When Domains Spill Over

Abstract

Life is filled with the demands of work and family. When conflict exists in one domain, research indicates it can spill over and affect the other. In corrections, many workplace factors have been shown to affect the organizational commitment of staff. As staff are the most valuable resource in this labor intensive field, this study focused on the effects of two types of organizational commitment (affective and continuance) on three work–family conflict variables (time based, strain based, and behavior based). Using ordinary least squares regression analysis of survey data from 160 correctional staff at a Midwest private prison, the results indicated that as affective commitment rises, all three work-on-family conflict variables decreased. Conversely, when continuance commitment rose, all three work-on-family conflict variables increased as well. Surprisingly, both forms of commitment had nonsignificant associations with family-on-work conflict. The only significant control variable was age, which revealed that older staff had less conflict between work and family.

Keywords

correctional staff private prison personnel organizational commitment affective commitment continuance commitment work–family conflict

The two major domains in the lives of most working adults are work and home (Michel, Kotrba, Mitchelson, Clark, & Baltes, 2011). In an ideal world, these two domains coexist without conflict. In the real world, however, problems and issues in one domain can spill over and cause conflict in the other. The literature refers to this phenomenon as work–family conflict (Brough & O’Driscoll, 2005). According to the scarcity model of personal resources, when too many demands are placed on a person, he or she will likely suffer from resource depletion, and this, in turn, can lead to work–family conflict (Gordon, Whelan-Berry, & Hamilton, 2007). In addition, work–family conflict is a bidirectional concept. Problems at work can follow employees home and cause conflict; likewise, problems at home can spill over and cause problems at work (Griffin, 2006; Triplett, Mullings, & Scarborough, 1999). Correctional staff can and do experience work–family conflict.

There is a growing body of literature on correctional staff work–family conflict, but it has mainly focused on the outcomes of work–family conflict. Work–family conflict has been linked with lower job satisfaction and life satisfaction, as well as decreased support for treatment of inmates and increased work stress and job burnout among correctional staff (Lambert & Hogan, 2009, 2010; Lambert, Hogan, & Barton, 2003; Lambert, Hogan, Paoline, & Baker, 2005). If left unchecked, work–family conflict can lead to mental and physical health problems (Allen, Herst, Bruck, & Sutton, 2000; Greenhaus, Allen, & Spector, 2006). These problems are ultimately paid for by the employee and the employing organization. There has been far less research on the possible antecedents of work–family conflict for correctional staff. For the benefit of both correctional staff and prisons, there is a need to examine how workplace factors may be linked to work–family conflict. Organizational commitment may be one of these workplace factors. Organizational commitment is the bond an employee forms with the employing organization. How the bond forms and the type of bond varies (Meyer & Allen, 1984). Affective and continuance commitment are two forms of organizational commitment (Allen & Meyer, 1990). This study examined the possible relationships of these two forms of organizational commitment with four different types of work–family conflict (time-based, strain-based, behavior-based, and family-on-work conflict).

Literature Review

In this section, definitions of work–family conflict and organizational commitment, including the different types and forms of each, are provided. These definitions provide a foundation for understanding these concepts, why they are important in the field of corrections, and how they are related to one another. Also reported in this section are relevant findings of past correctional studies. A review of these studies helps clarify the knowledge gaps in this important area, including what is known and not known.

Work–Family Conflict

According to Greenhaus and Beutell (1985), work–family conflict occurs when work and family roles are incompatible in some manner. Simply put, work–family conflict occurs when work and home roles spill over and cause conflict for a person (Buonocore & Russo, 2012). Work–family conflict is grounded in the role conflict theory developed by Kahn et al. (1964), which holds that if roles in the major domains of a person’s life are in agreement, then conflict is less likely. Early work in this area treated the conflict as being a one way process from work to home (Allen et al., 2000). Later work, however, expanded this premise and proposed that the conflict can go in both directions (i.e., work–family conflict can spill over from work to home or vice versa; Brough & O’Driscoll, 2005). When work issues and problems spill over and cause problems and interference at home, this form of work–family conflict is referred to as work-on-family conflict (Michel et al., 2011).

Work-on-family conflict can be divided into several types. The literature indicates the three major types of work-on-family conflict are time-based, strain-based, and behavior-based conflict (Netemeyer, Boles, & McMurrian, 1996). Time-based conflict refers to work time requirements that detract from a person’s life and cause conflict (Buonocore & Russo, 2012). Time-based conflict may arise when work issues (e.g., shift changes, unexpected overtime, inflexible work schedules) interfere with family interactions, events, emergencies, etc. (Byron, 2005). Prison staff are needed 24 hr a day, 7 days a week, and 52 weeks a year, including holidays. In addition, staff may be required to work unexpected overtime, and staff often need to schedule leave far in advance. This can lead to time-based conflict for some staff. Even in a well-managed prison, the time demands on staff can occasionally feel excessive; in poorly managed ones with inordinate use of mandatory overtime, the extreme time demands can place considerable stress on staff.

Strain-based conflict may arise when problems, issues, and events at work follow the person home, causing conflict at home and decreased interactions with family and friends (Byron, 2005). This type of work–family conflict usually occurs when the demands, problems, and tensions from work negatively impact the quality of a worker’s home life. As noted by Brough and O’Driscoll (2005), negative emotions resulting from work can cause strain-based conflict for a person. While staff may be told what happens in the prison should remain there when it is time to go home, this is often unrealistic. For example, a correctional employee who witnesses a vicious assault may find it impossible to avoid being preoccupied with this stressful event at home, which creates tension and conflict that can deteriorate the quality of their home life. Another example would be when a staff member feels frustrated after having a confrontation with a belligerent and uncooperative inmate, and this frustration follows the person home, leading to an argument with a family member over a trivial matter.

Behavior-based conflict can result when work and family roles are incompatible, and the use of one type of role in the other domain results in conflict and strain for the person (Greenhaus et al., 2006). As pointed out by Greenhaus and Beutell (1985), there may be particular in-role behaviors that are effective in one domain but incompatible in another domain. For example, prison work roles of being suspicious and questioning of the actions of inmates, are often not appropriate when dealing with family and friends where more loving and supportive roles are expected. These conflicting behavioral roles can lead to work–family conflict (Brough & O’Driscoll, 2005). In addition, caring and nurturing roles that are appropriate in the home may cause problems at work, particularly among coworkers who may view such behavior as being soft on inmates.

