Predictors of Employment Burnout Among VHA Peer Support Specialists
Abstract
Objective:
This study evaluated three domains of job burnout (emotional exhaustion, depersonalization, and personal accomplishment) and factors associated with burnout in a national sample of peer specialists (PSs) employed at 138 Veterans Health Administration (VHA) health care systems in 49 states.
Methods:
Data were drawn from an observational study in which participants (N=152) completed online, self-report surveys about their mental health recovery, quality of life, and employment experiences at baseline, six months, and 12 months. Levels of burnout were analyzed at each time point, and regression analyses that controlled for baseline levels identified potential predictors of burnout (demographic, clinical, and employment characteristics) at six and 12 months.
Results:
Compared with previously published burnout levels of other mental health workers in the VHA, PSs reported similar levels of emotional exhaustion, depersonalization, and personal accomplishment. At baseline, increased burnout was correlated with white race, fewer hours providing direct services, greater psychiatric symptoms, and lower self-efficacy. However, analyses did not reveal strong predictors of burnout scores at six or 12 months.
Conclusions:
In the first study to prospectively examine job burnout among PSs employed by the VHA, results illustrate the nuanced experience of burnout over a 12-month period and suggest the need for replication and further research on employment experiences of this emerging workforce.
Peer specialists (PSs) are individuals with psychiatric diagnoses and treatment histories who are hired to provide mental health services to others. Although the concept of peer-provided services is not novel, the past decade has seen a growing interest in the role of peer services, spurred in large part by current trends in mental health care reform (1). Within the Veterans Health Administration (VHA), increasing numbers of peers have been hired in paid, full-time PS positions to deliver services to veterans (2,3). PSs perform a number of job activities, including mentoring, teaching social skills, sharing recovery experiences, and attending staff meetings (3). Although most research on peer-provided services has focused on the outcomes of individuals receiving peer-delivered interventions (4–6), much less is known about the experiences of the peers themselves.
According to Skovholt’s helper therapy principle (7), individuals in helping roles can receive important benefits, including increased self-esteem and enhanced sense of self. Across a variety of general medical problems and mental disorders, peer providers report that helping facilitates improved awareness and acceptance of their own condition, builds coping skills, and increases sense of purpose and self-competence (8–11).
Peer providers also face challenges, including role confusion at work, unclear boundaries with other employees and veterans, unfamiliarity with standard workplace behavior, lack of technical knowledge, feeling overworked, recurrence of symptoms, and dissatisfaction with pay (9,12,13).
A concern among mental health workers is burnout (14,15), defined as a syndrome comprising three factors: emotional exhaustion, depersonalization, and reduced personal accomplishment (16). Burnout can manifest as feeling overextended, ineffective, and cynical about one’s job (17). Some researchers have argued that burnout is work-related depression (18). Burnout has a plethora of negative correlates, including poorer physical health (19–21), elevated psychiatric symptoms (20,22–24), greater rates of substance use (20,25), poorer work performance, lower customer service ratings (26), absenteeism (21), and intention to quit (17). Together, these correlates have significant implications for quality and continuity of care, work climate, job turnover, and the well-being of providers.
Identifying predictors of burnout among mental health service providers informs prevention and intervention strategies (27–29). Younger age, perceived organizational politics and bureaucracy, increased clinical workload, lack of control over one’s work, harsh criticism from supervisors, as well as dissatisfaction with salary, promotional opportunities, and praise, have all been identified as predictors (30–34). A conceptual model created by Maslach and colleagues (32) posits that incongruities between employees’ needs and job characteristics in six key areas of work life—workload, control, reward, community, fairness, and values—predict job burnout (35–37). For each of these areas, a PS’s dual identities in an organization as both a person with a mental health condition and a provider of mental health services could lead to higher levels of perceived pressure and responsibility for those served beyond the specialist’s capability to effect change (leading to discrepancies in control, workload, and values) and to less integration with other mental health providers (leading to discrepancies in community, reward, and fairness).
