Comparing Demographic Factors,Background Characteristics,and Workplace Perceptions as Predictors of Burnout Among Community Corrections Officers

Abstract

The purpose of this article was to explore the association between demographic and background characteristics, as well as workplace perceptions that may predict burnout among two connected groups of community corrections officers. Using the Maslach Burnout Inventory, we assessed whether burnout differed between probation/parole and residential officers and analyzed whether predictors of burnout varied across these two groups. Our results indicated that while probation/parole officers were more likely to report Emotional Exhaustion, they were not any more or less likely to experience Depersonalization or Personal Accomplishment. In addition, educational training had a stronger impact for residential officers, while schedule fit was more important for probation/parole officers, when predicting Personal Accomplishment. These results not only extended the existing research on burnout but also helped inform key correctional stakeholders about what policies and practices were working well, as well as indicated potential areas of change to help minimize burnout among staff.

Keywords

burnout community corrections probation officers residential officers

Introduction

Maslach, Jackson, and Leiter (1996) defined burnout as “a syndrome of emotional exhaustion, depersonalization, and reduced personal accomplishment that can occur among individuals who work with people in some capacity” (p. 4). They demonstrated that burnout was significant for the negative consequences it created for both professionals and the people or clients with whom they worked. A plethora of research has suggested that burnout can lead to “a deterioration in the quality of care or service provided by the staff” (see Maslach et al., 1996, p. 4 for a list of studies). Within the criminal justice system, significant attention has been paid to burnout in policing and institutional corrections work (see Hurst & Hurst, 1997; Ivie & Garland, 2011; Lambert, 2010; Lambert, Kelley, & Hogan, 2013; Martinussen, Richardsen, & Burke, 2007; McCarty, Zhao, & Garland, 2007; Morgan, Van Haveren, & Pearson, 2002; Savicki, Cooley, & Gjesvold, 2003).

While some work has been done with probation/parole officers’ experiences with burnout (Gayman & Bradley, 2013; Lewis, Lewis, & Garby, 2013; Whitehead & Lindquist, 1985), currently no research exists on burnout among residential officers (e.g., staff who work in half-way houses, day treatment centers, or work-release centers). In Iowa, probation/parole officers and residential officers often worked closely together, sometimes in the same buildings, but their job descriptions and tasks differed in important ways. For example, probation/parole officers were typically tasked with more counseling and/or treatment-related activities, combined with protecting society, while residential officers were responsible for maintaining the safety of the offenders and staff within a residential facility (e.g., half-way house). They often also had different backgrounds and prior work experiences. For example, probation/parole officers were typically, but not always, hired from a residential officer position, while residential officers had no prior work experience in the field.¹ In addition, residential officers were expected to have 2 years of college, while probation/parole officers were expected to have a 4-year degree (Iowa Department of Correctional Services [Iowa DOCS], Fifth Judicial District, 2015; Iowa DOCS, Second Judicial District, 2015).

The lack of research on burnout among both probation/parole officers and residential officers was noteworthy as burnout not only had implications for the health of community corrections staff, similar to the health and safety of correctional officers, but also had implications for the successful rehabilitation of offenders under community supervision. The research on correctional officer burnout has shown that it was a significant problem and that there were several individual and organizational variables that affected burnout symptoms for correctional officers (Carlson, Anson, & Thomas, 2003; Garland, 2004; Greenglass, Burke, & Ondrack, 1990; Lambert, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012; Morgan et al., 2002; Savicki et al., 2003; Whitehead & Lindquist, 1986).

As noted above, burnout has been established as a significant problem in institutional corrections and has been shown to affect offender/client success, which may ultimately affect society at large through offender recidivism. Therefore, it was imperative to examine burnout among community corrections staff who worked closely with offenders to facilitate rehabilitation and compliance with the law. The purpose of this article was to explore burnout among two groups of closely related community corrections officers and the background and workplace factors that influenced the experience of burnout between these two groups. Using the three subscales (e.g., Emotional Exhaustion, Depersonalization, and Personal Accomplishment) of the well-established Maslach Burnout Inventory (MBI; Maslach et al., 1996), we compared these different dimensions of burnout among two groups of community corrections officers in Iowa: probation/parole officers and residential officers.² While we expected some similarities in burnout based on the fact that probation/parole and residential officers work with a similar, or in some cases, the same, population, we also expected some variation based on specific differences in their backgrounds and workplace characteristics. Due to a lack of research on these occupational groups, we turned first to a discussion of burnout among correctional officers to provide an initial framework for the present study.

Predictors of Burnout in the Correctional Officer Literature

The vast majority of studies of burnout on correctional officers used the MBI as the measure of burnout. This scale assesses burnout as a three-dimensional concept (Maslach et al., 1996). The first dimension, Emotional Exhaustion, captures “feelings of being emotionally overextended and exhausted by one’s work” (Maslach et al., 1996, p. 4). The second dimension, Depersonalization, refers to an “unfeeling and impersonal response toward recipients of one’s service, care, treatment, or instruction” (Maslach et al., 1996, p. 4). The third dimension, Personal Accomplishment, taps into feelings of competence and successful achievement in one’s work with clients, so a lack of these feelings is indicative of higher levels of burnout. As these three dimensions are seen as distinctive aspects of the concept, the inventory itself includes three subscales so Emotional Exhaustion, Depersonalization, and Personal Accomplishment can be assessed separately in addition to combining items into a composite measure. As such, the MBI is considered to be the foremost indicator of burnout, and its psychometric properties have been validated with empirical evidence from studies conducted in various countries around the world (Maslach et al., 1996).

In spite of the extensive research validating the MBI, the literature examining burnout among probation/parole officers was sparse, and that on residential officers was virtually non-existent. There was, however, a plethora of studies assessing burnout among corrections staff, and to a lesser extent, treatment staff within correctional institutions. These studies have examined a number of phenomena related to burnout, including harassment (Savicki et al., 2003); organizational citizenship behavior (Lambert, 2010); different types of organizational commitment (Lambert et al., 2013); organizational structure (Lambert, Hogan, & Jiang, 2010); job characteristics, such as daily contact, supervisor support, job variety, feedback, and autonomy (Lambert, Hogan, Cheeseman Dial, Jiang, & Khondaker, 2012); work–family conflict (Lambert, Hogan, & Altheimer, 2010); supervisor and management trust (Lambert, Hogan, Barton-Bellessa, & Jiang, 2012); and distributive and procedural justice (Lambert, Hogan, Jiang, Elechi, et al., 2010). Although it was clear that researchers have considered a wide range of factors thought to influence burnout among correctional officers, the following section assesses the most common variables used as independent and/or control variables in the literature.

