker invests considerable resources in a job) leads to burnout. Given current economic conditions, this model suggests that burnout may actually be increasing as resources for mental health workers become more scarce -- a supposition also recently noted by others (Wells, 2011).

In the VA system in particular, workers may be feeling additional strain. The VA’s Mental Health Strategic Plan and Uniform Mental Health Services has included intense focus on mental health outcomes and improving mental health services for veterans. In addition, a recent study indicates that returning veterans from Iraq and Afghanistan entering VA services have high rates of mental health diagnoses (37%), indicating an increased demand for mental health services both now and in the years to come (Seal et al., 2009). Given the high rates of mental health problems in returning Veterans, combined with additional concerns and complexities related to increased suicide risk (Posey, 2009), post-traumatic stress disorder (PTSD; (Hoge, 2004; Hoge, 2007), and traumatic brain injury (Schneiderman, 2008), it may be that VA staff would be at greater risk for burnout and job dissatisfaction. For example, secondary trauma and compassion fatigue have been identified as staff-related concerns for those helping consumers with high levels of trauma (Figley, 2002). Conversely, VA mental health staff may have institutional resources that could offset the potentially greater stressors. For example, VA staff may be better paid and have more job security because of employment in a large federal agency. VA staff work in an integrated care setting, which should allow their consumers to have greater access to other health services. In addition, the VA has made efforts to become a learning organization, focused on quality improvement and integrating current research and knowledge as a training institution (Kizer et al., 2000), which could bring more resources for clinicians to work more effectively.

Few studies have examined levels of staff burnout in the VA system and how rates may compare with other non-VA samples. One VA study examined mental health workers -- therapeutic recreation staff primarily working with long-term psychiatric inpatient veterans-- and found that compared to normative samples, VA staff reported low to moderate levels of burnout (Wade-Campbell & Anderson, 1987). In a large study of VA nurses (not focused on mental health work), VA nurses reported a positive work environment and job satisfaction at levels similar to or better than nurses in other settings in the US, Canada, and Europe (Sales, 2005); the authors speculated that serving veterans as clientele may be viewed as an even greater calling than helping other patients. Burnout, however, was not assessed in this study. In a longitudinal study of VA leaders, burnout, (particularly emotional exhaustion and reduced personal accomplishment) significantly increased over time in the 1990’s (Mirvis et al., 1999). At the same time, leaders reported that their perceived resource adequacy significantly declined. However, no comparisons were made with non-VA staff.

Given the lack of research in VA mental health staff burnout, the purpose of this study was to explore potential differences in burnout, job satisfaction, and attitudes about the consumers they serve. We also explored areas of fulfillment and challenge that may differ in VA and community mental health work. We hope this will help us to better understand the working context for mental health providers and potentially point to areas of intervention to help ensure a content, productive workforce.

Methods

Participants

Participants were employed at either the Veteran’s Administration (VA) Medical Center or a Community Mental Health Center (CMHC) in the same large Midwestern city. The VA sample was derived from a survey of mental health staff in February 2009, conducted as part of a locally-initiated quality improvement project related to recovery attitudes. The research team sent staff emails inviting participation and containing a link to the Survey Monkey website (www.surveymonkey.com). Participating staff could enter a drawing for a $25 gift card. Of the 133 people who were emailed a link to the survey, 66 (49.6%) responded.

The CMHC sample was recruited from an agency that has been participating in annual staff surveys as part of an NIMH-funded quality improvement effort. Emails inviting all staff in the agency to participate and containing a link to the survey monkey website were distributed to staff in January. Participating staff could enter a drawing for a $25 gift card. We extracted data from the 2009 survey and only included participants who were serving adults in order to be most similar to the VA staff in terms of consumer age and time of data collection. Of the 340 staff who were emailed the survey, 150 (44%) responded; we included the 86 who served primarily adults. The study and its procedures were approved by the authors’ Institutional Review Board.

Measures

The survey included limited demographic information, burnout, job satisfaction, intentions to turnover, and expectations about consumers. We also asked open-ended questions about joys and challenges of their work.

