Work–Family Conflict and Enrichment Mediates the Relationship Between Job Characteristics and Well-Being at Work With Portuguese Marine Corps

Abstract

This study of 175 military employees working in three units of the Portuguese Marine Corps tested the mediated effect of work–family conflict and enrichment on the relationship between job characteristics and well-being at work (i.e., burnout; engagement). Using job demands, job autonomy, and supervisor support as job characteristics, and consistent with the assumptions of acclaimed work well-being models (i.e., job demands–control and support, job demands–resources model, and conservation of resources theory), the structural equation modeling analysis revealed that job characteristics are related to both work–family conflict and enrichment, which, in turn, explain militaries’ burnout and engagement. Work–family enrichment mediated the relationship between job characteristics (i.e., autonomy and supervisor support) and engagement, and work–family conflict not only mediated the relationship between job characteristics (i.e., demands and supervisor support) and burnout but also acted as a mediator between these variables and engagement.

Keywords

job characteristics work–family conflict work–family enrichment burnout engagement

Research on work–family literature has increased exponentially over the last decades, mainly due to its consequences for employees’ well-being (Carvalho & Chambel, 2016; Hammer, Demsky, Kossek, & Bray, 2016; Mullen, Kelley, & Kelloway, 2008). Well-being in the military service has been emphasized as an important dimension to attract and retain engaged and high-performing employees (Alarcon, Lyons, & Tartaglia, 2010; Chambel & Oliveira-Cruz, 2010). Several studies have explored the impact of military service on the psychological well-being of militaries and their family members in deployment situations (e.g., Hollingsworth, 2011; Hoshmand & Hoshmand, 2007; Wright, Foran, & Wood, 2014). However, there is little research on the complexity of the work–family relationship for those who have a professional career in the military service.

Indeed, as Wadsworth and Southwell (2011) argue, the militaries have to spend energy and both psychological and behavioral pressures in their work that evoke family tensions. Aspects of workload (i.e., working hours, hours of sleep, days training, and perceived work overload), health, and morale are considered the strongest predictors of the work–family conflict (WFC) in militaries (Britt & Craig, 2005).

On the other hand, the breadth of the work–family literature currently includes the existence of positive synergies between work and family roles, namely, work–family enrichment (WFE; Greenhaus & Powell, 2006), which has been largely ignored in military research. A basic tenet of this model is that the resources and psychological states presented in the work role are transferable to the family role.

In the military working context, there are specific resources which may be transferable to the family domain. For example, teamwork and self-reliance in military service training may lead to the development of personal resources that can help facilitate the performance of militaries in the family context (e.g., having more confidence as a parent).

Moreover, studies on the work–family relationship have demonstrated that the way individuals perceive their work–family relationship as a conflict or/and enrichment is related to their well-being at work (Carvalho & Chambel, 2016). In the same vein, WFC is associated with burnout, and WFE is related to engagement (Hakanen, Peeters, & Perhoniemi, 2011). Previous research has already demonstrated that maintaining high well-being levels in militaries is crucial, namely, to prevent junior military personnel from leaving the Army (Alarcon et al., 2010) and to protect militaries from the possible effects of stressful situations (Chambel & Oliveira-Cruz, 2010).

In this article, our aim is to investigate how the work–family relationship of military workers may affect their well-being at work. In order to accomplish this goal, our study focuses on the negative and positive perspectives of the work–family relationship (i.e., WFC and WFE) and on the negative and positive perspectives of well-being at work (i.e., burnout and engagement). Furthermore, we also aim to explore job characteristics as possible antecedents of WFC and WFE in military work environments. Specifically, we aim to explore the job characteristics taken into consideration in the acclaimed job demands–control–support (JDCS) model (Johnson & Hall, 1988; Karasek & Theorell, 1990), namely, job demands, job autonomy, and supervisor support. To date, these job characteristics have been largely contemplated in literature as important to employees’ well-being (Luchman & González-Morales, 2013).

Overall, this research offers four theoretical gains to military literature. First, it contributes to exploring the work–family relationship of militaries who are not in specific situations, such as deployment, an area that has been less explored in the literature. Second, the military activity is known for its collective values that may take precedence over all else, even the family (Lester et al., 2011). By introducing WFE to the realm of military literature, we explore how the military professional activity could be seen as beneficial to family life. Third, this research advances current understanding about military workers’ well-being through their work–family relationship. Fourth, this study sets out to highlight the contribution of specific job characteristics that can promote harmony between work and family life. Hence, we expect to contribute to the military’s job design in such a way that it may benefit his or her workplace well-being while also taking the work–family relationship into consideration.