Although a large body of work has examined burnout among human service workers, this topic has not been systematically examined among PSs (14). Many studies have found high rates of burnout among mental health service providers and those employed in public service systems (15,18,38). PSs, who are called upon to utilize their personal experiences with having and being treated for a mental disorder, may be especially susceptible to burnout (13,39). With formalized peer support being a relatively new discipline, PSs may also feel added pressure to “prove” their worth and maximize productivity, which may lead to feeling overworked. Thus a systematic characterization of burnout and its associated factors among PSs is important to support wellness in this group, maximize outcomes for recipients of peer-delivered services, and inform the development of burnout interventions.
This study capitalized on a recent national study (3) and aimed to examine levels of burnout among PSs at baseline, six months, and 12 months; evaluate the relationship between burnout and job and provider characteristics at baseline; and identify whether these variables predict burnout at six and 12 months, with analyses controlling for burnout levels at baseline.
Methods
Data were drawn from a national, observational study in which 152 PSs from 138 VHA systems in 49 states completed a 40-minute online survey reporting their employment experiences, mental health recovery, and quality of life (3). The response rate was 54% of 279 PSs contacted from a national Listserv of VHA PSs. PSs were informed about the study by e-mail and invited to participate; completion of the online survey constituted consent. Data were collected between December 2011 and June 2013, and participants were assessed at three time points (baseline, six months, and 12 months). All procedures were approved by the institutional review board (IRB) of the Edith Nourse Rogers Memorial Veterans Hospital in Bedford, Massachusetts. Data analyses and reporting procedures for this article were also approved by the Baltimore Veterans Affairs Medical Center IRB. Further details of the study design and procedures are reported elsewhere (3).
Measures
Variables used in this study included demographic characteristics (age, gender, race, and level of education), employment characteristics (such as hours providing direct services), and other measures, described below (3). These variables were selected for inclusion in our analyses given that they have been shown to be related to job burnout (20,22–24,30–36).
The Maslach Burnout Inventory (MBI) (16,17) is a 22-item measure assessing three domains of burnout in human services professions: emotional exhaustion (nine items), depersonalization (five items), and reduced personal accomplishment (eight items). Items are rated on a 7-point scale from 0, never, to 6, every day (15). High levels of burnout among mental health workers are represented by scores of ≥21 in emotional exhaustion, ≥8 in depersonalization, and ≤28 in personal accomplishment (17). The MBI, considered the gold standard in the assessment of burnout, has good reliability and validity (17).
The Behavior and Symptom Identification Scale (BASIS-24) (40) is a well-established, multidimensional mental health assessment with six subscales (depression/functioning, interpersonal relationships, self-harm, emotional lability, psychotic symptoms, and substance abuse) as well as an overall score. In this study, we used the overall score, with higher scores indicating greater overall symptom severity. Subscale and overall score reliability range from .77 to .91 with good convergent and discriminant validity (40).
The General Self-Efficacy Scale (41) is a ten-item measure assessing perceptions of problem-solving and coping skills; higher scores indicate greater self-efficacy. Internal consistency reliability coefficients range from .76 to .90. Criterion-related validity studies have demonstrated positive correlations with optimism, favorable emotions, and work satisfaction.
Hours providing direct services assessed hours of direct contact provided in person, by telephone, or by other means. This was measured as an ordinal variable (0–20 hours per week, 21–30 hours per week, or ≥31 hours per week) but treated as a continuous variable for analyses.
