Stressed Out: Predictors of Depression Among Jail Officers and Deputies

Abstract

Prevalence and predictors of depression, a debilitating medical illness, are unknown among officers working in jails. We conducted a cross-sectional survey with jail officers at four facilities, utilizing age, ethnicity, gender, musculoskeletal back disorder, global physical health and mental health, and psychological well-being as predictor variables. Descriptive analyses detailed prevalence, and hierarchical regression models identified depression predictors. The prevalence of depression among jail officers was high and strongly influenced by job burnout over and above other health indicators. Mitigation of workplace stressors and identification of targeted interventions are needed to reduce risks for depression among jail officers.

Keywords

mental health job burnout jail officer occupational health health promotion

Introduction

Nearly 40% of the U.S. public safety employees are jail-based officers and sheriff’s deputies (Bureau of Labor Statistics, 2016). Collectively referred to as jail officers, these workers serve in justice facilities where an estimated 11 million people cycle through the corrections system each year (Minton & Zeng, 2016). Nearly 500,000 jail officers are employed in 3,283 facilities housing over 2.2 million people in local- and county-level jails and prisons across the United States (Bureau of Labor Statistics, 2016; Kaeble & Glaze, 2016). This stands in stark contrast to the 1,821 state and federal prisons (Stephan, 2008) that serve approximately 1.5 million residents (Kaeble & Glaze, 2016).

In comparison to prisons, jails differ in their management, infrastructure, available resources, policies and procedures, day-to-day operations, staffing, duration of stay, and services (Lurigio, 2016). Although research on employee health has been described in studies of prison officers (Lambert et al., 2015; Obidoa et al., 2011; Stack & Tsoudis, 1997; Warren et al., 2015), there is limited data on jail-based officers working in city and county settings. This is an important omission because the criminal justice system is not only affected by the health of justice-involved individuals but also by correctional officers. While jails play a key role in the criminal justice system and have a major impact on local communities, they are often overlooked (Applegate & Sitren, 2008; Lurigio, 2016). Thus, there is a need for studies such as this project that describes the prevalence and predictors of depression among jail officers, an at-risk population of workers, to inform city and county jail-based workplace health promotion interventions.

Literature Review

Characterized as a “serious medical illness,” depression is a leading cause of disease worldwide for adults (World Health Organization, 2017), with associations to higher mortality risks from suicide and heart disease among other causes of death (Centers for Disease Control, 2016). Nearly 90% of individuals reporting depressive symptoms also indicate difficulties impacting their work, home, and/or school activities (Pratt & Brody, 2014). Although effective treatments for depression exist (National Institute of Mental Health, 2016), the rates of seeking treatment for depression are low (Wang et al., 2005), especially among those who may be identified through employee health programs.

Job stress, one of the greatest threats to correctional officer well-being (Bierie, 2012; Brower, 2013), is associated with job burnout and high rates of turnover (Carlson & Thomas, 2006; Hammen et al., 2009; Lambert et al., 2010). Ongoing high intensity and stressful correctional environments and work demands that contribute to negative well-being and poorer physical health issues for jail employees include lack of job control, hazardous conditions due to emergency situations, understaffing, and working mandatory overtime (Ferdik, 2017; Finney et al., 2013; National Occupational Research Agenda Public Safety Sector Council, 2013). In a review of prison officer wellness and safety literature, Brower (2013) described four categories of stressors, including inmate/people experiencing incarceration, occupational stressors, organizational/administrative stress, and psychosocial stressors. The impact of job burnout on general health among prison officers is also documented, however, not with jail officers.

Prison officer health is generally poor (Obidoa et al., 2011), and studies have revealed high rates of obesity and hypertension among prison staff that places them at risk of chronic disease (Morse et al., 2011). In contrast, examinations of physical health as a predictor of psychological health are limited (Harvey, 2014). In comparison with manufacturing workers, prison officers have higher prevalence and intensity of lower extremity musculoskeletal disorders involving injury to muscle, ligaments, tendons, and/or nerves (Warren et al., 2015). Associations between mental health disorders and cardiovascular disease exist (Ho et al., 2015; Offidani et al., 2017), in addition to musculoskeletal disorders. In a study comparing workers with and without co-occurring disorders, Ervasti et al. (2014) found those with chronic hypertension and musculoskeletal disorder were at higher risk of a recurrent depression-related work disability.