Job Characteristics and the Work–Family Relationship

The roots of WFC are based on a scarcity hypothesis (Goode, 1960) defending that an individual has limited resources such as energy, time, and attention to spend on life roles. Thus, when these resources become exhausted due to different norms and responsibilities, a conflict emerges and spills over from one domain to the other (Greenhaus & Beautel, 1985). Contrariwise, WFE has its roots in the expansionistic hypothesis that highlights the advantages of pursuing multiple roles (Marks, 1977; Sieber, 1974). An assumption of WFE is that there are five interdependent types of resources which are transferable between work and family domains that generate WFE: (1) skills, (2) psychological and physical resources, (3) sociocapital, (4) flexibility, and (5) material resources (Greenhaus & Powell, 2006). The WFE theory additionally acknowledges that the enrichment process may occur through two different processes: (1) an instrumental path in which the aforementioned resources are applied directly to the family domain and (2) an affective path where resources derived from one role (i.e., work) and produce positive affect in the other role (i.e., family) which, in turn, promotes high performance in the second role (i.e., family; Greenhaus & Powell, 2006).

Several studies have pointed to the importance of job characteristics as antecedents of both WFC and WFE (Carvalho & Chambel, 2014; Michel, Kotrba, Mitchelson, Clark, & Baltes, 2011). One of the most influential models to integrate important job characteristics is the JDCS model (Johnson & Hall, 1988; Karasek & Theorell, 1990). This model proposes that demands, control, and support are key job characteristics that predict outcomes in both negative and positive terms (Luchman & Gonzálex-Morales, 2013).

Job demands refer to those physical, psychosocial, and organizational aspects of the job that require sustained physical and/or mental effort and are, therefore, associated with certain physiological and/or psychological costs (Bakker & Geurts, 2004). The study of Burrell, Adams, Durand, and Castro (2006) analyzes specific demands in military service, which may be incompatible with the family harmony. Among the most critical factors, these authors described the permanent risk of mobility, residence in foreign countries, periodic separations from the family, and the risk of a service member injury or death. These demands may be a permanent concern for the militaries and their families. However, there are other demands in the military service that are referred to on a daily basis, such as the long, unpredictable hours of duty, pressures for military families to conform to accepted standards of behavior, and the masculine nature of the organizations (Burrell, Adams, Durand, & Castro, 2006). All things considered, we expect job demands to act as a threat in the family domain, to contribute to the presence of WFC, and to negatively impact the presence of positive synergies between work and family domains, that is, WFE.

The concept of job control can be defined as the degree of autonomy a worker has over his or her own immediate scheduling and tasks (Liu, Spector, & Jex, 2005). Military service is often characterized by unity, discipline, and sacrifice (Rahbek-Clemmensen et al., 2012), which may be regarded as antagonistic values to the presence of autonomy. A longitudinal study with militaries found that a lack of family-supportive work environments, where autonomy should have an important role, predicted military psychological strain over time (Odle-Dusseau et al., 2013). Thus, the lack of autonomy may be positively related to WFC. Nevertheless, during teamwork, militaries are relatively discreet when deciding which group tasks to perform and how to carry them out. More broadly, job autonomy has been theorized to be a job resource or an aspect of the working environment that allows an employee to, for instance, deal with job demands (Bakker & Demerouti, 2007). Hence, job autonomy may be considered a contribution to the emergence of WFE.

Generally, the support of a supervisor may be understood as the general expressions of concern by the supervisor (i.e., emotional support) or tangible assistance (i.e., instrumental support) that is intended to enhance the well-being of the subordinate (Kossek, Pichler, Bodner, & Hammer, 2011). The military working context has a highly centralized structure, where the supervisors play an essential role by managing the roll calls and strict orders that military workers are expected to follow (Chambel, Castanheira, Oliveira-cruz, & Lopes, 2015). Thus, the role of the supervisor is very well-defined. In this vein, Wadsworth and Southwell (2011) postulated that supervisors are often the lynchpins in service members’ quality of life and access to flexibility. This allows us to argue that the supervisor supportive role can act as a source of enrichment that spills over positively to the family domain. Moreover, the presence of this support does relate negatively to WFC. For instance, the fact that the supervisor listens to the employee’s problems could serve as an example for employees to develop their listening skills and apply them in the family context, that is, to listen to their children or spouse’s problems. Moreover, this supervisor listening attitude could prevent conflict occurrence. Taken together, we formulate in our first hypothesis:
Hypothesis 1: Job characteristics are related to WFE and WFC in a way that job demands are negatively related to WFE and positively related to WFC, and autonomy and supervisor support are positively related to WFE and negatively related to WFC.

