Talking ‘Bout My Generation’

Abstract

Much of the literature regarding correctional officer job stress and job satisfaction has examined the roles of organizational and demographic variables. This study examined the relationships among generation, job stress, and job satisfaction of correctional officers in a southern prison system. Hierarchical multiple regression was used to assess the relative impact of demographic variables and generation on job stress and job satisfaction, as well as the impact that stress and satisfaction have on one another. Results indicate that generation membership and job stress significantly shape correctional officers’ perceptions regarding job satisfaction. Conversely, gender and job satisfaction significantly influence job stress. The authors recommend that further research on generational differences among correctional officers be undertaken to assess the overall impact that generation has on employee perceptions of correctional employment.

Keywords

correctional officer job stress job satisfaction generational differences

Stress within the correctional work environment is an inherent part of work life. As noted by Slate and Vogel (1997) and Lambert and Hogan (2007), job stress can be quite costly to an organization in terms of decreased productivity, employee turnover, health care, disability payments, sick leave and absenteeism. Much of the research on stress in the correctional environment has focused on role problems/role ambiguity, job dangerousness, and the nature of the work itself (Griffin, 2006; Lambert & Hogan, 2007; Lambert, Hogan, & Barton, 2002; Lambert, Hogan, & Griffin, 2007). Studies also point to the role that personal attributes or demographics play in stress among line personnel.

Correctional agencies, of course, are concerned about employee job stress and its effect on job turnover and burnout (Dowden & Tellier, 2004; Lambert et al., 2007; Slate, Vogel, & Johnson, 2001). Stress and job dissatisfaction have been linked to a variety of negative consequences, including poor job performance, mental and physical illness, strain in personal relationships, and premature aging and death (Cornelius, 1994). Conversely, job satisfaction and lower levels of job stress have been linked to positive results that include greater job participation and decreased feelings of role conflict (Grossi & Berg, 1991; Hepburn & Albonetti, 1980; Hogan, Lambert, Jenkins, & Wambold, 2006).

Many correctional environment elements contribute to job stress. For instance, Dowden and Tellier (2004) noted that work-related attitudes, demographics, and job characteristics were important variables in correctional officer stress. In addition, it can be argued that while the influence of age had been examined by many studies on correctional officer stress, age and generation are inherently different concepts. Age is a variable that is in a constant state of change. Generation, by contrast, is a constant. Once you are born into a particular generation you cannot change that, regardless of your current or future age. One might conclude that age is a demographic variable and that generation is, in fact, a cultural expression. For example, three out of five women in generation X surveyed at ages 25 to 34 were married, while four out of five ‘baby boomer’ women surveyed at ages 25 to 34 were married (DiNatale & Boraas, 2002). Although age at time of survey remained the same, responses between generations were different. While thoughts and feelings about life often change as one ages, generational attitudes are less prone to change (Smith, 2008). Therefore, if generation is a reflection of a set of values or attitudes, it may potentially have an impact on how an individual experiences and copes with stress. This has yet to be examined at length in criminal justice research.

This article seeks to add to what is known about correctional officer job stress and job satisfaction and assess the impact of generation membership on those perceptions of correctional employment. Utilizing hierarchical multiple regression, the research examines the relative importance of demographic factors (race, gender, marital status, and education) and generation membership on job stress and job satisfaction, as well as the impact of job stress and job satisfaction on one another.

Personal Characteristics

Correctional officers occupy a unique work environment. Employment within a correctional institution involves hostile “clients,” inherent job danger, shift work, and often mandatory or optional overtime (Glenn, 2001). Each individual brings certain characteristics or attributes to a job or organization. These features include one’s demographic identity (e.g., age, gender, race,), individual background (e.g., place of upbringing, education), current circumstances (e.g., marital status, children, years on the job,), and other attributes (e.g., total family income, commute to and from work, religion, values). These factors have an effect on an individual’s employment outlook as well as how they view their lives and community. A review of selected personal characteristics is presented below.