Statistical Analyses
We first calculated descriptive statistics on the three MBI subscales (emotional exhaustion, depersonalization, and personal accomplishment) at baseline, six months, and 12 months and compared them with published scores from a sample of VHA-employed mental health staff (38). We then conducted a repeated-measures analysis of variance (ANOVA) to examine changes in burnout over time, with time included as the main effect. When there was a significant time effect, paired comparison between any two time points was then conducted with a Bonferroni correction to adjust for multiple comparisons. Next, we conducted bivariate analyses to examine the associations of baseline burnout scores with PS characteristics, including demographic characteristics, overall psychiatric symptoms, self-efficacy, and hours providing direct services. We used correlational analyses, t tests, or one-way ANOVA as appropriate. Variables that were significantly associated with baseline burnout levels were included in a multivariable linear regression model to identify baseline factors (personal and job characteristics) that predicted burnout at six and 12 months. We controlled for baseline burnout levels in the regression model; consequently, the model predicted changes from baseline to follow-up burnout levels. Separate regression models were used for the three burnout subscales. We calculated both unstandardized and standardized regression coefficients to indicate effect size (42).
Results
Sample Characteristics
Most of the 152 participants were male (N=121, 80%), with an average age of 52.0 and a median age of 53.0 (Table 1). Fifty-seven percent identified as white, and 42% indicated they were married or with a partner. A majority (N=130, 86%) had some college education, including 33% with a bachelor’s or advanced degree. Seventy-two percent (N=110) of participants had been certified as PSs. Half (50%) reported receiving disability benefits. Of the 152 participants, 125 (82%) completed surveys at six months, and 109 (72%) completed surveys at 12 months. There were no significant differences in baseline burnout, hours providing direct services, psychiatric symptom severity, or general self-efficacy between respondents who completed only baseline surveys and those who completed follow-up surveys at six and 12 months.
| Characteristic | Peer specialists (N=152) | |
|---|---|---|
| N | % | |
| Gender | ||
| Male | 121 | 80 |
| Female | 31 | 20 |
| Race | ||
| White | 86 | 57 |
| Nonwhite | 66 | 43 |
| Marital status | ||
| Married or with partner | 64 | 42 |
| Separated, divorced, or widowed | 67 | 44 |
| Never married | 21 | 14 |
| Education | ||
| High school graduate, GED, or less | 22 | 15 |
| Some college | 80 | 53 |
| Bachelor’s degree or more | 50 | 33 |
| Receiving disability benefits | 76 | 50 |
a
Mean±SD age was 52.0±8.5 years.
Levels of Job Burnout
PSs reported levels of emotional exhaustion, depersonalization, and personal accomplishment similar to previously published levels of burnout of VHA-employed mental health staff (38) across all three time points (Table 2). There was a significant overall change in emotional exhaustion score across time (F=.25, df=2 and 208, p=.044), with an increase from baseline to six months but no change from baseline to 12 months or from six to 12 months. Depersonalization scores also differed significantly across time (F=5.47, df=2 and 208, p=.005), increasing from baseline to six months but not changing significantly from baseline to 12 months or from six to 12 months. There were no significant changes across time in personal accomplishment scores.
| Burnout subscale | Baseline (N=149) | 6 months (N=125) | 12 months (N=110) | Comparison group (N=66)a | ||||
|---|---|---|---|---|---|---|---|---|
| M | SD | M | SD | M | SD | M | SD | |
| Emotional exhaustionb,c | 12.9 | 11.0 | 15.4 | 11.7 | 13.6 | 11.3 | 15.3 | 11.5 |
| Depersonalizationc,d | 2.5 | 4.0 | 3.5 | 4.7 | 3.1 | 4.2 | 4.1 | 4.6 |
| Personal accomplishmente | 43.2 | 5.1 | 43.3 | 5.0 | 43.8 | 4.8 | 41.4 | 5.8 |
a
Burnout scores from a sample of mental health staff employed by the Veterans Health Administration (38). The means presented here have been converted from those in the published article to be consistent with the scoring of the Maslach Burnout Inventory (16,17) and to enable comparison with the study sample.
b
Possible scores range from 0 to 54, with higher scores indicating greater burnout.
c
The six-month measure was significantly higher than baseline (p<.05 with Bonferroni multiple comparison adjustment).
d
Possible scores range from 0 to 30, with higher scores indicating greater burnout.
e
Possible scores range from 0 to 48, with higher scores indicating a greater sense of accomplishment.
