Vol. 34. Num. 2. 2018. Pages 69-81

Employee Well-being and Life Satisfaction in Argentina: The Contribution of Psychological Detachment from Work

[Bienestar laboral y satisfacción vital en Argentina: el rol del distanciamiento psicológico]

Leonardo A. Medrano and Mario A. Trógolo

Universidad Siglo 21, Córdoba, Argentina

Recibido a 12 de Julio de 2017, Aceptado a 23 de Febrero de 2018


Los estudios en el ámbito organizacional han demostrado la influencia de varios dominios en el bienestar laboral de los empleados. Sin embargo, estos dominios han sido analizados por lo general de manera separada, al tiempo que la mayoría de la investigación empírica sobre el bienestar laboral proviene de Estados Unidos y los países europeos, especialmente Holanda y España. En comparación, la investigación científica sobre el bienestar laboral en los países latinoamericanos es limitada. El presente trabajo consistió en desarrollar y poner a prueba un modelo de bienestar laboral en Argentina. Se aplicaron medidas de ocio, distanciamiento psicológico, recursos laborales, conflicto trabajo-familia, bienestar laboral (engagement y burnout) y bienestar general (satisfacción vital) a una muestra representativa nacional de 1,060 trabajadores. Los análisis mediante modelo de ecuaciones estructurales indicaron que el modelo presenta un buen ajuste. Se discuten las implicaciones de este estudio y se recomiendan futuras líneas de investigación que podrían contribuir a una comprensión más refinada de los resultados obtenidos en este estudio.


Previous research has demonstrated the impact of various life domains on employee well-being. However, these domains have been commonly examined separately. In addition, most existing studies on this topic stem from North America and Western European countries, particularly Spain and Netherlands. Comparatively, little research has been conducted in Latin American countries. The aim of this research was to develop and test a model of employee well-being in Argentina. One thousand and sixty employees from a national representative sample completed measures of leisure, psychological detachment from work, job resources, work-family conflict, work-related well-being (engagement and burnout), and subjective well-being (life satisfaction). Results from structural equation modeling indicated that the model fit the data well. We discuss practical implications of the findings for employee well-being and suggest future research building upon study limitations that may contribute to a more refined understanding of the results outlined in this study.

Palabras clave

Recursos laborales, Distanciamiento psicológico, Conflicto familia-trabajo, Bienestar laboral, Argentina.


Leisure, Job resources, Detachment, Work-family conflict, Employee well-being, Argentina.


Research on employee well-being, its antecedents and consequences has flourished in last decades (Salanova, Del Líbano, Llorens, & Schaufeli, 2014). Plenty of research has shown that job characteristics are crucial for employee well-being (e.g., Lee & Ashforth, 1996; Quick & Tetrick, 2003; Warr, 1999). In addition to workplace factors, the way people spend their off-job time to recover from workdays is also relevant (e.g., Amstad, Meier, Fasel, Elfering, & Semmer, 2011; Fritz, Yankelevich, Zarubin, & Barger, 2010; Siltaloppi, Kinnunen, & Feldt, 2009). Many studies have also stressed the influence of work-family interface on employee well-being (e.g., Frone, Russell, & Cooper, 1992; Grant-Vallone & Donaldson, 2001; Parasuraman & Simmers, 2001). However, as Sonnentag, Mojza, Binnewies, and Scholl (2008) emphasized, these domains have been commonly studied separately but their effects on well-being might not be independent from each other and, actually, they may interact. Thus, it remains necessary to combine these domains in one single study and to develop multivariate models in order to better understand their effects on employees’ well-being.

Additionally, despite the acceleration of cultural convergence due to the intensifying globalization, which leads some voices to advocate for the emerging of a universal culture (Friedman, 2005), national cultural differences still remain and affect attitudes and behaviors at the workplace (Taras, Steel, & Kirkman, 2011). Indeed, people perceive differently their job characteristics, organizational conditions, and well-being across countries and there is also evidence for cross-national differential effects of working conditions on well-being (Pisanti, van der Doef, Maes, Lazzari, & Bertini, 2011). Hence, employee well-being is influenced by cultural and contextual factors that can vary from one country to another, which may limit the generalizability of research findings and theoretical models developed elsewhere. Thus, it is important to build up culture-sensitivity models that support interventions to enhance well-being at work. More importantly, research on employee well-being in Argentina is limited (e.g, Díaz Echenique, Stimolo, & Caro, 2010; Omar, 2011; Paris & Omar, 2008; Trógolo, Pereyra, & Spontón, 2014) and, to the authors’ best knowledge, no theoretical model has been yet proposed.

A number of studies on well-being at work have been conducted in Spain (e.g., Bòria-Reverter, Crespi-Vallbona, & Mascarilla-Miró, 2012; Durán, Extremera, Montalbán, & Rey, 2005; Moreno-Jiménez & Gálvez Herrer, 2013; Salanova et al., 2014). Despite the similarities between Spain and Argentina, there are some important differences in working conditions. Specifically, in spite of the rapid economic growth and the reduction of unemployment, an elevated number of Argentinean works in precarious job (Beccaria & Groisman, 2015). It is estimated that nearly 34% of the Argentinean workers are currently unregistered (INDEC, 2017). Thus, more than one third of employees are in precarious jobs, without contract that guarantee and protect their labor rights, which make them more vulnerable to abuses and injustices (Grisolia, 2012) and at higher risk of becoming impoverished due to low income (Garzón-Duque, Cardona-Arango, Rodríguez-Ospina, & Segura-Cardona, 2017). By contrast, precarious and unregistered jobs are markedly lower in Spain (Secretaría de Políticas Sociales, Empleo y Seguridad Social, 2017). Such differences in job-related conditions may have different impact on employee well-being and, consequently, findings from Spain may not be applicable to Argentina.

The first objective of the current study was to propose an integrative model of employee well-being by merging theoretically and empirically relevant variables from leisure, recovery, job, and work-family interaction. The second objective was to test the proposed model in a large representative sample of Argentinian workers. Specifically, the model includes effects of leisure activities, psychological detachment from work, job resources and work-family conflict on individuals’ work-related well-being (i.e., engagement and burnout), and general well-being (i.e., life satisfaction). In doing so, the current study extends past research by integrating various areas of research.