The final type of work–family conflict is family-on-work conflict which can occur when issues and problems from home spill over and cause interference and conflict at work (Michel et al., 2011). This type of work–family conflict occurs when issues and problems at home follow staff to work and detract from their work life. While staff are often told to leave their home problems at the front gate when they arrive at work, this is not realistic. For example, a staff member who is going through a rough and difficult period with a significant other at home and may take out his/her anger and frustrations on coworkers and inmates. In addition, a staff member can be preoccupied mentally at work thinking about a seriously ill loved one at home, which can result in reduced performance and conflict at work. Like most people, correctional staff have home lives that at times are far from perfect, and this can result in family-on-work conflict.

Studies on Correctional Staff Work–Family Conflict

There are a handful of studies on correctional staff work–family conflict. The literature indicates that work–family conflict among correctional staff may vary by personal characteristics. Griffin (2006) reported that work-on-family conflict was a greater issue for female staff than male staff. Triplett et al. (1999) reported that behavior-based conflict was associated with higher levels of work stress for female, but not male, staff. Similarly, work-on-family conflict had a positive relationship with work stress and a negative association with job satisfaction for female correctional staff but not for their male counterparts (Lambert, Altheimer, & Hogan, 2010). Occupational position has also been linked with work-on-family conflict, with correctional officers reporting greater amounts of time-based and strain-based conflict than staff working in noncustody positions (Lambert & Hogan, 2006; Lambert, Hogan, & Barton, 2004). Lambert et al. (2004) observed that both educational level and tenure had negative associations with the time-based work-on-family conflict. Supervisory status was positively associated with a combined measure of time- and strain-based work-on-family conflict (Lambert & Hogan, 2006). While not directly tested in correctional staff studies, studies with other organizations suggest that employees with dependent children experience higher levels of all types of work–family conflict (O’Driscoll, Brough, & Kalliath, 2006).

Studies have also linked work-on-family conflict to salient outcomes. Time-, strain-, and behavior-based conflict all appear to lead to higher levels of work stress for correctional staff (Griffin, 2006; Lambert, Hogan, Camp, & Ventura, 2006; Lambert, Hogan, & Griffin, 2007; Triplett et al., 1999). Furthermore, all three types of work-on-family conflict appear to increase the likelihood of job burnout (Lambert & Hogan, 2010; Lambert, Hogan, & Altheimer, 2010). Both the time and strain based forms of work-on-family conflict have been linked with reduced job satisfaction (Lambert et al., 2003, 2006). Also a composite measure of time- and strain-based conflict and family-on-work conflict has been reported to reduce the life satisfaction of correctional staff (Lambert et al., 2005). A composite measure of time- and strain-based conflict was associated with less support for treatment of inmates and increased support for inmate punishment (Lambert & Hogan, 2009; Lambert, Altheimer, Hogan, & Barton, 2011). Perceived job dangerousness and role conflict were found to have positive associations with work-on-family conflict, while perceptions of organizational fairness had a negative association with a composite time- and strain-based measure of work–family conflict (Lambert & Hogan, 2006). Finally, the time and strain types of work–family conflict were found to be negatively associated with the affective form of organizational commitment (Hogan, Lambert, Jenkins, & Wambold, 2006).

Organizational Commitment

Organizational commitment refers to the bond formed between the employee and the employing organization (Stazyk, Pandey, & Wright, 2011). This bond represents a commitment to the overall organization and not just a subpart, such as a department or work group (Lambert, Hogan, & Jiang, 2008). Organizational commitment is a multidimensional concept with different forms of commitment based on how the bond forms (Meyer, Stanley, Herscovitch, & Topolnytsky, 2002). Meyer and Allen (1984) theorized that there are different forms of organizational commitment, with affective and continuance being major ones.

Affective commitment is a positive emotional/psychological bond between the worker and the employing organization (Somers, 2008). The core elements of affective organizational commitment are organizational pride, identification with organization’s goals and objectives, loyalty and dedication toward the organization, and a willingness to perform above and beyond expectations (Meyer & Allen, 1991). Affective commitment is postulated to develop over time based on the social exchange theory (Blau, 1964). The reciprocity principle of the social exchange theory holds that employees who are treated in a positive manner by the organization will develop favorable views of the organization and bond with it over time (Cropanzano & Mitchell, 2005). However, if employees are treated negatively and believe their needs are not being met, a weak or nonexistent affective bond is likely to occur (Meyer & Allen, 1991). With affective commitment, employees bond with the organization because they choose to do so, not because they feel they must do so (McElroy, Morrow, & Wardlow, 1999).

According to Hrebiniak and Alutto (1972), continuance commitment is a phenomenon that results in investments made by the employee over time and these investments bind the person to the organization. Iverson and Buttigieg (1999) contended that with continuance commitment a person becomes locked into remaining with the employing organization because the perceived costs of leaving are too high. Likewise Carson and Carson (2002) viewed continuance commitment as a feeling of necessity to remain with the organization because the sacrifices of leaving would be too great based on a perception that there were few other employment opportunities. Simply stated, under continuance commitment, investments made over time by working for a particular organization lead to the formation of a bond tying a worker to the organization (McElroy et al., 1999). According to Becker’s (1960) side-bet theory, these investments represent “sunken costs” which bind the person to the organization, such as time, money, pension, or social relations. In essence, employees commit to the organization or risk losing their investments (Jaros, Jermier, Koehler, & Sincich, 1993). Employees with continuance commitment bond with the organization because they think they have to, not because they freely choose to do so.

Affective and continuance commitment are distinct from one another. Being committed to an organization because of investments represents reciprocity of necessity. Being committed because the organization has treated the person in a positive manner is reciprocity by desire (Meyer & Allen, 1991). Using turnover as an example, Carson and Carson (2002) pointed out that with continuance commitment a concern of the costs of leaving bind a person to the organization rather than a sense of loyalty found with affective commitment. Another metaphor would be commitment in a marriage. Under continuance commitment, a person remains married because of the investments made in the marriage and the high costs of ending the marriage. Under affective commitment, a person remains married due to emotional bonds with the other person, sharing common interests and values, and identifying as one part of the marital unit.