Given this literature on the health effects of job stress among prison officers, jail officers are also at heightened risk of physical and mental health conditions, respectively. In this study, we utilize indicators of demographic, physical and mental health function, and medical diagnosis to describe the largely poorly represented jail officer population. Furthermore, we consider the vulnerabilities or diatheses that may potentially place jail officers at risk of depression, a common work-related disability, and how the relationship may be moderated by the provision of officer emotional support, including empathy or advice (Salsman et al., 2013).

Diathesis–Stress Theory

Individuals typically have the capacity to withstand a moderate amount of exposure to stressors. Perceived stressors or vulnerabilities that exceed an individual’s capacity may contribute to symptoms of pathology (e.g., physical, emotional, depression). The diathesis–stress model provides a conceptual framework for depicting stress relationships and was recently operationalized for depression (Colodro-Conde et al., 2017). The model describes a synergistic relationship between vulnerabilities or diatheses and stress and their combined (additive and multiplicative) interactive effects on depression (Colodro-Conde et al., 2017).

In this study, we apply the diathesis–stress model to consider physical and mental health issues to be individual vulnerabilities that may increase risk of depression in jail officers (Figure 1). Following the model from left to right, each of the vulnerabilities and related measures, individual-level demographics, physical health, mental health, and job burnout combined, impact overall worker heath. Studies have indicated that emotional support is a key buffer to depression. Said another way, increasing levels of support at work may lead to improved health and wellness of employees working in jail-based settings.

Figure 1.

Measures applied in a diathesis–stress model of depression among jail officers.

Current Study

This study extends existing correctional workplace health research by examining the relationship of demographic, physical health, and occupational stressor characteristics to depression in a sample of jail-based employees. More specifically, we determine the prevalence of depression among jail-based corrections officers and deputies working in rural and urban jails and examined the extent to which demographic variables and indicators of physical and psychological health predict depression among jail officers. Finally, we explore emotional support as a moderator to depression among jail officers.

The following four hypotheses were tested:

Hypothesis 1: After controlling for demographic characteristics (age, ethnicity, and gender), indicators of physical health will share a significant negative relationship with depression.

Hypothesis 2: Indicators of mental health will share a significant negative relationship with depression above and beyond both demographic and physical health indicators.

Hypothesis 3: Job burnout will share a significant positive relationship with depression above and beyond demographic, physical, and mental health indicators.

Hypothesis 4: Emotional support will moderate the relationship between job stress and depression, such that as emotional support increases, the main effect decreases. Furthermore, as emotional support decreases, the main effect increases.

Method

Program Details

Through the Saint Louis University Transformative Justice Initiative and Health Criminology Research Consortium, we seek to develop evidence-informed improvements to health protection and health promotion in justice systems. This study is a portion of a larger Total Worker Health^® participatory health and safety needs assessment of Midwest U.S. rural and urban jails (Jaegers et al., in press). Ethical approval was obtained prior to data collection and informed consent was obtained from each participant. This study was approved by the Institutional Review Board at Saint Louis University.

Jail Sites, Participants, and Procedures

Sites were selected using purposive sampling of jails located within a 60-mile radius (1-hour drive) of the researchers’ location. We contacted seven facilities, four rural and three urban jails and county sheriff’s departments. Of the seven, four agreed to participate. Two rural and two urban jail facilities employing a total of 401 jail officers were recruited for this project.

Participants were at least 18 years old and employed as a correctional officer or jail-based sheriff’s deputy at the participating facility. During shift change meetings at each facility between October and November 2015, researchers informed jail officers about the study and invited them to take part by filling out a self-administered, hard copy questionnaire. Participation was voluntary, anonymous, and occurred during shift changes. A total of 320 jail officers returned surveys, with a response rate of approximately 80% based on the number of officers employed at the time of data collection. As remuneration for their participation in the study, jail officers received a US$20 gift card.