Race and Ethnicity

The majority of research on the influence of race and/or ethnicity on work stress has been inconclusive. Most studies suggest that there is a not a definitive national consensus, but rather that differences in perceptions of employment vary across regions of the United States (Cullen, Link, Wolfe, & Frank, 1985; Griffin, 2006; Jurik & Halemba 1984; Lambert et al., 2002; Wright & Saylor, 1991). In 1991, VanVoorhis, Cullen, Link, and Wolfe found that Black officers were more likely to perceive the job as dangerous and found correctional work dissatisfying. Of those studies that found significant relationships between race and job satisfaction, nearly all were studies of Southern correctional staff (Lambert et al., 2002). As such, the influence of race on perceptions of satisfaction could be a function of culture or geography rather than racial identity. It also could also be argued that race relations have improved in recent years, given that much of the research noting job dissatisfaction among minority groups was conducted in the late 1970s and early 1980s. Current research indicates (at best) a minimal relationship between race and work stress (Lambert et al., 2002, 2007; Wright & Saylor, 1991).

Marital Status

While many studies have included marital status as a variable of interest in correctional officer stress, few studies have found it to be a significant predictor of job stress or job satisfaction. In addition, it could be argued that marital status is analogous to social support from friends and family. Cheek and Miller (1983) examined how social support systems affected correctional officer stress and burnout, and found that correctional officers experience family-related issues due to stress experienced in the workplace—such as high rates of family conflict and divorce. Cheek and Miller (1983) also noted that although correctional officers did not report experiencing problems at home, the rate of divorce for correctional personnel was two times that of other blue-collar workers. The stress of working in prison has a dramatic effect on correctional officers, and was seen as a root cause for family discord and/or higher divorce rates. Marriage, in essence, might either serve as a coping mechanism or become just another element of stress to the correctional officer. Additionally, Cheek and Miller’s (1983) study found that correctional officers frequently reported releasing tensions in the wrong places (i.e., at home), tightening discipline at home, and expressing the desire to spend less time at home on their days off. As such, correctional officers may find support in friendship relationships or from coworkers, lessening the effect of marital status on job stress. Given the ambiguity regarding marital status and its effects, relationships between correctional officer stress and job satisfaction may be difficult to detect.

Gender

The number of females working in correctional facilities has risen substantially over the past 35 years. Efforts to study and understand the effect women have on correctional institutions has also increased, as well as studies that assess the impact that gender has on correctional officer stress and job satisfaction (Cheeseman, Mullings, & Marquart, 2001; Horne 1985; Philliber 1987; Zimmer, 1986, 1987). Most of these studies have found little or no relationship between gender and job satisfaction. Jurik and Halemba (1984) noted that gender of correctional officers did not have a significant impact on job stress and that women tended to exhibit many of the same attitudes as their male counterparts. Research by Zimmer (1986) contradicts those findings, however, and concludes that women have higher levels of stress because they have little or no peer and supervisory support (in addition to work related stress). Camp and Steiger (1995) and Britton (1997) reported that female correctional officers had higher job satisfaction than their male counterparts.

Hemmens and Stohr (2000) found that sociodemographic characteristics such as gender and prior military service influence officers’ perceptions of their correctional roles. That is, women favor the human service side of correctional work more than men, and ex-military correctional officers favor the “hack” role of correctional work more than those who have not served in the armed forces. This research points to the fact that men and women see corrections work differently, and training might address how to create a more centered and balanced role-approach that is neither wholly ‘hack or human service.’ Female correctional officers, more often than men, cited this as a weakness of their correctional agency (Carlson, Anson, & Thomas, 2003). One study found that females in the 1990s were better able to adapt to prison settings because more than one fifth of the correctional officer guard force was female, compared with earlier studies done in the 1980s (Carlson et al., 2003).

Griffin (2006) examined gender and stress, comparing stress among male and female correctional officers, and assessed four broad sources of stress among correctional officers: organizational policies and practices, interpersonal relationships, safety, and balance between work and personal life. Contrary to expectations, the Griffin (2006) study found few differences between male and female officers on workplace stressor effects on levels of job stress. Work–family conflict proved to have the greatest impact on stress for both male and female officers. However, concerns regarding organizational support for equal treatment policies affected stress only among male officers (Griffin, 2006).