In addition, the current study contributes to the large body of empirical studies on psychological detachment and employee well-being by examining potential mediators that have not been addressed before. In particular, given that being mentally attached by work during non-work time interferes with behaviors at home (Sonnentag, Binnewies, & Mojza, 2010), and that work-family balance is an important source of well-being (Greenhaus, Collins, & Shaw, 2003), we examined whether work-family conflict (i.e., a state of negative balance between work and family roles) plays a mediational role between psychological detachment and employee well-being. By examining unexplored, mediational effects, our research seeks to provide new insights into the relationship between psychological detachment and employee well-being. Moreover, studies reported in the literature have shown inconsistent relationships so far between leisure activities and well-being, with some studies showing passive leisure activities to be negatively correlated with well-being (Argyle, 2001; Csikszentmihalyi & Hunter, 2003), and active pursuits to be positively associated with higher levels of well-being (Csikszentmihalyi & Hunter, 2003; Holder, Coleman, & Shen, 2009) while others studies showed both passive and active leisure to have a positive effect on well-being (Sonnentag, 2001). One possible explanation for the mixed findings is that the association between leisure and well-being is a more complex one. In particular, based on theoretical reasoning, we look at job resources as a moderator between leisure activities and psychologically detachment, which subsequently influence employee well-being. Finding moderators for this relation is particularly important because it may help to understand why some employees find it easier to psychological detach from work during off-job time while other employees do not, providing a possible entry for target interventions that may facilitate employees to mentally disengage from work and enhance well-being. Finally, by testing the model in Argentinian workers, we expect to provide a useful framework that guides practitioners in developing evidence-based interventions to increase well-being at work.

Empirical and Theoretical Background

Employee Well-being

According to Salanova et al. (2014), the multidimensional model of employee well-being, engagement and burnout are core aspects of well-being at work. Engagement is a pervasive state of positive emotional attachment and motivation toward one’s work (Hallberg & Schaufeli, 2006). It is characterized by vigor (i.e., high levels of energy while working and willingness to invest effort in work), dedication (i.e., sense of enthusiasm, inspiration, pride, and being challenged by work), and absorption (i.e., being happily immersed in one’s work, whereby time passes quickly and one has difficulties detaching; Schaufeli, Salanova, González-Romá, & Bakker, 2002). Burnout, on the other hand, is considered to be the conceptual opposite of engagement and is defined as a response to prolonged occupational stress characterized by exhaustion (i.e., low levels of energy), cynicism (i.e., lack of enthusiasm and negative attitude towards one’s job), and reduced professional efficacy (i.e., the belief that one is no longer efficacious in fulfilling one’s job responsibilities; Maslach, Schaufeli, & Leiter, 2001). Despite such theoretical formulations, studies have shown that vigor and dedication are the core aspects of engagement (e.g., Llorens, Schaufeli, Bakker, & Salanova, 2007) while exhaustion and cynicism are considered the core dimensions of burnout (Green, Walkey, & Taylor, 1991). Thus, in the current study we focus on the core dimensions of engagement and burnout.

Previous research has revealed that engagement and burnout are particularly important for an individual’s general well-being. For example, Durán et al. (2005) showed that engagement and burnout correlated positively and negatively, respectively, with life satisfaction. In a similar vein, using a three-wave longitudinal research, Hakanen and Schaufeli (2012) found that engagement and burnout predicted depressive symptoms and life satisfaction over time, and not vice versa. Specifically, they found that burnout positively predicted depressive symptoms and negatively life satisfaction while engagement had a negative effect on depressive symptoms and a positive effect on life satisfaction. Thus, well-being at work appears to spill over to general well-being, either enhancing or impairing it. Based on this argument and prior studies, we expected that work-related well-being (i.e., burnout and work engagement) spreads to overall subjective well-being. In this study, we focus on life satisfaction as a main indicator of subjective well-being. Life satisfaction refers to a subjective global assessment of a person’s quality of life (Diener, Emmons, Larsen, & Griffin, 1985). Thus, we proposed the following hypotheses:

Hypothesis 1a (H1a): Work engagement is positively related to life satisfaction.

Hypothesis 1b (H1b): Burnout is negatively related to life satisfaction.

Job Resources

According to the Job Demands-Resources (JD-R) Model (Bakker & Demerouti, 2007), work conditions can be represented into two broad categories regardless of any occupation: job demands and job resources. Briefly, job demands are those aspects of job that entail physical and/or mental effort and are therefore associated with costs (e.g., fatigue). In contrast, job resources reduce job demands and the subsequent costs, facilitate the accomplishment of work goals, and/or stimulate personal growth. Since job demands drain employees’ physical and mental resources while job resources buffer the impact of job demands on job strain, poor job resources lead to depletion of individuals’ energy, which eventually results in health problems such as burnout (Bakker, Demerouti, & Euwema, 2005; Xanthopoulou, Bakker, Demerouti, & Schaufeli 2007). Complementary, job resources play an important motivational process since they foster employees’ growth, learning, and development, which lead to invest energy and dedication. Thus, the presence of job resources increases engagement, whereas their absence leads to burnout (Bakker, Hakanen, Demerouti, & Xanthopoulou, 2007; Nahrgang, Morgeson, & Hofmann, 2011). Building on JD-R model and empirical research, we proposed the next two hypotheses:

Hypothesis 2a (H2a): Job resources are positively associated with engagement.

Hypothesis 2b (H2b): Job resources are negatively associated with burnout.

Psychological Detachment

According to JD-R, workplace conditions are relevant to employee well-being. However, it does not explain why some employees are more likely to be burned-out (or engaged) whereas others are not in spite of working at the same place. This is probably the reason why researchers have focused in the last years on leisure time and specific activities people pursue during off-job time to recover from work (Demerouti, Bakker, Geurts, & Taris, 2009; Rook & Zijlstra, 2006). Recovery refers to a process of psycho-physiological unwinding after effort investment at work (Geurts & Sonnentag, 2006). In particular, psychological detachment from work has been identified as the most relevant recovery experience (Sonnentag & Fritz, 2007). Etzion, Eden, and Lapidot (1998) defined detachment as “individual’s sense of being away from the work situation” (p. 579). As such, psychological detachment refers to temporary mental disengagement from one’s job during leisure time. It implies to stop thinking about job-related issues and not working at home during off-job time.

