Abstract
Purpose
Although there is a small body of empirical research on the working lives of managers, both the popular media and the academic literature tend to ignore the distinct ways that role identities such as age and gender intersect to create a complex work–life interface for diverse managers. This gap is especially surprising considering that managerial roles are defined by unique demands and expectations that likely intersect with the differential life course shifts experienced by men and women, which has the potential to create specific challenges across the work and life domains of managers. The current study aims to address this gap through an intersectional examination of the non-linear effects of age and gender on the work–life balance of managers.
Design/methodology/approach
Using a sample of 421 managers, the authors apply statistical tests of the incremental validity of non-linear interaction terms to examine the complex relationship between age, gender and work–life balance.
Findings
Results support a non-linear U-shaped main effect of age on leader work–life balance. This effect is moderated by gender, however, with a non-linear U-shaped effect of age on work–life balance being supported for male managers – with female managers displaying no effect of age on work–life balance.
Practical implications
Based on these findings, the authors highlight the need for increased availability of flexible schedules and employee empowerment for managers as well as general employees.
Originality/value
The current study offers one of the first tests of the intersection of age and gender on the work–family interface of managers.
Keywords
Citation
Thrasher, G.R., Wynne, K., Baltes, B. and Bramble, R. (2022), "The intersectional effect of age and gender on the work–life balance of managers", Journal of Managerial Psychology, Vol. 37 No. 7, pp. 683-696. https://doi.org/10.1108/JMP-03-2021-0169
Publisher
:Emerald Publishing Limited
Copyright © 2022, Emerald Publishing Limited
Introduction
Managerial roles are defined by a broad set of expectations that involve not only organizing the tasks and relationships of others (DeRue et al., 2011) but also managing one's tasks and relationships across both the work and life domains (Manz, 1986). The complex and multi-domain challenges associated with managerial roles have a long history within the popular media, with there being no shortage of popular press management books offering insight on how to “Lead the Life You Want” (Freidman, 2014), “Integrate Successful Careers and Fulfilling Personal Lives” (Kofodimos, 1993), or “Lead with Balance” (Hutchinson, 2016) – to name a few. The popularity of such books reflects a desire in modern managers to develop strategies to balance their complex lives. However, although there is a small body of empirical research on the working lives of managers (e.g. Akani et al., 2020; Graves et al., 2007; Kelly et al., 2019) both the popular management media and the academic literature tend to ignore the distinct ways that role identities such as age and gender intersect to create a complex work–life interface for diverse managers. This gap is especially surprising considering that managerial roles are defined by unique demands and expectations. These unique managerial expectations likely intersect with the differential life course shifts experienced by men and women (Moen, 2011), creating the potential to create specific challenges across the work and life domains of diverse managers.
The small, but important, body of research that has examined the work–life intersection of managers has largely done so through an examination of gender within specific role occupancy. Specifically, results suggest that multiple role occupancy may lead to increased well-being among female managers (Ruderman et al., 2002), and managers in general experience role enhancement as a result of a commitment to marital roles (Graves et al., 2007). Although these findings highlight the important and unique effects of managerial roles on the work–life interface, emerging trends in this space have highlighted that (1) the working lives of men and women are distinct and dynamic across the lifespan (Allen and Finkelstein, 2014; Moen, 2011) and (2) that as non-work roles become increasingly less traditional work–life balance is less about specific role demands and more about one's perceived fit or satisfaction with their engagement in work and non-work domains (Greenhaus et al., 2003; Kelliher et al., 2019).
A primary rationale for the unique work–life experiences of managers can be drawn from social role theory. Social role theory states that all humans hold a variety of social roles (e.g. work, family, gender, age and manager) at any given time – with each role being defined by a set of specific expectations that drive behaviors and cognition within those roles (e.g. Biddle, 1986; Eagly, 1987; Frone and Rice, 1987). Although role theory has been applied to understand cognition and behavior across a myriad of various social institutions, how individuals experience the intersection of these pervasive role norms is less understood. The intersection of multiple social roles is especially prevalent among managers where researchers have long highlighted distinct societal expectations of managers to be powerful, competitive, and hard-working – displaying generally masculine – or agentic – traits (Schein, 1973; Schein et al., 1996). It is within these strong managerial role norms that the intersection of age-based role norms (younger individuals are assertive and older individuals are nurturing) and gender-based role norms (men are associated with the work role and women are associated with the family role; Duxbury and Higgins, 1991) – create a complex work–life interface for diverse managers.