Hypotheses

It is unclear how the two forms of organizational commitment would be related to the various types of work–family conflict among correctional staff. Only a handful of studies have examined how affective commitment and the different forms of work–family conflict are associated with one another. Affective commitment and time-based conflict had a negative relationship among correctional staff (Hogan et al., 2006; Lambert, Hogan, Barton, Jiang, & Baker, 2008). Clearly, there have not been sufficient studies to determine how organizational commitment and various types of work–family conflict are linked to one another. Furthermore, no published studies could be located that compared the relationship of both forms of organizational commitment and the various types of work–family conflict among correctional staff; therefore, this study was initiated.

This study is grounded in the person–environment fit theory. This theory holds that if there is a good match between the person and the environment, then there should be positive outcomes. Conversely, if there is a poor fit, there will be negative outcomes (Edwards, Cable, Williamson, Lambert, & Shipp, 2006). Within the person–environment fit theory are the resource conservation model and the strain (job demands) model (Karasek, 1979; Neveu, 2007). The resource conservation model postulates that when employees perceive valued workplace factors to be present, they tend to have positive psychological states, which can spill over into how they perceive different aspects of their lives. When these valued resources are missing or lost, the chances for psychological strain increase. This strain can then spill over and negatively affect other areas of the lives of employees (Hobfoll & Freedy, 1993).

Affective commitment is an employee’s voluntary psychological bond with the employing organization. It results because the organization has treated the staff member in a positive fashion and has met his/her salient needs. The bond itself can be a valuable resource for staff, as it can help insulate staff from negative aspects of working in corrections, including forces that contribute to work–family conflict. Conversely, a lack of affective commitment can lead to strain and frustration for a worker. Over time, this strain can open staff up to other forms of workplace strain, such as work-on-family conflict. Specifically, affective commitment can result in a positive mindset for an individual, helping insulate him/her from strain, conflict, and burnout (Begley & Czajka, 1993). Buonocore and Russo (2012) contended that high levels of affective commitment may result in individuals experiencing a positive psychological mood, and this could lead to reduced effects from role conflict. However, employees with low levels of affective commitment may be more vulnerable to a psychological strain. Over time, this strain can wear them down and exacerbate their perception that they work for an organization for which they have little affection or allegiance. This process may spill over and lead to various types of work-on-family conflict (Byron, 2005). Staff with high levels of affective commitment may be more likely to focus and reflect on positive aspects of their work, and those with low levels of affective commitment may be more likely to dwell on the negative and problem areas of their work (Buonocore & Russo, 2012). Affective commitment, therefore, may moderate the effects of various types of work–family conflict for correctional staff.

Glazer and Kruse (2008) reported that role strain becomes less important for people with high levels of affective commitment because they feel they have a meaningful purpose with the organization, and thus they are willing to endure role stressors for the sake of this commitment. Similarly, Williams (2010) pointed out that affective commitment gives people a sense of belonging and stability within an organization, and these feelings help deflect concerns about work stressors, time-based, strain-based, behavior-based, and family-on-work conflict. Furthermore, the social exchange theory holds that when people feel that they owe someone or something, they are more willing to make sacrifices and downplay strain (Blau, 1964; Cropanzano & Mitchell, 2005). In other words, the social exchange theory holds that people reciprocate favorable treatment (Buonocore & Russo, 2012). As affective commitment “bubbles up” in correctional staff because of positive treatment by the organization, they may become more resistant to various types of work-on-family conflict. In other words, affective commitment may provide staff with a sense of purpose, and, as such, it can act as a buffer to prevent the various types of work–family conflict from arising or being perceived as a problem (Meyer & Maltin, 2010). Affective commitment can also be a coping mechanism for the forces that lead to work-on-family and family-on-work conflict by allowing the person to attach meaning to the conflict (Glazer & Kruse, 2008). For example, a person with high affective commitment may view the time demands of working for a correctional institution as part of the job and the time sacrifice as something that will ultimately benefit the organization in the long run. As such, this individual is less likely to be concerned with time-based conflict. Positive work emotions can spill over and improve the home life of individuals and may lessen the chances of family-on-work conflict from occurring (Allen et al., 2000). In a meta-analysis using studies involving noncriminal justice employees, a negative correlation was reported for affective commitment and a combined overall measure of work–family conflict, and therefore, work–family conflict was theorized to be a consequence rather than an antecedent of organizational commitment (Meyer et al., 2002). In sum, affective commitment can be a resource for correctional staff under the resource conservation model, and a lack of affective commitment can be a strain for correctional staff under the strain (job demands) model. Personal characteristics, such as position, supervisory status, gender, age, tenure, educational level, race, having a partner at home, and having children at home may influence the level of different types of commitment and work–family conflict, these variables were included in the study. In addition, past research has shown that affective and continuance commitment are negatively associated with one another (Lambert, Hogan, & Jiang, 2008). The following hypotheses were made:

Hypothesis 1: Affective commitment would have a negative association with time-based conflict among correctional staff even after controlling for the shared effects of personal characteristics and continuance commitment.

Hypothesis 2: Affective commitment would have a negative association with strain-based conflict among correctional staff even after controlling for the shared effects of personal characteristics and continuance commitment.

Hypothesis 3: Affective commitment would have a negative association with behavior-based conflict even after controlling for the shared effects of personal characteristics and continuance commitment.

Hypothesis 4: Affective commitment would have a negative association with family-on-work conflict among correctional staff even after controlling for the shared effects of personal characteristics and continuance commitment.