Gender

Nearly all the research on burnout among correctional officers included gender as a variable. Results on the impact of gender on burnout among correctional personnel have been somewhat mixed depending on the measure of burnout that was used. Generally, no significant gender differences were found in predicting overall burnout when using the composite measure of the MBI among correctional officers (Hurst & Hurst, 1997; Lambert, Hogan, & Altheimer, 2010). Similarly, almost all studies failed to find statistically significant gender differences for the Emotional Exhaustion subscale of the MBI (Carlson et al., 2003; Hurst & Hurst, 1997; Lambert, 2010; Lambert, Hogan, & Jiang 2010; Lambert, Hogan, Jiang, Elechi, et al., 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012; Lambert, Hogan, Cheeseman Dial, et al., 2012; Lambert et al., 2013; Morgan et al., 2002; Savicki et al., 2003).

When looking at the other two subscales of the MBI, the results were more mixed. In terms of Depersonalization, some studies failed to find gender differences (Hurst & Hurst, 1997; Carlson et al., 2003; Lambert, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012), while others demonstrated that women had lower levels of Depersonalization than men (Greenglass et al., 1990; Morgan et al., 2002; Savicki et al., 2003). Similarly, some studies found no gender differences in terms of the Personal Accomplishment/Ineffectiveness subscale of the MBI (Hurst & Hurst, 1997; Morgan et al., 2002; Savicki et al., 2003). However, some found that female officers were more likely than male officers to report feeling Ineffective in their work (Lambert, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012).

Age

Age was another variable commonly used in the correctional officer burnout literature. A number of studies found no age difference for Emotional Exhaustion (Lambert, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012; Lambert, Hogan, Cheeseman Dial, et al., 2012; Lambert, Hogan, & Jiang, 2010; Lambert, Hogan, Jiang, Elechi, et al., 2010; Lambert et al., 2013), while other studies demonstrated that younger correctional officers reported higher levels of Depersonalization than older officers (Carlson et al., 2003; Garland, 2004; Lambert, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012; Whitehead & Lindquist, 1986). The results for the Personal Accomplishment/Ineffectiveness subscale were more mixed. While Morgan et al. (2002) found that older officers reported higher levels of Personal Accomplishment, Lambert (2010) and Lambert, Hogan, Barton-Bellessa, and Jiang (2012) found no age differences on this subscale.

Education

Level of education was also a commonly used variable in studies on correctional officer burnout. The vast majority of studies found no significant effect of education on Emotional Exhaustion (Lambert, Hogan, & Altheimer, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012; Lambert, Hogan, Cheeseman Dial, et al., 2012; Lambert, Hogan, & Jiang, 2010; Lambert, Hogan, Jiang, Elechi, et al., 2010; Lambert et al., 2013), Depersonalization (Lambert, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012), Ineffectiveness (Lambert, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012), or an overall/composite measure of burnout (Lambert, Hogan, Barton-Bellessa, & Jiang, 2012). However, Morgan et al. (2002) found that more educated officers reported higher levels of Personal Accomplishment than those with less education.

Tenure

A number of studies analyzed the impact of the length of time a correctional officer had been employed in his or her current job (e.g., at the prison he or she was working when he or she completed the study) on burnout. The results were mixed across studies. Some studies found no relationship between tenure and a composite measure of burnout (Lambert, 2010; Lambert, Hogan, Jiang, Elechi, et al., 2010) or the Emotional Exhaustion subscale (Lambert, Hogan, Cheeseman Dial, et al., 2012; Lambert, Hogan, & Jiang, 2010; Lambert, Hogan, Jiang, Elechi, et al., 2010; Lambert et al., 2013). Other studies found that officers with less than 1 year of experience reported lower levels of Emotional Exhaustion than officers with more experience (Morgan et al., 2002). Still others found that officers with longer tenure in their current job were more likely to report higher levels of Emotional Exhaustion than those with less tenure (Lambert, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012).

The relationship between tenure and Depersonalization was more complex. Morgan et al. (2002) found that officers with less than 1 year of experience reported lower levels of Depersonalization than officers with more than 3 years of experience, but more than officers with 1 to 2 years of experience (Morgan et al., 2002). Lambert, Hogan, Barton-Bellessa, and Jiang (2012) found no relationship between tenure and Depersonalization. Similarly, there were mixed results for the relationship between tenure and Personal Accomplishment/Ineffectiveness. Morgan et al. (2002) found that officers with less than 1 year of experience reported higher levels of Personal Accomplishment than officers with more years of experience (Morgan et al., 2002). Lambert, Hogan, Barton-Bellessa, and Jiang (2012) found no relationship between tenure and Personal Accomplishment/Ineffectiveness.

Health

Finally, another factor that was present in the correctional officer literature was health, or some measure that captured health-related issues. These variables have been considered as both predictors and potential outcomes of burnout in the existing studies. For example, Carlson and Thomas (2006) used sick days as an indicator of overall health. Interestingly, they found that the number of sick days one took was not related to burnout. Other studies used variables more closely related to symptomology to determine whether burnout played a role in determining negative health outcomes. Gayman and Bradley (2013) studied factors that predicted depressive symptoms as a measure of mental health. They found that the Emotional Exhaustion aspect of burnout was indeed a strong predictor of depressive symptoms among correctional officers.

Burnout Comparison between Correctional Officers and Others

In addition to these commonly used variables, a handful of studies have examined whether there were any differences in burnout between correctional officers and non-custody staff. Some studies looked generically at correctional officers versus non-custody staff (e.g., treatment staff; Lambert, 2010; Lambert, Hogan, & Altheimer, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012; Lambert, Hogan, Cheeseman Dial, et al., 2012; Lambert, Hogan, & Jiang, 2010; Lambert, Hogan, Jiang, Elechi, et al., 2010; Lambert et al., 2013), while just one study compared correctional officers with correctional caseworkers (Carlson & Thomas, 2006). Research comparing correctional officers with non-custody staff showed mixed results across the three MBI subscales. Lambert, Hogan, and Altheimer (2010) found that correctional officers reported higher levels of a composite measure of burnout than non-custody staff, while Lambert, Hogan, and Jiang (2010) and Lambert et al. (2013) found that correctional officers reported lower levels of emotional burnout than non-custody prison staff. Other studies found no difference between these two groups in terms of Emotional Exhaustion (Lambert, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012; Lambert, Hogan, & Jiang 2010).