Burnout was assessed with the Maslach Burnout Inventory (Maslach et al., 1996) a widely-used measure of three components of burnout: emotional exhaustion, depersonalization, and personal accomplishment. The subscales have shown good internal consistency, stability over time, and convergent validity with related constructs (Maslach, et al., 1996). In this sample, Cronbach’s alpha was .93 for emotional exhaustion, .79 for depersonalization, and .85 for personal accomplishment.

Job Satisfaction was assessed with 5 items from the Job Diagnostic Survey (Hackman et al., 1974). The scale has good internal consistency (Hackman & Oldham, 1975) and evidence of convergent and divergent validity (Fried, 1991). In this sample, Cronbach’s alpha was .83.

Intentions to turnover were assessed by two individual items: “How often have you seriously considered leaving your job in the past six months?” (rated from 1=never to 6=several times a week) and “How likely are you to leave your job in the next six months?” (rated from 1=not likely at all to 4=very likely).

Staff expectations of consumers were measured with the Consumer Optimism scale, adapted from an earlier 7-item version (Grusky et al., 1989). Staff were asked to think about consumers they currently work with and to answer questions about how many consumers they expect to have specific outcomes (e.g., in housing, employment) on a 5-point scale ranging from 1=Almost All to 5=None. This 16-item scale has good internal consistency and correlates with related constructs (Salyers et al., 2007; Tsai & Salyers, 2010). The alpha coefficient in the current sample was .89.

Open-ended questions included “what is the best thing about your work?” and “what is the most challenging thing about your work?”

Data Analysis

The primary purpose of this study was to examine job related outcomes: burnout, job satisfaction, intentions to turnover, expectations of consumers, and sources of work satisfaction “joys” and challenges. We explored differences in VA and CMHC settings by directly comparing scores from both sites. First we examined differences in background variables, using chi-squares for categorical variables and t-tests for continuous variables to identify potential confounds. Second, we directly compared VA to CMHC staff on job-related variables using t-tests. Analyses of covariance were then conducted to compare sites, controlling for confounds. Using the Hochberg (Hochberg & Benjamini, 1990) adjustment for multiple comparisons, the smallest p value was compared to .007 (.05/7) and the largest compared to .029. Data from the open-ended questions were coded and aggregated into themes. Two raters read responses and created categories together. They then independently coded all responses and discussed any discrepancies; consensus codes are reported.

Results

Regarding demographics, mental health staff at the VA and CMHC were similar in terms of gender (71% female versus 68%; X2 =.09, n.s.) and length of time in the mental health field (13.3± 9.1 years versus 11.6± 8.6, t = 1.17, n.s.). However, the VA staff had significantly higher levels of education (x2= 45.10, p<.001). The distribution for education for VA staff was: 9% less than bachelors degree, 7% bachelor’s degree, 48% master’s degree, and 36% doctoral degree. For CMHC staff, education rates were 18% less than bachelor’s degree, 37% bachelor’s degree, 45% master’s degree, and 0% doctoral degree. We included all three background variables as covariates in comparisons of VA and CMHC staff on job-related variables.

As shown in Table 1, there were several areas of difference between VA and CMHC. After controlling for gender, length of time in the mental health field, and education, VA staff reported significantly higher job satisfaction, less intention to turnover (i.e., were less likely to consider leaving in the next six months), less emotional exhaustion, and greater personal accomplishment. Each of these still significant using the Hochberg procedure. To better understand reasons for these differences, we examined what staff reported to be the best and most challenging things about their work.

Table 1.

Job-related variables of VA and Community Providers

VA (N=66) Local CMHC (N=86) Test of significance ANOVA, controlling for education, gender, and tenure in mental health field
Job Satisfaction1 5.8 (0.9) 5.2 (1.1) t=3.65, p=.000 Overall F=3.88, p=.005; Site F = 7.35, p=.008
Turnover Intentions
 Considered leaving job past 6 months2 1.8 (1.2) 2.3 (1.4) t=−2.15, p=.034 Overall NS
 Likely to leave job in next 6 months3 1.3 (0.6) 1.7 (0.9) t=−3.79, p=.000 Overall F=3.55, p=.009; Site F = 4.87, p=.029
Burnout 4
 Emotional Exhaustion 24.3 (11.5) 28.9 (10.8) t=−2.48, p=.014 Overall F=2.88, p=.025; Site F = 7.28, p=.008
 Depersonalization 9.1 (4.6) 9.8 (4.2) t=−.92, p=.360 Overall F=3.73, p=.007; Site F =0.16, n.s.
 Personal Accomplishment 49.4 (5.8) 42.9 (6.5) t=6.29, p=.000 Overall F=13.94, p<.001; Site F = 13.26, p<.001
Consumer Optimism5 3.5 (0.5) 3.4 (0.5) t=1.51, p=.134 Overall F=2.98, p=.022; Site F = 0.01, NS
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1