The various types of work–family conflict are postulated to be the result of demands and strains that occur for a person either at work or home (Eby, Casper, Lockwood, Bordeaux, & Brinley, 2005). As previously mentioned, under the strain (job demands) model, demands placed on a person can cause psychological strain, and this strain can spill over affecting different aspects of a person’s life, including home life (Sekiguchi, 2004). Continuance commitment may cause strain for some correctional staff because it may foster a sense of organizational dependency. These staff members may feel they are trapped in their jobs because leaving would be too costly in terms of the investments they have made with the organization (Namasivayam & Zhao, 2007). Meyer et al. (2002) reported that people with high levels of continuance commitment frequently report feeling resentful and hopeless. In addition, staying from necessity rather than choice can create strain and cognitive dissonance (Casper, Martin, Buffardi, & Erdwins, 2002). Meyer et al. (2002) argued that feeling trapped with an organization can cause stress for a person which can spillover and negatively affect home life. Furthermore, the need to remain with an organization may lead individuals to put up with different types of work–family conflict because they see no alternatives for dealing with their situation. In addition, continuance commitment can increase sensitivity to negative aspects of work and cause a person to ruminate on them (Meyer & Maltin, 2010). Similarly, Buonocore and Russo (2012) postulated that continuance commitment may exacerbate the negative effects of the different types of work–family conflict because people feel trapped in their jobs with no alternatives than to stay and bear the effects of strain-based, time-based, behavior-based, and/or family-on-work conflict. Similarly, a feeling that one must stay could also lead to feelings of guilt which could magnify the perceptions of the various types of work–family conflict. In a meta-analysis using studies involving noncriminal justice employees, a small positive correlation was reported for continuance commitment and a combined overall measure of work–family conflict; however, there had been too few studies on the relationship between continuance commitment and work–family conflict to estimate a reliable meta-analytic correlation. In this meta-analysis, work–family conflict was theorized to be a consequence and not an antecedent of organizational commitment (Meyer et al., 2002). As continuance commitment could be a strain for some correctional staff, the following hypotheses were made:

Hypothesis 5: Continuance commitment would have a positive association with time-based conflict among correctional staff even after controlling for the shared effects of personal characteristics and affective commitment.

Hypothesis 6: Continuance commitment would have a positive association with strain-based conflict among correctional staff even after controlling for the shared effects of personal characteristics and affective commitment.

Hypothesis 7: Continuance commitment would have a positive association with behavior-based conflict even after controlling for the shared effects of personal characteristics and affective commitment.

Hypothesis 8: Continuance commitment would have a positive association with family-on-work conflict among correctional staff even after controlling for the shared effects of personal characteristics and affective commitment.

Method

Participants

All the available staff at a private maximum security prison received packets that contained a cover letter, the survey, a bifurcated raffle ticket, and a return envelope.¹ Due to various forms of leave (e.g., sick leave, annual, administrative, etc.), only 200 of the 220 staff received a survey packet. The cover letter explained that participation in the study was voluntary, that all responses would be anonymous, and that only the researchers would view any returned survey. The survey was returned using the provided metered addressed envelope which could either be mailed to the researchers or placed in a locked box in the main prison area (only the research team had a key for the lock). A total of 160 usable surveys were returned, representing a response rate of 80% based upon the 200 staff members who received the survey packet. At the time of the survey, the prison housed approximately 450 youthful male offenders who were serving long sentences (typical sentence was more than 10 years in length). All these inmates had been convicted in adult court even though they were under the age of 18. The prison was a high-security, closed facility located in a rural area.

Except upper administration, all staff employed at the prison were surveyed. In terms of position, 62% were correctional officers, 9% were custody supervisors, 6% worked in the business office, 4% worked in education, 3% were unit management staff (i.e., counselors, case managers, and unit managers), 3% worked in the medical department (including mental health professionals), and 13% worked in other areas. Twenty-one percent indicated that they were supervisors of other staff at the prison. Fifty-nine percent marked they were men, and 41% marked they were women. The mean age was 35.77 years old, with a standard deviation of 10.82. The median age was 33 years old and ranged from 19 to 68 years. The median tenure at the prison was 17 months and ranged from 1 to 53 months. The reason for the low tenure was because the prison had been in operation for only 5 years prior to the time of the survey. In terms of highest educational level, 6% indicated that they had a high school degree or general education development diploma, 47% had some college but no degree, 24% had an associate’s degree, 16% had a bachelor’s degree, and 7% had a graduate or professional degree. All correctional officers in the state, including those working for a private facility, were required to have at least 15 college credit hours to be employed, and this explains the high percentage of staff with some type of college experience. In terms of race/ethnicity, 79% marked they were White, 11% Black, 2% Hispanic, 3% Native American, and 4% other.

Institutional records indicated that at the time of the survey approximately 81% of the all the employees at the prison were White, 61% were male, 60% of staff held the position of correctional officer, the median age was 34, and the average tenure was 20 months; therefore, the participants appeared to be demographically representative of the staff at the private prison.

Variables

Dependent variables

The four types of work–family conflict were measured using items established in previous research (Bacharach, Bamberger, & Conley, 1991; Bohen & Viveros-Long, 1981; Carlson, Kacmar, & Williams, 2000). All the work–family conflict items are located in the Appendix, and the items for each area were summed to form an index. Time-based conflict was measured using seven items, which had a Cronbach’s α of 0.84. Strain-based conflict was measured using 11 items, which had a Cronbach’s α of 0.93. Behavior-based conflict index measured using three items, which had a Cronbach’s α of 0.61. Family-on-work conflict was measured using five items, which had a Cronbach’s α of 0.71. Principal axis factor analysis with varimax rotation was conducted for the work–family conflict items, and the results indicated convergent validity among the indicators. Specifically the work-family conflict items loaded on the predicted factors (i.e., four different factors were found-one for time-based conflict, one for strain-based conflict, one for behavior-based conflict, and one for family on work conflict). The factor loading scores for each item are reported in the Appendix. It is important to note that factor analysis is most robust when there are 300 or more cases (Tabachnick & Fidell, 2013). There were only 160 cases in this study.

Independent variables

Affective commitment was measured by summing six items from Mowday, Porter, and Steers (1982) (see Appendix for these items), which had a Cronbach’s α of 0.84. Continuance commitment was measured by summing four items from Allen and Meyer (1990; see Appendix for the items), which had a Cronbach’s α of 0.77. All the commitment items were measured using a 5-point Likert-type response scale ranging from strongly disagree (coded 1) to strongly agree (coded 5). Principal axis factor analysis with varimax rotation was conducted for the commitment items, and the results indicated convergent validity among the indicators. Specifically, the items loaded on the predicted factor (i.e., the affective commitment items loaded on one factor and the continuance commitment items loaded on one factor). The factor loading scores for each item are reported in the Appendix.