Education Level

Criminal justice reformers have historically suggested that education enhances professionalization of a workforce (e.g., Jurik & Musheno, 1986). This would ideally allow officers to have more positive interactions with supervisors, coworkers, and inmates, and could also facilitate officers’ abilities to deal more effectively with ambiguities and complexities inherent in the correctional work environment (Cullen et al., 1985). Grossi and Berg (1991) found that education was positively linked to job satisfaction. Five years later, however, additional research by Grossi, Keil, and Vito (1996) found that officers with higher levels of education were more likely to have high levels of job dissatisfaction.

Other studies have determined that correctional personnel who are educated experience more emotional and physical exhaustion than other personnel (Gerstein, Topp, & Correll, 1987). VanVoorhis et al. (1991) also found that the more educated the officer, the more likely he or she is to experience job dissatisfaction. They concluded that this could be a lack of social integration or due to frustrated career expectations. Educated officers may have higher expectations placed on them and, therefore, are more likely to experience work-related stress and job dissatisfaction. Research has also pointed to higher turnover rates among more educated correctional officers due to more employment alternatives (Jurik & Winn, 1987). Other research suggests that there is no conclusive link to education and stress level in correctional employment (Triplett et al., 1996).

Age and Generation

Interestingly, as with most demographic or personal characteristics, most studies find little or no relationship between age and job satisfaction (Camp & Steiger, 1995; Lambert et al., 2002). As such, employment experience is often used as a proxy representation of age. There are two differing opinions as to whether years in correctional employment affect job stress and satisfaction. One position notes that as correctional officers perform “dirty work” on a regular basis, they will eventually suffer from “burnout” (Cheek & Miller, 1983). The contrasting viewpoint suggests that job experience may function as a resource that helps officers cope effectively with the complexity and risks of prison life (Cullen et al., 1985). Given the difference between age and generation (as variable and constant), it seems logical to explore generation (rather than experience) as an alternative expression of age (given the inconclusive evidence regarding the relationships between age and job stress and job satisfaction).

Studies in work forces external to the criminal justice system have often assessed generational differences in perceptions of employment. Currently, there are four generations of workers present in the American workforce: (a) The mature, silent, or “veteran” generation, (b) baby boomers, (c) generation X, and (d) generation Y, also known as millennials (Hammill, 2005; Hollon, 2008; Lancaster & Stillman, 2002; Lovely & Buffam, 2007; O’Donovan, 2009; Patterson, 2007).

The “veteran” generation includes anyone born from 1922 to1943. According to Patterson (2007), members of this generation are more likely to hold traditional values and promote the status quo. This traditional thinking manifests itself in a strong work ethic and the belief that those in authority deserve respect (Hammill, 2005; Patterson, 2007). The “veterans” adhere to the rules, seek out formal communication, and often derive satisfaction in doing a job well (Hammill, 2005). This generation experienced the Great Depression, Pearl Harbor, and World War II, thus they are known for their values of hard work, fiscal conservatism, and traditional values of home, family, and patriotism (Lovely & Buffam, 2007; O’Donovan, 2009). For the purposes of this study, this generation is referred to as the “traditional” generation.

Baby boomers represent all those persons born between 1944 and 1964. Defining events to baby boomers include the Vietnam War and the Civil Rights movement. Baby boomers are more likely to challenge the status quo and make up their own rules (vs. “veteran” workers); they desire recognition and money as a reward for a job well done (Hammill, 2005; Lovely & Buffam, 2007; O’Donovan, 2009; Patterson, 2007). Baby boomers currently hold the majority of positions of power in corporations and government. Patterson (2007) noted that many baby boomers plan to retire later or stay in the workforce in some capacity for life. Additional business source literature concluded that due to the recent downturn in the economy, many baby boomers are holding on to jobs longer than before (Lovely & Buffam, 2007; O’Donovan, 2009).