Satisfaction is scored on a scale of 1–7, with higher numbers indicating higher satisfaction.

2

This turnover item is scored on a scale of 1–6, with higher numbers indicating more likely to turnover.

3

This turnover item is scored on a scale of 1–4, with higher numbers indicating more likely to turnover.

4

Emotional Exhaustion is scored on a scale of 0–56, Depersonalization 0–30, and Personal Accomplishment 0–48, with higher numbers indicating higher burnout for all subscales except Personal Accomplishment, where higher numbers indicate a higher sense of accomplishment.

5

Consumer optimism is scored on a scale of 1–5, with higher numbers indicating higher anticipation of consumer success.

As shown in Table 2, we created categories based on the responses to open-ended questions. The most common “joy” was working with clients (31%). The next most common response was being a change agent (25%) where staff described an active role in helping achieve positive outcomes, usually with consumers (witness change was also fairly common with 17% responses, but included more passive responses of seeing change without explicitly attributing a role for themselves in that change). Coworkers/supervisors were mentioned by 20% as being the best thing about their work. VA and CMHC staff did not differ significantly in the types of positive aspects mentioned.

Table 2.

Joys for VA and Community Providers

Example Quote VA (N=50) Local CMHC (N=64) X2
Change Agent The best thing about my work is having the ability to make an impact in someone’s life 12 24% 16 25% 0.02
Grow as a person Has helped me grow personally; I learn so much from them 3 6% 2 3% 0.55
Working with people (not specifying clients or coworkers) I like the people that I work with; Get to work with or meet many people 2 4% 4 6% 0.29
Job description Flexibility and variety; To have the power to make some decisions. 10 20% 13 20% 0.00
Working with clients Variety of clients; Relationships w/clients. 16 32% 19 30% 0.07
Type of clients Contact with patients in acute care setting; Providing help to vets suffering combat-related PTSD 6 12% 2 3% 3.39
Witness change in clients Seeing client getting better and having more control over their own lives; The best thing is seeing the recovery in consumers 6 12% 14 22% 1.89
Coworkers/supervisors I work with a supportive and motivated team of providers; I have a great team leader 13 26% 10 16% 1.88
Other I enjoy working with the consumer and the community; Everything is good; Resources available to veterans and research 1 2% 2 3% 0.14
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Note: No comparisons statistically significant at p < .05.

The most challenging aspects of work, shown in Table 3, were time constraints (17%) such as feeling pressured by deadlines, difficulties with time management, and/or not having enough time. The next most frequent categories were workload and lack of resources (both at 12%). Workload frequently overlapped with time constraints in that staff often mentioned having too much to do in too little time. The reported lack of resources were often related to staffing shortages, but sometimes also referred directly to consumer-related resources (e.g., bus passes). VA and CMHC providers differed significantly in two categories. Staff in the CMHC were significantly more likely to report job-related aspects as being challenging, such as lack of flexibility in the schedule, and little pay (19% in CMHC versus 2% in the VA, X2 = 7.47, p < .01). Staff in the VA were significantly more likely than CMHC staff to report administrative issues as being challenging, for example, bureaucracy, red tape, and policies (22% in VA versus 2% in CMHC, X2 = 11.67, p < .001).

Table 3.