Job Characteristics, the Work–Family Relationship, and Well-Being at Work

Burnout is generally used to describe a state of mental weariness. Maslach (2003) defined it as a psychological state associated with prolonged response to stressors in the work environment. Engagement reflects a motivational process characterized by positive feelings in relation to work (Schaufeli, Salanova, Gonzalez-Roma, & Bakker, 2002). Schaufeli and Bakker (2004) described burnout as a negative dimension of well-being, whereas work engagement is the positive dimension. These two constructs have been considered independent, moderately and negatively connected states, and are regarded as the best constructs for understanding well-being at work (Schaufeli & Bakker, 2004).

Inspired by the aforementioned JDCS model (Johnson & Hall, 1988; Karasek & Theorell, 1990), the job demands–resources (JD-R) model (Schaufeli & Bakker, 2004) explains how negative (burnout) as well as positive (engagement) aspects of well-being occur. First, the health impairment process occurs when high job demands (e.g., work overload, emotional demand, and organizational demand), which require sustained effort, may exhaust employees’ resources and possibly lead to burnout and health deterioration (Hakanen, Bakker, & Schaufeli, 2006). The literature already acknowledges that these high demands spill over to the family domain, giving rise to a conflict (Greenhaus & Beutell, 1985). Consequently, presence of WFC may be considered part of these chronic job demands. For instance, the fact that the employee has the urge to spend more time among the family and frequently feels that his or her work does not allow such availability may deplete the employee’s mental health and physical resources, ultimately leading to the presence of burnout (Schaufeli & Bakker, 2004).

Second, the motivational process occurs when the presence of resources (e.g., job autonomy and supervisor support) have the potential to increase employees’ motivation (Hackman & Oldham, 1980) and may lead to engagement. Therefore, through the motivational process, employees are susceptible to being more involved in the work domain, in meaningful tasks that may help them to acquire new skills or psychological states that enrich the family domain. Moreover, the work domain can also be associated with positive affect through this motivational process which, in turn, improves the family domain. Hence, WFE may be achieved and acts as a potential resource to increase motivation and, ultimately, work engagement.

Furthermore, the principles of the conservation of resources (COR) theory (Hobfoll, 2002) may also help to understand WFC and WFE as vehicles for the establishment of well-being at work. ten Brummelhuis and Bakker (2012) applied the COR model to the work–home interface by explaining how WFC and WFE emerge. Specifically, the primacy of loss resources, a central principle of COR, defends that individuals expend resources to address the presence of a stressor (i.e., role ambiguity and role conflict) and the stress develop if the individual has to invest in many resources (i.e., time, cognitive and physical energy; ten Brummelhuis & Bakker, 2012). Once stress sets in, it interferes with resource investment in the family, creating WFC (ten Brummelhuis & Bakker, 2012). The COR also states the presence of a primacy of resource investment in which individuals must invest resources in order to protect themselves against resource loss, recover from losses, and gain resources. Thus, WFE can be seen as a process whereby resources acquired in work domains lead to the development of personal resources (ten Brummelhuis & Bakker, 2012) that enrich the family domain. Moreover, the COR theory has contributed greatly to the explanation of well-being at work. In other words, resource depletion is viewed as the core of the burnout process (Westman, Hobfoll, Chen, Davidson, & Laski, 2005), and engagement may be viewed under the dynamics of resource gains (Hakanen, Perhoniemi & Toppinen-Tanner, 2008).

Accordingly, early findings have already acknowledged that WFC is positively related to burnout (Innstrand, Langballe, Espnes, Falkum, & Aasland, 2008) and WFE related to the presence of engagement (Hakanen et al., 2011). Thus, we established our second hypothesis:
Hypothesis 2: WFE and WFC are related to well-being at work in a way that WFE is positively related to engagement and WFC is positively related to burnout.

WFE and WFC as Mediators Between Job Characteristics and Well-Being at Work

Underpinned by the JD-R (Schaufeli & Bakker, 2004) and COR (Hobfoll, 2002) principles, we argue that WFC and WFE might explain the relationship between job characteristics (i.e., job demands, job autonomy, and supervisor support) and well-being at work (burnout and engagement). As discussed earlier, job characteristics can have an important role in the way the individual spills over the work role to the family role, whether positively or negatively. Indeed, once WFC and WFE emerge, they can play a pivotal role in both resource deterioration and resource gain (ten Brummelhuis & Bakker, 2012) and, consequently, be important mechanisms to explain the origins of burnout and engagement. Research has thus far shown that WFE and WFC are mediators between job characteristics and well-being (e.g., Carvalho & Chambel, 2014). Therefore, we established:
Hypothesis 3: The relationship between job characteristics and well-being at work is mediated by WFE and WFC in a way that:

Hypothesis 3a: The relationship between job characteristics and burnout is mediated by WFC.

Hypothesis 3b: The relationship between job characteristics and engagement is mediated by WFE.

Method

Participants and Procedure

This study was conducted in three units of the Portuguese Marine Corps: the Naval School, the Marine Rifle School, and the Marine Technology School. We choose these three units because workers had similar demographic characteristics and job conditions.