Generation X is made up of individuals born between 1965 and 1980. According to Lovely and Buffam (2007), generation X lived in the shadow of the baby boomers and is shaped by excesses of the baby boomer generation. Generation X is skeptical of authority and often prefer to rely on themselves or members of their own generation (Hollon, 2008; Lancaster & Stillman, 2002). Generation X workers are more likely to embrace technology than previous generations and are much more likely than baby boomers to want balance in their personal and professional lives (Patterson, 2007). Generation X desires more feedback, and due to increased education levels, seek out rapid advancement.

Generation Y, or “Millennials,” were born from 1981 to present. These “digital natives” expect access to technology. They tend to communicate more readily, using text messages, social networking web sites (e.g., Facebook, MySpace, etc.), or email. They may prefer a more participatory work environment and desire feedback and rewards immediately (Hammill, 2005; Patterson, 2007). It has also been noted that these individuals are actually much like “traditionals” in terms of their optimism, confidence, respect for authority, and can do attitude (Lovely & Buffam, 2007). Less is known about this group, in general, as they are such a recent addition to the workforce.

While many in the business community have discussed the issue of a multigenerational workforce, relatively little criminal justice literature assesses whether or not generational differences affect criminal justice employee perceptions of the workforce. As such, it seems appropriate to examine potential generational impacts on employee perceptions of correctional employment.

Method

Procedures

Data for this study were gathered through surveys administered to correctional officers attending regional in-service training for a southern prison system. This region has 13 institutions that supervise offenders from all custody designations. Prison units include the facility that houses death row offenders as well as a high-security (Supermax) facility. The survey was administered seven times to various in-service training groups over a 3-month period. Subsequent to the survey’s administration, the primary author was available to answer participants’ questions. After all surveys had been collected, data were coded and entered into an SPSS database.

Sample

This study utilized a purposive sample of correctional officers required to attend the in-service training (those having 8 months of experience or more). The only qualification in sample selection (other than length of service) was that correctional officers must have had direct contact with inmates. No consideration was made to stratify for race or gender or any other demographic characteristic.

A total of 630 surveys were distributed, with 501 officers opting to respond (response rate of 79.4%). Given the requirements for in-service training, respondents reporting less than 8 months of service were excluded from the sample (n = 16). Respondents not reporting their age were also excluded (n = 14). As such, 471 respondents were retained for analyses. Table 1 presents the demographic characteristics of the final sample.

Table 1.

Demographic Characteristics

Variable	N	P
Race
White	316	67.1
Black	98	20.8
Hispanic	30	6.4
Other	23	4.9
No response	4	0.8
Gender
Male	314	66.7
Female	156	33.1
No response	1	0.2
Education
G.E.D./Diploma	194	41.2
Some college	220	46.7
College degree	46	9.8
Graduate school	8	1.7
No response	3	0.6
Marital status
Married	231	49.0%
Divorced	74	15.7%
Separated	14	3.0%
Single	144	30.6%
No response	8	1.6%
	Mean	SD
Age	38.1	12.9
Job stress	0.0	1.0
Job satisfaction	0.0	1.0

The sample is representative of the larger population of correctional officers employed at the correctional agency. Official statistics delineate the racial breakdown for the agency as 51.9% White, 28.2% Black, 18.8% Hispanic, and 1.1% Other (Texas Department of Criminal Justice [TDCJ-CID], 2006). The gender breakdown of “security” employees within the agency was 63.5% male and 36.5% female, and average age of security employees was 39.0 years (TDCJ-CID, 2006).

Dependent Variables

For the purposes of this study, the two dependent variables of interest (job stress and job satisfaction) were adapted from Cullen et al. (1985) and Triplett et al. (1996). Five items were used to assess job stress among correctional officers: (a) When I am at work I often feel tense or uptight; (b) A lot of times, my job makes me very frustrated or angry; (c) There are several aspects of my job that make me upset about things; (d) I am usually calm and at ease at work; and (e) I don’t consider this to be a stressful job. Officers responded to each item using a 5-point Likert-type scale (1 = strongly disagree to 5 = strongly agree). Items (d) and (e) were reverse-coded to cross-check responses. Factor analysis was then used to generate standardized scores for job stress (M = 0, SD = 1). Reliability analysis indicated that the items were internally consistent (Cronbach’s α = .777).