Challenges for VA and Community Providers

Example Quote VA (N=49) Local CMHC (N=59) X2
Coworkers/supervisors Staff and clients get bogged down in “that’s the way we’ve always done it and staff do not always have the energy for change; The most challenging thing is maintaining consistent team unity. 5 10% 6 10% 0.00
Working with clients Getting yelled at by veterans; Teaching the consumers daily living skills is the most challenging. 2 4% 4 7% 0.37
Type of clients Dealing with dual diagnoses of PTSD with other major mental illness or substance abuse; My biggest challenge is dealing with certain cognitive disorders that are represented in this population. 3 6% 4 7% 0.02
Client environment Improvement in their socio-economic support network 1 2% 0 0% 1.22
Client motivation Clients resisting becoming more independent; Getting people motivated in their care 1 2% 3 5% 0.70
Witnessing client setbacks Seeing clients deteriorate and not get depressed about it; Seeing positive results with stagnant clients 1 2% 3 5% 0.70
Job description Occasional monotony; Schedule; The biggest challenge is the lack of public support and relatively low pay. 1 2% 11 19% 7.47**
Admin/agency/management Managerial bureaucracy, organizational issues; Administrative meetings; Hospital policies and procedures that work against the veterans. 11 22% 1 2% 11.67***
Organizational change Rotating staff (student, residents); The unexpected changes on a day to day basis. 2 4% 3 5% 0.06
Productivity Most challenging is meeting productivity when doing so much that isn’t billable; Lack of office time, tons of paperwork combined with productivity levels interfere with effectiveness 1 2% 3 5% 0.70
Lack of resources Most challenging is covering when there is turnover and staff shortage; Need more bus passes 8 16% 5 9% 1.56
Time constraints Time management; Too much to do, too little time, and our population of vets require a lot of support since most have no other support system; too much to do in a fixed time…I never feel the job is complete 10 20% 8 14% 0.90
Paperwork The paperwork, treatment plans, deadlines for each; Paperwork and documentation 2 4% 8 14% 2.86
Workload Way too much to do in a 75 hour week; Most challenging thing is that I am given multiple roles & responsibilities. 7 14% 6 10% 0.43
Personal/individual Feeling isolated as a provider in the mental health walk in clinic; Learning to work on an ACT team; Ensuring I am not becoming stagnant in my skill set and approach to clinical work. Being able to leave work at work and not become emotionally drained myself 4 8% 7 12% 0.40
Larger system Dealing with Medicaid, Medicare, and Social Security offices and them not responding to messages; Threats re: funding, Medicaid, etc. 1 2% 3 5% 0.70
Other The economy; The most challenging is helping those see cultural diversity. 2 4% 2 3% 0.04
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**

p < .01;

***

p < .001

Discussion

Mental health staff working in the same city, but in different settings, reported significantly different levels of burnout and job satisfaction, even after controlling for background variables. Mental health workers in the VA setting endorsed fewer symptoms of burnout, particularly less emotional exhaustion and a greater sense of personal accomplishment. VA staff also were more satisfied with their jobs and were less likely to report intentions to leave employment at their current setting.

Very little research has compared VA and other settings in terms of burnout, but our findings support an earlier study comparing therapeutic recreation workers serving VA psychiatric inpatients that found VA staff had low to moderate levels of burnout compared to Maslach’s normative sample (Wade-Campbell & Anderson, 1987). While we have no way of knowing what may have contributed to greater levels of job satisfaction and lower burnout, we have several speculations which could serve as hypotheses for future research. First, given decreasing economic resources for mental health and other human service work, the large VA system, with direct federal funding, may not be as dominated by pressure for “billable hours” to Medicare or Medicaid to maintain financial viability of the service system. A potentially more stable financial future may provide a buffer for the individual worker. At the time of the survey, the community mental health center participating in this study was preparing for impending state Medicaid policy changes that later necessitated closing and/or restructuring multiple treatment teams and reducing the size of their adult workforce. Anecdotally, though, some VA staff have reported increasing levels of pressure as the VA is facing its own economic tightening and widespread use of performance measures. It is also possible that because this local VA is a training site for a variety of disciplines, interaction with students is invigorating and could bring additional meaning to the work. The VA system may also provide resources to staff in the form of better pay, benefits, and training opportunities. For example, the starting salary in our state for a master’s level, team leader clinician in a CMHC would be approximately $35,500, compared to $69,000 for the VA, a substantial difference. Some research suggests pay and job security are critical factors in satisfaction and intentions to leave (Clark, 2001). Although we did not examine perceived resources directly, there is some indirect support from the sources of challenge at work. Staff in the community reported more concerns with job-specific aspects like their schedule and pay; whereas VA staff were challenged more often by administrative concerns. Future research should investigate perceived resources in more detail, both in terms of personal resources for staff (e.g., salary, benefits) and resources for completing the job at hand.