The current study adopts a social role theory framework to investigate the intersectional effects of age and gender roles on the work–life balance of managers. Through this framework, we contribute to the literature on work–life balance in three primary ways. First, in our investigation of the work–life balance of managers, we move the work–life balance literature forward by extending the established theoretical framework of role-balance and role satisfaction to an understudied, yet a practically relevant, area of managerial roles across life domains. Second, we move role theory forward by integrating three established, yet siloed, theoretical framings of role theory in gender, age, and managerial roles to understand the work–life balance of managers. Third, we move research on intersectionality at work forward through a perspective that acknowledges the complex interplay between multiple social roles at any given time – via a gendered life course model. Fourth, through a statistical test of the incremental validity of non-linear interaction terms, we offer the first true test of the non-linear interactions that describe the complex relationship between age, gender, and work–life balance. Lastly, we test our hypotheses using a gender-balanced diverse sample of working managers.
An intersectional approach to manager work–life balance
Work–life researchers have historically applied role theory to characterize both the conflict and balance individuals experience between various roles. For example, research on work–family conflict is rooted in the proposition that work and family roles are defined by differential behavioral expectations creating the potential for competing demands resulting in role conflict (Greenhaus and Beutell, 1985). Intuitively, one may assume work–life balance is represented by the absence of conflict; however, modern definitions of work–life balance propose that balance is reflective of a cognitive evaluation of one's cross-domain activities that highlights: (1) personal preferences in engagement or satisfaction across work and life roles (Greenhaus et al., 2003; Kelliher et al., 2019) and/or (2) a fit between values within certain roles and one's effectiveness and satisfaction within those roles (Moen, 2011; Greenhaus and Allen, 2011). Consistent across the emergent conceptualization of work–life balance is the foundation of perceived satisfaction with various roles and the importance of understanding the interactions of the multitude of socially constructed roles (e.g. man, woman, parent, adult-child, manager, etc.) individuals occupy across the work–life interface (Casper et al., 2018).
Age-based role effects
While there is no specific research on the effect of age on the work–life balance of managers or the general working population, research on the relationship between the work–family interface and age has examined the effect of age on work–family conflict with some evidence for a curvilinear relationship. Specifically, this body of research suggests that work–family conflict increases as individuals enter mid-career stages and decreases as they approach retirement (e.g. Allen and Finkelstein, 2014; Huffman et al., 2013). Considering the effects of age on work–life constructs from a role theory perspective, the curvilinear relationship between age and work–family conflict makes intuitive sense as the aging process can be defined both as a transition through various life stages (parent to empty nester; Allen and Finkelstein, 2014) and socially as a shift in social roles from the work-centric norms of youth to the more family-centric and communal norms of later life (Thrasher et al., 2015). Existing research on age and the work–life interface has primarily focused on the life-stage approach which breaks the lifespan into distinct role-based groupings, highlighting young adulthood, middle adulthood, and late adulthood as distinct phases of life that are defined by a unique set of life and family demands and resources (Levinson, 1986). Huffman et al. (2013) investigated age–work–family conflict trajectories, finding support for the inverted-U hypothesis while also identifying several mediators related to the presence of demands and resources. More specifically, the authors find that while hours worked and characteristics of the family mediate the relationship between age and work–family conflict, a consistent inverted-U relationship was exhibited. Huffman and colleagues support the idea that WFC is generally lowest in later life with levels peaking during stages associated with early career and young children (Huffman et al., 2013). Allen and Finklestein (2014) offer further support for Huffman and colleagues' findings by examining mean differences across six life stages characterized by the presence and age of children at home. Within these life stages, the authors find that individuals in the “empty nest” stage display the lowest levels of WFC, with conflict peaking in mid-life stages.