Measures

Dependent variables

Depression was measured by the Center for Epidemiologic Studies Depression Scale 10-item short form (CES-D-10) first developed by Radloff (1977) with subsequent revised versions (Andresen et al., 1994). The CES-D-10 measured depressive symptoms experienced in the last week including sadness, loss of interest, appetite, sleep, thinking/concentration, guilt, and fatigue. Responses followed a 4-point scale ranging from “all of the time” to “rarely or none of the time” and were weighted from 0 to 3 for scoring. Items were summed to calculate a total score, where 10 or greater is the clinical cutoff for depression. Acceptable reliability (α = .73) was found in the current sample.

Independent variables

Healthy Workplace All Employee Survey

We used the publicly available Healthy Workplace All Employee Survey (Center for Promotion of Health in the New England Workplace, 2014) to explore health diagnoses by including the following question, Has a doctor or other health care provider told you that you currently have any of the following conditions? Participants responded to our list of selected health diagnoses including hypertension/high blood pressure and low back or spine (musculoskeletal) disease using a yes or no response.

PROMIS^® Global Health v1.1

The Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health Short Form v1.1 included 10 items that were scored as components of global physical health (GPH) and global mental health (GMH). Items of the GPH component rated overall health, physical health, pain, fatigue, and ability to carry out everyday physical activities. The GMH items rated quality of life, mental health, satisfaction with social activities and relationships, and being bothered by emotional problems such as feeling anxious, depressed, or irritable. Exemplar items include “To what extent are you able to carry out your everyday physical activities such as walking, climbing stairs, carrying groceries, or moving a chair?” and “In general, how would you rate your satisfaction with your social activities and relationships?” Scoring involved calculation of each set of items and converting raw scores to T-score values that were standardized on a U.S. general population mean. The average population score was 50 (SD = 10), where a high score represented more of the health concept being measured. Internal consistency was higher for GMH (α = .75) than GPH (α = .62), which fell below the generally accepted threshold of .70.

PROMIS^® Emotional Support v2.0

For the moderator analysis, we utilized a four-item measure of emotional support from the PROMIS measures (HealthMeasures, 2018). Item examples include having someone who makes him or her feel appreciated and having someone to give him or her good advice about a crisis. Responses were scaled from 1 (never) to 5 (always). A total score was calculated by averaging all items. Emotional support displayed high internal consistency (α = .91).

Psychological well-being

According to Ryff and Keyes (1995), this tool measured positive psychological functioning through seven items exploring self-acceptance, personal growth, purpose in life, positive relations with others, environmental mastery, and autonomy. Examples of items include has a sense of direction and purpose in life and enjoys making plans for the future and working to make them a reality. Item options ranged from 1 (strongly disagree) to 6 (strongly agree). A total score was calculated by reverse coding four of the seven items and averaging them. The reliability coefficient was also below the generally accepted threshold of .70 (α = .68).

Burnout–Prison Social Climate Survey

The job burnout scale included six individual items from the work environment section of the Prison Climate Survey (Saylor et al., 1996) that asked about feelings of becoming harsh toward people since taking their job, worry that the job is emotionally hardening to themselves, emotionally drained at the end of the workday, treating some inmates as if they were objects, working with people all day is really a strain, and they feel fatigued when get up in morning. Response options were on a Likert-type Scale ranging from 1 (never) to 7 (all the time) and the average of all six items was computed prior to analysis. Internal consistency of the burnout measure was high (α = .85).

Analytic Strategy

All analyses were conducted in version 3.4.3 of the R environment (R Development Core Team, 2013). Descriptive statistics, mean values, and standard deviations were calculated for all continuous measures. All bivariate relationships were in the expected direction, and a correlation matrix of study variables was computed (Table 1). Issues associated with common method variance were investigated prior to conducting primary analyses.¹

Table 1.

Mean, Standard Deviations, and Zero-Order Correlations.