Overall, staff at both sites reported similar types of joy in work—predominantly stemming from interactions with consumers. Staff described enjoying relationships with consumers, watching consumer success, and for many, being an active part in helping consumers move towards recovery. Some research indicates that physicians who spend more time performing job duties they appraise as meaningful, report lower levels of burnout (Shanafelt, 2009). It would be interesting to assess how much time staff in these respective settings are able to spend with consumers or how often staff are able to witness and contribute to positive consumer outcomes.

Our study is limited by a reliance on a convenience sample of staff at two agencies in one city and may have limited generalizability. However, it would not be possible to randomize staff to work in different organizations, and we capitalized on the opportunity to build on existing studies using similar measures in two samples of mental health workers. We were also limited in the depth of assessment we could perform. We were cognizant of staff potentially feeling burdened and did not want to add to that workload; but this came at a cost of not being able to measure other variables that could better illuminate potential factors in the differences we found. Our response rates of 44% and 50% are similar to a recent meta-analysis showing average response rates for mailed or web-based organizational surveys of 44.1% (Anseel et al., 2010); however, we cannot examine possible response bias in our data. Finally, this was an exploratory study, and we posed several comparisons which could result in spurious associations. Applying the Hochberg correction for multiple comparisons (Hochberg & Benjamini, 1990), we found significant differences for job satisfaction, emotional exhaustion, personal accomplishment, and turnover intentions. However, we did not apply such procedures to the qualitative comparisons given the exploratory nature and the interrelatedness of categories (i.e., responses were often coded in multiple categories).

Our findings point to some potential avenues for further research, for example, in better understanding sources of challenge and resources to support mental health work. More research could also examine sources of fulfillment in work, and how to increase those positive aspects that attract and maintain caring providers to this field. In addition, the differing sources of burden from the sites have implications for what these organizations can do to reduce burnout. Both types of facilities may benefit from finding ways to help workers spend more time in the most meaningful aspects of their work, particularly helping consumers in recovery. CMHC leadership and mental health authorities may need to find ways to address concerns related to job responsibilities (e.g., pay, schedule) whereas VA may need greater focus helping workers navigate administrative concerns.

Acknowledgments

The research reported here was supported in part by the Department of Veterans Affairs, Veterans Health Administration, Health Services Research & Development Service (IAC 05-254-3; Illness Management and Recovery for Veterans with Severe Mental Illness) and by an IP-RISP grant from the National Institute of Mental Health (R24 MH074670; Recovery Oriented Assertive Community Treatment). The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs. We appreciate the participation of staff at both organizations, the helpful comments of our writing group, as well as the assistance of Brittany Hood, Sylwia Oles, Laura Stull, and Candice Hudson.

Footnotes

Disclosures: None for any author.

Administration and Policy in Mental Health and Mental Health Services Research

Contributor Information

Michelle P. Salyers, Research Scientist, VA HSR&D Center on Implementing Evidence-based Practice, Roudebush VAMC and Regenstrief Institute, Inc; Co-Director, ACT Center of Indiana; Associate Professor, Department of Psychology, Indiana University Purdue University Indianapolis (IUPUI).

Angela L. Rollins, Research Scientist, VA HSR&D Center on Implementing Evidence-based Practice, Roudebush VAMC; Research Director, ACT Center of Indiana; Assistant Research Professor, Department of Psychology, IUPUI.

Yu-Fan Kelly, Staff Psychologist, Oklahoma City VAMC.

Paul Lysaker, Clinical Psychologist Roudebush VA Medical Center and Associate Professor of Clinical Psychology, Department of Psychiatry Indiana University School of Medicine.

Jane R. Williams, Associate Professor, Department of Psychology, IUPUI.

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