Position, supervisory status, gender, age, tenure, educational level, and race were included more as control than explanatory variables. Position reflected whether the respondent held the position of nonsupervisory correctional officer (coded 1) or worked in another position (e.g., case manager, counselor, etc.; coded 0), and this variable was named correctional officer. Supervisory status was a dichotomous variable representing if the participant was a supervisor of other prison staff (coded 1) or was not (coded 0). In this study, this variable was labeled as supervisor. Gender was coded as women = 0 and men = 1, and this variable was labeled as male. Age was measured in continuous years, and this variable was labeled as age. Tenure at the prison was measured in continuous months, and was labeled as tenure. Highest educational degree earned measured whether the participant had earned a college degree (coded as 1) or not (coded as 0), and was labeled as college degree. Race/ethnicity was measured as a dichotomous variable representing whether the person was White, non-Hispanic (1), or Nonwhite/Hispanic (0), and was labeled as White. Finally, as the literature suggests that work-on-family and family-on-work conflict can be greater among people who are single with dependent children, measures for being partnered and having children living at home were included (O’Driscoll et al., 2006). Respondents who indicated that they were married or single with a partner at home were coded 1 and those who indicated that they were single, divorced, or widowed were coded as 0. A dichotomous variable representing whether the respondent had a dependent child/children living at home was created, which was coded 0 if no children at home or 1 if one or more children were present.

Findings

Descriptive statistics for the measures used in this study are presented in Table 1. The variables appeared to be normally distributed.² The Cronbach α values, a measure of internal reliability, were 0.60 or higher, which is viewed as being acceptable, with values higher than 0.70 being viewed as good (Gronlund, 1981).

Table 1.

Univariate Statistics of Study Variables.

Variable	Description	Breakdown of Categories
Correctional officer	0 = Nonline correctional officer	62% were line correctional officers and 38% held nonline correctional officer positions
Correctional officer	1 = Line correctional officer
Supervisor	0 = Nonsupervisor of other staff	21% were supervisors and 79% were not supervisors of other staff
Supervisor	1 = Supervisor of correctional staff
Male	0 = Female	41% were women and 59% were men
Male	1 = Male	41% were women and 59% were men
College degree	0 = No college degree	53% had no college degree and 47% had some type of college degree
College degree	1 = College degree
White	0 = Nonwhite	21% were Nonwhite and 79% were White
White	1 = White	21% were Nonwhite and 79% were White
Partnered	0 = No partner at hone	70% had a partner at home and 30% had no partner at home
Partnered	1 = Partner at home	70% had a partner at home and 30% had no partner at home
Children at home	0 = no child/children at home1 = child/children at home	55% had a child/children living at home and 45% had no child/children at home
		Md	Min	Max	Mn	SD
Age	Measured in continuous years	33	19	68	35.77	10.82
Tenure	Measured in continuous months working at the prison	17	1	53	20.64	13.84
Affective commitment	Six-item additive index, α = 0.88	19	10	26	18.14	4.00
Continuance commitment	Four-item additive index, α = 0.77	12	4	20	11.84	3.88
Time-based conflict	Seven-item additive index, α = 0.84	21	9	35	21.74	5.97
Strain-based conflict	11-item additive index, α = 0.93	25	11	55	27.91	9.50
Behavior-based conflict	Three-item additive index, α = 0.61	8	4	15	8.64	2.46
Family-on-work conflict	Five-item additive index, α = 0.71	10	5	23	10.74	3.14

Note. Md stands for the median value, Min for the minimum value, Max for the maximum value, Mn for the mean value, SD for the standard deviation value, and α for Cronbach’s alpha value for internal reliability. The number of participants was 160 after listwise deletion.

The correlations for the study variables are presented in Table 2. Three of the nine personal characteristics had a statistically significant correlation with the time-based conflict variable. Correctional officers on average reported higher levels of time-based conflict. Increases in age were associated with lower levels of time-based conflict. Having children was positively correlated with this type of conflict. While both forms of commitment had significant correlations, they were in opposite directions. Affective commitment had a negative correlation, and continuance commitment had a positive correlation.

Table 2.

Correlation Matrix for Study Variables.

Variables	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.	12.	13.	14.
1. Correctional officer	1.00
2. Supervisor	−0.47**	1.00
3. Male	0.28**	0.12	1.00
4. Age	−0.53**	0.16*	−0.17*	1.00
5. Tenure	−0.20**	0.39**	0.00	0.07	1.00
6. College	−0.29**	0.19*	−0.13	0.16*	0.12	1.00
7. White	−0.02	0.04	0.08	−0.05	0.06	0.08	1.00
8. Partnered	−0.01	0.04	0.03	0.01	−0.05	−0.07	0.10	1.00
9. Children	0.04	0.01	−0.09	−0.11	0.05	−0.06	−0.06	0.07	1.00
10. Affective	−0.24**	0.23**	0.05	0.17*	−0.04	0.07	0.00	0.08	−0.11	1.00
11. Contin	0.16*	−0.10	−0.06	−0.15	0.12	−0.01	−0.08	−0.04	0.17*	−0.39**	1.00
12. Time	0.37**	−0.11	0.14	−0.37**	0.08	−0.13	−0.04	0.05	0.18*	−0.43**	0.37**	1.00
13. Strain	0.07	−0.09	−0.07	-0.15	0.14	0.02	−0.01	0.05	0.22**	−0.35**	0.41**	0.70**	1.00
14. Behavior	0.12	−0.13	0.06	−0.21**	0.05	−0.04	0.09	0.04	0.18*	−0.40**	0.32**	0.58**	0.66**	1.00
15. Family	0.14	−0.06	0.07	−0.23**	0.04	0.04	0.01	−0.04	0.14	−0.10	0.19*	0.46**	0.53**	0.41**

Note. See Table 1 for a description of the variables and how the variables were coded. Corr Officer stands for correctional officer, College for college degree, Children for children at home, Affective for affective commitment, Contin for continuance commitment, Time for time-based conflict, Strain for strain-based conflict, Behavior for behavior-based conflict, and Family for family-on-work conflict. The number of participants was 160.

p ≤ .05. **p ≤ .01.

Of the independent variables, only having children, affective, and continuance commitment had significant correlations with strain-based conflict. Those with children living at home reported higher levels of this type of work–family conflict. Increases in affective commitment were associated with decreases in the level of strain reported at home. Continuance commitment was associated with higher levels of strain-based conflict.

The only personal characteristics to be correlated with behavior-based conflict were age and having children. Older staff generally reported fewer problems with work and home roles causing them conflict while staff who had children at home reported greater levels of this type of work–family conflict. Affective commitment had a negative correlation, while continuance commitment had a positive correlation.

For the family-on-work conflict index, age was the only personal characteristic variable to have a significant correlation, which was negative (i.e., older workers had fewer problem with problems at home causing conflict at work). Among the two types of commitment, only continuance had a significant correlation. Increases in continuance commitment were associated to higher levels of this type of work–family conflict.