Although there are no studies that explicitly examine age and the work–life balance of managers, within the small body of work that has examined the work–life balance of those in managerial roles we can find similar small correlational effects between age and work–life balance as what is reported in the literature on the general working population (e.g. Lyness and Judiesch, 2008). Within the literature on the work–life balance of general employees, small correlational effects with age are suggested to be a result of non-linear age effects on work–life balance. As managers likely experience similar life course shifts around family and career development as other employees, we argue that managers should also experience a non-linear relationship between age and work–life balance. This non-linear effect will be represented by a U-shape with work–life balance decreasing into mid-career and increasing towards retirement.
The relationship between age and work–life balance is non-linear such that the relationship will be represented by a U-shape.
The intersection of age and gender roles
While research does support the general non-linear effects of age on work–life balance within non-manager roles, there is evidence to suggest that men and women experience distinct role norms associated with age-related shifts (Allen and Finklestein, 2014; Moen, 2011; Phares et al., 2009). Although the presence of role norms does not define the actual demands of the role (i.e., women may experience norms associated with nurture, but not have children/men may experience norms around assertiveness, without identifying as such) – role norms influence how we evaluate and perceive our behavior. This distinction is outlined within propositions made by the gendered life course (Moen, 2011), which highlights that perceptions of fit across work–life domains are intertwined with the “distinctive life paths of men and women” (Moen, 2011, p. 82). The gendered life course further proposes that the strength and stability of social norms not only create distinct life paths for men and women but that these disparities in work–life role norms grow more apparent with age (Moen, 2011).
Gendered and age-based work–life paths are highlighted by research which suggests that although there are little to no mean differences between men and women on perceptions of work–life conflict (Shockley et al., 2017), there is evidence to suggest that gender may influence work–life constructs differently across various ages. For example research on gender and work–life conflict suggests that men and women experience different levels of conflict based on age as a result of socially based work and family role expectations, varying levels of work and family demands, and asymmetrical role boundaries (Shockley et al., 2017). Considering gender differences in age–work–life balance relationships, research on the general working population does support such effects. For example, gender differences in how work–life balance is experienced across the life span are highlighted by Allen and Finklestein (2014) who investigated gender differences in work–family conflict across various life stages by testing for life-stage by gender interactions with work–family conflict. Their findings suggest that while the relationship between age and work-family conflict is characterized by an inverted-U for both men and women, men experience higher levels of work interfering with family when the youngest child is aged 13–18. Further, the authors demonstrate that men experience the lowest levels of work–family conflict within the empty nest stage, while women see a plateauing of work–family conflict in later stages of life. Hill et al. (2014) further support the presence of gender differences in work–family conflict across the lifespan in a study examining factors that contribute to work–family conflict among 41,000 IBM employees. The authors' findings show that while work–family conflict is lowest in the empty nest stage for both men and women, this effect was much larger for men. Taken together these findings support propositions from the gendered life course suggesting gender differences across the work–life interface may be exacerbated through distinct age-related shifts in role norms that are experienced by men and women differently.
The primary rationale for why female managers may experience distinct relationships between age and work–life balance results from conflicting expectations between female gender roles and traditionally masculine social norms associated with managerial roles (e.g. Eagly and Karau, 2002). Research on gender role expectations highlights the power that social role expectations have on individual behavior. The powerful influence that societal roles have on individual behavior suggests that female managers will be driven to behave following both gender-based, as well as managerial-based expectations (Eagly and Karau, 2002). This thinking is exemplified by Eagly (2005) who states that “women have the burden of behaving competently as leaders while reassuring others that they conform at least partially to expectations concerning appropriate female behavior (p. 469)”. From a work–life balance perspective, the conflict between female-gender roles and managerial role expectations are likely to result in differential age effects around work–life balance for men and women. More specifically, men whose gender roles align with the competitiveness and agency associated with managerial roles (Schein, 1973) are socially warranted in placing work roles over life roles. This may, in turn, result in men's work–life balance largely being dependent on the norms associated with their career trajectories. In other words, for men, as managerial norms and expectations shift with age so will their perceptions of work–life balance. Conversely, women are socially expected to prioritize family and non-work role expectations, while also engaging in increased effort within a managerial role to overcome gender-role barriers resulting from the incongruity of female and managerial expectations (Eagly, 2005; Eagly and Karau, 2002). This likely will result in the work–life balance of female managers being more heavily dependent on the expectations of both their managerial roles, as well as their non-work roles. In other words, female managers must maintain effort in their managerial role across the lifespan to overcome negative stereotypes, while also being influenced by strong gendered non-work norms associated with different life stages.