Before distributing the questionnaires, permission was obtained from the ethical committee of the Faculty of Psychology and from the Office of the Chief of Staff of the Navy. After that, the psychologist of each unit explains in person the study aim and the importance that the participation of them have. The next step was the distribution of the questionnaires by all workers (n = 400). After answer, workers returned the questionnaire to the researcher in a sealed envelope. The participation was voluntary, and the anonymity of answers was ensured.

A total of 274 (68.5%) questionnaires were collected. Since the goal of this study was to understand the work and family relationship of military employees, we selected the questionnaires of militaries who reported having at least one child and/or who were married or in a common law relationship. Thus, the final sample was 175. The participants performed different duties: soldier (N = 63; 36%), sergeant (N = 76; 43.4%), and officer (N = 35; 20.6%). Most respondents were males (155 = 88.6%) compared to the number of females (20 = 11.4%). In all, 3.4% of the sample are military for 1–5 years, 8.6% for 5–10 years, 38.3% for 10–20 years, and 49.7% for more than 20 years. Considering their marital situation, 8.6% were unmarried, 85.1% were married or in a common law relationship, and 6.3% were divorced or widowed.

Measures

Job characteristics

We measured job characteristics using the Job Content Questionnaire (Karasek et al., 1998), which was used in a previous Portuguese study (Carvalho & Chambel, 2014). Items for job demands were workload and time pressure (7 items)—“I have too much to do” and autonomy (4 items)—“I have the opportunity to decide how to organize my work.” Items were scored on a 5-point rating scale from (1) totally disagree to (5) totally agree. (α = .83 for workload and time pressure, and α = .83 for autonomy.)

Supervisor support

We measured supervisor support using a 5-item scale developed by Scandura and Graen (1984). This questionnaire was also previously used in a Portuguese military context (Chambel et al., 2015). A sample item is “My supervisor understands my problems and needs” and “My supervisor recognizes my potential.” Items were scored on a 5-point rating scale from (1) totally disagree to (7) totally agree (α = .94).

Work-to-family enrichment

We measured WFE using the 9-item scale of Carlson, Kacmar, Wayne, and Grzywacz (2006) that was used in a previous Portuguese study (Carvalho & Chambel, 2014). A sample item is “My involvement with my work helps me to understand different viewpoints and this helps me be a better family member” and “My involvement in my work helps me to develop my abilities and this helps me be a better family member.” Items were scored on a 5-point rating scale from (1) totally disagree to (5) totally agree (α = .94).

Work-to-family conflict

We measured WFC using an extended Portuguese version of a 15-item scale (Carlson, Kacmar, & Williams, 2000). Example items included “After work, I am too tired when I come home to do some of the things I’d like to do” and “My job takes time from me that I would like to spend with my family/friends.” The items were answered on a 5-point rating scale ranging from hardly ever (1) to almost always (5), and higher scores indicated greater interference with the family. This scale was previously used for the Portuguese population (Carvalho & Chambel, 2016; α = .93).

Well-being at work was measured with the assessment of work engagement and burnout. Work engagement was measured with a Portuguese version of a scale (Schaufeli, Bakker, & Salanova, 2006) that included vigor (3 items; e.g., “When I wake up in the morning, I feel good about going to work;” α = .87) and dedication (3 items; e.g., “My work inspires me;” α = .86). Burnout was assessed using a Portuguese version of a scale (Maslach, Jackson, & Leiter, 1996) that included exhaustion (5 items; e.g., “I feel emotionally drained by my work”; α = .92) and cynicism (5 items; e.g., “I question the significance of my work”; α = .87). Respondents answered the items of both subscales on a 7-point scale ranging from never (1) to every day (7). Both subscales have previously been used with Portuguese militaries (Chambel et al., 2015).

Control Variables

To explore the possible main effects of participants’ demographics, we included gender, tenure, and professional category in the structural models: gender as a dummy variable (0 = woman; 1 = man), tenure in years, and professional category also as a dummy variable (0 = soldier; 1 = officer or sergeant).

Statistical Analysis

Before testing our hypotheses, we conducted confirmatory factor analysis (CFA), with the use of the AMOS 23.0 program. This statistical procedure enabled us to examine our measurement model and compare it with other alternative models, following the two-step approach recommended by Anderson and Gerbing (1988). By performing the CFA, we aimed to analyze the extent to which the measures of the different constructs analyzed are empirically distinguishable (Mathieu and Taylor, 2006). This model—a seven-factor model—included all observed items loading on their respective latent variables, namely, job demands, autonomy, supervisor support, WFE, WFC, work engagement, and burnout. Work engagement was a second-order variable with vigor and dedication as first-order latent variables, and burnout was a second-order variable with exhaustion and cynicism as first-order latent variables. The latent variables were allowed to correlate with each other. We then conducted a Harman’s single-factor test (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003), which involved a CFA where all variables were allowed to load onto one general factor, one-factor model. Finally, another nested models with six latent variables were computed to test alternative combinations of observed variables. In one six-factor model, WFE and WFC were loaded onto one-factor model and in other six-factor model work engagement and burnout were loaded onto one factor.