	M (SD)	1	2	3	4	5	6	7
1. Depression	7.58 (4.86)	.73	−.15*	−.51***	−.54***	−.35***	.50***	−.36***
2. Age	43.33 (11.40)	−.15**	−	−.09	−.01	.09	−.17**	.02
3. PROMIS physical health	47.01 (7.29)	−.50***	−.10*	.62	.57***	.21***	−.34***	.23***
4. PROMIS mental health	47.24 (7.82)	−.54***	−.01	.57***	.75	.32***	−.33***	.39***
5. Psychological well-being	4.86 (0.77)	−.35***	.08	.22***	.34***	.68	−.20***	.37***
6. Job burnout	3.06 (1.45)	.50***	−.18**	−.33***	−.33***	−.19**	.85	−.21***
7. Emotional support	15.86 (4.05)	−.36***	.03	.23***	.41***	.39***	−.21***	.91

Note. Lower diagonal: bivariate relationships of imputed data. Upper diagonal: bivariate relationships of observed data with pairwise deletion. Mean values and SD calculated for observed data. Observed α on diagonal where appropriate. PROMIS = Patient-Reported Outcomes Measurement Information System. Figures in italics indicate standard deviation values.

p < .05. **p < .01. ***p < .001.

Removing cases via listwise deletion would remove 14.1% of cases from the sample which is outside the cutoff at which missingness could be ignored (≤5%), suggested by Bennett (2001). After investigating any patterned missingness in the data,² multiple imputations by chained equations were employed³ utilizing the “mice” package (van Buuren & Groothuis-Oudshoorn, 2011).

Following imputation, a hierarchical regression was then conducted to test Hypotheses 1 to 3 to determine the relationship between vulnerabilities, job burnout, and emotional support to depression. Demographic variables were entered in the first block (age, ethnicity, and gender). Indicators of physical health were entered in the second block (PROMIS GPH measure, hypertension diagnosis, and back or spine disease). Next, indicators of mental health were entered in the third block (psychological well-being and PROMIS GMH measure). Finally, burnout was entered into the final block. Overall model significance was reviewed at each step as well as chi-square tests for nested models and ΔR² to understand the incremental contribution of variables added at each step to the overall model. Hierarchical regression was preferred over structural equation modeling as the focus of the study is on the incremental contribution of various indicators after controlling for preceding variables. In addition, given the focus on corrections-related employees, the sample size would not produce stable estimates given the number of parameters in the model (Anderson & Gerbing, 1988). Finally, to test the moderating influence of perceived emotional support on the relationship between burnout and depression, hierarchical regression was again utilized, by which depression was regressed onto the interaction of burnout and perceived emotional support.

Results

Descriptives and Prevalence

Descriptive statistics are presented in Table 2. Participants’ age was evenly distributed from early employment at 18 years to nearing mandatory retirement age of 60 years. The majority of participants were female (52%), African American or Black (78%), and frontline correctional officers/deputies (79%).

Table 2.

Demographic Characteristics of Jail Officers and CES-D-10 Depression Scores (N = 320).

	Total N
Variable	N	%
Gender (n = 317)
Female	166	52.37
Male	151	47.63
Age (n = 314)
18–30	50	15.92
31–40	76	24.20
41–50	94	29.94
51–60	73	23.25
>60	21	6.69
Ethnicity (n = 320)
African American, Black, and Other	251	78.44
European Descent and White	69	21.56
Job Category (n = 320)
Jail Deputy/Correctional Officer	253	79.06
Supervisor	63	19.69
Unspecified	4	1.25
Years employed (n = 315)
<1	30	9.52
1–5	87	27.62
6–10	68	21.59
11–15	57	18.10
>15	73	23.17
Education (n = 319)
High school	69	21.63
Some college	133	41.69
College degree	94	29.47
Graduate degree	23	7.21
Depression CES-D-10 (N = 320), >10, depressed	100	31.25
PROMIS mental health (N = 313), <50, less healthy	209	66.77
Psychological well-being (N = 313), <5, low	152	48.56
PROMIS physical health (N = 318), <50, less healthy	206	64.78
Musculoskeletal/low back or spine disease (N = 309)	34	11.00
Hypertension/high blood pressure (N = 316)	61	19.30

Note. Center for Epidemiologic Studies Depression Scale 10-item short form (CES-D-10) with clinical cutoff score of greater than 10 as depressed and less than 10 as not depressed; Patient-Reported Outcomes Measurement Information System (PROMIS) with clinical cutoff score of greater than 50 is healthy and less than 50 is less healthy.

