Burnout
Healthcare providers, like MRTs, counselors, social workers, or nurses, treatment center staff encounter a breadth of occupational stressors: resistance from clients, poor treatment outcomes, coworker turnover, and pressure to meet organizational goals.
An Overview of “Burnout”
Burnout is broadly defined as the interaction of the stresses of work and the ways in which a person copes or, more accurately, fails to cope (Lacoursiere, 2001). As the pressures and stressful experience of a job increase, the employee may begin to feel burnt out as their coping skills deteriorate. According to Maslach (2001), a leading figure of job burnout research and developer of a popular burnout instrument, the burnout experience can be deconstructed into three dimensions: [1] overwhelming exhaustion, [2] feelings of cynicism and detachment from the job, [3] and a sense of ineffectiveness and lack of accomplishment (p. 160). We can imagine how an opioid use counselor may experience each of these facets. If the counselor has more clients than hours in the workday, he/she could easily become exhausted. Counseling multiple clients that may have been through treatment multiple times could lead to cynicism about the effectiveness or benefits of treatment. Finally, when counselors experience a lack of closure as clients leave the center and are never heard from, accomplishments are difficult to conceptualize.
Job burnout as a conceptual model and theory has been driven predominantly by Leiter and Maslach (1999). While incorporating the basic three-dimension framework of exhaustion, cynicism, and ineffectiveness, the authors expanded their theory to include the organizational, contextual, or environmental aspects of burnout.
Six organizational risk factors for job burnout were identified and modeled into the “Areas of Worklife:” workload, control, reward, community, fairness, and values. Leiter and Maslach argue that organizational burnout antecedents, may be categorized into one of these areas. A survey, the Areas of Worklife Scale (AWS), was constructed to measure the predictors of burnout on an organizational level (Leiter and Maslach, 2004). Whereas the Maslach Burnout Inventory (MBI) (Maslach, Jackson, & Leiter, 1986) was created to assess burnout in individuals based on the three dimensions, exhaustion, cynicism, and inefficacy, the AWS can be used by organizations or leaders to assess for systematic contributions to employee burnout. As Leiter and Maslach concluded (2008), “it is more likely that signs of impending problems… will tend to cluster within particular units or organizational groups” (p. 509). For leaders in addiction treatment settings, one question concerns, “Where are the problem clusters and what can be done to alleviate and prevent this?”
Contributing Factors
Before considering protective factors against job burnout and how organizations may implement or strengthen them, it is important to understand the factors contributing to this psychological syndrome following Maslach & Leiter (2016). The literature classically established a multitude of individual factors (Pines & Maslach, 1978) and researchers later sought to describe organizational contributors (Leiter & Maslach, 1999).
Individual Contributing Factors
Two of the three dimensions of the burnout experience, exhaustion and cynicism, could be considered solely on the personal level. True, the workplace environment moderates these, but individual feelings of exhaustion and cynicism exist primarily at the individual level. In other words, there can be no tangible workplace expression of exhaustion or depersonalization, whereas with reduced accomplishment there can be, for example, a lack of annual raises or no reinforcement from management. Lacoursiere (2001) suggested that there could be certain work events or environments in which a feeling of burnout might be a normal response. This contrasts with the conceptualization of burnout as a disease-model. Regardless, in response to individuals experiencing unhealthy levels of burnout components like exhaustion or cynicism, Lacoursiere (2001) purports that employers ought to demonstrate the same effort as when dealing with other problems like quality, style and performance levels of work.
Corroborating these two primary, individual contributing factors Knudsen, Ducharme, and Roman (2009) applied burnout principals to measure other job-related individual factors. The authors, recognizing a lack of research on emotional exhaustion and turnover intention for organizational leaders, completed research on leaders of addiction treatment organizations and focused on the leader turnover intent and emotional exhaustion. Turnover intention, rather than actual turnover, was chosen since true turnover data requires longitudinal research. The authors used two job demand related independent variables, performance demand and centralization (making more day-to-day decisions), and two job resource related independent variables, innovation in decision-making and long-range strategic planning. The researchers’ hypotheses were mostly confirmed; higher levels of emotional exhaustion were significantly associated with larger turnover intention (p < .001) and the two job demands were also significantly associated with emotional exhaustion (both p < .01).
As opposed to reduced accomplishment, the third primary component of burnout, Volker et al. (2010) analyzed job satisfaction in relation to risk of burnout. Job satisfaction could be considered the individual form of the third primary dimension, inefficacy; job satisfaction is parallel in many ways with perceived inefficacy. The researchers gathered treatment provider data from six different opioid treatment centers across Europe: Athens, London, Padua, Stockholm, Zurich, and Essen. The study is part of the larger Treatment-systems Research on European Addiction Treatment study (TREAT). The participants (n = 902) were only required to be health care workers delivering therapy or counseling to primarily opioid users. Participants completed, in addition to other batteries, the Maslach burnout inventory (MBI) and a job satisfaction scale. As mentioned, the MBI covered three constructs: emotional exhaustion, depersonalization, and reduced personal accomplishment. The authors’ regression model, however, only included a subset of persons from Essen, Stockholm, and Zurich (n = 142). Health care workers with low job satisfaction had 13.2 the odds of experiencing burnout compared to those with higher job satisfaction. Opioid treatment providers with high levels of burnout view their work situation as out of their control and try to avoid their negative emotions.
In addition to these causes, Kulesza, Hunter, Shearer, and Booth (2017) used provider stigma as a predictor of job satisfaction and burnout. The secondary data analysis tested whether provider stigma predicted three primary outcomes at a community-based addiction treatment facility: job satisfaction, burnout, and workplace climate. The authors argued that previous burnout studies on substance use disorder (SUD) treatment providers were conducted in either medical settings or resource-rich facilities, thus limiting generalizability. A 2014 and 2015 survey of Los Angeles treatment providers at publicly-funded centers (N = 38) were used to measure job satisfaction, workplace climate, burnout, and provider stigma.
Using stepwise linear regression, the authors concluded that higher provider stigma was significantly related to lower job satisfaction and low ratings of workplace climate. Burnout, however, did not show evidence of being significantly related to provider stigma. A small sample size likely hindered this study and prevented findings similar to previous studies that significantly associated provider stigma and burnout. Still, the study was helpful in establishing the need to study under-resourced community centers. Hopefully, more longitudinal data can be collected to build off this cross-sectional study.
Organizational Contributing Factors
Lacoursiere (2001) linked both increased work pressure and unclear work policies to burnout. Some of these factors, like work pressure, can contribute to the intrapersonal dimensions of burnout. Increased work pressure would seem to accentuate exhaustion but is still considered an organizational factor since work pressure exists on the occupational plane. Further research could explore individual perceptions of organizational factors, e.g. is an individual’s perception of work pressure or unclear policies a stronger predictor of burnout than objectively, measured constructs?