An additional five items were used to assess job satisfaction among correctional officers. These items and their responses included (a) All in all how satisfied would you say you are with your job? (1 = Not at all satisfied, 2 = Not too satisfied, 3 = Somewhat satisfied, 4 = Satisfied); (b) If you were free to go to any type of job you wanted, what would your choice be? (1 = Prefer some other job to what I have now, 2 = Retire and not work at all, 3 = Keep my present job); (c) Knowing what you know now, if you had to decide all over again whether to take the job you now have, what would you decide? (1 = Definitely not take this job, 2 = Have second thoughts about taking this job, 3 = Decide without hesitation to take the same job); (d) How well would you say this job measures up to the sort of job you wanted when you took it? (1 = Not very much like the job I wanted, 2 = Somewhat like the job I wanted, 3 = Very much like the job I wanted); and (e) If a good friend told you they were interested in working in a job like yours what would you tell them? (1 = Advise them against taking the job, 2 = Have doubts about recommending the job, 3 = Strongly recommend the job). Factor analysis was then used to generate standardized scores for job stress (M = 0, SD = 1). Reliability analysis indicated that items measuring satisfaction was also internally consistent (Cronbach’s α = .812).

Independent Variables

As shown in Table 1, respondents indicated their gender, race, educational status, marital status, and age in the demographic portion of the instrument. Overall, the sample was largely comprised of males (66.7%, n = 314). In addition, most correctional officers reported their race as White (67.1%, n = 316). Education levels were reported as G.E.D./graduated high school (41.2%, n = 194), some college (46.7%, n = 220), college degree (9.8%, n = 46), and graduate school (1.7%, n = 8). Three respondents (0.6%) failed to report their education. Marital status was reported as married (49.0%, n = 231), divorced (15.7%, n = 74), separated (3.0%, n = 14), and single (30.6%, n = 144). Eight respondents (1.6%) did not report their marital status. Respondents’ ages ranged from 18 to 80 (M = 38.1, SD = 12.95).

Prior to analyses, age was used to compute respondents’ generational membership. Generations included (a) traditionals (or veterans)—born from 1922 to 1943 (15.2%, n = 15), (b) baby boomers—born from 1944 to 1964 (37.2%, n = 175), generation X—born from 1965 to 1980 (42.9%, n = 202), and generation Y—born from 1981 to present (16.8%, n = 79; Hammill, 2005; Hollon, 2008; Lancaster & Stillman, 2002; Lovely & Buffam, 2007; O’Donovan, 2009; Patterson, 2007). In addition, categorical variables were dichotomized to allow for entry into regression models. Race was coded as (0) White and (1) non-White, education was coded as (0) no college and (1) some college/degree, and marital status was coded as (0) not married and (1) married. Generation was dummy coded to reflect membership in a particular category (0 = no, 1 = yes), with generation X excluded from the model as the reference category.

Results

Prior to estimating the models regarding job satisfaction and job stress, an intercorrelation matrix was generated to examine bivariate relationships among all dependent and independent variables to be included multivariate models. In addition, relationships of considerable strength between independent variables were examined to assess possible instances of multicollinearity (see Table 2).

Table 2.