In terms of health status, results indicated that about a third of the sample (31%) met clinical cutoff scores for depression. Diagnosed conditions were less prominent for hypertension (19%) and back/spine (10%). Findings also revealed that 66% of global physical and mental health scores were lower (less healthy, <50) when compared with the general population norms.

Predictors

The results of this analysis are shown in Table 3. In the first step of the model, age (B = −0.08) was significantly related to depression while ethnicity and gender were not. As age increased, depression decreased. The next step introduced three indicators of physical health. PROMIS GPH (B = −0.97) and a diagnosis of hypertension (B = 1.51) were significantly related to depression after controlling for variance attributed to demographic characteristics while a report of back or spine disease was not significant, partially supporting Hypothesis 1. As physical health increased, depression decreased, and having a hypertension diagnosis was related to higher levels of depression.

Table 3.

Multiple Imputed (m = 5) Hierarchical Regression.

	DV: Depression
	B	CI	B	CI	B	CI	B	CI
(Intercept)	6.62***	[5.42, 7.82]	6.47***	[5.34, 7.60]	6.31***	[5.26, 7.35]	6.58***	[5.56, 7.61]
Age	−0.08**	[−0.13, −0.03]	−0.11***	[−0.15, −0.06]	−0.09***	[−0.13, −0.05]	−0.07**	[−0.11, −0.03]
Ethnicity^a	0.59	[−0.81, 1.99]	0.75	[−0.46, 1.96]	0.84	[−0.27, 1.95]	0.88	[−0.18, 1.93]
Gender^b	0.99	[−0.14, 2.12]	0.12	[−0.86, 1.11]	0.42	[−0.50, 1.35]	−0.10	[−0.99, 0.80]
Global physical health			−0.97***	[−1.16, −0.78]	−0.55***	[−0.77, −0.34]	−0.45***	[−0.65, −0.24]
Hypertension diagnosis^c			1.51*	[0.32, 2.69]	1.24*	[0.16, 2.33]	1.20*	[0.17, 2.24]
Back/spine Disease^d			1.25	[−0.30, 2.79]	1.06	[−0.36, 2.47]	0.79	[−0.66, 2.23]
Psych well-being					−1.12***	[−1.71, −0.53]	−0.94**	[−1.51, −0.37]
Global mental health					−0.47***	[−0.64, −0.29]	−0.39***	[−0.56, −0.23]
Job burnout							0.94***	[0.62, 1.26]
R² (ΔR²)	.038		.320 (.282)		.428 (.108)		.489 (.061)
Δχ²			41.06***		27.61***		33.03***

Note. Continuous predictors are mean-centered. CI = 95% confidence interval. Δχ² calculated with Wald statistic. N = 320. Ethnicity, gender, hypertension diagnosis, and back/spine disease are categorical predictors while the remaining predictors are treated as continuous.

Ethnicity: 0 = White/Caucasian, 1 = African American, Black, & Other. ^bGender 0 = Male, 1 = Female. ^cHypertension diagnosis: 0 = No diagnosis, 1 = Diagnosis. ^dBack/spine disease 0 = No diagnosis, 1 = Diagnosis.

p < .05. **p < .01. ***p < .001.

Indicators of mental health were included in the third step. Reports of psychological well-being (B = −1.12) and the PROMIS GMH (B = −0.47) were both significant predictors of depression after controlling for the variance attributed to both demographic and physical health indicators supporting Hypothesis 2. Increased mental health and psychological well-being resulted in decreased depression. Perceptions of burnout were included in the final step. Burnout was a significant predictor of depression (B = 0.94) after controlling for the variance attributed to all preceding variables supporting Hypothesis 3. An increase in burnout resulted in an increase in depression. The overall model accounted for 49% of variance in depression. Job setting, job category, tenure, and education were entered as variables in earlier models and were found to be nonsignificant. In an effort to refine this model and improve interpretation of each model step, these variables were removed from the final model.