Considering gender differences in social role norms within both managerial and non-work roles, it appears that the relationship between age and work–life balance may be distinct for male and female managers. More specifically, due to a need to maintain managerial role effort (Eagly and Karau, 2002) and non-work role effort (Kramer and Kipnis, 1995), there is reason to believe that female managers will experience consistently lower levels of work–life balance that gradually increase towards later life (e.g. Allen and Finklestein, 2014). Conversely, men tend to experience a more drastic increase in work–life balance levels towards older ages through more dramatic shifts in non-work role norms (e.g. empty nest stages; Kramer and Kipnis, 1995) and decreasing work centrality (Thrasher et al., 2015) will likely experience a more tradition U-shaped relationship between work–life balance and age. As such, we hypothesize the following:
The non-linear relationship between age and work–life balance is moderated by gender such that, more variance is explained by the non-linear effect for men than for women.
Method
Participants and procedure
Participants included 421 managers from the United States of America who took part in a development program administered by a large leadership development firm within the United States of America [1]. Participants held a variety of job functions and roles including information technology, project management, marketing and sales, health care, human resources, finance, and research and development. Participants represented a variety of managerial levels with 41% in executive roles, 7% in top management roles, 38% in upper management roles, 13% in middle management roles, and 1% in entry-level manager roles. All participants had at least one direct report with an average of 4.77 direct reports per manager. The sample was represented by 66% women. The average age of the full sample was 43.53 (SD = 6.92, min = 30, max = 64), the average age of the male managers was 43.2 (SD = 7.41, min = 32, max = 64) the average age of the female managers was 43.7 (SD = 6.66, min = 30, max = 61).
Measures
All managers completed the Benchmarks survey which is a 360-feedback tool that includes 155 items representing 16 dimensions of a variety of managerial constructs. The Benchmarks survey has been applied across several domains of empirical managerial research including research on political skill (Gentry et al., 2012), self-other rater agreement (Fleenor et al., 2010), and leadership across the lifespan (Thrasher et al., 2020). Multiple validation studies on the Benchmarks survey (e.g. CCL, 2000; Leslie and Fleenor, 1998; McCauley et al., 1989) further support the validity and the appropriateness of using the Benchmarks tool within empirical research. In the current study, self-report responses to the Balance Between Personal Life and Work scale of the Benchmarks survey were used as a measure of work–life balance. Although the Benchmarks survey includes measures of self, peer, leader, and other reports of a wide range of managerial behaviors, the current study applies only self-ratings of the work–life balance metric (for a similar application of this scale see Lyness and Judiesch, 2008). The inclusion of self-ratings on the primary dependent variable was done to reflect the operationalization of work–life balance as an individual's cognitive evaluation of their satisfaction or perceived fit concerning their engagement across multiple domains (Greenhaus et al., 2003; Greenhaus and Allen, 2011; Moen, 2011). The work–life balance dimension is composed of three items; “acts as if there is more to life than just having a career”, “has activities and interests outside of career”, and “does not take career so seriously that his/her personal life suffers”. The average work–life balance for the full sample was 3.75 (SD = 0.79), the male managers were 3.67 (SD = 0.76), and the female managers was 3.76 (SD = 0.80). These descriptive balances suggest that the age distributions of male and female managers were comparable for analysis. Reliability for the work–life balance scale was 0.78 for the full sample, 0.76 for the male sample, and 0.80 for the female sample. Age and gender were measured via self-report options selecting male or female and listing their age at the time of survey participation. Descriptive statistics and Pearson's r correlations (with two-tailed significance tests) for the full sample and gender-specific samples can be seen in Table 1.