Correlates of Job Burnout at Baseline
None of the three burnout subscale scores were related to gender, age, or level of education. However, compared with nonwhites, whites reported significantly higher levels of emotional exhaustion (2.77±1.04 versus 1.98±1.25, p<.001) and depersonalization (1.69±.47 versus 1.25±.95, p<.001). There were no significant racial differences with regard to personal accomplishment. Spending more hours per week providing direct services was associated with lower depersonalization and higher personal accomplishment, but there was no significant correlation between hours of direct services and emotional exhaustion (Table 3). Baseline psychiatric symptom severity was significantly associated with all three burnout variables. Greater emotional exhaustion and depersonalization were associated with higher psychiatric symptom severity, whereas greater personal accomplishment was associated with lower psychiatric symptom severity. Similarly, greater baseline self-efficacy was significantly associated with lower emotional exhaustion and depersonalization and higher personal accomplishment.
| Characteristic | Emotional exhaustion | Depersonalization | Personal accomplishment |
|---|---|---|---|
| Age | .06 | .00 | .06 |
| Hours providing direct services | –.09 | –.20* | .26** |
| Overall psychiatric symptoms | .58** | .32** | –.41** |
| General self-efficacy total score | –.31** | –.21** | .31** |
*
p<.05, **p<.01
Predictors of Job Burnout at Six Months
None of the potential baseline predictors (race, hours providing direct services, overall psychiatric symptom severity, or self-efficacy) significantly predicted six-month emotional exhaustion after analyses controlled for baseline emotional exhaustion. After controlling for baseline depersonalization, analyses indicated that only white race was a significant predictor of higher depersonalization at six months. After controlling for baseline personal accomplishment, lower overall psychiatric symptom severity and lower general self-efficacy were significant predictors of higher personal accomplishment at six months, but effect sizes were small (Table 4).
| Emotional exhaustion | Depersonalization | Personal accomplishment | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Unstandardized | Standardized | Unstandardized | Standardized | Unstandardized | Standardized | ||||
| Independent variable | Β | SE | β | Β | SE | β | Β | SE | β |
| 6 months | |||||||||
| Racea | .041 | .166 | .016 | .310* | .136 | .172 | .125 | .100 | .099 |
| Hours of direct services | .164 | .100 | .097 | .164 | .084 | .140 | –.071 | .063 | –.086 |
| Overall psychiatric symptoms | .250 | .152 | .123 | –.004 | .113 | –.003 | –.212* | .084 | –.215 |
| General self-efficacy total score | .027 | .021 | .083 | .001 | .017 | .006 | –.031* | .014 | –.195 |
| 12 months | |||||||||
| Racea | –.167 | .191 | –.066 | .165 | .145 | .100 | .057 | .118 | .046 |
| Hours of direct services | –.077 | .114 | –.047 | .126 | .087 | .119 | .095 | .073 | .118 |
| Overall psychiatric symptoms | .290 | .164 | .154 | –.235* | .113 | –.191 | –.131 | .093 | –.141 |
| General self-efficacy total score | .060* | .023 | .191 | –.023 | .018 | –.114 | .024 | .016 | .158 |
a
Reference group: nonwhite
*
p<.05
Predictors of Job Burnout at 12 months
Greater general self-efficacy at baseline was a significant predictor of higher emotional exhaustion at 12 months after we controlled for baseline emotional exhaustion, although the effect size was small (Table 4). After controlling for baseline depersonalization, we found that only overall psychiatric symptom severity was a significant predictor of depersonalization at 12 months, but the effect size was small. Greater overall psychiatric symptom severity was associated with less depersonalization at 12 months. There were no significant baseline predictors for 12-month personal accomplishment after we controlled for baseline personal accomplishment.