Intercorrelation Matrix

Variable^a	1	2	3	4	5	6	7	8	9	10
1. Job stress	1.000
2. Job satisfaction	−0.421**	1.000
3. Race	−0.014	−0.077	1.000
4. Gender	0.148**	−0.007	0.131**	1.000
5. Marital status	−0.026	0.029	−0.094*	−0.215**	1.000
6. Education	−0.026	0.045	0.006	−0.001	−0.031	1.000
7. Generation Y	0.018	−0.010	0.115*	0.094*	−0.309**	0.034	1.000
8. Generation X	0.085	−0.222**	0.130**	−0.007	0.022	–0.011	−0.389**	1.000
9. Baby boomer	−0.068	0.167**	−0.180**	−0.029	0.221**	–0.010	−0.345**	−0.666**	1.000
10. Traditional	−0.092*	0.186**	−0.122**	−0.102*	−0.010	–0.014	−0.081	−0.157**	−0.139**	1.000

Race (0 = White, 1 = non-White); Gender (0 = male, 1 = female); Marital status (0 = not married, 1 = married); Education (1 = no college, 1 = some college/degree); Generation Y (0 = no, 1 = yes); Generation X (0 = no, 1 = yes); Baby boomer (0 = no, 1 = yes); Traditional (0 = no, 1 = yes).

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

As displayed in Table 2, job stress was significantly correlated with job satisfaction (r = –.421, p < .001), gender (r = .148, p < .01), and membership in the traditional generation (r = –.092, p < .05). Job satisfaction was significantly correlated with membership in generation X (r = –.222, p < .001), membership in the baby boomer generation (r = .167, p < .001), and membership in the traditional generation (r = .186, p < .001). There was a particularly strong relationship between membership the baby boomer generation and generation X (r = .666, p < .001), indicating that multicollinearity could be an issue in multivariate models. However, as stated previously, generation X was excluded from the model as the reference category. In addition, diagnostics (tolerance and VIF coefficients) indicated that multicollinearity was not a problem. As such, the models were estimated as planned.

Two hierarchical multiple regression models assessing impacts of demographic characteristics (Model 1), generation (Model 2), and job satisfaction/job stress (Model 3) were estimated for the dependent variables (see Tables 3 and 4). Hierarchical multiple regression is advantageous in that it allows for examination of explained variance in the dependent variable after inclusion of additional independent variables at multiple stages in the model (Field, 2005). As such, the relative impact of demographic characteristics, generation, job satisfaction, and job stress can be assessed by examining the significance of the change in R² at each step of the model. Given the fact that the impact of each independent variable at each stage of the model is of primary interest, only standardized coefficients (β) and t values are reported for individual independent variables.

Table 3.

Job Satisfaction—Hierarchical Multiple Regression Model

	Model 1		Model 2		Model 3
Variable	β	t	β	t	β	t
Constant	—	0.04	—	−2.61**	—	−2.71**
Race	−.072	−1.53	−.020	−0.44	−.044	−1.02
Gender	.016	0.34	.025	0.54	.081	1.89
Marital status	.035	0.74	.019	0.39	.019	.43
Education	.047	1.00	.048	1.06	.038	.91
Generation Y			.083	1.66	.074	1.61
Baby boomer			.216	4.33**	.176	3.85**
Traditional			.214	4.60**	.179	4.20**
Job stress					−.401	−9.56**
Model fit	F = 1.00		F = 5.42**		F = 17.10**
	R² = .009		R² = .077		R² = .232
	ΔR² = .009		ΔR² = .068**		ΔR² = .155**

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

Table 4.

Job Stress—Hierarchical Multiple Regression Model

	Model 1		Model 2		Model 3
Variable	β	t	β	t	β	t
Constant	—	0.38	—	0.74	—	0.43**
Race	−.034	−0.73	−.058	−1.21	−.066	−1.53
Gender	.144	3.03**	.141	2.95**	.151	3.47**
Marital status	−.011	−0.23	.001	0.03	.009	0.20
Education	−.025	−0.54	−.026	−0.56	−.006	−0.14
Generation Y			−.024	−0.46	.011	0.24
Baby boomer			−.100	−1.96	−.009	−0.19
			−.088	−1.84	.002	0.05
Job satisfaction					−.419	−9.56**
Model fit	F = 2.58**		F = 2.36**		F = 13.89**
	R² = .022		R² = .035		R² = .197
	ΔR² = .022**		ΔR² = .013		ΔR² = .162**

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

Table 3 indicates that demographic variables entered in Model 1had no significant impact (F = 1.00, p > .05) and explained little variance (R² = .009) in the dependent variable job satisfaction. Generation categories were included in Model 2, and did significantly affect job satisfaction (F = 5.42, p < .01) when controlling for demographic characteristics in Model 1. In addition, generation variables explained an additional 6.8% of the variance in job satisfaction, significantly increasing the explanatory power of the model (ΔR² = .068, F = 11.21, p < .05). Membership in both baby boomer (β = .216, p < .01) and traditional (β = .214, p < .01) generations increased job satisfaction.