Results
All primary hypotheses were tested via two regression models within the lm package in R. To increase the interpretability of unstandardized effects of age, a linear transformation of age/10 was performed (Thrasher et al., 2020) – all subsequent references to the age variable refer to this transformed variable. Mean-centered continuous predictor variables (and non-linear transformations) were used in all models (Cohen et al., 2003). A four-step moderated hierarchical regression process was used to incrementally test main effects, interactive effects, and finally our substantive non-linear interactive effects (for a similar process see Chung-Yan, 2010) [2]. A final primary regression model that included age, gender, age2, ageXgender, age2Xgender as predictors of work–life balance was used to test the significance of all predictors. Gender was dummy coded as male = 0/female = 1. To test the incremental validity of the non-linear interaction between age2 and gender in predicting work–life balance an ANOVA was conducted between the full model and a model that did not include the non-linear interaction term. As such, all linear and non-linear effects should be interpreted in light of the higher-order non-linear interaction. See Table 2 for all model effects.
Hypothesis 1 stated that there would be a non-linear effect of age on work–life balance as represented by a U shape. Results from the full model including all terms show a significant non-linear effect of age on work–life balance (b = 0.64, SE = 0.22, p < 0.01) – supporting Hypothesis 1. Hypothesis 2 stated that there would be a significant non-linear interaction between age and gender in predicting work–life balance such that the non-linear effect would explain more variance for men than women. Results displayed a significant effect of the non-linear interaction on work–life balance (b = −0.36, SE = 0.14, p = 0.01). An ANOVA test comparing the model including the non-linear interaction term to that without this term was also significant (F(1, 414) = 6.86, p = 0.01, ΔR2 = 0.02). To further interpret the non-linear interaction effect, incremental validity tests were conducted examining linear and non-linear age effects on work–life balance for men and women separately. For male managers, results show a significant non-linear effect of age on work–life balance (b = 0.29, SE = 0.10, p < 0.01), with a significant ANOVA test suggesting the non-linear age term adds incremental variance beyond the linear term (F(1, 140) = 8.62, p < 0.01, ΔR2 = 0.06). For female managers, results show non-significant linear (b = −0.07, SE = 0.07, p = 0.35) and non-linear effects (b = −0.07, SE = 0.09, p = 0.45) of age on work–life balance, with a non-significant ANOVA test between these two models (F(1, 274) = 0.58, p = 0.45, ΔR2 = 0.00). Taken together these results suggest that male managers experience a significant U-shaped non-linear effect of age on work–life balance with female managers experiencing no effect of age on work–life balance – offering support for Hypothesis 2. See Figure 1 for a plot of the non-linear interaction effect.
Discussion
Through the application of a social role theory approach to examining how age and gender intersect to influence the work–life balance of managers, the current study moves the literature on managerial work–life balance forward in several ways. First, we move research on female managers forward by highlighting that gendered effects on the work–life balance of managers are likely dependent on age. Second, through the application of an intersectional role theory framework, the current study sheds light on the complexity of the multiple social roles held by individuals across age, gender, and managerial roles. Lastly, our test of the incremental validity of non-linear interaction terms allows for statistical tests of gender differences that have only been inferred within previous research on age-gender intersections in work–life constructs (e.g. Allen and Finkelstein, 2014). Results from the current study specifically suggest that while the relationship between age and work–life balance is represented by a general non-linear U shape, this effect is defined differently for male and female managers. We specifically find that the U-shaped effect is driven by a strong non-linear effect for male managers, with female managers experiencing relatively consistent levels of work–life balance across all ages.