Discussion
PSs in the study sample reported similar levels of emotional exhaustion, depersonalization, and personal accomplishment compared with other VHA-employed mental health staff (38). This finding suggests that although the role of a PS may be demanding, concerns that PSs may be more vulnerable to burnout were not supported by this study. Burnout was also relatively stable across time, which is consistent with previous literature (43). Although there were statistically significant changes in emotional exhaustion and depersonalization from baseline to six months, these were small effects, and there was no change in emotional exhaustion or depersonalization at 12 months and no change in personal accomplishment over time.
Results also indicate that burnout among PSs was not associated with age, gender, or level of education. However, although there were no racial differences in personal accomplishment, white PSs reported greater levels of emotional exhaustion and depersonalization at baseline. White race was also a significant predictor of greater depersonalization at six-month but not 12-month follow-up. Studies reporting on racial and ethnic differences in burnout have shown mixed results (44,45), and it is unclear why white PSs in this sample endorsed higher burnout at baseline and the six-month follow-up.
PSs who reported providing more hours of direct services per week endorsed lower levels of depersonalization and higher levels of personal accomplishment at baseline. This finding provides encouraging data that greater client contact was not found to be associated with increased burnout among PSs employed in the VHA. In line with this finding, number of hours providing direct services was not a significant predictor of burnout at six or 12 months. These results challenge fears about and resistance against the implementation of PSs (12,46) that could lead to limitations on PS workload, job activities, and career advancement.
Greater symptom severity was associated with higher levels of emotional exhaustion and depersonalization and lower levels of personal accomplishment at baseline. Further, higher BASIS-24 overall scores predicted lower personal accomplishment at six months. These results are consistent with prior research that found a positive association between burnout and mental health concerns (20,22–24). Interestingly, however, greater psychiatric symptom severity at baseline significantly predicted lower depersonalization at 12 months after we controlled for baseline depersonalization. Whereas current psychiatric symptom exacerbation was related to greater burnout, greater symptom severity may reduce feelings of depersonalization and increase empathy toward one’s clients at a later time.
The finding that greater self-efficacy was associated with lower burnout at baseline is consistent with previous research (30–32); that is, individuals who expressed greater confidence in their problem-solving and coping skills reported lower levels of burnout. However, as with the findings on psychiatric symptoms, the longitudinal data on self-efficacy as a predictor of burnout at six and 12 months indicated that the direction of these relationships can shift across time. Specifically, greater baseline self-efficacy was a significant predictor of lower personal accomplishment at six months after analyses controlled for baseline personal accomplishment. And at 12 months, greater baseline self-efficacy was a significant predictor of greater emotional exhaustion after analyses controlled for emotional exhaustion at baseline. Therefore, whereas greater confidence in one’s problem-solving skills was initially associated with lower burnout, over the course of one year, these preliminary findings indicate that higher self-efficacy at baseline may in fact be predictive of greater burnout over time. Although effect sizes were small and replication is needed, we can reason that PSs who initially felt confident about their problem-solving skills and resourcefulness may have experienced more burnout at follow-up when their expectations were not met with reality (for example, clients did not improve, or the PS was frustrated with challenges and barriers faced on the job). Thus, although greater self-efficacy is generally considered a positive and desirable trait, PSs and their supervisors may want to dedicate time during supervision to addressing frustrations that arise. These findings, while preliminary, have implications for how PS positions and supervision are structured.