Affective and continuance commitment had a moderately sized negative correlation with one another, which indicates that they are distinct concepts and an increase in one form of commitment is associated with a decrease in the other. Finally, all four types of work–family conflict were positively associated with one another, but not to a degree of colinearity (i.e., high correlation of 0.80 or higher). This was expected because they are all measuring dimensions of work–family conflict.

Four ordinary least squares (OLS) regression equations were estimated with the four types of work–family conflict as dependent variables. OLS regression allows for the effects of a variable to be estimated while controlling for the shared effects with the other independent variables. The results for the four OLS regression equations are reported in Table 3. The variance inflation factor and tolerance statistics (not reported) indicated no problem of multicollinearity among the independent variables. In addition, the issues of outliers, influential cases, normality, linearity and homoscedasticity of residuals, and independence of errors in the regression analysis were tested and were found to be nonproblematic. As multivariate regression results may be influenced by sample size, it is important to note that there were only 160 cases and 11 independent variables. While the number of cases exceeds the minimum number of 110 cases based on the 10 to 1 ratio of number of cases to independent variables, the small sample size could affect the effect size and the confidence interval (Cohen, Cohen, West, & Aiken, 2003; Tabachnick & Fidell, 2013).

Table 3.

Ordinary Least Squares Regression Results of the Relationships of Affective and Continuance Commitment With Private Correctional Staff Work–Family Conflict.

	Time-based conflict		Strain-based conflict		Behavior-based conflict		Family-on-work conflict
Variable	B	β	B	β	B	β	B	β
Correctional officer	2.26	0.18	−1.82	−0.09	−0.76	−0.15	0.02	0.01
Supervisor	0.73	0.05	−2.06	−0.09	−0.76	−0.13	−0.44	−0.06
Male	0.94	0.08	−0.10	−0.01	0.62	0.12	0.48	0.08
Age	−0.10	−0.19*	−0.10	−0.11	−0.04	−0.16	−0.05	−0.19*
Tenure	0.03	0.08	0.08	0.11	0.01	0.04	0.01	0.04
College degree	−0.20	−0.02	0.81	0.04	0.03	0.01	0.56	0.09
White	−0.06	−0.04	−0.11	−0.01	0.52	0.09	0.08	0.01
Partnered	1.10	0.08	1.60	0.08	0.30	0.06	−0.22	−0.03
Children at home	0.96	0.08	2.57	0.14	0.56	0.11	0.67	0.11
Affective commitment	−0.44	−0.29**	−0.51	−0.21**	−0.19	−0.30**	0.00	0.00
Continuance commitment	0.89	0.19**	0.69	0.28**	0.11	0.18*	0.11	0.14
F-statistic	7.85**		4.65**		4.30**		1.47**
R ²	0.37		0.26		0.25		0.10
Adjusted R²	0.32		0.20		0.19		0.03

Note. See Table 1 for a description of the variables and how they were coded. B represents the unstandardized regression coefficient and β the standardized regression coefficient. The number of participants in each regression analysis was 160.

p ≤ .05. ** p ≤ .01

The independent variables explained approximately 37% of the variance observed in the time-based conflict index, and three variables were significant predictors. Increases in age were associated with reduced time-based conflict. Affective commitment had a negative relationship, which means increases in this form of commitment were associated with decreased reports of time-based conflict. Conversely, continuance commitment had a positive relationship, which means increases in continuance commitment were linked with higher levels of self-reported time-based conflict for correctional staff. Affective commitment had the largest standardized sized effect, followed by continuance commitment and age.

The independent variables explained about 26% of the variance in the strain-based conflict measure. None of the control personal characteristics had a significant relationship; however, both forms of commitment did. Higher levels of affective commitment were associated with less strain-based conflict reported by the responding correctional staff. Continuance commitment not only had a positive relationship with this type of work–family conflict but had a larger sized effect than affective commitment.

Approximately 25% of the variance in the behavior-based conflict index was accounted for by the independent variables. None of the control personal characteristics had a significant relationship. Affective commitment had a negative relationship, and continuance commitment had a positive association, with affective commitment having a larger size effect.

Only 10% of the variance observed in the family-on-work conflict measure was explained by the independent variables. Only age was a significant predictor. Increases in age were associated with reductions in reported conflict at work from home. Both affective and continuance commitment had no significant relationship with family-on-work conflict.

Finally, regression equations were estimated with only personal characteristics (i.e., correctional officer, supervisor, male, tenure, college degree, White, partnered, and having children at home) as the independent variables. In addition, regression equations were run with only the two forms of commitment as the independent variables. This was done to see how much variance in the different types of work–family conflict could be explained by each group of independent variables. For time-based conflict, the personal characteristics explained about 23% of the variance and the R² value for the two forms of commitment was 0.24. For strain-based conflict, the R² value for the personal characteristics was 0.11, and affective and continuance commitment accounted for about 21% of the observed variance. The R² value for behavior-based conflict for personal characteristics and two forms of commitment were 0.10 and 0.19, respectively. The personal characteristic variables explained about 8% of the variance of the family-on-work conflict index, while affective and continuance commitment only accounted for 3% of the variance. Finally, with the exception of family-on-work conflict, the two forms of commitment explained a similar or greater amount of the variance for each type of work–family conflict as compared to the nine personal characteristic variables.

Discussion and Conclusion

Overall, the findings provide support for the person–environment fit theory based on the resource conservation model and the strain (job demands) model. Of the eight hypotheses, six were supported. As predicted, affective commitment was negatively associated with the three forms of work-on-family conflict (hypotheses 1 to 3). Likewise, continuance commitment was positively linked with time-, strain-, and behavior-based conflict (hypotheses 5 to 7). The results for hypotheses 4 and 8, concerning the predicted relationship between family-on-work conflict and affective and continuance commitment, were not statistically significant.

It would appear that when a person elects to form a voluntary attachment to the organization, it signifies a good fit between the person and the organization. This form of commitment probably results in a resource that is valued by the staff member and may help to protect them against strains faced working in a correctional facility as suggested by the resource conservation model of the person–environment fit theory. Forming a bond based on investments probably results in a feeling of being trapped, which in itself can lead to strain as proposed by the strain (job demands) model.