Cumulative research indicates that employees who are able to psychologically detach from work during non-work hours report a better health and well-being than employees who are less able to do so (Moreno-Jiménez & Gálvez Herrer, 2013; Sonnentag & Bayer, 2005; Sonnentag & Fritz, 2007). In support of this, Fritz et al. (2010) found that individuals who have difficulties to mentally switch-off from work report increased levels of burnout. Similar results were found in a two-year longitudinal study (Söderström, Jeding, Ekstedt, Perski, & Akerstedt, 2012) suggesting that lack of psychological detachment might be one of the causal precursors of burnout. Additionally, there is some evidence that psychological detachment from work may matter for engagement as well (Kühnel, Sonnentag, & Westman, 2009). For example, Sonnentag (2003) found in a diary study that day-level recovery was positively associated to day-level work engagement during the subsequent workday. The Conservation of Resources (COR) theory (Hobfoll, 1989) and the Broaden-and-Build (B&B) theory (Fredrickson, 2001) provide a useful framework to explain how psychological detachment works. The core assumption of the COR theory is that people are motivated to obtain, retain, and protect their resources. Since facing job demands requires effort and therefore drain individuals’ resources, people need to recover from work as a way to restore their lost resources (Sonnentag & Fritz, 2007). Based on this idea, continued immersed with job-related problems and thoughts during non-work time add to energy depletion, leading to exhaustion. Exhausted employees, in turn, may tend to withdrawal at work (i.e., cynicism) as a self-regulatory mechanism in order to protect their limited energetic resources and avoid further loss (Carver, 2004). Nonetheless, psychological detachment from work also provides the opportunity to engage in relaxing and pleasurable activities (e.g., watching TV, taking a walk in a sunny day, doing hobbies or exercises) during off-job hours that contribute to gain new resources. According to the B&B theory, positive emotions broaden an individual’s mental and actions repertoire, that is, it provides new resources (Fredrickson, 2001). Thus, psychological distance from work helps one to build up personal resources (Sonnentag et al., 2008), which should facilitate individuals to experience engagement at work (Kühnel et al., 2009). In sum, psychological detachment from work may operate in different ways. It may generate opportunities for cessation or restoration of drained resources, as well as to obtain new resources (Davidson et al., 2010). Drawing upon COR and B&B resource-based theories, we hypothesized that:

Hypothesis 3a (H3a): Psychological detachment from work during off-job time is positively related to engagement.

Hypothesis 3b (H3b): Psychological detachment from work during off-job time is negatively related to burnout.

It is worth noting that whereas there is a lot of evidence supporting the beneficial effects of psychological detachment on employee well-being, some studies have shown only a modest contribution. For instance, Fritz et al. (2010) found that psychological detachment from work accounted for only 6% of the variance in burnout and 7% of the variance in life satisfaction. These results point to the possibility that the main effect of psychological detachment from work on employee well-being might be rather indirect, which calls for the analysis of third variables as potential mediators.

Work-family Conflict

In particular, psychological detachment from work might affect behaviors at home (Sonnentag et al., 2010). A person who is continuously self-absorbed in work-related thoughts might devote at home less attention to family members. Thus, they become less involved in the family domain and as a result the quality of social interaction at home might be negatively affected (Story & Repetti, 2006).

The negative influence of employees’ work on their personal functioning at home has been referred to as work-family conflict (WFC; Greenhaus & Beutell, 1985). WFC is a form of inter-role conflict in which pressure at work intrudes into family, interfering with family roles. Implicit to the definition of WFC is the role of psychological detachment. Accordingly, lack of psychological detachment implies doing work and being mentally occupied by job-related concerns during non-work time, which makes work to encroach into family more easily. Because dealing with work issues at home spend additional energy and resources, employees who are unable to detach from work may reduce their resources available to fulfill obligations associated with their family roles (Eckenrode & Gore, 1990). Such situation, then, may increase conflicts at home as family members expect the entirely commitment of the individual in family life and the fulfillment of family demands (Demerouti, Taris, & Bakker, 2007). Therefore, low psychological detachment not only continues draining energetic resources, but may also lead to WFC, putting additional stressors on individuals’ psycho-physiological system, which takes away additional resources, creating a resource “loss spiral” (Hobfoll, 1989, p. 514) that, ultimately, may lead to increased feelings of burnout (Allen, Herst, Bruck, & Sutton, 2000). Thus, we proposed the following hypotheses:

Hypothesis 4a (H4a): Psychological detachment from work is negatively related to WFC.

Hypothesis 4b (H4b): WFC is positively related to burnout.

Hypothesis 4c (H4c): The relationship between psychological detachment from work and burnout is partially mediated by WFC.

In contrast to decreased involvement in family roles and the associated higher WFC, Graves, Ohlott, and Ruderman (2007) argued that family commitment leads to work role enhancement because positive family experiences generate resources. According to this view, one might assume that being psychological detached from work would lead to more family commitment and therefore to less WFC, as individuals can temporarily forget about job-related concerns and fully concentrate on other aspects of life (Sonnentag, Unger, & Nägel, 2013), such as family life. Engaging in family life, in turn, would provide new resources leading to work role enhancement (high work engagement; cf. Rothbard, 2001). However, Montgomery, Peeters, Schaufeli, and Den Ouden (2003) failed to find an association between WFC and engagement. Additionally, Halbesleben, Harvey, and Bolino (2009) in a multi-sample study found that engagement increased work interference with family over time, indicating that engagement should be considered as an antecedent rather than a consequent of WFC. In short, it appears that WFC may be a relevant precursor of burnout but not of engagement. On the basis of this literature review, we argue that the mediating role of WFC may be only relevant for the relationship between psychological detachment and negative experience of well-being at work (i.e., burnout), but does not account for the relationship between psychological detachment and positive experience of well-being at work (i.e., engagement).