A potential study limitation was loss to follow-up from individuals who left their jobs due to burnout. However, among the 152 PSs who participated in the study, we identified only five who left their positions. This was determined by self-report for those who responded at the 12-month follow-up, supplemented for nonrespondents by whether they still had a functional VHA e-mail address, which they would not have if they had left the VHA, although they could have moved to a different VHA position. Based on these two data sources, the proportion of PSs who appeared to have left their jobs was very low (<5%). Further, although there were no differences in baseline burnout, hours providing direct services, psychiatric symptom severity, or general self-efficacy between respondents who completed only baseline surveys and those who completed follow-up surveys at six and 12 months, it is possible that PSs who did not complete six- and 12-month surveys were experiencing more burnout. Another potential limitation is that although all PSs were providing peer support, there may have been differences in how PSs were deployed across various VHA systems. Future research may consider examining how differing responsibilities or clinic settings may affect burnout for PSs. Finally, although burnout levels of other VHA-employed mental health staff (38) were referenced as a general comparison, differences in sample and employment characteristics, including length of employment and job responsibilities, are important to consider but were beyond the scope of this study.
Conclusions
This study is the first to prospectively examine job burnout and predictors of burnout of PSs employed by the VHA. Study participants included over half of all PSs who were employed at VHA facilities nationwide when the study began, with representation from 138 VHA health care systems in 49 states. Results support potential positive effects of employment in that very few left their jobs, and those who stayed did not report high or increasing levels of burnout over one year. Furthermore, we did not find consistent or strong predictors of burnout over one year, which was possibly due to small changes in burnout over time. The small effects we found were not consistent across time points and suggest the need for replication and caution in drawing firm conclusions. Future studies may also benefit from examination of organization-level or other work-life factors that were not included in this study (31,35,36). Our findings illustrate the nuanced experience of burnout over a 12-month period among PSs employed at the VHA and contribute to the literature on job burnout of mental health workers.
Acknowledgments
This work was supported by VA Health Services Research and Development grant IIR 10-332; the Office of Academic Affiliations, VA Advanced Fellowship Program in Mental Illness Research and Treatment; the VA Capitol Health Care Network (VISN 5) MIRECC; and the ENRM Veterans Hospital.
References
1.
Achieving the Promise: Transforming Mental Health Care in America: Final Report. Pub no SMA-03-3832. Rockville, Md, US Department of Health and Human Services, President’s New Freedom Commission on Mental Health, 2003. http://www.mentalhealthcommission.gov/reports/reports.htm
2.
VHA Handbook 1160.01 Uniform Mental Health Services in VA Medical Centers and Clinics. Washington, DC, US Department of Veterans Affairs, Sept 11, 2008
3.
Eisen SV, Mueller LN, Chang BH, et al: Mental health and quality of life among veterans employed as peer and vocational rehabilitation specialists. Psychiatric Services 66:381–388, 2015
4.
Chinman M, George P, Dougherty RH, et al: Peer support services for individuals with serious mental illnesses: assessing the evidence. Psychiatric Services 65:429–441, 2014
5.
Fuhr DC, Salisbury TT, De Silva MJ, et al: Effectiveness of peer-delivered interventions for severe mental illness and depression on clinical and psychosocial outcomes: a systematic review and meta-analysis. Social Psychiatry and Psychiatric Epidemiology 49:1691–1702, 2014
6.
Lloyd-Evans B, Mayo-Wilson E, Harrison B, et al: A systematic review and meta-analysis of randomised controlled trials of peer support for people with severe mental illness. BMC Psychiatry 14:39, 2014
7.
Skovholt TM: The client as helper: a means to promote psychological growth. Counseling Psychologist 4:58–64, 1974
8.
Mackenzie S, Pearson C, Frye V, et al: Agents of change: peer mentorship as HIV prevention among HIV-positive injection drug users. Substance Use and Misuse 47:522–534, 2012
9.
Miyamoto Y, Sono T: Lessons from peer support among individuals with mental health difficulties: a review of the literature. Clinical Practice and Epidemiology in Mental Health 8:22–29, 2012
10.
Moran GS, Russinova Z, Gidugu V, et al: Benefits and mechanisms of recovery among peer providers with psychiatric illnesses. Qualitative Health Research 22:304–319, 2012
11.