In terms of Depersonalization, Lambert, Hogan, and Jiang (2010) found no difference between correctional officers and non-custody staff, while Lambert, Hogan, Barton-Bellessa, and Jiang (2012) found that correctional officers reported higher levels of Ineffectiveness than non-custody staff. Carlson and Thomas (2006) also found differences in burnout between correctional officers and correctional caseworkers. Specifically, they found that correctional officers reported lower levels of Emotional Exhaustion and Depersonalization than caseworkers. They did not find a statistically significant difference between Ineffectiveness and burnout between these two groups.

Burnout in Probation/Parole Officer Literature

While extensive research existed on the various work experiences of institutional correctional officers, very little has been conducted on similar issues among probation/parole officers. In addition, there was no research at all on the work experiences of residential officers. The existing literature on the work experiences of probation/parole officers covered topics such as job stress (O’Donnell & Stephens, 2001; Pitts, 2007; Slate, Wells, & Johnson, 2003; Wells, Colbert, & Slate, 2006), turnover intention (Lee, Joo, & Johnson, 2009; Matz, Woo, & Kim, 2014; Simmons, Cochran, & Blount, 1997), workplace decision-making (Jones & Kerbs, 2007; Slate et al., 2003), probation justification and work tasks (Payne & DeMichele, 2011), attitudes toward substance abuse treatment (Here, Cunningham, & Martin, 2000), attitudes toward girls (Gaarder, Rodriguez, & Zatz, 2004), perceptions of arming probation/parole officers (Roscoe, Duffee, Rivera, & Smith, 2007), secondary trauma (Severson & Pettus-Davis, 2013), and juvenile probation officer experiences (Blevins, Cullen, Frank, Sundt, & Holmes, 2006; Rush, 1991; Salyers, Hood, Schwartz, Alexander, & Aalsma, 2015).

In addition, a small number of studies looked at burnout among adult probation/parole officers. The first study to do this was conducted by Whitehead and Lindquist (1985). They surveyed all line probation/parole officers in Alabama. Using the MBI, they found that social support (measured by four items, including helpfulness of supervisor and ability to talk to supervisor) and correctional seniority (measured as months employed in corrections) predicted Emotional Exhaustion, while social support, role conflict, age, and correctional seniority predicted Depersonalization. Higher Emotional Exhaustion was reported by probation/parole officers who indicated lower levels of social support and greater seniority. Greater Depersonalization was reported by officers who were younger and those who indicated “lower levels of social support, greater role conflict and greater seniority” (Whitehead & Lindquist, 1985, p. 114).

Lewis et al. (2013) also studied burnout among probation officers, sampling five departments in three states (Arizona, California, and Texas). They found that probation officers who had specific types of clients on their caseloads were more likely to experience burnout than those who did not have these same types of clients. Officers who had clients with the following characteristics were more likely to experience burnout: violent recidivism with a child, sexual recidivism, threatened probation officer or officer’s family, threatened to kill probation officer, assaulted probation officer, and/or committed suicide.

Gayman and Bradley (2013) analyzed one aspect of burnout—Emotional Exhaustion—in a study of 825 North Carolina probation and parole officers. They used a five-item scale to measure Emotional Exhaustion,³ which included items such as “I feel fatigued when I get up in the morning and have to face another day on the job” and “I feel like I am at the end of my rope.” They found that compared with other officers, African American officers reported lower levels of burnout, but females and those who had been in their current job longer, reported higher levels of burnout. In addition, they found that officers who reported higher levels of work stress, role overload, role conflict, and role ambiguity also reported higher levels of burnout.

Burnout and Workplace Perceptions

As this was an exploratory study of burnout of occupational groups that have been relatively understudied, we sought to further advance the literature by incorporating additional variables that may be related to burnout. As burnout research in this area was so sparse, we looked at other studies on probation/parole officers that analyzed predictors of other important variables, such as job stress.

Some of the job stress research focused on occupational predictors, including perceptions of one’s work situation. For example, in a nationwide study of 3,144 probation and parole officers, Pitts (2007) provided subjects with a list of the most influential stressors for correctional officers. Respondents were asked to indicate, on a scale of 0 to 7, how much stress each of the items caused them. Based on the responses, Pitts (2007) identified a list of the 15 most influential stressors, out of a total of 31 items, for probation/parole officers. Interestingly, the No. 1 stressor was inadequate salary, while No. 15 was insufficient training. In addition, Pitts (2007) assessed perceptions of one’s educational competency as a source of stress for probation/parole officers. He found that educational competency was significantly related to stress, such that officers who indicated their educational training adequately prepared them for their job as a probation/parole officer had lower levels of stress than those who felt their educational training was insufficient.

Implications for the Present Study

A review of the research identified a number of variables that were commonly used to assess burnout among correctional officers, many of which showed mixed results. These variables included gender, age, educational level, tenure, and health. Based on the findings from Pitts (2007), combined with our goal of expanding the literature on burnout, we added three variables that were related to job stress among probation and parole officers. We chose educational competency, which we measured as adequate educational training, primarily because education level is a common, but very rarely significant variable used to assess burnout among correctional officers. Insufficient training was also a significant predictor of stress in past research (Pitts, 2007). As we included educational training, we felt it essential to also consider how job training might relate to burnout. Furthermore, we chose inadequate salary (pay dissatisfaction) because it was the top stressor identified by probation and parole officers (Pitts, 2007).

Given the limited research available on probation/parole and residential officers, it was pertinent to examine how these variables related to burnout for these two groups of community correctional personnel across the three subscales of the MBI. In Iowa, adult community corrections officers worked for one of eight judicial districts under the DOCS and were classified into two distinct groups: probation/parole officers and residential officers. In general, a probation/parole officer’s job was to

investigate and report findings and recommendations in clear and concise statements concerning persons assigned to field or residential supervision. A probation/parole officer identifies offender needs and problems through various intake and counseling techniques and devises a plan for the offender to successfully complete the course of supervision. (Iowa DOCS, Fifth Judicial District, 2015)

A residential officer’s job, however, was to “perform paraprofessional tasks in the rehabilitation, control, and security of clients in a community correction facility” (Iowa DOCS, Second Judicial District, 2015). Probation/parole officers were typically located within residential facilities (often referred to as half-way houses or work-release centers), meaning they worked in close proximity to and interacted regularly with residential officers and often worked with the same group of offenders. Throughout the state, the traditional path to a probation/parole position was by first spending time as a residential officer. Although one did not have to be a residential officer before being hired as a probation/parole officer, the typical pattern resulted in a direct connection between a residential officers’ job and their expectations of advancing in their career to a probation/parole officer. Nonetheless, their job tasks were different, and we expected some differences in the predictors of burnout across these two groups as a result of these different job experiences. For example, for probation/parole officers to develop treatment strategies, they had to read and discuss each offender’s history in great detail, including all of the things that the offender had experienced in his or her life, as well as the things that they had done to others. Residential officers, however, were not required to engage with offenders on this same level. Their primary responsibility was to check offenders in and out of the facility for work assignments, and to make sure offenders were adhering to the rules of the facility. Therefore, because probation/parole officers were exposed to more extensive content of an offender’s history and behavior, their work experiences might have been quite different from residential officers, and this might have resulted in higher levels of burnout for them.