Job Resources and Psychological Detachment

Empirical research has shown that psychological detachment depends to a great extent on specific job characteristics at the work setting (Sonnentag, 2012; Sonnentag, Arbeus, Mahn, & Fritz, 2014; Sonnentag & Bayer, 2005). A common finding indicates that high job resources lead to high psychological detachment from work. For example, in a longitudinal study, Rodríguez-Muñoz, Sanz-Vergel, Demerouti, and Bakker (2012) found that job autonomy positively predicted recovery opportunities, suggesting that employees who have decision latitude to organize their work tasks and decide when to stop may have more available time to engage in recovery activities, making psychological detachment more likely. In addition, some other studies (Blanco-Donoso, Garrosa, Demerouti, & Moreno-Jiménez, 2017; Sonnentag & Fritz, 2007) found that social support from colleagues was positively related to psychological detachment. Accordingly, social support offers both instrumental and emotional support (van den Tooren, de Jonge, & Dormann, 2012) enabling employees to achieve their work goals and to share their personal feelings, which may help to reduce the tendency to worry and ruminate about work-related issues and therefore to facilitate mental disengagement from work. Based on this literature, we proposed the next hypothesis:

Hypothesis 5 (H5): Job resources are positively related to psychological detachment from work.


Leisure involves non-work activities engaged in for enjoyment (Hills & Argyle, 1998), being freely chosen, based on an individual’s interest (Lu & Hu, 2005). Leisure researchers have commonly distinguished between passive and active leisure (Sonnentag, 2001; Sonnentag & Natter, 2004). While the former typically involve low-effort activities (e.g., watching TV, listening to music, or lying on the couch) that pose no demands on the psycho-physiological system, the latter imply pursuing activities that require some degree of effort, such as social (e.g., meeting with friends, family members) and physical (e.g., doing exercise or sports) activities. Empirical evidence has shown that both types of activities are relevant to well-being, although results have been inconsistent. For example, Sonnentag (2001) found that low-effort and social activities were positively related to well-being, while Sonnentag and Natter (2004) and Rook and Zijlstra (2006) found negative or no effect of such activities on well-being. In contrast, results have quite consistently shown positive relations between physical activities and well-being (Hassmén, Koivula, & Uutela, 2000; Jiménez, Martínez, Miró, & Sánchez 2008).

A possible explanation is that the type of activity pursued itself may be not the only factor relevant for well-being. Rather, it may depend on an individual’s characteristics and preferences (Demerouti & Sanz-Vergel, 2012). However, we also note that there might be other explanations accounting for such mixed findings. For example, imagine an individual running in a warm evening or meeting with friends but at the same time thinking (or talking) about the task that remained unfinished or ruminating about how to deal with the workload of next working days to come. In such a situation, the likelihood of becoming fully immersed in leisure activities would be low (Sonnentag et al., 2008), which may negatively influence recovery and well-being. Thus, it seems that distraction rather than the activity pursued may be essential, as it provides a respite from work-related thoughts and daily job stressors (Yeung, 1996). As job resources reduce the demanding aspects of a job, it is conceivable that employees with higher job resources (e.g., autonomy and social support) may find it easier to forget from work and stop thinking about job-related issues after work hours, being more able to fully immerse in leisure activities, which facilitates psychological detachment from work. Thus, we propose that leisure activities have a positive impact on psychological detachment from work, and that this effect will be stronger for employees with more availability of job resources. Thus, we proposed the following hypotheses:

Hypothesis 6a (H6a): Leisure is positively related to psychological detachment.

Hypothesis 6b (H6b): Job resources moderate the relation between leisure and psychological detachment from work.

Summary and Hypothetical Model

When integrating all the hypotheses that were formulated, the following model emerges (see Figure 1). Specifically, the model proposes that employees are likely to be more satisfied with their life when they: (a) experience high work-related well-being (i.e., high engagement and low burnout; (b) have low work-family conflict; (c) posess high job resources (e.g., skill variety, task significance, autonomy, social support) that allow to cope with demanding aspects of job and provide feelings of personal growth and competence; (d) are more able to relax and unwind by psychologically detaching from work during off-job time; and (e) engage more frequently in pleasurable and relaxing activities during leisure time. The model predicts that only work-related well-being has a direct effect on life satisfaction, while the other variables have an indirect effect via their impact on employee well-being. In addition, both for theoretical reasons and because of their assumed relevance for practical interventions, the model also incorporates mediating and moderating relations between variables. Specifically, the model predicts that WFC partially mediates the influence of psychological detachment from work on burnout, and that job resources moderate the influence of leisure activities on psychological detachment.

Figure 1

Hypothesized Research Model. Sign in parentheses indicate a positive (+) or a negative (–) relationship. Solid lines indicate hypothesized direct effects and dotted lines indicate hypothesized mediated or moderator effects.



Questionnaires were administered to 1,060 workers from different cities of Argentina using a national random telephone survey. The sample included employees from Capital Federal (30.9%), Comodoro Rivadavia (11%), Córdoba (17.3%), Corrientes (8.3%), Mendoza (10.1%), Rosario (14.6%), and San Miguel de Tucumán (7.8%) cities. Fifty-one percent of respondents were females. The mean age was 40.89 (SD = 11.99, range = 18-60). With regard to the job status, 50.9% of the participants were employees, 46.4% were self-employed, and 2.6% worked simultaneously both as employee and self-employed. The majority of respondents (28.5%) held a university or postgraduate educational-level, 18.6% held an incomplete university degree, 17.5% held a secondary educational-level, 21.3% held an incomplete or complete tertiary educational-level, and the remaining participants held an incomplete secondary educational-level (8.7%) or complete primary educational-level (4.2%).


Leisure. We used six items drawn from Csikszentmihalyi and Graef’s (1980) checklist of diary activities. Based on the experiential sampling method, the authors identified six categories of pleasurable, freely chosen activities which people usually engage in during leisure time: socializing, TV-watching, reading, idling, sport and games, club, culture, and movies. Watching television, idling, and movies represent low-effort, passive leisure activities; socializing and playing sport and games correspond to active leisure activities (Csikszentmihalyi & Hunter, 2003). In the current study, participants were asked to indicate how often they carried out each activity in the last weeks on a 5-point Likert scale ranging from 1 (never) to 5 (very regularly). Reliability of both passive and active leisure subscales was rather low (Cronbach’s α = .55-.62 for each subscale). However, the total scale yielded a relatively acceptable index of reliability (Cronbach’s α = .68). Hence, the total score was used in the study.

Psychological detachment from work. Psychological detachment from work was assessed through the four-item scale developed by Sonnentag and Fritz (2007). An example of item is “During after-work hours, I forget about work”. All items are rated on a 5-point Likert scale ranging from 1 (I fully disagree) to 5 (I fully agree). The alpha coefficient for the scale was .81 in the current sample.