The relationships between the different forms of organizational commitment with various types of work-on-family conflict reflect the classical issue of stressor–strain causal relationships. While it is clear that the two concepts appear to be related to one another, it is unclear which causes the other, at least in this study. What cannot be definitively said is that either form of organizational commitment causes or moderates work-on-family conflict among correctional staff because the current study was based on cross-sectional data. In order to demonstrate the causal direction of the relationships, longitudinal data is needed. In this study, both forms of commitment were theoretically argued to affect various types of work–family conflict, and the theoretical rationale for the proposed direction of these associations makes sense and is supported in the literature. There, however, is not complete agreement in the literature about the direction of the association. At least for affective commitment, it could be that work-on-family conflict is a predictor of this form of commitment and not the other way around.

It has been proposed that in the long run work-on-family conflict can lead to a negative view of the organization and erode one’s level of affective commitment (Hogan et al., 2006; Lambert et al., 2006). In other words, correctional staff suffering from work–family conflict may blame the organization for allowing the situation to occur. This can harm the staff member’s positive view of the organization, which is necessary for the voluntary psychological bond to occur. It is also possible that the relationship between affective commitment and time-, strain-, and behavior-based conflict is more complex over time. High levels of affective commitment may help mitigate the perceptions of work-on-family conflict at first, but after a long period of exposure to the forces leading to work-on-family conflict, the level of affective commitment may lessen as strain and conflict take their toll. Future longitudinal studies are needed to disentangle the direction of the relationship between the forms of organizational commitment and the types of work-on-family conflict. What is clear from the findings of this study is that affective commitment is negatively associated with time-, strain-, and behavior-based conflict among correctional staff. This finding is consistent with the handful of past studies that have examined this relationship for correctional staff.

It becomes more theoretically difficult to postulate that work-on-family conflict leads to greater continuance commitment. It is unclear how time-, strain-, or behavior-based conflict would lead to higher levels of continuance commitment. This would mean that work-based strain in some way causes people to feel they must remain with their organization because the sunken costs bind them to do so. This appears to make less intuitive sense than postulating that continuance commitment is stressful in itself and leads to greater work-on-family conflict for correctional staff. Continuance commitment could lead to conflict at home if it leads to feeling trapped in a job. The feelings of desperation and hopelessness that often relate to this claustrophobic experience may increase employees’ awareness of work-on-family conflict and decrease their ability to tolerate it. Thus, remaining on the job for the wrong reasons (i.e., investments rather than enjoyment) could lead to conflict at home. This, of course, is an untested explanation that needs to be researched using a longitudinal design.

The current findings suggest that neither form of commitment is related to family-on-work conflict. Of the four regression equations, the equation for family-on-work conflict had the lowest R². This means that variables other than the personal characteristics and organizational commitment account for the level of family-on-work conflict reported by the correctional staff in this study. As affective and continuance commitment represent workplace factors, it makes sense that they may not be related to problems at home that spill over and cause conflict at work. Future research is needed to determine what variables are linked with correctional staff family-on-work conflict. For example, the quality of relationships at home could be more important in shaping family-on-work conflict than affective or continuance commitment.

Except for age, none of the other personal characteristics had a significant relationship with any of the types of work–family conflict in the multivariate analyses. This finding supports the contention by Lambert and Hogan (2006) that other factors, especially workplace ones, are more important in explaining work-on-family conflict among correctional staff. This is good news because while correctional administrators have little control over personal characteristics, they have substantial control over workplace factors. Age had a negative relationship with both time-based and family-on-work conflict and had a nonsignificant association with both strain-based and behavior-based conflict. An explanation of why age would have a negative association with family-on-work and time-based conflict but not strain- or behavior-based conflict, is unclear. Age could be important in dealing with certain types of work-on-family and family-on-work conflict and not others. It is also unclear if the negative relationship with time-based and family-on-work conflict is the result of a person aging, a cohort effect, or some other reason.

Interestingly, neither being partnered nor having children at home were significantly linked to any of the four types of work–family conflict in the multivariate analyses. It could be that neither variable is important in explaining correctional staff any of the four types of work–family conflict once organizational commitment and other personal characteristics are taken into account. It could also be that the measures of being partnered and having children at home fail to capture other situations at home (e.g., lack of monetary resources, unsupportive spouse) which can lead to greater time-based, strain-based, behavior-based, and family-on-work conflict. In addition, a limited measure of having children at home was used. If the number of children and their ages were taken into account, different results may have been found. Similarly, the shift of the staff members was not measured. It could be that working evening or morning shifts and having young children at home may result in greater time-based conflict than working the day shift or having older children at home. Likewise, a more detailed measure of being partnered, such as knowing if and when the other partner worked, and how much effort/time this person provided at home and with the children would probably shed more light on the issue of work–family conflict. As previously indicated, there has been very little research on work–family conflict among correctional staff and this limited research has not included measures of having a partner and/or children at home. As such, it is unknown if the current results are the norm for correctional staff or not. Clearly, more research is needed.

As with many studies, the current study has shortcomings. Staff at a single private prison were surveyed, and as such, the results may not apply to public prison staff. Furthermore, the staff in this study dealt with older juveniles sentenced as adults which is a unique inmate population not found at many prisons. Most prisons deal with adult inmates. It could be the relationships between affective and continuance commitment with different types of work–family conflict are contextual and situational, and vary across different types of correctional facilities, inmate populations, regions, and/or countries. Additional research needs to be conducted at various types of correctional facilities to determine whether these results can be replicated or if they vary by type and location of correctional institution.

Another limitation is the small sample size of 160 participants. As previously indicated, the results of factor analysis may be influenced if there are less than 300 cases. Similarly, OLS regression is more robust if there are more than 20 cases for each variable in the model, and in this study, there were 11 independent variables (Tabachnick & Fidell, 2013). It is possible that the small sample size could have affected the factor analysis and regression results. Future research needs to ensure that there are an ample number of cases in order to see if the findings can be replicated. Furthermore, the small sample size precluded examining whether the relationships observed held among subgroups of correctional staff, such as men and women, correctional officers, and noncustody staff.