Emotional Support

The results of the moderation analysis are shown in Table 4. The overall model was found to be significant and accounted for 33% of variance in depression. A main effect of both burnout (B = 1.48) and emotional support (B = −0.32) on depression was found. The interaction of burnout and emotional support was not significant, suggesting that emotional support was not a significant moderator on the relationship between burnout and depression. Therefore, Hypothesis 4 was unsupported, where emotional support does not moderate the relationship between burnout and depression.

Table 4.

Multiple Imputed (m = 5) Conditional Effect of Emotional Support on Depression (N = 320).

	DV: Depression
	B	SE	CI
(Intercept)	7.51***	0.24	[7.04, 7.98]
Job burnout	1.48***	0.16	[1.16, 1.80]
Emotional support	−0.32***	0.06	[−0.44, −0.20]
Job Stress × Emotional Support	−0.02	0.04	[−0.10, 0.06]
R ²		.327

Note. Predictors are mean-centered. CI = 95% confidence interval.

p < .05. **p < .01. ***p < .001.

Discussion

Jail-based correctional officers are an important yet understudied population in the criminal justice system. Informed by diathesis–stress theory, this study explored the prevalence and predictors of depression among jail officers working in Midwestern U.S. jails. We controlled for a variety of demographic characteristics, and all but one of our study hypotheses were supported. Results contribute to four main conclusions. First, nearly one third of our sample experienced depressive symptoms, indicating a high prevalence of depression among the jail officer workforce. Second, age was a significant predictor of depression, indicating an inverse relationship where increased age was correlated with decreased depression. Thus, the older the jail officer was, the less likely the individual was experiencing symptoms of depression. Third, indicators of GPH, GMH, and psychological well-being were significant inverse predictors of depression, meaning that these factors also imbued consequences for the jail officer’s mental health. Fourth, job burnout was a significant predictor of depression over and above demographic variables and indicators of physical and mental health. Unexpectedly, emotional support was nonsignificant for moderating the relationship between the predictors and depression. This study contributes to the needed jail workplace health literature and indicates a need for identifying solutions for reducing job stress and depression risks, especially influential when physical and/or mental health issues are also present.

The results of this study confirm that jail officers, like prison officers, experience depression and related job stress. Depression among prison officers was also found to be prevalent at 31% (Obidoa et al., 2011) as compared with an estimated 9% for the general population (Vilagut et al., 2016). Given the high rate of depression among jail officers in this study, individuals who experience this mood disorder may also be at higher risk of attempting suicide (Isometsä, 2014), depression-related work disability (Ervasti et al., 2014), and concentration and sleep issues that could significantly affect an officer’s responsiveness to potentially dangerous situations. The significance of job burnout over and above the other vulnerabilities predicting depression supports the diathesis–stress model of multiplicative interactions found by Colodro-Conde et al. (2017). In line with previous findings, this study demonstrates that job stress is a major concern in correctional workplaces including jails (Bezerra et al., 2016). To this point, job burnout accounted for 6% of the variance in depression over and above all predictors.

With regard to age, the sample was relatively young, with two thirds of workers age 50 years or below, and more female than male officers. Most workers reported ethnicity in the African American/Black category (75%) following demographics of the geographic locations of the urban jail facilities that represented a larger portion of the study sample. Sixty percent of jail officers were employed for 10 years or less, supporting the known challenges of high turnover and relatively brief longevity of tenure in corrections work (Lambert et al., 2010).