Job resources. To assess job resources we developed a 9-item self-report measure based on job characteristics that promote job-related well-being proposed by Warr (1990): role clarity, job autonomy, social support, skill utilization, skill variety, task feedback, salary, safety, and task significance. All items were scored on a 5-point Likert scale ranging from 1 (very little) to 5 (very much). Confirmatory factor analysis (CFA) supported the unidimensionality of the scale, χ2 = 511.9, df = 96, CFI = .94, GFI = .93, TLI = .93, RMSEA = .07. In the current sample, the internal consistency was acceptable (Cronbach’s alpha = to .79).

Work-family conflict. Work-family conflict was measured with the negative work-home interaction (WHI) subscale from the Survey Work-Home Interaction - Nijmegen (SWING; Geurts et al., 2005). The negative WHI is made of 8 items rated on a 4-point scale ranging from 0 (never) to 3 (always). A sample item is “How often does it happen that… you do not have the energy to engage in leisure activities with your spouse/family/friends because of your job?” In our sample, Cronbach’s alpha was .80.

Burnout. Burnout was measured with two subscales from the Argentinean adaptation (Spontón, Trógolo, Castellano, & Medrano, in press) of the Maslach Burnout Inventory-General Survey (MBI-GS; Schaufeli, Leiter, Maslach, & Jackson, 1996): (a) emotional exhaustion (4 items; e.g., “I feel emotionally drained from my work”) and (b) cynicism (5 items; e.g., “I have become less enthusiastic about my work”). The items are scored on a 7-point frequency rating scale ranging from 0 (never) to 6 (daily). Coefficient alpha values in our sample were .75 and .85 for emotional exhaustion and cynicism, respectively.

Engagement. Engagement was assessed with two subscales from the Argentinean version (Spontón, Medrano, Maffei, Spontón, & Castellano, 2012) of the Utrecht Work Engagement Scale (UWES; Schaufeli et al., 2002): (a) vigor (6 items; e.g., “When I get up in the morning, I feel like going to work”) and (b) dedication (6 items; e.g., “I am enthusiastic about my job”). All items are responded on a 7-point Likert scale ranging from 0 (never) to 6 (always). In the current sample, the internal consistency was satisfactory with alpha coefficients equal to .72 and .83 for vigor and dedication, respectively.

Life satisfaction. Life satisfaction was measured with the Satisfaction with Life Scale (SWLS; Diener et al., 1985). The SWLS is a 5-item global measure of life satisfaction rated on a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree). The alpha coefficient for reliability of the SWLS for the present sample was .77.

Socio-demographic questionnaire. Personal details were obtained about sex, age, educational level, and job status (employee, self-employed, or both).


Five trained telephone interviewers applied the scales and the socio-demographic questionnaire to the national sample using the random-digit-dialing methodology. Subjects were invited to participate in a national study about people’s experience at work. A specific household was called at different times of the day and on different days to optimize contact with a resident. At least five attempts were made to contact a resident of each household. Response rates to phone calls were high (92%). Respondents were eligible if they were 18 years of age or older, were living in the household, and where either employed, self-employed, or both. All participants were clearly informed about the purpose of the study and no rewards were offered for participation.

Data Analysis

Data analyses were performed using AMOS20 program (Arbuckle, 2010). First, as the current study exclusively relies on self-report data, we tested for possible bias due to common method variance using Harman’s single factor test (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Second, the hypothesized model (displayed in Figure 1; Model 1) was examined through structural equation modeling (SEM). Next, we tested the hypothesized mediational effect of WFC in the relationship between psychological detachment and burnout. SEM was also used in this case since it possesses many advantages compared to the conventional multiple regression method, such as control for measurement error, information regarding degree of fit of the entire model, and more flexibility (Frazier, Tix, & Barron, 2004). Following suggestions from Holmbeck (1997), we compared the hypothesized model (with both direct and indirect paths from psychological detachment to burnout trough WFC) with a model in which the direct path from psychological detachment to burnout was eliminated (i.e., mediation model for burnout; Model 2). In a final step, we removed the path from psychological detachment to WFC and included only direct paths from psychological detachment to burnout and from WFC to burnout (i.e., direct model for burnout; Model 3). The mediational model is supported if the models described latter do not provide a better fit to the data (i.e., the direct paths between predictor and outcome is not significant).

Finally, moderation analysis was carried out by means of latent interaction modeling (Steinmetz, Davidov, & Schmidt, 2011) using SEM in order to test hypothesized moderator effects of job resources between leisure activities and psychological detachment from work. In particular, we used the unconstrained mean-centered approach (Marsh, Wen, & Hau, 2004) in which a latent product variable is included in the model to represent the interaction term. If the unconstrained model show a significant improvement in model fit compared to a constrained model (an assumption of no moderation effect), then there is evidence of moderation (Ro, 2012).

For all the models tested, maximum likelihood method of estimation was used and several goodness-of-fit-indices were calculated to examine the overall model fit: the absolute fit index (χ2), the goodness of fit index (GFI), the Tucker-Lewis index (TLI), the comparative fit index (CFI), and the root mean square error of approximation (RMSEA). GFI, TLI, and CFI values greater than .90 and RMSEA values smaller than .08 indicate acceptable model fit, while values greater than .95 (for GFI, TLI and CFI) and smaller than .05 (for RMSEA) are indicative of excellent fit (Browne & Cudeck, 1993; Hu & Bentler, 1999). In addition, comparing for nested models chi-square difference test was computed (Furr, 2011).


Descriptive Results

The means, standard deviations, and Pearson correlations between the study variables are presented in Table 1. As expected, engagement subscales (i.e., vigor and dedication) were positively correlated with life satisfaction (H1a), whereas burnout subscales (i.e., exhaustion and cynicism) were negatively correlated with life satisfaction (H1b). In addition, job resources were positively related to engagement (H2a) but, contrary to our expectation (H2b), they were not related to burnout. Psychological detachment formed positive correlations with engagement and negative correlations with burnout, particularly with cynicism, providing support for H3a and partial support for H3b. Furthermore, in accordance with H4a, psychological detachment from work was negatively related to WFC. Work-family conflict, in turn, was positively correlated with burnout, supporting H4b. Finally, job resources were positively related to psychological detachment from work, providing evidence for H5. Taken together, findings confirm the hypothesized linear relationships between variables included in the model, except for the relation between job resources and burnout.