As already stated, the data in this study was cross-sectional. Longitudinal research is needed to determine the causal direction between organizational commitment and each type of work–family conflict. Also, because a limited measure of continuance commitment was used, future studies should consider using a more in-depth measure of this form of commitment. Likewise, a more in-depth measure of family-on-work conflict should be used. As the behavior-based conflict index had a low Cronbach’s α of 0.61, future researchers should consider developing a more reliable measure of behavior-based conflict for correctional staff. Moreover, other outcome areas for affective and continuance commitment need to be explored, such as work stress, job satisfaction, work performance, absenteeism, turnover intent, turnover, and work burnout. Without this research, the true picture of the effects of different forms of organizational commitment among correctional staff will remain unclear.

Assuming that these results are confirmed in future studies, it is important to investigate how continuance commitment develops among correctional staff in light of its positive association with the three types of work-on-family conflict. Outside of the field of corrections, the literature paints a pessimistic picture of continuance commitment. Meyer et al. (2002) argued continuance commitment is unrelated to job performance and building this form of commitment should be avoided. Instead efforts should be made to increase affective commitment. In their comprehensive review of the organizational literature, Meyer and Maltin (2010) concluded that continuance commitment was negatively related to employee well-being. Meyer and Maltin (2010) further argued that organizations need to avoid contributing to the development of continuance commitment, even if done unintentionally. They pointed out that an organization might indirectly increase continuance commitment “by introducing programs designed to encourage retention without addressing quality of life issues. This can create a conflict for employees who would like to escape from the undesirable working conditions but are reluctant to incur the economic costs” (p. 334). This research is essential to determine how retention efforts are perceived by correctional staff. The goal of these efforts should not be to make it too painful to leave by giving up pay and benefits, but rather the aim should be to transform the position into one so sufficiently desirable that its positive aspects enhance affective commitment over time.

The feeling that one must stay under continuance commitment is thought to arise because of a lack of alternatives and the perceived costs of leaving (Meyer, Stanley, Jackson, McInnis, Maltin, & Sheppard, 2012). Only a few published studies could be found that examined the possible antecedents of correctional staff continuance commitment. Lambert, Hogan, and Jiang (2008) reported that none of the measured workplace factors (i.e., input into decision-making, job autonomy, perceived promotional opportunities, instrumental communication, and organizational justice perceptions) were associated with continuance commitment among staff at a state prison. The only workplace variable related to continuance commitment was job stress, and the positive relationship between these two variables suggests that continuance commitment maybe a stressor for correctional staff. Griffin and Hepburn (2005) reported that a perception of having nontransferable job skills and a lack of alternative employment opportunities had a positive effect on continuance commitment, but a nonsignificant relationship with affective commitment. This suggests that different workplace factors lead to affective and continuance commitment. There is even the question of whether continuance commitment can be managed or avoided in the field of corrections as it might require massive changes in the system. Iverson and Buttigieg (1999) pointed out that while organizations must have competitive compensation for workers, affective commitment cannot be bought—it has to be earned. There is literature on how to build affective commitment among correctional staff, such as allowing greater input into decision making, providing supervisory and administrative support, reducing role conflict, role ambiguity, and role overload, ensuring quality communication, allowing job autonomy, and providing job variety (see Lambert, Hogan, & Jiang, 2008). It is clear that far more research is needed on the different forms of commitment and their effects on both correctional staff and prisons.

Having staff not being stressed from domain spillover is critical in an era of reduced budgets and increased pressure to accomplish more with less; therefore, how workplace factors are related to other workplace factors is important. As pointed out by Griffin and Hepburn (2005), correctional organizations need to be aware of the different forms of organizational commitment and what they represent. This study examined the relationship between affective and continuance commitment with time-based, strain-based, behavior-based, and family-on-work work–family conflict. Affective commitment was observed to have a negative relationship with the three types of work-on-family conflict (i.e., time-, strain-, and behavior-based conflict), and continuance commitment had a positive association with these three types of work–family conflict. The findings indicate that scholars and correctional administrators must understand that organizational commitment is not a monolithic concept, but has different dimensions that have varying relationships with workplace outcomes. While this was a single study with limitations, it is hoped this study will spark interest in continued research on how organizational commitment is associated with each type of work–family conflict for correctional staff. As noted by Allen et al. (2000), work–family conflict has significant negative costs for the worker, family members, friends, the employing organization, and society. There is still much unknown about how workplace factors affect correctional staff and this puzzle will only be solved by future research. Without more solid knowledge in this area, making recommendations to correctional administrators will continue to be problematic and haphazard.

Footnotes

Appendix

All the below items were measured using a 5-point Likert-type scale of strongly disagree (coded 1) to strongly agree (coded 5). The principal axis factor analysis loading score is presented in the parentheses for each item.

Acknowledgements

The authors thank Janet Lambert for editing and proofreading the article. The authors also thank the editor and the anonymous reviewers for their comments and suggestions. These comments and suggestions improved the article.

Author’s Note

All the authors contributed to the paper and the authorship is random.

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

Notes

Author Biographies

Eric G. Lambert is a professor of criminal justice at Wayne State University. He received his PhD from the School of Criminal Justice at the State University of New York at Albany. His research interests include organizational issues, job and organizational effects on the attitudes, intentions, and behaviors of criminal justice employees, and the international perceptions, attitudes, and views on criminal justice issues.

Nancy L. Hogan is a professor in the School of Criminal Justice at Ferris State University and Graduate Program Coordinator at Ferris State University. She received her PhD in Justice Studies from Arizona State University. Her research interests include job satisfaction and organizational issues of correctional staff, use of force, and cognitive behavioral treatment for inmates.

Thomas M. Kelley is an associate professor in the Department of Criminal Justice. Also a licensed psychologist. Research interests include delinquency, child abuse and neglect, correctional counseling, and positive psychology.

Bitna Kim is an assistant Professor in the Department of Criminology at Indiana University of Pennsylvania. She received her PhD from the College of Criminal Justice at Sam Houston State University. Specific areas of interest include cross-cultural study, gender issues in CJ system, and statistics. Recent publications have appeared in the International Journal of Offender Therapy and Comparative Criminology, the Journal of Criminal Justice, Violence and Victims and Crime and Delinquency.

Brett Garland is an associate professor and graduate director in the Department of Criminology and Criminal Justice at Missouri State University. He has served as a juvenile caseworker and prison pre-release program coordinator in Indiana. Brett has published articles and chapters on topics related to criminal justice management and staff, prisoner reentry, and public opinion on criminal justice policy. His current research focuses on correctional staff work environments and offender compliance during community supervision.

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