Both physical and mental global health measures were found to predict depression where higher health was related to lower depression. Functional global health measures for physical and mental health were more significant in the model as compared with less person-centered diagnostic indicators of health such as back and spine pain. Indicators of physical health accounted for 28% of the variance in depression, demonstrating the strong relationship between physical health and this mood disorder. Surprisingly, low back musculoskeletal disease, reported by 10% of jail officers, was not associated with depression, but this may be related to statistical power. Further research exploring work tasks and exposure to activities such as altercations and critical incidents may assist to explain musculoskeletal vulnerabilities within corrections work tasks as compared with exposures found in manufacturing, hospital, construction, or other work sectors (Dale et al., 2016; Dennerlein et al., 2017).

The current trend of criminal justice reform is to reduce incarceration, improve humane treatment of justice-involved people, prevent recidivism, and decrease costs. One way to contribute to reform is to reshape the way that we treat the corrections workforce and people residing in jail facilities. We know that job stress is a precursor to job burnout, which leads to turnover of correctional staff and costly burdens to facility operations (Lambert et al., 2015). Results from this study indicate positive health attributes have an inverse relationship and job stressors have a negative relationship to depression. Interventions that improve morale, encourage resilience (Leitch, 2017), and promote positivity are examples that could be applied across facilities to have an impact on workers and resident experiences in correctional settings. Building a culture toward mental health awareness, convenient and private access, and use of resources is imperative among these law enforcement personnel who have historical low rates of treatment seeking.

This study utilized a general measure of correctional job burnout, with items exploring stress related to people incarcerated, personal psychosocial, and concerns of emotional changes in themselves as a result of the job, similar to constructs suggested by Brower (2013). However, future research should employ broader measures of correctional job stress, and subdomains should be utilized in health outcomes research to parse through specific issues about the workplace environment, co-worker dynamics, policy, outside community, media, compensation, and other potential stressors. Some studies have described categories of stressors to explore corrections work (Finney et al., 2013; Mahfood et al., 2013), and more detailed descriptors of sources of job stress are needed to inform research and interventions. By “peeling the onion,” workplace health interventions can be specifically tailored to the stressors related to mental health issues such as depression, and, furthermore, design locally relevant workplace solutions.

Few solutions tested for the remediation of job stress in corrections work exist, especially those specific to jails. There are job stressors in the correctional environment that may be more difficult to reshape than others. For instance, access to healthy food options during the work shift can be addressed relatively easily while elimination of verbal abuse from an incarcerated person (resident) many not be possible. However, stressors contributed by residents could potentially be reduced by improving the jail environment for everyone, offering skills training for jail officers to work with residents rather than promote a cycle of punitive treatment, and introducing meaningful occupations (e.g., activities) for both officers and residents to contribute to rehabilitation and occupational justice (Durocher et al., 2014), not punishment. Prisons and jails operate differently as do rural and urban facilities (Applegate & Sitren, 2008), and their local attributes must be taken in to consideration for tailored interventions.

Strategies suggested for coping with job stress include instruction of behavior change through training, social support, and psychological care. These strategies mostly rely on worker-led change and lack macro-level initiatives for workplace policy, procedures, and environmental modifications (Bezerra et al., 2016). Corrections research suggests the need for studies that identify how stress is related to the individual and workplace, with strategies to involve both levels. This intuitive observation is supported by a strategy developed by the National Institute for Occupational Safety and Health (NIOSH) for the development of integrated research and workplace interventions that addresses a more holistic approach to job stress reduction among other occupational health risks (Schill, 2017).

Limitations

There are several limitations that must be considered for the interpretation of study results. This study employed a cross-sectional design limiting its generalizability to the larger correctional officer population, and no causal inferences can be made. A systematic review (Finney et al., 2013) found only cross-sectional studies of correctional officer health. However, we are aware of at least one longitudinal research project describing health issues and participatory interventions among prison officers (Cherniack et al., 2016). In response to this gap in jail workplace research, we have implemented an ongoing prospective, etiological study of jail officer health. Missing data could not be ignored for this sample, and multiple imputation by chained equations provided a robust method for measuring missing data at random. During the informed consent process, jail officers were educated on their risks as a research participant and that their individual data would remain confidential. However, even with a high rate of survey return, we learned that individual demographic characteristics were missing the most often from surveys, and this is a common risk with self-reported data. The sample was limited in comparing job stress of jail officers to other professions and populations. Aspects of workplace culture, features of the workplace, location of the jails, and internal policies and procedures may also impact the incidence of depression, and this was not explored within this study.