Table 1

Means, Standard Deviations and Intercorrelations for All Study Variables

SEM Analyses

Firstly, we conducted Harman’s single factor test. Results revealed a poor fit to the data, χ2(27) = 293.54, GFI = .88, CFI = .66, TLI = .54, RMSEA = .14. Consequently, common method variance is not a serious deficiency in our dataset. Secondly, we tested the hypothesized model (Model 1) which included four observed variables (i.e., leisure, job resources, psychological detachment from work, and life satisfaction) and two latent variables (i.e., engagement and burnout). Findings showed that the proposed model did not fit adequately the data. Inspection of modification indices indicated that allowing co-varying errors of cynicism and dedication would increase model fit. After allowing the errors of these variables to co-vary, the model (Model 1a) fit reasonably well the data (see Table 2). Except for the direct path from psychological detachment to engagement, all the path coefficients in the model were significant and in the expected direction (see Figure 2).

Table 2

Goodness-of-Fit Indices for Models Tested

Figure 2

Research Model with Standardized Path Coefficients.*p < .05, ***p < .001.

Further, we examined the mediating role of WFC in the psychological detachment-burnout relationship (hypothesis H4c) by comparing the hypothesized revised model (Model 1a) with the mediation model (Model 2) in which the direct path from psychological detachment from work to burnout was eliminated. Results from the comparison of Model 1a with Model 2 yielded a significant deterioration in model fit, Δχ2(1) = 5.45, p < .05. Moreover, Model 1a showed significant better goodness-of-fit indices compared to Model 3, in which the path from detachment to WFC was deleted, Δχ2(1) = 33.33, p < .001. Thus, psychological detachment from work appears to influence burnout both directly and indirectly, through work-family conflict, supporting the mediational hypothesis.

To examine moderation effect of job resources between leisure and psychological detachment from work (hypothesis H6b) we compared the hypothesized revised model (Model 1a) with an unconstrained model (Model 4). Based on recommendations from Marsh et al. (2004), firstly all indicators of leisure and psychological detachment variables were centered. Then, we multiplied the items centered to create the indicators of the latent interaction variable (leisure x job resources) using a match-pair strategy. Next, the means of the predictor (leisure) and moderator (job resources) were fixed to zero and the mean of the latent product variable (leisure x job resources) was constrained to be equal to the covariance between leisure and job resources. Finally, all exogenous variables (i.e., leisure, job resources, and the latent product variable) were allowed to correlate. Results from the comparison showed that Model 4 provided a worse fit to the data relative to Model 1a, Δχ2(5) = 12.29, p < .05. Thus, the moderating hypothesis of job resources was not supported.


The main objective of the study was to test a model of employee well-being in Argentinian workers, building on relevant theories and empirical research in the literature. Drawing upon empirical studies and resource-based theories, we hypothesized that certain experiences outside work (i.e., physical, social, and low-effort activities pursued during leisure time) and within job conditions, particularly job resources, facilitate employees to psychologically detach from work. Since psychological detachment from work promote the restoration of depleted resources (Sonnentag & Fritz, 2007), we hypothesized that mentally switch-off from work decrease burnout and increase engagement, as employees may feel renewed and vigorous when back into work (Sonnentag, 2003). Work-family conflict was expected to influence burnout directly and to mediate the effect of psychological detachment on burnout. In this sense, as we have pointed out earlier, doing work and keeping mentally occupied in work-related thoughts at home may lessen attention and responsiveness to member families, which may arise conflicts at home (Demerouti et al., 2007). Finally, because of well-being at work is associated with general well-being (Hakanen & Schaufeli, 2012), we expected that engagement and burnout have positive and negative effects on life satisfaction, respectively. Results from SEM analysis showed that the model fits reasonably well the data. All path coefficients were significant and in the expected direction, providing support for our hypothesis. The only exception was the hypothesized relationship between psychological detachment and engagement, which were not found to be significantly associated to each other. Although this finding is contrary to those reported in earlier studies (Kühnel et al., 2009; Sonnentag, 2003) it is not surprising at all. Indeed, mental disengagement from work helps individuals to recover from work and to recharge their energy resources for the next workday (Fritz & Sonnentag, 2005). As such, people may feel more energized when returning into job. However, engagement not only comprises a high state of energy; it also involves the desire to enthusiastically apply that energy to work (Bakker & Leiter, 2010). Thus, being mentally disconnected from work during off-job time helps to build up energetic resources but it does not mean that employees refreshed may be necessarily more engaged at work.

As predicted by our hypothesis (H4c), mediational analysis showed that WFC partially mediated the relationship between psychological detachment and burnout. This finding indicates that being able to stop thinking about job-related matters and avoid working during off-job time not only prevent employees from further loss of resources and breakdown (burnout) – which is consistent with resource loss spiral (Hobfoll, 1989) – but also contribute to less conflict within family due to intrusion of work into family life, decreasing further demands from family members. Therefore, detaching from work may help to balance work and family life by facilitating daily role transitions or “micro transitions” (Ashforth, Kreiner, & Fugate, 2000) from work roles to family roles after work-hours, decreasing the probability of stressful situations (i.e., conflicts) that consume further resources, which helps to protect employee well-being.

Contrary to our hypothesis (H6b), we found that job resources did not moderate the influence of leisure on psychological detachment. Thus, as opposed to what we reasoned, having job resources does not make employees more likely to mental disengage from work when they pursue leisure activities. A possible reason may be that we only focused on one type of resources (job resources). However, recent findings have shown that personal resources are important to become able to distance from work after a workday. For example, a high level of mindfulness may be necessary to keep mentally focused on the off-job activities once employees leave the workplace which in turn may promote psychological detachment from work (Hülsheger et al., 2014). Accordingly, one would expect that individuals low in mindfulness might find it more difficult to stop thinking about work, even when actively pursuing pleasurable leisure activities during non-work time, as they become less absorbed – which is consistent with the distraction hypothesis (Yeung, 1996). In support of this, Cropley and Purvis (2003) found that teachers less able to “cognitively switch-off” after work reported more intrusive work-related thoughts than teachers who were more able to do so, even when they pursued the same activities during leisure time. Additionally, previous research has demonstrated that personal resources moderate the effects of job resources on personal outcomes (Xanthopoulou et al., 2007). Thus, more research is needed to gain more insights into the role of job and personal resources in psychological detachment and well-being. Further studies examining the role of personal resources and their potential interaction effects with job resources in leisure and psychological detachment from work would be fruitful to clarify the results found herein.