Model 3 included job stress, generation variables, and demographic characteristics. This model was also significant (F = 17.10, p < .01), and explained the greatest portion of variance in job satisfaction (R² = .232). The addition of job stress also significantly increased the explanatory power of the model (ΔR² = .155, F = 91.30, p < .05). Membership in baby boomer (β = .176, p < .01) and traditional (β = .179, p < .01) generations continued to positively influence job satisfaction in Model 3, but job stress was identified as the most powerful factor in the model (β = –.401, p < .01). The final iteration of the model regarding job satisfaction indicates that older generations and correctional officers experiencing less job stress will report greater job satisfaction when controlling for race, gender, marital status, and education.

Table 4 depicts the results of a hierarchical multiple regression model with job stress as the dependent variable. Demographic characteristics included in Model 1 did have a significant impact on job stress (F = 2.58, p < .01) and explained 2.2% of the variance in the dependent variable (R² = .022). Gender (β = .144, p < .01) was the only specific significant variable in the model. Model 2 included generation categories and demographic characteristics and remained significant (F = 2.36, p < .01). Although the addition of generation categories did increase the explained variance in job stress (R² = .035), it did not significantly increase the explanatory power of the model (ΔR² = .013, F = 2.04, p > .05). Gender (β = .141, p < .01) remained the only significant variable in Model 2.

Model 3 included job satisfaction, generation categories, and demographic characteristics, and remained significant (F = 13.89, p < .01). The inclusion of job satisfaction significantly increased the explanatory power of the model (ΔR² = .162, F = 91.30, p < .05), which accounted for 19.7% of the variance in the dependent variable job stress (R² = .197). Gender (β = .151, p < .01) was still a significant factor affecting job stress in Model 3; however, job satisfaction (β = –.419, p < .01) was the most influential variable. The final iteration of this model indicates that female correctional officers with low levels of job satisfaction will report greater job stress when controlling for race, marital status, education, and gender.

Discussion

Relatively little research has been conducted on the impact that generation has on perceptions of employment in criminal justice, including corrections. Results of our analyses point to the importance of generation on perceptions of job satisfaction and the importance of gender on job stress. It should be noted that the relative impacts of job stress and satisfaction on each other were the strongest in both hierarchical multiple regression models. Although it may seem intuitive to assume that these variables would be related, there are clear differences in the personal characteristics of correctional officers affecting each dependent variable. For job satisfaction, generation is important. For job stress, gender is important. As such, increasing job satisfaction is not merely dependent on decreasing job stress—but rather decreasing job stress among female correctional officers. Conversely, decreasing job stress is not solely dependent on increasing job satisfaction—but rather increasing satisfaction in younger generations of correctional officers. Interestingly, race, marital status, and education did not significantly affect job stress or job satisfaction at any point in either hierarchical model.

With the onset of more female staff present in male correctional institutions, women may still be facing unique challenges. This research supported the notion that women may still be struggling in an organization that was created by men for male workers (Acker, 1992). Female characteristics (i.e., compassion, family orientation) might be perceived as undervalued in a correctional environment where notions of “toughness” and physical strength are respected. As noted by Farkas (1999), men and women have unique styles of handling offender supervision. The males in Farkas’ (1999) study indicated that women were far more lenient and less aggressive, while women viewed their approach as more service oriented. While the Farkas study was not aimed at assessing stress in correctional officers, it did point to potential differences between males and females and the way in which they perceive stress in their work environments. These differences might cause women to feel pressure to conform to job characteristics as viewed by their male counterparts.