Theoretical implications
At the core of social role theory is the idea that individual cognition and behavior are driven by the expectations associated with the various social roles one holds (e.g. Eagly, 2005). Within a managerial context, role theory has largely been applied to explain the barriers and penalties associated with female managers who experience incongruity between the agentic stereotypes of managerial roles and the communal stereotypes prescribed to women (Eagly and Karau, 2002). Our results extend this proposition into the domain of work–life balance, by suggesting that across all ages female managers perceive a relatively consistent – albeit at times lower than male managers – fit across life domains. We propose that the null effect of age on work–life balance for female managers is likely a result of lifelong complex role expectations. Across their careers, female managers are influenced by high expectations within their managerial roles to display competence as a manager and overcome social barriers associated with gender-role incongruity. Conversely, male managers who experience social norms more strongly associated with managerial role expectations (Schein, 1973), may experience a more dynamic work–life balance trajectory as a result of less stable life-role demands coupled with baseline gender stereotypes that fit managerial expectations. For example, the baseline assumptions around the presence of managerial traits among men (Schein et al., 1996) allow male managers to be less vigilant in their displays of competence, while also avoiding social penalties when they “choose work over non-work” for example. To be clear, we are not suggesting that male managers engage in less effort to become successful managers, but that the societal expectations of male managers may create an environment that is less critical of their non-work choices.
Our findings that male and female managers experience distinct age-related work–life balance trajectories have specific implications for the broad literature on intersectionality at work. Theories of intersectionality grew out of the sociological and legal literature intending to highlight how individual social experiences are “… often shaped by other dimensions of their identities, such a race, gender, and social class.” (Crenshaw, 1993, p. 1242). By highlighting the gendered effects of age on the work–life balance of managers, findings from the current study move research on intersectionality at work forward by addressing calls for an increased focus on intersectionality within research on aging at work as well as within the managerial literature (Marcus, 2022).
Although we did not hypothesize about the main effects of gender at specific ages, our finding that work–life balance levels appear to flip around the age of 50 is somewhat surprising, and as such warrants a brief discussion. We specifically find that the non-linear interaction between age and gender is defined by younger female managers experiencing higher levels of work–life balance than younger male managers, with male managers experiencing a sharp non-linear increase in work–life balance in later life. Based on the high level of social expectations female managers experience in both work and non-work roles (Eagly, 2005), one might expect work–life balance to be more stable and lower for female managers across the lifespan. A potential explanation for our contradictory finding can be found by looking to more recent definitions of work–life balance as a unique and distinct construct from work–family conflict (e.g. Greenhaus and Allen, 2011; Greenhaus et al., 2003) which conceptualizes work–life balance as less about resource allocation, and more about satisfaction, fit, and effectiveness across work and life roles. It may be that female managers, who experience strong social norms towards engaging in family roles, while also overcoming gender-based managerial barriers, experience higher levels of role identity integration. As such, although female managers may be socially expected to deploy more resources into both work and life roles, they may be more satisfied across domains due to success across multiple roles that are central to their identity. This may, in turn, lead to increased work-life synergies and increased perceptions of work–life balance for female managers, with this effect remaining stable across the lifespan. This effect may be especially relevant within the current sample, which consisted of managers who had been placed in a leadership development program. Men, who are socially expected to engage more heavily in work roles, may experience higher levels of perceived role conflict during early life stages when career development takes priority. Early in their career, male managers may perceive resources deployed into career roles as a trade-off for later benefits. Later in life, as male managers become more established in their career and non-work role demands decrease, work–life balance for these individuals may increase due to increased fit between work–life identities and role demands.
Practical implications
The findings from the present study suggest several practical implications to be considered. Managers of employees working into the later stages of life must be especially cognizant, particularly in terms of the potential differential experiences of work–life demands among men and women. While we do not suggest organizations should implement varying practices for men and women, our findings suggest that organizations should not assume work–life balance is a young people issue. Interventions, such as flextime, targeted at decreasing the effects of role imbalance should be made available across all age groups. Further, and in line with emerging trends in work–life balance research (e.g. Kelliher et al., 2019) organizations are advised to take a broader view of what constitutes non-work roles. As family trends shift, as should our understanding of what roles individuals value outside of work. By abandoning specific family-centric policies and turning to more general “personal” accommodations, organizations can better support the diverse non-work expectations of modern employees.
Beyond specific interventions, research by O'Neill et al. (2009) suggests that a manager's level of work–life balance influences their employees' likelihood of leaving the organization. Although managers have largely been described as a resource for fostering employee work–life balance (e.g. Hammer et al., 2009), managers need to be cognizant that they are looked at as agents of the organization. Managers who value their work–life balance are likely to foster the norms and assumptions that reflect cultures that are family supportive.