Proudfoot JG, Jayawant A, Whitton AE, et al: Mechanisms underpinning effective peer support: a qualitative analysis of interactions between expert peers and patients newly-diagnosed with bipolar disorder. BMC Psychiatry 12:196, 2012
12.
Hamilton AB, Chinman M, Cohen AN, et al: Implementation of consumer providers into mental health intensive case management teams. Journal of Behavioral Health Services and Research 42:100–108, 2015
13.
Moran GS, Russinova Z, Gidugu V, et al: Challenges experienced by paid peer providers in mental health recovery: a qualitative study. Community Mental Health Journal 49:281–291, 2013
14.
Paris M Jr, Hoge MA: Burnout in the mental health workforce: a review. Journal of Behavioral Health Services and Research 37:519–528, 2010
15.
Morse G, Salyers MP, Rollins AL, et al: Burnout in mental health services: a review of the problem and its remediation. Administration and Policy in Mental Health and Mental Health Services Research 39:341–352, 2012
16.
Maslach C, Jackson SE: The measurement of experienced burnout. Journal of Occupational Behaviour 2:99–113, 1981
17.
Maslach C, Jackson SE, Leiter MP: Maslach Burnout Inventory, 3rd ed; in Evaluating Stress: A Book of Resources. Edited by Zalaquett CP, Wood RJ. Lanham, Md, Scarecrow, 1996
18.
Awa WL, Plaumann M, Walter U: Burnout prevention: a review of intervention programs. Patient Education and Counseling 78:184–190, 2010
19.
Acker GM: The challenges in providing services to clients with mental illness: managed care, burnout and somatic symptoms among social workers. Community Mental Health Journal 46:591–600, 2010
20.
Peterson U, Demerouti E, Bergström G, et al: Burnout and physical and mental health among Swedish healthcare workers. Journal of Advanced Nursing 62:84–95, 2008
21.
Stalker C, Harvey C: Professional Burnout: A Review of Theory, Research, and Prevention. Partnerships for Children and Families Project. Waterloo, Ontario, Wilfrid Laurier University Press, 2002
22.
Ahola K, Honkonen T, Isometsä E, et al: The relationship between job-related burnout and depressive disorders: results from the Finnish Health 2000 Study. Journal of Affective Disorders 88:55–62, 2005
23.
Corrigan PW, Holmes EP, Luchins D, et al: Staff burnout in a psychiatric hospital: a cross-lagged panel design. Journal of Organizational Behavior 15:65–74, 1994
24.
Wykes T, Stevens W, Everitt B: Stress in community care teams: will it affect the sustainability of community care? Social Psychiatry and Psychiatric Epidemiology 32:398–407, 1997
25.
Rohland BM: A survey of burnout among mental health center directors in a rural state. Administration and Policy in Mental Health and Mental Health Services Research 27:221–237, 2000
26.
Taris TW: Is there a relationship between burnout and objective performance? A critical review of 16 studies. Work and Stress 20:316–334, 2006
27.
Rabin S, Feldman D, Kaplan Z: Stress and intervention strategies in mental health professionals. British Journal of Medical Psychology 72:159–169, 1999
28.
Scarnera P, Bosco A, Soleti E, et al: Preventing burnout in mental health workers at interpersonal level: an Italian pilot study. Community Mental Health Journal 45:222–227, 2009
29.
van Dierendonck D, Schaufeli WB, Buunk BP: The evaluation of an individual burnout intervention program: the role of inequity and social support. Journal of Applied Psychology 83:392–407, 1998
30.
Consiglio C, Borgogni L, Vecchione M, et al: Self-efficacy, perceptions of context, and burnout: a multilevel study on nurses. La Medicina del Lavoro 105:255–268, 2014
31.
Green AE, Albanese BJ, Shapiro NM, et al: The roles of individual and organizational factors in burnout among community-based mental health service providers. Psychological Services 11:41–49, 2014
32.
Maslach C, Schaufeli WB, Leiter MP: Job burnout. Annual Review of Psychology 52:397–422, 2001
33.