This coping mechanism was noted by Acker (1992) as a means of women adapting to a work environment so they could fit into a male-dominated subculture. While Carlson et al. (2003) found women derived greater satisfaction and a sense of purpose from their employment, it may come at a price. Farkas (1999) concluded that women were still in need of assistance in becoming fully integrated into a male-dominated environment. Essentially, as noted by Britton (2003), women are still facing barriers to promotion and supervisory positions. Women may also be perceived by supervisors as individuals who cannot be trusted either due to their family obligations or a perception on the part of supervisors that they will be absent more than male officers, even if this is not the case (Lambert & Hogan, 2007; Lambert, Jiang, & Hogan, 2008).

Individuals who are part of the younger X and Y Generations are far more likely to be dissatisfied with their job as correctional officers than older members of the baby boomer or traditional generations. As more and more individuals from the generation Y enter the correctional workforce, it will be important to understand what motivates these younger employees. In addition, the needs of workers of every generation should be considered by management and administration in developing retention strategies and increased job satisfaction. Solutions used by business and industry may shed insight into how to effectively manage and motivate workers of all four generations who work in correctional institutions in an effort to increase job satisfaction for all employees.

Patterson (2007) points to strategies that employers can use to increase productivity and job satisfaction across all generations. Correctional agencies may need to provide more flexibility for individual preferences and technological support. While this may be more easily achieved in a traditional work environment, correctional agencies could still foster flexibility by offering compressed work schedules (i.e., 4 10-hr days vs. 5 8-hr days). Furthermore, correctional agencies could implement correctional officer taskforce teams with diversity of gender, race, and generation to work together to generate ideas about ways to improve working conditions and promote positive peer support (Dial & Johnson, 2008). In addition, correctional institutions usually employ a top-down style of leadership based on a chain of command model. As agencies continue to face issues in hiring and retaining correctional officers, correctional managers might consider using a more participatory style of leadership and management so that generation X and Y workers’ needs and values are considered.

This study is exploratory in nature; therefore, further research on the elements involved in generation, job satisfaction, and job stress would benefit not only correctional agencies but also other criminal justice agencies. Path modeling might also be a way that can better unravel how these factors affect correctional officers’ employment experiences. Although examination of post hoc assumptions regarding multivariate normality (e.g., normally distributed and independent error terms) did not reveal any problems, this study does have some limitations. First, our research was conducted in a southern prison system. The results of this study are important but may not be generalizable to all regions of the United States. A study that incorporates other regions of the United States and compares generational differences would be an important addition to the literature. Also, the use of a purposive sample excluding correctional officers with less than 8 months of service may have affected our results. New employees may provide information that could be critical in retaining employees, and prove useful in assessing what generations are being drawn to work in the correctional field. Limitations aside, the empirical findings have potential policy implications.

Corrections is a “people business” that often requires intense and frequent interactions with offenders. The synergistic effects of stressors associated with working in corrections are exhibited in a variety of physical and mental symptoms. Correctional executives and first-level supervisors who ignore these effects will inevitably be faced with lower levels of employee morale and higher levels of employee absenteeism, health concerns, and turnover. It should also be noted that stress and satisfaction in the workplace are multifaceted and complex constructs. To imply that generation and gender are the only variables of importance would be an overstatement. They are, however, an important piece of the puzzle that must be addressed if correctional agencies wish to reduce stress in their employees and increase job satisfaction (thereby increasing retention rates).

Footnotes

Acknowledgements

The authors gratefully acknowledge the assistance and support of countless Texas Department of Criminal Justice—Institutional Division employees for making this research possible. The authors also acknowledge the valuable input of staff at local prison units.

This research was coordinated in part with the Texas Department of Criminal Justice (Research Agreement No. 236-R99). This does not imply the Department’s endorsement or concurrence with statements or conclusions contained therein.

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

The authors received no financial support for the research, authorship, and/or publication of this article.

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