Limitations and future directions
While we believe our findings have important implications surrounding the intersectional effects of age and gender on the work–life balance of managers, our study does contain several limitations. The cross-sectional nature of our data prevents us from specifically examining temporal changes in work–life balance across the lifespan. While we can infer causality of age and gender on work–life balance, we are unable to differentiate age from potential cohort effects. Future research should attempt to examine gender differences in work–life balance through the application of longitudinal methods. Further, age is often used as an indicator of, or proxy for, life stage. Although we do not specifically claim to test a life stage model, as work and life roles become increasing complex and “less traditional” (e.g. people have children at later ages, refraining from children, the prevalence of eldercare and increased focus on other important non-work roles) age may not be an ideal reflection of life stage. While we do not suggest abandoning age as a variable of interest, we encourage future researchers to consider other factors such as specific role demands and role commitment that may influence the intersection of age and gender across managerial samples. While secondary data allows for the application of large and diverse samples, it limits our ability to include relevant variables in all models. For example, research on gender differences has highlighted role commitment and role occupancy (Graves et al., 2007; Rudderman et al., 2002) as relevant for managerial work–life balance, along with other specific role demands (e.g. number of children and hours worked). Although the lack of these variables does present a limitation, we also suggest that the conceptualization of work–life balance as a perception of fit between work and non-work, or life, roles suggests it is less about specific demand-resource allocations and more about a perceived fit between valued life roles. Further, the secondary data applied in the current study were collected between 2010 and 2015. While this time lag is comparable to other studies using similar datasets (e.g. Lyness and Judiesch, 2008) – it does create a potential cohort limitation pertaining to work–life balance specifically. Over the past decade, the nature of work has shifted and role norms may have become less traditional and less distinct across both gender and the work and life domains. The literature on managerial work–life balance would benefit from future research that examines how work–life trends (e.g. the prevalence of remote work, non-traditional family dynamics, and family leave) have shifted the way that modern work and life roles intersect. Lastly, we acknowledge that while the intersection of age and gender is important to consider when examining managerial outcomes such as work–life balance, intersectional identities can be complex and include several distinct identity components. Future researchers are encouraged to examine how the intersection of other identities (e.g. race, social class and disability status) can influence important outcomes for both managers and general employees.
Conclusion
The current study sheds light on how the complex interplay between the various roles individuals holds influences levels of work–life balance. At any given time, individuals experience competing and synergistic role expectations. Understanding the complexity of those expectations is essential for understanding how managers manage their work and life roles within an increasingly diverse workforce. Research on successful aging at work (e.g. Zacher, 2015) points to work–life balance as a predictor of well-being for aging employees. As the workforce continues to age, as will the age of the average manager. By understanding how age intersects with other role expectations, organizations can continue to develop successful managers far into the later years of working life.