Therefore, the purpose of the current study was to expand on the previous work by not only considering commonly used variables in the correctional officer literature but also including additional background factors and certain workplace perceptions that might be significant in predicting burnout in community corrections settings. The main focus of the current study, however, was to examine whether or not burnout differed across probation/parole and residential officers. Specifically, this research assessed three exploratory hypotheses related to differences between probation/parole officers and residential officers on each of the three subscales of the MBI burnout measure. Due to the lack of research comparing probation/parole officers with residential officers, the following hypotheses are based on existing studies comparing correctional officers with non-custody correctional staff. In this case, residential officers were similar to correctional officers, based on their shared focus on security and facility compliance, while probation/parole officers were more similar to caseworkers, based on their mutual emphasis on rehabilitation.

Hypothesis 1: Probation/parole officers will have higher levels of Emotional Exhaustion than residential officers. This rationale is based on the existing correctional literature showing an equal number of studies supporting both this relationship (Lambert, Hogan, Cheeseman Dial, et al., 2012; Lambert et al., 2013) and no significant difference (Lambert, 2010; Lambert, Hogan, Barton-Bellessa, & Jiang, 2012; Lambert, Hogan, & Jiang 2010).

Hypothesis 2: Probation/parole officers will have higher levels of Depersonalization than residential officers. This hypothesis was based on the research by Carlson and Thomas (2006) who found that correctional officers reported lower levels of Depersonalization than caseworkers.

Hypothesis 3: There will be no significant difference between probation/parole officers and residential officers on the Personal Accomplishment MBI subscale. Similar to the second hypothesis, this expectation was consistent with the Carlson and Thomas (2006) study, which did not find a difference in Personal Accomplishment across correctional officers and non-custody correctional staff.

Method

Participants

Data were collected using a survey instrument that included demographic and background characteristics, workplace perceptions, and the 22-item MBI (Maslach et al., 1996). Directors in all eight of Iowa’s Judicial District DOCS were contacted by email and asked whether they would be interested in assisting with an email survey on the work experiences of Iowa probation/parole and residential officers. Seven of the eight district directors responded, with six agreeing to participate in the survey. Directors were then sent an email containing a link to the survey. Directors forwarded the email to all the probation/parole and residential officers in their respective districts. The data were collected anonymously using the Qualtrics online survey program, which was set to automatically strip IP addresses from survey responses. Two reminder emails were sent to directors, each at approximately 2-week intervals. Participants were allowed to use work time to complete the survey, if they chose to do so. Survey links were emailed to 615 probation/parole officers and residential officers in the participating districts. Of these, 277 surveys were completed for an overall response rate of 45.04%, but the rate of response differed across the two groups of correctional officers. Surveys were completed by 179 of 356 probation/parole officers for a response rate of 50.28%, while we received surveys from 98 of 264 residential officers for a response rate of 37.12%. Although noteworthy, this difference was not surprising given that residential officers did not have personal office space and therefore had more limited access to private spaces with computers in their work settings. As a result, it was likely that residential officers had fewer opportunities to complete the survey during work time compared with the probation/parole officers in the study. This difference in access to private workspace could have accounted, at least in part, for the difference in response rates across the two groups.

Measures

Independent and Control Variables

Position was measured by a question asking participants to indicate their current job. Responses were coded 0 for residential officer and 1 for probation/parole officer. Similarly, participants were asked to indicate their gender. This variable was coded 0 for female and 1 for male. Age was determined by asking participants to indicate the year they were born. This year was then subtracted from the year they completed the survey (either 2014 or 2015, depending on the district). The health variable was measured by a question asking participants to rate in general how their health was on a 5-point scale (1 = poor to 5 = excellent). Education was measured by asking participants to identify their highest degree. Categories for this variable were high school diploma or General Educational Development (GED; 1), some college (2), AA/AAS degree (3), BA/BS degree (4), some graduate work (5), or MA/MS degree (6). The tenure variable asked participants about the total length of time they have worked in this field, combining job experience with this agency and any previous similar employers (e.g., probation/parole/residential). Response categories were less than 1 year (1), 1 to 5 years (2), 6 to 10 years (3), 11 to 15 years (4), 16 to 20 years (5), 21 to 25 years (6), and 26 years or more (7).

Another variable included in the analysis was primary location. It was measured by an item indicating where the majority of the participant’s work took place, in either a rural (0) or urban area (1). This item was not included in the initial survey sent out to the first of the six participating districts. That same survey asked participants to indicate in which facility they worked. We then asked the district director to determine which facilities would be considered “rural” and which ones would be considered “urban.” Based on the director’s response, we manually coded this variable for the completed surveys from this one particular district.

We also included variables measuring participants’ perceptions of how well their educational and job training prepared them for their current job. Educational training was based on responses to a single-item regarding agreement with a statement indicating that their educational training had adequately prepared them for their current position (1 = strongly disagree to 5 = strongly agree). Similarly, job training was measured by asking participants to assess their agreement (or disagreement) with five statements related to perceptions of how well their on-the-job training prepared them for their job (e.g., I have received proper training on how to keep myself safe while doing my job in the office/facility; Probation/parole and residential officers are given adequate training related to their individual jobs).

In addition to these views on educational and job training, we were also interested in participants’ perceptions of how well their current work schedule fit their needs. Only one study on correctional officer burnout included a measure of officers’ schedule. Morgan et al. (2002) found no relationship between the shift a participant worked and burnout. We wanted to assess whether or not participants’ perceptions of schedule flexibility was related to burnout. Accordingly, schedule fit was determined by responses to two statements regarding how much their current workday schedule met their needs and offered the flexibility they need (1 = strongly disagree to 5 = strongly agree). The final workplace perception variable was a measure of pay dissatisfaction. This item asked participants how much they disagreed or agreed with a statement about being underpaid for the work that they do at their job (1 = strongly disagree to 5 = strongly agree). Individual items for each of the measures described above and reliability coefficients for the additive scales are presented in the appendix.