Conclusion

Described as the “toughest beat” in law enforcement, work as a prison officer is challenging (Lambert et al., 2015). Study of job stress in correctional work has an established history in prison research and now holds precedence in jail settings as well. This study described the high prevalence of depression among jail officers where job burnout, a result of job stress, was a significant predictor of depression even after controlling for demographics and mental and physical health characteristics. Job stress screening and evidence-informed health and safety interventions are needed to reduce and prevent depression among jail officers. Given the challenges posed by work-related stressors and the environment of incarceration, studies of correctional employee health are needed to inform new directions for jail facility reform. Future intervention research needs to address the predictors of depression and target specific types of job stress for workplace health promotion and protection with this at-risk population of public safety workers. Correctional workplace health promotion and protection within jail systems, is of particular importance in the United States.

Footnotes

Acknowledgements

The authors graciously thank the correctional officers, sheriff’s deputies, and jail facilities for their participation in the study. The authors are grateful for the assistance of the graduate students, Gregory Scheetz, Emily Bixler, and Saketh Nadimpalli, and staff who contributed to this research project.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a pilot project grant from the Healthier Workforce Center of the Midwest (HWC) at the University of Iowa. The HWC is supported by Cooperative Agreement No. U19OH008868 from the Centers for Disease Control and Prevention (CDC)/National Institute for Occupational Safety and Health (NIOSH). The contents are solely the responsibility of the author(s) and do not necessarily represent the official views of the CDC, NIOSH, HWC, or participating jails.

Notes

Author Biographies

Lisa A. Jaegers, PhD, is an assistant professor in the Saint Louis University Department of Occupational Science and Occupational Therapy and co-director of the Health Criminology Research Consortium. Her work focuses on health criminology, especially correctional workplace health promotion and participatory interventions to reduce and prevent incarceration.

Monica M. Matthieu, PhD, is an associate professor in the Saint Louis University School of Social Work. Her areas of interest include access to and quality of mental health services, public health and clinical approaches to suicide prevention, and evidence-based treatments for trauma, especially among veterans.

Paul Werth, MS, is a doctoral candidate in the Saint Louis University Program in Industrial-Organizational Psychology. His research interests include occupational health psychology and humanitarian work psychology, with a special focus on quantitative analysis and research methodology.

Syed Omar Ahmad, OTD, PhD, is a professor in the Saint Louis Department of Occupational Science and Occupational Therapy. His research areas include neurological disorders, mental stress, post-traumatic stress disorder, depression, and other diseases of the brain that have an impact on workers’ safety and health.

Ellen Barnidge, PhD, is an associate professor of Behavioral Science and Health Education, Saint Louis University. Her work focuses on the promotion of health behaviors through environmental and policy interventions in rural and urban settings.

Michael G. Vaughn, PhD, is a professor and director of the Health Criminology Research Consortium and director of the interdisciplinary doctoral program, Saint Louis University School of Social Work. His areas of expertise include health criminology, violence, and the epidemiology of drug abuse and mental health disorders. He is the author of over 350 peer reviewed articles and book chapters.

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Stressed Out: Predictors of Depression Among Jail Officers and Deputies

Abstract

Keywords

Introduction

Literature Review

Diathesis–Stress Theory

Current Study

Method

Program Details

Jail Sites, Participants, and Procedures

Measures

Dependent variables

Independent variables

Healthy Workplace All Employee Survey

PROMIS® Global Health v1.1

PROMIS® Emotional Support v2.0

Psychological well-being

Burnout–Prison Social Climate Survey

Analytic Strategy

Results

Descriptives and Prevalence

Predictors

Emotional Support

Discussion

Limitations

Conclusion

Footnotes

Acknowledgements

Declaration of Conflicting Interests

Funding

Notes

Author Biographies

References

PROMIS^® Global Health v1.1

PROMIS^® Emotional Support v2.0