Our research hypotheses were then verified by using structural equation modeling (SEM). Testing mediation analysis through SEM has some similarities to the approach adopted by Baron and Kenny (1986) and also provides several advantages (James, Mulaik, & Brett, 1982). As a confirmatory approach, SEM simultaneously tests the relationships among an initial variable(s), a mediator(s), and an outcome variable(s). In addition, SEM analyses derive from nested model comparisons, allowing us to hone in on the specific parameters of interest and to contrast a given pattern of effects against viable alternatives. To test the mediation relationship, three sets of SEMs were computed. First, a mediation model including full mediation of the relationship between the job characteristics (job demands, autonomy, supervisor support) and the two dimensions of work well—being—work engagement and burnout mediated by WFE and WFC, respectively, was analyzed. Then, in addition to the relationships established in the above mediation model, a partial mediation model was elaborated, which included direct relationships between the three job characteristics and the two dimensions of work well-being. Finally, we performed another partial mediation model that included not only the direct connection with job characteristics and workplace well-being but also a connection between WFC and engagement and a connection between WFE and burnout. To control for potential confounding effects, control variables were introduced in the models as observed variables.

Following established recommendations (Hu & Bentler, 1999), the evaluation of the overall goodness of fit of the models was based on the combination of several fit indices. Models were compared based on χ² difference tests and on other fit indices: the standardized root mean square (SRMR), the incremental fit index (IFI), the Bentler’s comparative fit index (CFI), and the root mean square error of approximation (RMSEA). For IFI and CFI, values above .90 represent a good model fit; and for SRMR and RMSEA, values equal to or below .07 indicate a good model fit.

Results

CFA

Our theoretical model with seven factors (i.e., job demands, job autonomy, supervisor support, WFE, WFC, burnout, and engagement) obtained a good fit (see Table 1). We compared this model with another three models: (1) one single-factor model where all items loaded on a single latent variable, (2) a six-factor model where WFE and WFC were grouped together under one factor, and (3) a six-factor model where all items of well-being at work (i.e., burnout and engagement) were grouped together under one factor. Our analysis showed a significantly poorer fit in the single-factor model as also in the other six-factor models compared to our theoretical model. In that sense, our theoretical model presented the best fit to the data.

Table 1.
Results of Confirmatory Factor Analysis.

Models χ²(df) Δχ²(df) SRMR IFI CFI RMSEA

Seven-factor model χ²(857) = 1,414.68 .07 .91 .91 .06

Six-factor model^a χ²(863) = 2,587.82 Δχ²(6) = 1,173.14 .13 .71 .71 .11

Six-factor model^b χ²(863) = 1,488.34 Δχ²(6) = 73.66 .09 .90 .90 .07

One-factor model χ²(879) = 3,535.90 Δχ²(22) = 2,121.22** .17 .56 .55 .13

Note. SRMR = standardized root mean square; IFI = incremental fit index; CFI = comparative fit index; RMSEA = root mean square error of approximation.

^aSix-factor model where work–family conflict and work–family enrichment were grouped in one factor. ^bSix-factor model where engagement and burnout were grouped in one factor.

p < .001.

Descriptive Analysis

The means, standard deviations, and correlation matrix are presented in Table 2. Analyzing the correlations among the studied variables (see Table 2), we found a significant negative relationship between job demands and WFE (r = −.14, p < .05). Job autonomy and supervisor support were significantly and positively related with WFE (r = .38, p < .01; r = −.43, p < .01, respectively). Furthermore, we found a significant positive relationship between job demands and WFC (r = .39, p < .01). Job autonomy and supervisor support were significantly and negatively related with WFC (r = −.24, p < .01; r = −.34, p < .01, respectively). Finally, we also found that WFE and vigor and dedication were significantly and positively related (r = −.45, p < .01; r = −.48, p < .01, respectively) and that WFC and exhaustion and cynicism were also positively related (r = −.44, p < .01; r = −.42, p < .01, respectively).

Table 2.
Means, Standard Deviations, and Correlation Coefficients Between Variables.