Figures
Descriptive statistics and intercorrelations for combined and gender specific samples
| Mean | SD | 1 | 2 | 3 | ||
|---|---|---|---|---|---|---|
| Full Sample | 1 Gender | – | – | 1.00 | ||
| 2Age | 43.53 | 6.92 | 0.04 | – | ||
| 3Work–life balance | 3.75 | 0.79 | 0.02 | −0.02 | (0.78) | |
| Males | 2Age | 43.20 | 7.41 | – | 1.00 | |
| 3Work–life balance | 3.67 | 0.76 | – | 0.09 | (0.76) | |
| Females | 2Age | 43.70 | 6.66 | – | 1.00 | – |
| 3Work–life balance | 3.76 | 0.80 | – | −0.08 | (0.80) |
Note(s): *p < 0.05, Male = 0, Female = 1. Nfullsample = 421, Nmales = 144, Nfemales = 277. Values in parentheses reflect sample specific alpha coefficients
Unstandardized effects for all models
| Model 1 | Model 2 | Model 3 | Model 4 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| B | SE | B | SE | B | SE | B | SE | ||
| Intercept | 3.69** | 0.14 | 3.63** | 1.36 | 3.61** | 0.14 | 3.35** | 0.18 | |
| Main effects | Age | −0.02 | 0.06 | −0.07 | 0.07 | 0.22 | 0.20 | −0.08 | 0.23 |
| Gender | 0.03 | 0.08 | 0.05 | 0.08 | 0.06 | 0.08 | 0.22* | 0.22 | |
| Quadratic | Age2 | 0.09 | 0.07 | 0.08 | 0.07 | 0.64** | 0.22 | ||
| Linear interaction | Age × Gender | −0.18 | 0.11 | 0.01 | 0.13 | ||||
| Non-linear interaction | Age2 × Gender | −0.36** | 0.14 | ||||||
| R2 | 0.00 | 0.00 | 0.01 | 0.03* | |||||
| F(Model 3, Model 4) | 6.86** | ||||||||
| Males | Intercept | 3.72** | 0.08 | 3.57** | 0.08 | ||||
| Age | 0.09 | 0.09 | −0.03 | 0.10 | |||||
| Age2 | 0.29** | 0.10 | |||||||
| Females | Intercept | 3.76 | 0.05 | 2.77 | 1.84 | ||||
| Age | −0.09 | 0.07 | −0.07 | 0.09 | |||||
| Age2 | −0.07 | 0.09 | |||||||
Note(s): N = 421, All effects unstandardized, age was linearly transformed as age/10 to increase effect size interpretability and avoid abnormally large interaction and squared terms. Male = 0, Female = 1. All continuous predictors have been grand mean-centered. Model 1 = main effects (e.g. age and gender) on WLB, Model 2 = Non-linear effect of age on WLB, Model 3 = Inclusion of interaction of age and gender on WLB, Model 4 = Inclusion of non-linear interaction of age and gender on WLB. Model 4 was used for all hypotheses tests
Notes
Data were collected between the years 2010 and 2015. Participants may have engaged in the development program for a variety of reasons – due to the use of secondary data the authors do not have information on specific participant motivation to sign up for the program.
Chung-Yan (2010) applied a 5-step regression model that includes the interaction between the squared terms of both independent variables as a fifth step. As gender is dummy coded at 1/0 gender2 = gender, as such the current study applies a four-step hierarchical regression analysis with the interaction between age2 and gender representing the final step.
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Corresponding author
About the authors
Gregory R. Thrasher is Assistant Professor of Management at Oakland University. He received his PhD in Industrial-Organizational Psychology from Wayne State University. His research interests focus on understanding workplace phenomenon across the lifespan. His work has been published in journals such as the Journal of Business and Psychology, Occupational Health Science, and Work, Aging, and Retirement.
Kevin Wynne is Assistant Professor of Management at the University of Baltimore (UB). Prior to UB, he conducted research at the U.S. Air Force Research Laboratory as a postdoctoral research fellow. He has previous internal and external consulting experience, particularly in the areas of selection/testing, data analysis/validation, and assessment design. He currently conducts research in three domains: (1) leadership, (2) trust and technology, and (3) work–life interface. He received an MS in Management from Mays Business School at Texas A&M University and a PhD in Industrial/Organizational Psychology from Wayne State University. He can be reached at kwynne@ubalt.edu.
Boris Baltes is Associate Provost for Faculty Affairs and Professor of Psychology at Wayne State University. His major research interests include examining biases in performance appraisal, age and workplace issues, and the area of work–family conflict. His work has appeared in many journals, including the Journal of Applied Psychology, Organizational Behavior and Human Decision Processes, Journal of Management, and the Journal of Organizational Behavior. He has been Associate Editor for the Journal of Organizational Behavior and Guest Editor for the Journal of Business and Psychology and is on the editorial boards of various journals. He is also a fellow of the Society for Industrial/Organizational Psychology.
Reed Bramble is Doctoral Candidate in industrial-organizational psychology at Wayne State University. He has co-authored several book chapters related to aging and work–family issues, work motivation across the lifespan, and job performance in later life. He has published research in journals such as Journal of Business and Psychology, Journal of Occupational and Organizational Psychology, Personality and Individual Differences, and Work, Aging, and Retirement.