Dependent Variables

We measured burnout using the Maslach Burnout Inventory (MBI), which consisted of 16 items that identified three distinct components of burnout: Emotional Exhaustion, Depersonalization, and Personal Accomplishment (Maslach et al., 1996). Emotional Exhaustion consisted of five items that related to how work makes one feel, including emotionally drained, fatigued, and frustrated. Depersonalization referred to “negative, cynical attitudes and feelings about one’s clients” (Maslach et al., 1996, p. 4), and consisted of five items that related to one’s feelings about the people they work with, including treating people like objects, being more callous, and not caring about what happens to their clients. Personal Accomplishment was measured with six items that related to one’s feelings about how successful they were at their jobs, including being able to easily understand how their clients feel and feeling that they deal very effectively with their client’s problems. Given the nature of these items, low scores on Personal Accomplishment indicated high levels of burnout. For each statement on the inventory, participants were asked to respond according to response categories that ranged from never (1) to every day (7). Copyright precluded listing the specific items that comprise the MBI, so this information was not included as part of the appendix; however, alpha values for Emotional Exhaustion, Depersonalization, and Personal Accomplishment were .92, .87, and .72, respectively. Specific items from the MBI can be obtained from the publisher at www.mindgarden.com.

Analysis Procedures

The main focus of this study was to determine what factors influenced burnout among community corrections staff and to consider whether or not these factors differed for probation/parole officers compared with residential officers. To address these issues, t tests were first conducted to determine whether there were significant mean differences on the study variables by job position (i.e., probation/parole vs. residential). Next, ordinary least squares (OLS) regression equations were estimated to assess the main effects of job position, background characteristics, and workplace perceptions on three separate measures of burnout (i.e., Emotional Exhaustion, Depersonalization, and Personal Accomplishment). Finally, separate OLS models for probation/parole officers and residential officers were also estimated to examine the potential joint effects of job position and other relevant factors on the three burnout measures. The z score tests involving comparisons of the coefficients for probation/parole versus residential officers were used to assess the presence of statistically significant differences across the models (Paternoster, Brame, Mazerolle, & Piquero, 1998). For purposes of clarity, effects across the models separated out by job position will only be discussed if statistically significant differences emerged.

Results

The distributions of variables in the study are presented in Table 1, differentiated first by the total sample and then by residential and probation/parole officer participants. Of the total 277 participants, 98 (35.40%) were residential officers while 179 (64.60%) were probation/parole officers. The sample was also characterized by a strikingly even distribution of gender as 126 (49.80%) males and 127 (50.20%) females participated in the study.

Table 1:

Descriptive Statistics for Study Variables

Variable name	Value	Total		RO		P/PO
Variable name	Value	n	%	n	%	n	%
Independent
Position	0 RO	98	35.40
Position	1 P/PO	179	64.60
Gender	0 Female	127	50.20	52	55.90	75	46.90
Gender	1 Male	126	49.80	41	44.10	85	53.10
Age	M =		42.85		41.11		43.86*
	SD =		10.75		13.01		9.08
	Median =		43.00		39.50		44.00
	Range =		23-72		23-68		27-72
Health	M =		3.34		3.10		3.48**
	SD =		0.88		0.92		0.82
	Median =		3.00		3.00		4.00
	Range =		1-5		1-5		2-5
Education	M =		3.98		3.63		4.19**
	SD =		1.02		1.03		0.96
	Median =		4.00		4.00		4.00
	Range =		1-6		1-6		1-6
Tenure	M =		4.30		3.67		4.65**
	SD =		1.76		1.84		1.61
	Median =		4.00		3.00		5.00
	Range =		1-7		1-7		1-7
Primary location	0 = Rural	72	32.60	15	20.00	57	39.00**
Primary location	1 = Urban	149	67.40	60	80.00	89	61.00
Educational training	M =		3.57		3.65		3.52
	SD =		1.00		0.98		1.01
	Median =		4.00		4.00		4.00
	Range =		1-5		1-5		1-5
Job training	M =		16.26		17.00		15.84*
	SD =		4.52		4.55		4.46
	Median =		17.00		18.00		16.00
	Range =		5-25		5-25		5-25
Schedule fit	M =		7.17		5.95		7.84**
	SD =		2.44		2.41		2.20
	Median =		8.00		6.00		8.00
	Range =		2-10		2-10		2-10
Pay dissatisfaction	M =		2.64		2.69		2.61
	SD =		1.13		1.08		1.15
	Median =		2.00		2.00		2.00
	Range =		1-5		1-5		1-5
Dependent
Emotional exhaustion	M =		12.71		11.09		13.61*
	SD =		8.10		7.84		8.12
	Median =		11.00		10.00		12.00
	Range =		0-30		0-28		0-30
Depersonalization	M =		12.26		10.88		13.05*
	SD =		8.00		8.36		7.71
	Median =		11.00		9.00		12.00
	Range =		0-30		0-30		0-30
Personal accomplishment	M =		28.30		28.55		28.16
	SD =		5.61		5.40		5.74
	Median =		29.00		29.50		29.00
	Range =		0-36		12-36		0-36

Note. N = 277. Number of cases vary due to missing values. RO = residential officer; P/PO = probation/parole officer.

p < .05. **p < .01.

In addition to descriptive statistics, Table 1 also provides results of the t tests for mean differences on study variables between residential officers and probation/parole officers. Probation/parole officers were older (t = 1.92, p = .050), indicated better health (t = 3.42, p = .001), had higher levels of education (t = 4.31, p < .001), had worked in the field longer (t = 4.57, p < .001), and were more likely to work primarily in a rural location (t = 2.90, p = .004) when compared with residential officers. In addition, probation/parole officers were less likely to indicate that their job training had adequately prepared them (t = 2.03, p = .043), but they were more likely to say that their schedule was meeting their needs (t = 6.53, p < .001) than residential officers. In terms of the three MBI burnout subscales, probation/parole officers were more likely to indicate symptoms of Emotional Exhaustion (t = 2.39, p = .018) as well as Depersonalization (t = 2.07, p = .040) compared with residential officers. There was no significant difference, however, between probation/parole and residential officers in terms of Personal Accomplishment.

The regression results predicting each of the three dimensions of burnout—Emotional Exhaustion, Depersonalization, and Personal Accomplishment—are provided in Table 2.