Variables Mean SD 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

1. Gender^a — —

2. Tenure^a — — .25

3. Job demands 3.14 0.67 −.04 −.06

4. Job autonomy 3.42 0.80 .08 .14* −.07

5. Supervisor support 5.39 1.25 .12* .10 −.12* .29**

6. WFE 3.36 0.74 −.02 .02 −.14* .38 .43

7. WFC 2.42 0.77 .02 −.09 .39 −.24 −.34 −.23

8. Exhaustion 2.53 1.64 −.08 −.12* .36 −.17 −.28 −1.30 .48

9. Cynicism 1.92 1.63 −.04 −.09 .10 −.24 −.28 −.37 .34 .58

10. Vigor 4.53 1.33 −.06 .07 −.14* .38 .38 .45 −.44 −.23 −.40

11. Dedication 4.61 1.35 .02 .10 −.16* .38 .41 .48 −.42 −.20 −.43 .87**

Note. Gender was a dummy variable (women = 0; men = 1) than correlations between this variable and continuous variables were point biserial; tenure was an ordinal variable (1 = less than 1 year, 2 = between 1 and 5 years, 3 = between 5 and 10 years, 4 = between 10 and 20 years, and 5 = more than 20 years) than correlations between this variable and continuous variables were biserial; and the correlation between gender and tenure was rank serial. WFE = work–family enrichment; WFC = work–family conflict.

p < .05. p < .01.

Structural Models

To test the hypothesized relationships, we first tested our theoretical model (Model 1) where we considered a full mediation among the constructs of the study. Model 1 provided an adequate fit for the data. Then, we compared our theoretical model with another two models in which we included different paths that were also theoretically plausible (Table 3).

Table 3.
Results of Structural Equation Models.

Models Goodness-of-Fit Indicators of Structural Models

χ²(df) Δχ²(df) SRMR RMSEA IFI CFI

Model 1 (theoretical model) χ²(980) = 1,582.41 .09 .06 .90 .90

Model 2 χ²(974) = 1,562.46 Compare to Model 1 Δχ²(6) = 19.95 .08 .06 .90 .90

Model 3 χ²(971) = 1,535.89 Compare to Model 2 Δχ²(3) = 26.57 .08 .06 .91 .91

Note*. SRMR = standardized root mean square; IFI = incremental fit index; CFI = comparative fit index; RMSEA = root mean square error of approximation.

**p < .001.

Model 2, to which the connection between job characteristics and well-being at work (i.e., burnout and engagement) was added to test partial mediation, also presented an acceptable fit. When we compared this model with the theoretical model (Model 1), Model 2 presented a better fit, Δχ²(6) = 19.95, p < .001. Then, we compared Model 2 with Model 3 that included not only the direct connection with job characteristics and well-being but also a connection between WFC and engagement and a connection between WFE and burnout. When we compared Model 3 with Model 2, the former presented a better fit, Δχ²(3) = 26.57, p < .001. Therefore, Model 3 became our final model.

Analyzing the standardized coefficients for each of the significant paths in Model 3 (see Figure 1), we observed a significant and negative relationship between job demands and WFE, a significant and positive relationship between job autonomy and WFE, and a significant and positive relationship between supervisor support and WFE. Additionally, we observed a significant and positive relationship between job demands and WFC, a significant and negative relationship between autonomy and WFC, and a significant and negative relationship between supervisor support and WFC. Taken together, these results support our Hypothesis 1.

Figure 1.
The final model (standardized path coefficients).

Moreover, we found a significant and positive relationship between WFC and burnout, and a significant and positive relationship between WFE and engagement. Thus, our Hypothesis 2 was supported.

To analyze our mediation hypothesis (Hypothesis 3a), we performed the Sobel test in order to confirm whether WFC mediated the relationship between job characteristics and burnout. We verified that the relationship between job autonomy and burnout through WFC was not statistically significant. However, we verified that the relationship between job demands and burnout through WFC was significant (Z = 3.05; p < .001) and that the relationship between supervisor support and burnout through WFC was also significant (Z = −2.38; p < .001). Thus, WFC acted as a mediator between the relationship of job demands and burnout and between supervisor support and burnout. Thus, our Hypothesis 3a was partially supported.

Regarding WFE as mediator (Hypothesis 3b), we observed that the relationship between job demands and engagement through WFE was not statistically significant. However, the relationship between job autonomy and engagement through WFE was significant (Z = 2.44; p < .05) and also between supervisor support and engagement through WFE (Z = 3.22; p < .001). Therefore, WFE acted as a mediator between the relationship of job autonomy and engagement and between supervisor support and engagement. Thus, Hypothesis 3b was partially supported.

Based on our predictions, we also found (1) a significant and negative relationship between WFC and engagement, (2) a significant and negative relationship between WFE and burnout, and (3) a significant and directly positive relationship between job autonomy and engagement. Accordingly, as we also verified that the relationship between all job characteristics and WFC and WFE were significant, we tested to ascertain whether WFC played a mediating role between job characteristics and engagement and whether WFE also played a mediating role between job characteristics and burnout. The Sobel test revealed that WFC also played a mediating role between job demands and engagement (Z = −2.55; p < .05) and between supervisor support and engagement (Z = 2.11; p < .05). However, WFE did not play a mediating role between any job characteristic and burnout.