However, we found both leisure activities and job resources had a direct positive effect on psychological detachment, suggesting that leisure activities during non-work time and job resources contribute directly to mental disengagement from work. These findings are in line with earlier studies supporting the benefits of engaging in leisure activities, such as sports, social, or low-effort activities, in order to disconnect from work (Sonnentag, 2001; Sonnentag, 2003; Sonnentag & Zijlstra, 2006). Additionally, our findings are also in agreement with past research examining the influence of job resources on psychological detachment (Blanco-Donoso et al., 2017; Rodríguez-Muñoz et al., 2012; Sonnentag & Fritz, 2007; Zijlstra & Sonnentag, 2006). According to these studies, having job resources such as autonomy and flexible working times provide employees with more decision latitude to organize their work task and more control to decide when to work and when to take a break, increasing the likelihood of psychologically distancing themselves from work. Moreover, social support from coworkers offers emotional and material support that helps to cope with stressors at work, decreasing the sense of overload and the persistent activation of job-related thoughts (Sonnentag et al., 2013), thereby facilitating mental disengagement from work. In sum, job resources appear to facilitate psychological detachment from work either by creating more opportunities to engage in activities that promote psychological detachment or by helping to cope with demanding aspects of work, reducing the propensity to worry and think about job-related matters after the end of the workday.

Practical Implications

Although practical implications are somewhat speculative, based on our cross-sectional findings, some suggestions can be made. First, as psychological detachment from work had a direct negative effect on burnout, mental disengagement from work is crucial for protecting employees’ well-being. Thus, employees should be encouraged to detach themselves from their work during off-job time. There are several ways in which individuals may distance from work (cf. Kreiner, Hollensbe, & Sheep, 2009). Our results point out that increasing job resources and leisure activities during off-job time are particularly important. Therefore, organizations may help employees to disengage from work when they are no longer working by increasing job resources (Rodriguez-Muñoz et al., 2012). In addition, organizations may also contribute to psychological detachment of employees by offering and promoting leisure activities outside the work, such as sports, cultural, or social activities (Sonnentag & Zijlstra, 2006).

Second, the null correlation between psychological detachment from work and engagement has also practical implications. Since employee well-being is a broader and more encompassing experience than the mere absence of ill-being and that engagement and burnout are main aspects of well-being at work (Salanova et al., 2014), practitioners should develop strategies that prevent burnout and foster engagement. Our results suggest that while interventions aimed at increasing psychological detachment from work are crucial for recovery and protect employee well-being (i.e., burnout), it might have no effect on increasing levels of employee well-being (i.e., engagement). Thus, organizations interested in optimizing employees’ well-being might want to consider alternative interventions. According to our results and in line with suggestions made in previous research (Demerouti et al., 2007; Schaufeli, Bakker, & Van Rhenen, 2009), such interventions should include increasing job resources, including social support from coworkers and superior, performance feedback, autonomy, task variety, and training facilities.

Our results also pointed that when employees psychologically detach from work, work-family conflicts are less likely to occur. Thus, enhancing psychological detachment may have also benefits for work-family balance. Separating work and family domains by setting and maintaining clear boundaries may facilitate employees to disconnect from work when they are at home. In particular, reducing the use of communication technology at home for work-related purposes may serve as a useful strategy (Park, Fritz, & Jex, 2011). Organizations may also contribute to segmentation of work and family domains through formal or informal policies and practices. For example, by strictly forbidding making work-related phone calls or sending e-mails after regular workhours, unless it is an emergency. These kinds of practices may discourage technology use at home (i.e., fewer permeable technological boundaries at home) as employees perceive that there is a strong norm to do so, thereby facilitating mental switch-off from work (Park et al., 2011). One might argue whether completely reducing communication technologies use for work purposes is feasible due to technology becoming more integrated into everyday experiences at work and at home (Chesley, 2005). This may be particularly true for teleworking, which is continuously expanding (Baruch, 2000). Nonetheless, in such cases organizations could contribute by helping employees that inevitably work from home to develop structured boundaries around communication technologies use at home, in a manner that enable them to psychologically detach from work (Barber & Jenkins, 2013). Both impermeable home boundaries (i.e., segmentation) and structured crossing boundaries from work to family domains not only prevent work from spilling into home and reduce potential family conflicts; it also serves to protect scarce resources for further depletion, decreasing the likelihood for developing burnout.

Limitations and Future Directions

The current study has several limitations that warrant mentioning. First, it is important to note that the model tested in this study revealed an adequate fit to the data, albeit after correlating measurement errors between dedication and cynicism scales. The same problem has been reported in previous studies (e.g., Hakanen, Bakker, & Schaufeli, 2006; Llorens, Bakker, Schaufeli, & Salanova, 2006; Schaufeli & Bakker, 2004), which correlated errors following post hoc modifications without any explicit theoretical justification. As indicated by Furr (2011), post-hoc model’s re-specification based upon statistical criterion with the sole purpose of improving model fit, rather than theoretically-justified changes, must be taken cautiously. Indeed, correlations between errors may indicate that the model is misspecified (Hermida, 2015). In particular, Landis, Edwards, and Cortina (2009) suggested that correlated errors may be the result of a common cause (e.g., third variable) that is not specified in the model. Since dedication and cynicism represent two endpoints of a continuum labelled “identification” (González-Romá, Schaufeli, Bakker, & Lloret, 2006), this may be the reason why errors of the indicator variables are not independent. Thus, for further research it would be valuable to re-examine the nature of these burnout and engagement dimensions.

Second, our study was exclusively based on self-report data, which increase the probability of common method variance (Podsakoff et al., 2003). Although the single factor test showed a poor fit to the data — suggesting that observed relations between the variables are not accounted for common method bias — it would be important for future research to replicate the present study by including multiple data sources, such as coworkers and family.