Table 2:

Equations Predicting Emotional Exhaustion, Depersonalization, and Personal Accomplishment

Variable name	Emotional exhaustion			Depersonalization
	Full	RO	P/PO	Full	RO	P/PO
	(1)	(2)	(3)	(4)	(5)	(6)
Position	3.04* (1.28)			0.95 (1.41)
Gender	−3.83** (1.04)	−4.49* (1.88)	−3.70** (1.32)	−1.81 (1.13)	−.87 (2.48)	−2.61* (1.29)
Age	0.02 (0.07)	−0.07 (0.10)	0.11 (0.10)	0.09 (0.07)	−0.07 (0.14)	0.21* (0.10)
Health	−3.11** (0.65)	−2.96** (1.05)	−3.04** (0.86)	−2.25** (0.69)	−1.74 (1.39)	−2.24** (0.81)
Education	0.38 (0.55)	1.24 (0.99)	−0.01 (0.73)	0.39 (0.60)	0.52 (1.27)	0.19 (0.72)
Tenure	0.47 (0.44)	1.34 (0.73)	−0.11 (0.61)	0.31 (0.49)	1.27 (0.97)	−0.41 (0.60)
Primary location	0.11 (1.05)	1.51 (2.36)	−0.38 (1.25)	−1.48 (1.15)	0.92 (3.04)	−2.22 (1.24)
Educational training	−1.23* (0.57)	−0.91 (0.99)	−1.33 (0.74)	−1.45** (0.61)	−1.61 (1.24)	−1.27 (0.72)
Job training	−0.23* (0.12)	−0.24 (0.21)	−0.26 (0.16)	−0.41** (0.13)	−0.48 (0.27)	−0.43** (0.16)
Schedule fit	−0.47* (0.23)	−0.32 (0.40)	−0.33 (0.34)	0.08 (0.25)	0.36 (0.51)	0.12 (0.33)
Pay dissatisfaction	1.96** (0.47)	2.03* (0.92)	1.96** (0.60)	1.81** (0.51)	1.15 (1.18)	1.88** (0.59)
R ²	.42**	.47**	.40**	.32**	.25	.38**
Variable name	Personal accomplishment
	Full		RO		P/PO
	(7)		(8)		(9)
Position	−0.46 (1.12)
Gender	−0.27 (0.90)		−0.88 (1.42)		0.73 (1.14)
Age	0.06 (0.06)		0.08 (0.08)		0.18* (0.09)
Health	0.69 (0.55)		0.08 (0.77)		1.16 (0.73)
Education	−0.15 (0.49)		0.01 (0.74)		−0.23 (0.66)
Tenure	−0.80* (0.39)		−1.06 (0.57)		−1.16* (0.54)
Primary location	1.29 (0.93)		0.98 (1.78)		1.27 (1.11)
Educational training	0.82 (0.50)		2.42** (0.71)		−0.40^a (0.67)
Job training	0.13 (0.11)		0.04 (0.15)		0.18 (0.15)
Schedule fit	0.36 (0.20)		−0.02 (0.30)		0.90**^a (0.30)
Pay dissatisfaction	0.58 (0.42)		0.63 (0.71)		0.89 (0.52)
R ²	.13*		.31*		.19**

Note. Unstandardized regression coefficients; standard errors in parentheses. RO = residential officer; P/PO = probation/parole officer.

Indicates coefficient comparison tests yielded statistically significant differences at p < .05.

p < .05. **p < .01.

Findings presented in column 1 of Table 2 indicated that the full model explained 42% of the variance in Emotional Exhaustion. As expected, probation/parole officers were more likely to report Emotional Exhaustion than residential officers (b = 3.04, p = .019), controlling for the other variables in the model. This evidence provided support for Hypothesis 1. Furthermore, women and those reporting poorer health also exhibited more Emotional Exhaustion than men and those reporting better health (b = −3.83, p < .001 and b = −3.11, p < .001, respectively). Interestingly, perceptions of adequate educational (b = −1.23, p = .032) and job training (b = −.23, p = .037) both had significant negative effects on Emotional Exhaustion. Given the coding of these variables, this suggested that those reporting inadequate training, either in the context of their education or on-the-job, experienced more Emotional Exhaustion than those reporting more adequate training experiences. Schedule fit also had a negative effect on Emotional Exhaustion (b = −.47, p = .047). This meant that those with schedules not meeting their needs reported more Emotional Exhaustion than those who experienced better schedule fit. Finally, participants who were dissatisfied with their pay were more likely to be Emotionally Exhausted than those who found their pay to be sufficient (b = 1.96, p < .001).

A slightly different pattern of results emerged when predicting Depersonalization. As shown in column 4, Table 2, a smaller amount of the variance was explained (R² = .32) compared with Emotional Exhaustion and there was not a statistically significant difference between probation/parole officers and residential officers on the Depersonalization burnout subscale. This indicated a lack of support for Hypothesis 2. Similarly, job position, gender, and schedule fit all failed to demonstrate significant effects on Depersonalization; however, other effects were notable. Similar to the findings reported above, health (b = −2.25, p = .001), educational training (b = −1.45, p = .010), job training (b = −.41, p = .003), and pay dissatisfaction (b = 1.81, p = .001) were all significant determinants of the dependent variable. These findings suggested that those reporting poorer health, who found their educational and job training to be lacking, and who were dissatisfied with their pay experienced more feelings of Depersonalization than those in better health, who felt they had adequate training, and who were satisfied with the amount they are paid.

The results for Personal Accomplishment differed markedly from the models predicting Emotional Exhaustion and Depersonalization. The full model presented in column 7 of Table 2 explained a much lower amount of the variance (i.e., R² = .13) than the full models for the other dependent variables. In addition, there was no significant difference between probation/parole officers and residential officers on Personal Accomplishment. Although this was consistent with the expectations of Hypothesis 3 and prior research comparing correctional officers with caseworkers (Carlson & Thomas, 2006), it was surprising that tenure was the only variable with a statistically significant effect on Personal Accomplishment (b = −.80, p = .041). As the effect was negative, this suggested that participants who reported greater years in the field were less likely to report feelings of Personal Accomplishment than those with less experience. Given that this was somewhat unexpected, and together with the lack of other significant predictors in the model, these findings underscored the point that factors determining burnout varied across the different aspects of it that were being considered.

In addition to the main effects discussed above, we were also interested in the potential joint effects of job position and the other study variables on the three burnout measures. Given that job position had a significant effect on Emotional Exhaustion (Table 2, column 1), this provided sufficient evidence to test for significant interaction effects in the models. Accordingly, separate models were estimated for probation/parole and residential officers on each dependent variable. The results are again presented in Table 2 for Emotional Exhaustion (columns 2 and 3), Depersonalization (columns 5 and 6), and Personal Accomplishment (columns 7, 8 and 9).