The squared multiple correlations suggested that 40% of the variance of the WFC, 32% of the variance of the WFE, 58% of the variance of burnout, and 48% of the variance of engagement were explained by the relations in the path model. The control variables contributed to explain the variance. Gender was related to supervisor support (β = .17, p < .05); professional category was related to job autonomy (β = .30, p < .001), supervisor support (β = .25, p < .001), and WFC (β = −.18, p < .05).

Discussion

The aim of this study was to shed some light on the role that the work–family relationship plays in the militaries’ workplace well-being. We observed that job characteristics contribute to explaining the presence of WFC and WFE, which also contribute to explaining well-being at work. Furthermore, both WFC and WFE play a mediating role to explain the relationship between job characteristics and workplace well-being. Interestingly, WFC is also related to engagement and WFE to burnout. Moreover, WFC plays an important role in explaining the relationship between job characteristics (i.e., job demands and supervisor support) and engagement.

The findings largely support that job characteristics are related to WFC and WFE. This result is consistent with the principles of JDCS (Johnson & Hall, 1988; Karasek & Theorell, 1990). More specifically, job demands contribute to the presence of conflict situations between work and family roles. Conversely, job autonomy and supervisor support help militaries to transfer positive synergies that improve their quality of life in the family domain. Early findings have already advanced the importance of these job characteristics for the work–family relationship in different work environments: bank employees (Carvalho & Chambel, 2014) and hospital and childcare employees (Geurts, Kompier, Roxburgh, & Houtman, 2003). However, in this study, we particularly observed that job demands are a threat to work–family harmony, while job autonomy and supervisor support are important job characteristics to promote WFE in military contexts.

The results also show that WFC contributes to the presence of burnout and WFE contributes to the presence of engagement. More interestingly, our study found support for the role of WFC in explaining the relationship between job characteristics (i.e., demands and supervisor support) and burnout. This result underlined that as a consequence of the presence of demands and lack of supervisor support, militaries feel a depletion of their resources which threatens their energy and evokes a conflict in their family context. As a consequence, health deterioration of the military will be revealed in the work domain and he or she will feel exhaustion and cynicism (i.e., burnout). This result is consistent with the assumption of the JD-R model and the primacy of resource loss of the COR theory, which considers that chronic job demands may deplete employees’ mental and physical resources, giving rise to a resource loss and leading to burnout and health deterioration (Hobfoll’s, 2002; Schaufeli & Bakker, 2004; ten Brummelhuis & Bakker, 2012). This study also found support for the role of WFE in explaining the relationship between job characteristics (i.e., autonomy and supervisor support) and engagement. Hence, the presence of job autonomy and supervisor support helps militaries to gain resources and to feel positive affect regarding their work, which has positive consequences for their family lives. Correspondingly, these militaries will feel more vigor and dedication in their work (i.e., engagement). The motivational process of the JD-R and the primacy of resource investment that begins with the presence of a suitable job which increases employees’ motivation and leads to work engagement (Hobfoll, 2002; Schaufeli & Bakker, 2004; ten Brummelhuis & Bakker, 2012) are in keeping with these findings.

However, the results did not support the mediating role of WFC between job autonomy and burnout and the mediating role of WFE between demands and engagement. This result is consistent with the JDCS (Johnson & Hall, 1988; Karasek & Theorell, 1990) where job autonomy offered a considerable contribution to positive psychological states (i.e., motivation and learning), whereas job demands played a role in the emergence of negative psychological states (i.e., strain, poor health, and ill-being). Moreover, the role of job autonomy is reinforced as important in the establishment of well-being at work whether through WFE or directly. Halbesleben (2010), in the meta-analytic study of antecedents of engagement, already acknowledged the primacy of job autonomy in explaining this positive psychological state in the work context. Since the mind-sets of military leaders are perceived as closed-minded and unyielding (Wadsworth & Southwell, 2011) and the supervisor–employee relationship is characterized by submission to the hierarchy (Chambel et al., 2015), it seems particularly challenging to create a military work environment characterized by autonomy and control over work.