Third, the study design was cross-sectional, which prevents us from making causal inferences regarding the relationships between the study variables. In this sense, although our model ordering is theoretically justified we cannot rule out alternative interpretations, such as reciprocal or reverse causation. For instance, not detaching from work may reduce the opportunity to engage in leisure activities (Sonnentag et al., 2008). One might assume that as keeping thinking about work and doing work during off-job time deplete scarce resources after effort expenditure at work, employees who are unable to detach from work may have limited available resources (e.g., time and energy) to pursue leisure activities. Also, they may tend to preserve their scarce resources as a self-regulatory strategy (Carver, 2004). Consequently, individuals with low psychological detachment may be less prone to initiate and uphold active leisure activities. In addition, although cross-sectional and longitudinal research have shown that lack of psychological detachment from work is related to increased levels of burnout, particularly emotional exhaustion (Fritz et al., 2010; Söderström et al., 2012), there is evidence suggesting that the opposite relation might be possible as well. For example, Sonnentag et al. (2014) found that exhaustion negatively predicted psychological detachment from work over a period of four weeks. Therefore, future research using longitudinal design is needed to shed light on causal linkages between the variables outlined in this study.

Fourth, while researchers have recognized that work and family interferences are reciprocal (Frone, 2000), the present study focused only on one direction (work-to-family conflict), which may limit our understanding of how work-family interface influences well-being. There are, however, good reasons that justify the focus on work-to-family conflict. One of them is that work-to-family conflict are more pervasive than family-to-work conflict (Frone et al., 1992; Kinnunen & Mauno, 1998). The other reason is that studies revealed that work-to-family conflicts are more strongly related to employee and general well-being compared to family-to-work conflicts (Kinnunen, Feldt, Geurts, & Pulkkinen, 2006). Beyond that, future research might seek to incorporate an enriched perspective by examining the positive aspects of work-family interaction as well (cf. Grzywacz & Marks, 2000) and their relations with psychological detachment from work and employee well-being in order to extend the present study in potentially important ways. For example, it has been pointed out that not detaching from work may have also benefits, such that when employees ruminate after a workday about positive events that happened at work (Fritz & Sonnentag, 2005). Such job-related thoughts may lead to enhanced mood and “energy expansion” (Marks, 1977) that spill over into home, heightening family roles (cf. Rothbard, 2001). In sum, it could be possible that not detaching from work, under certain conditions, has beneficial effects on work-family interface and subsequently on employee well-being. Additional research addressing these points is particularly valuable to gain a more comprehensive and refined understanding of results obtained in this study.

Fifth, despite our model was built regarding relevant variables in empirical literature concerning employee well-being, we note that the model is simplistic and does not fully capture the complexity of well-being at work. For example, there is a number of potentially moderating or mediating variables omitted in this study that would be worth examining in future studies. In particular, it would be useful to examine the impact of role salience. Indeed, people whose work role is more salient may be more prone to engaging in job-related activities while at home (e.g., checking their email or making phone calls), making psychological detachment more difficult. Such situation may decrease involvement in family life, leading to increased work-family conflict (Sanz-Vergel, Demerouti, Bakker, & Moreno-Jiménez, 2011). In addition, when these people continue working during off-job time it is less likely that they actively engage in leisure activities. Although the study by Sanz-Vergel et al. (2011) did not find evidence supporting the moderation effects of work role salience, we note that this is an intriguing line of research that deserves further investigation.

Other potentially relevant variables concern to the effects of partner’s psychological detachment and the presence of children at home on employees’ psychological detachment and well-being. For example, Hahn and Dormann (2013) found that employees with low psychological detachment engaged in more work-related verbal communication with their partners at home, decreasing partners’ psychological detachment, which negatively influenced both employees’ and their partners’ life satisfaction. Moreover, they found that the presence of children at home buffered the negative effect of employees’ lack of psychological detachment on their partners’ psychological detachment, such that when employees spend time with their children they get easily distracted by them and result less affected by their partners’ lack of disengagement from work. Nonetheless, as couples usually spend time together and pursue joint activities (Voorpostel, van der Lippe, & Gershuny, 2010), and the presence of children in the house reduce share leisure time between couples (Campos, Graesch, Repetti, Bradbury, & Ochs, 2009), employees with children may engage in fewer leisure activities. All in all, these studies suggest that intimate partners and children at home are relevant for better understanding relationships between leisure, psychological detachment, employee well-being, and general well-being. A last but not less important variable omitted in this study concerns job demands. In this sense, although we focused on job resources, job demands are working conditions equally relevant in explaining employee well-being (Bakker & Demerouti, 2007). Indeed, previous studies demonstrated that high job demands, such as quantitative workload and time pressure, impact negatively on psychological detachment from work (Sonnentag & Bayer, 2005; Sonnentag & Kruel, 2006) and are also associated with increased WFC (Illies et al., 2007), which in turn influence negatively well-being. Thus, future research incorporating such important variables is necessary to obtain a more refined understanding of the results outlined in this study.

A final limitation concerns to the low reliability of the instrument measuring leisure activities. Accordingly, it would be valuable to replicate findings using alternative methodologies, such as diary methods. Self-report measures based on diary method have many benefits; they allow the examination of experiences in their natural, spontaneous context, providing a more ecological way to obtain data that can be obtained by more traditional designs. They also reduce the likelihood of retrospective biases by minimizing the amount of time elapsed between an experience and the account of such experience (Bolger, Davis, & Rafaeli, 2003). Therefore, daily measures would provide more accurate self-report of leisure activities.

Despite all limitations, the present study contributes to the literature on employee well-being by examining variables that have been usually studied in isolation, providing an enriched perspective concerning linkages between leisure, work, and work-family interface. At the same time, we provide a useful evidence-based model that may guide practitioners in developing individual-level and organizational-level interventions to increase employee well-being in Argentina.


Cite this article as: Medrano, L. A. & Trógolo, M. A. (2018). Employee well-being and life satisfaction in Argentina: The contribution of psychological detachment from work. Journal of Work and Organizational Psychology, 34, 69-81. https://doi.org/10.5093/jwop2018a9

Funding: This study was supported by Universidad Siglo 21, Córdoba, Argentina.

Correspondence: leomedpsico@gmail.com (L. A. Medrano).

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