Tests involving comparisons of the coefficients for probation/parole versus residential officers revealed the existence of only two statistically significant differences across the models that occurred when predicting Personal Accomplishment. As indicated in Table 2, columns 8 and 9, the positive impact of educational training on Personal Accomplishment was significantly greater for residential officers than their probation/parole counterparts. In contrast, the positive effect of schedule fit on Personal Accomplishment was significantly greater for probation/parole officers than it was for residential officers.

Discussion

The purpose of this study was to determine if there were differences in burnout among probation/parole and residential officers and to consider if the predictors of burnout differed across these two groups. Overall, our results provided mixed support for the hypotheses framing the study. Controlling for other variables in the model, probation/parole officers were more likely to report Emotional Exhaustion than residential officers (support for Hypothesis 1), but they did not experience significantly different levels Depersonalization (non-support for Hypothesis 2) or Personal Accomplishment (support for Hypothesis 3). Support for Hypothesis 1 may be explained by the fact that probation/parole officers have much more exposure to an offender’s case file, must listen to an offender describe his or her behavior, and are often more involved with counseling and/or treatment-related activities than residential officers. It appears that probation/parole officers’ more intimate relationships with clients may take a personal toll on them over time and result in more Emotional Exhaustion in the workplace as compared with residential officers.

The lack of significant differences in Depersonalization when we expected to find it (Hypothesis 2) may be based on the fact that we were relying on the existing institutional correctional officer literature to frame the hypotheses. Based on these studies, we expected there to be a difference between these two job positions, primarily because of specific functions each job position holds (i.e., rehabilitation vs. security; Carlson & Thomas, 2006). Our lack of findings suggests first that perhaps residential officers are not as similar to institutional correctional officers as we initially speculated, but in fact are more similar to probation/parole officers instead. In terms of Personal Accomplishment (Hypothesis 3), it makes sense that officers’ perceptions of how well they do their job may not be based on their specific job position. Rather, Personal Accomplishment is likely generated from one’s ability to do his or her job well and take pride in it, and not on the specific type of work one does (e.g., rehabilitation vs. security). One can have a great sense of accomplishment over his or her rehabilitation work with offenders, as well as with his or her work in maintaining a safe and secure facility.

It was somewhat unexpected that very few of the relationships between other study variables and the burnout measures were conditioned by job position. In fact, only two significant interaction effects emerged in the analysis, and only when predicting Personal Accomplishment. As noted above, educational training had a stronger positive impact on Personal Accomplishment for residential officers than probation/parole officers. One explanation for this finding is the different nature of the two jobs. Residential officers may feel that their education has more adequately prepared them for the job, simply because of the kinds of tasks they are required to do, such as documenting offender behavior and ensuring offenders are following facility rules, require less specialized education. Probation/parole officers, many of whom have previously been a residential officer for a number of years, may not feel that their education adequately prepared them for their daily tasks as they engage in a wider variety of higher level responsibilities requiring more training and education, such as dealing with offenders in a more one-on-one, intense, treatment-focused setting.

In addition, schedule fit evidenced a significant effect on Personal Accomplishment for probation/parole officers but not for residential officers. One explanation for this finding is that probation/parole officers have much more choice over their schedule. They are not as restricted by scheduled hours as are residential officers, who must report to and end a shift at the same time every day. Because probation/parole officers have more flexibility in their schedule, they may simply feel better about themselves and the work that they are doing, compared with residential officers, whose schedule may be affecting both their personal and professional happiness.

It is also noteworthy that the results in this study showed both similarities and differences when compared with the existing burnout literature for correctional officers. For example, we found that for all three subscales, education was not a significant predictor of burnout. This is very consistent with the correctional officer literature that often included education as a variable but did not typically find it to be a significant determinant of burnout. Similarly, tenure has demonstrated mixed results among correctional officer research, with some studies finding it to be significantly related to all three subscales, while others found no such relationship. Our study also produced mixed results in that tenure was only significant for the Personal Accomplishment subscale of burnout, but not Emotional Exhaustion or Personal Accomplishment. Age, however, did not have a significant effect on burnout in our study, which differed from findings in the correctional officer literature in which age was related to both Depersonalization and Personal Accomplishment in some cases. Our results also showed that perceptions of one’s health was an important variable to consider when studying burnout, as it was significant in predicting both Emotional Exhaustion and Depersonalization.

The most notable difference between our findings and the correctional officer literature involved gender. We found that gender was a significant predictor of Emotional Exhaustion, but not Depersonalization or Personal Accomplishment. Gender was not a significant predictor of Emotional Exhaustion in nearly all of the correctional officer studies and was sometimes found to be a significant predictor of Depersonalization. Plausible explanations for these differences are the interactions of gender with the type of environment and nature of the work itself for correctional officers compared with either probation/parole or residential officers. Probation/parole officers have caseloads of offenders with whom they work with over a period of time and are charged with facilitating treatment for these offenders. Correctional officers often move around to different units in the prison and do not have the same influence over treatment for offenders. Their job entails less personal interaction with offenders compared with either probation/parole or residential officers. While residential officers do not work with offenders in the same way as probation/parole officers, there is more daily, personal interaction with offenders compared with correctional officers. The key difference appears to be that women working as correctional officers process working with offenders differently than women working in community corrections.

In addition to exploring how the most common demographic and background variables associated with burnout among correctional officers applied to burnout among community corrections officers, we also included several new variables. For example, our results suggested that officers’ perceptions of their salary were important in predicting Emotional Exhaustion. Similarly, we found that perceptions of the adequacy of one’s educational and job training were more important than one’s actual level of education in predicting burnout related to Emotional Exhaustion and Depersonalization. Future studies on burnout among community corrections officers should consider adding these variables.

We were surprised to find that where community corrections officers work (e.g., rural vs. urban location) did not influence burnout, at least not when included with the other variables in this study. Rural locations tend to be more isolated, with fewer staff and fewer offenders in the facility. Future studies may wish to include this variable, as it may be significant when combined with other variables such as dangerousness of the job, job stress, job satisfaction, or work–family conflict.

While this study contributes to the community corrections literature, there are a few limitations. The first is that the study includes only Iowa probation/parole and residential officers. Other states may organize their community corrections departments quite differently, such that the results may have limited generalizability across all states. A related concern is that we were unable to include race as a demographic variable. Iowa is a racially homogeneous (Caucasian) state, and the DOCS is similarly homogeneous. With a relatively small sample size, we had only a small percentage of participants from other racial groups, which precluded us from including race as an independent or control variable. While this is a limitation of the current study, it is worth noting that the majority of studies on burnout among correctional officers finds no relationship between race and burnout (Lambert, 2010; Lambert, Hogan, & Altheimer, 2010; Lambert, Hogan, Cheeseman Dial, et al., 2012; Lambert, Hogan, & Jiang, 2010; Lambert, Hogan, Jiang, Elechi, et al., 2010; Lambert et al., 2013; Morgan et al., 2002).