Based on our predictions, this study presents some findings that allow us to address additional conclusions. We observed that WFE is negatively related to burnout and WFC is negatively related to engagement, which is also consistent with the assumption that WFE contributes negatively to negative states at work and WFC also contributes negatively to positive states at work. Similarly, Lu and Chang (2014) also demonstrated that WFE is negatively related to burnout and WFC is negatively related to a positive work variable, that is, job satisfaction. Therefore, the importance of the simultaneous analysis of the negative and positive perspectives of the work and family relationship and their positive and negative effects is highlighted. Moreover, our findings additionally suggested that WFC acts as a mediator between the relationship of job characteristics (i.e., job demands and supervisor support) and engagement. This finding could also be related to the COR theory (Hobfoll, 2002) assumptions: (1) the loss of resources occurs quickly and powerfully and (2) the loss is more potent than the gain. Future longitudinal studies should analyze the empirical support of these assumptions. Notwithstanding, it is important to underline the importance of these findings for the military context. More specifically, different studies have already stated that work engagement is essential to prevent junior military personnel from leaving the Army (Alarcon et al., 2010), to protect soldiers from the negative effects upon arrival from deployment and stressful events (Britt & Bliese, 2003), and, generally, to maintain officers’ and soldiers’ well-being and motivation (Chambel & Oliveira-Cruz, 2010). Similarly, it is crucial to avoid burnout in military employees in order to prevent a lack of motivation toward their work (Chambel et al., 2015), breakdown through its effects on group cohesion, morale, job performance, and physical and psychological health (Wilcox, 1994). Accordingly, our results demonstrated that engagement is potentiated via WFE by explaining the relationship between job characteristics (i.e., job autonomy and supervisor support) and this positive state. Nonetheless, this study also emphasized that engagement is restrained through the presence of WFC which also plays a mediating role between job characteristics (i.e., job demands and supervisor support) and this positive psychological state. Moreover, burnout is also potentiated via WFC by explaining the relationship between job characteristics (job demands and supervisor support) and this strain syndrome. Overall, these results underlined that in order to maintain militaries’ well-being, the prevention of WFC and simultaneously the promotion of WFE should be taken into consideration.

The present study findings should be considered in light of certain limitations. First, the conclusions of our study are based solely on self-reported data, collected at one point in time, causing common method variance. This cross-sectional design of the study does not allow for firm conclusions regarding causality. For example, it would be interesting to analyze the dynamics of WFC and WFE for well-being at work based on COR and JDR tenets longitudinally. However, it should be noted that the recommendations of Podsakoff, MacKenzie, Podsakoff, and Lee (2003) have been followed to minimize potential common method biases. Second, the generalization of these results cannot be extended to militaries working in different contexts or situations, since military employees may face different challenges and environmental conditions during their job. Therefore, future studies should analyze the presented model with other militaries, namely, from the Army, those in peacekeeping missions or with those in war situations.

From a practical point of view, this study stresses the importance of taking the work–family relationship into account for militaries’ well-being by promoting WFE and decreasing WFC. The role that job characteristics can have in this process has been highlighted, namely, the presence of job autonomy, supervisor support, and low job demands.

Models	χ²(df)	Δχ²(df)	SRMR	IFI	CFI	RMSEA
Seven-factor model	χ²(857) = 1,414.68**		.07	.91	.91	.06
Six-factor model^a	χ²(863) = 2,587.82**	Δχ²(6) = 1,173.14**	.13	.71	.71	.11
Six-factor model^b	χ²(863) = 1,488.34**	Δχ²(6) = 73.66**	.09	.90	.90	.07
One-factor model	χ²(879) = 3,535.90**	Δχ²(22) = 2,121.22**	.17	.56	.55	.13

Variables	Mean	SD	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.
1. Gender^a	—	—
2. Tenure^a	—	—	.25**
3. Job demands	3.14	0.67	−.04	−.06
4. Job autonomy	3.42	0.80	.08	.14*	−.07
5. Supervisor support	5.39	1.25	.12*	.10	−.12*	.29**
6. WFE	3.36	0.74	−.02	.02	−.14*	.38**	.43**
7. WFC	2.42	0.77	.02	−.09	.39**	−.24**	−.34**	−.23**
8. Exhaustion	2.53	1.64	−.08	−.12*	.36**	−.17**	−.28**	−1.30**	.48**
9. Cynicism	1.92	1.63	−.04	−.09	.10	−.24**	−.28**	−.37**	.34**	.58**
10. Vigor	4.53	1.33	−.06	.07	−.14*	.38**	.38**	.45**	−.44**	−.23**	−.40**
11. Dedication	4.61	1.35	.02	.10	−.16*	.38**	.41**	.48**	−.42**	−.20**	−.43**	.87**

Models	Goodness-of-Fit Indicators of Structural Models
Model 1 (theoretical model)	χ²(980) = 1,582.41**		.09	.06	.90	.90
Model 2	χ²(974) = 1,562.46**	Compare to Model 1 Δχ²(6) = 19.95**	.08	.06	.90	.90
Model 3	χ²(971) = 1,535.89**	Compare to Model 2 Δχ²(3) = 26.57**	.08	.06	.91	.91

Footnotes

Declaration of Conflicting Interests

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

Funding

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

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