Garcia HA, McGeary CA, McGeary DD, et al: Burnout in Veterans Health Administration mental health providers in posttraumatic stress clinics. Psychological Services 11:50–59, 2014
34.
Martin U, Schinke SP: Organizational and individual factors influencing job satisfaction and burnout of mental health workers. Social Work in Health Care 28:51–62, 1998
35.
Maslach C, Leiter MP: The Truth About Burnout. San Francisco, Jossey-Bass, 1997
36.
Leiter MP, Maslach C: Areas of worklife: a structured approach to organizational predictors of job burnout; in Research in Occupational Stress and Well Being: Vol 3. Emotional and Physiological Processes and Positive Intervention Strategies. Edited by Perrewé P, Ganster DC. Oxford, JAI Press/Elsevier, 2004
37.
Leiter MP, Maslach C: Nurse turnover: the mediating role of burnout. Journal of Nursing Management 17:331–339, 2009
38.
Salyers MP, Rollins AL, Kelly YF, et al: Job satisfaction and burnout among VA and community mental health workers. Administration and Policy in Mental Health and Mental Health Services Research 40:69–75, 2013
39.
Mancini MA, Lawson HA: Facilitating positive emotional labor in peer providers of mental health services. Administration in Social Work 33:3–22, 2009
40.
Eisen SV, Normand SLT, Belanger AJ, et al: The Revised Behavior and Symptom Identification Scale (BASIS-R): reliability and validity. Medical Care 42:1230–1241, 2004
41.
Schwarzer R, Jerusalem M: Generalized Self-Efficacy Scale; in Measures in Health Psychology: A User’s Portfolio: Causal and Control Beliefs. Edited by Weinman J, Wright S, Johnston M. Windsor, UK, NFER-Nelson, 1995
42.
Nieminen P, Lehtiniemi H, Vähäkangas K, et al: Standardised regression coefficient as an effect size index in summarising findings in epidemiological studies. Epidemiology Biostatistics and Public Health 10(4): e8854-1–e8854-15, 2013
43.
Burke RJ, Richardsen AM: Psychological burnout in organizations; in Handbook of Organizational Behavior. Edited by Golembiewski RT. New York, Marcel Dekker, 1993
44.
Leiter MP, Harvie PL: Burnout among mental health workers: a review and a research agenda. International Journal of Social Psychiatry 42:90–101, 1996
45.
Blankertz LE, Robinson SE: Who is the psychosocial rehabilitation worker? Psychiatric Rehabilitation Journal 19:3–13, 1996
46.
Chinman M, Lucksted A, Gresen R, et al: Early experiences of employing consumer-providers in the VA. Psychiatric Services 59:1315–1321, 2008
Information & Authors
Information
Published In
Cover: Tea infuser and strainer, by Marianne Brandt, circa 1924. Silver and ebony. The Beatrice G. Warren and Leila W. Redstone Fund, 2000, The Metropolitan Museum of Art, New York City. Image copyright © The Metropolitan Museum of Art; image source: Art Resource, New York City.
History
Received: 16 June 2015
Revision received: 22 December 2015
Accepted: 1 February 2016
Published online: 1 June 2016
Published in print: October 01, 2016
Authors
Competing Interests
Dr. Eisen receives a proportion of licensing fees collected by the copyright holder from private organizations for use of one of the outcome measures in this research. However, government agencies use the instrument free of charge. Consequently, there was no financial remuneration for use of the measure in this research. The other authors report no financial relationships with commercial interests.
Funding Information
VA Health Services Research & Development (HSR&D): IIR 10-332
Metrics & Citations
Metrics
Citations
Export Citations
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
For more information or tips please see 'Downloading to a citation manager' in the Help menu.
View Options
View options
PDF/EPUB
View PDF/EPUBLogin options
Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.
Personal login Institutional Login Open Athens loginNot a subscriber?
PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.
Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).