In addition, the small sample size limited the number of variables that could be included in the analysis. For example, some research suggests that when work environment variables, such as role conflict, role ambiguity, input into decision-making, and supervision, are added to the model, that the strength of the demographic characteristics drops significantly (Lambert, Hogan, & Barton, 2002; Lambert & Paoline, 2010). Due to the number of variables we could include in the model based on our sample size, we were not able to assess these variables in this study. Future research should consider examining these relationships in greater detail.

Along these same lines, the results may be viewed as limited because some of the variables were measured by single-item indicators (e.g., health, educational training, and pay dissatisfaction) instead of composite measures. While we were somewhat constrained by the number of questions we could ask on an email survey that was distributed in an occupational setting, future research should incorporate more complex indicators as appropriate to increase the predictive power of the models that are estimated.

In spite of these limitations with the data, there are several important implications of these results. Given that probation/parole officers evidenced higher levels of Emotional Exhaustion than residential officers, it suggests that practical changes may be needed to lessen Emotional Exhaustion for this group. For example, perhaps certain health initiatives would lead to better perceptions of one’s overall health, which may result in lower levels of both Emotional Exhaustion and Depersonalization. In addition, perceptions of the adequacy of job training were significantly related to both Emotional Exhaustion and Depersonalization, so it is possible that some changes in on-the-job training may be helpful to probation/parole officers as well as residential officers. Before such measures are implemented, it is important to first discuss with these officers what they perceive is needed to make job training more effective.

Our results also suggest the need for future research on burnout among community corrections staff. First, our results demonstrate the importance of determining what factors best predict each type of burnout among community corrections personnel, especially Personal Accomplishment. While there were several predictors of both Emotional Exhaustion and Depersonalization, it is striking that tenure was the only significant determinant of Personal Accomplishment and the effect was actually negative (i.e., more tenure indicated less sense of Personal Accomplishment). The lack of significant predictors in this model makes it clear that other factors such as organizational structure, supervisor support, and decision-making capabilities should be considered to give us a better understanding of what contributes to a lower sense of Personal Accomplishment among community corrections personnel. Future research should consider taking these factors into account when assessing burnout among this population.

Second, our results indicate that more research is needed on residential officers. Although not detailed above, a lack of significant predictors was also evident in the models that separated out for residential officers. Very few of the included variables predicted Emotional Exhaustion or Personal Accomplishment, and no variables affected Depersonalization. As mentioned previously, one explanation for the lack of findings for residential officers is that their job is more security focused, making sure offenders follow the rules of the facility. Therefore, the factors that affect them may be quite different than they are for probation/parole officers. For example, perhaps other variables such as job autonomy, occupational stress, peer support, or supervisor support may play a larger role in predicting residential officer burnout. Residential officers also spend a great deal of time with offenders; therefore, their interactions with offenders may influence offender success while in the work-release or half-way house facility. It is important to understand what factors influence burnout for this group, especially so steps may be taken to minimize symptoms of burnout that can negatively influence the health of the officers as well as the success of the offenders.

In addition, while the present study provides some indication of the factors that influence burnout among probation/parole officers, research on correctional officers suggests that there are other variables that also need to be looked at to determine what factors are most influential in predicting burnout among this group. For example, future studies should include variables related to job stress and satisfaction, work–family conflict, decision-making abilities, management/supervisor styles, and so forth.

Despite the need for additional research, the results indicate that job training was influential in predicting Depersonalization among probation/parole officers. In other words, officers who perceived that their job training was inadequate were more likely to express negative, cynical attitudes and feelings toward the offenders they work with. Districts may want to discuss job training protocols with their probation/parole officers to determine whether any changes can be made that may lessen officers’ negative feelings about the offenders with whom they work. Districts may also wish to consider health-related programs and wellness opportunities for their officers. Officers’ perceptions of their health were significantly related to Emotional Exhaustion for both probation/parole and residential officers and to Depersonalization for just probation/parole officers. It is possible that some health initiatives may result in a decrease in Emotional Exhaustion and Depersonalization. Improvements in this area may in turn lead to better work experiences for community corrections personnel as well as more positive outcomes for offenders.

Footnotes

Appendix

Independent Variables, Individual Item(s), and Cronbach’s Alpha Reliability Coefficients

Variable	Item(s)	Alpha
Position	What is your current job title?
Gender	What is your gender?
Age	What year were you born?
Health	In general, would you say your health is poor, fair, good, very good, or excellent?
Education	Please select your highest degree and, where applicable, indicate your field of study.
Tenure	What is the total length of time you have worked in this field, combining job experience with this.
Primary location	Please indicate the geographic location of where you do the majority of your work.
Educational training	My educational training (e.g., college) has adequately prepared me for my current career position.
Job training	I have received proper training on how to keep myself safe while doing my job in the office/facility.	.86
	I have received proper training on how to keep myself safe when working outside the building (e.g., on home visits, etc.).
	Probation/parole and residential officers are given adequate training related to their individual jobs.
	Officers are encouraged to attend various trainings aimed at assisting them to advance.
	Supervisors and/or team leaders provide adequate orientation and on-the-job training for new hires.
Schedule fit	My current workday schedule meets my needs.	.89
Schedule fit	My work schedule offers the flexibility I need.	.89
Pay dissatisfaction	I am underpaid for the work that I do at this job.

This project was supported in part by the University of Northern Iowa’s College of Social and Behavioral Sciences Small Project Grant and a Graduate College Summer Fellowship.

Notes

Gayle Rhineberger-Dunn, PhD, is an associate professor in the Department of Sociology, Anthropology, and Criminology at the University of Northern Iowa. Her research focuses on media and crime and on work experiences of community corrections officers and juvenile court and corrections officers.

Kristin Y. Mack, PhD, is a professor of sociology in the Department of Sociology, Anthropology, and Criminology at the University of Northern Iowa. Her research interests include how significant life events influence individual well-being and family relationships and the link between family factors and occupational outcomes.

Kimberly M. Baker, PhD, is an associate professor in the Department of Sociology, Criminology, and Anthropology at the University of Northern Iowa. As a sociologist, her research focuses on the social control of substance use. Her earlier work analyzes the decision-making process among officials in drug court. Her current research has turned to addiction-themed reality television shows, with a particular focus on the ways that treatment professionals interact with and respond to individuals with substance use problems.

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