work life balance scientific research

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Work–Life Balance: Weighing the Importance of Work–Family and Work–Health Balance

Associated data.

To date, research directed at the work–life balance (WLB) has focused mainly on the work and family domains. However, the current labor force is heterogeneous, and workers may also value other nonworking domains besides the family. The aim of this study was to investigate the importance of other nonworking domains in the WLB with a particular focus on health. Moreover, the importance of the effects of the work–family balance (WFB) and the work–health balance (WHB) on job satisfaction was investigated. Finally, we explored how the effects of the WFB and the WHB on job satisfaction change according to worker characteristics (age, gender, parental status, and work ability). This study involved 318 workers who completed an online questionnaire. The importance of the nonworking domains was compared with a t -test. The effect of the WFB and the WHB on job satisfaction was investigated with multiple and moderated regression analyses. The results show that workers considered health as important as family in the WLB. The WHB explained more of the variance in job satisfaction than the WFB. Age, gender and parental status moderated the effect of the WFB on job satisfaction, and work ability moderated the effect of the WHB on job satisfaction. This study highlights the importance of the health domain in the WLB and stresses that it is crucial to consider the specificity of different groups of workers when considering the WLB.

1. Introduction

The term work–life balance (WLB) has gained increasing popularity in the public discourse [ 1 ]. It is a term that is commonly used in companies, especially large ones, and it is often said to be at the core of their corporate welfare, e.g., [ 2 , 3 , 4 ]. However, academic knowledge around the WLB concept is not as solid and extensive as the widespread use of the term would suggest [ 1 ]. Researchers have argued that WLB theoretical development has not kept pace with the popularity of the concept [ 5 , 6 ]. Among the many issues raised by recent critical reviews [ 1 , 7 , 8 , 9 ], the present study focuses on the limited consideration that has been given to the heterogeneity of the contemporary labor force in the WLB literature [ 8 ]. The extant research has largely assumed that the WLB is a concern mainly for working parents, where caring for dependent children is the relevant load in the life part of the WLB [ 1 ]. This became clear when we realized that the majority of the studies about the WLB actually only considered the family in the “life” part of the balance; that is, they considered the work–family balance (WFB) [ 6 , 9 , 10 , 11 ].

Currently, in addition to the massive presence of women in the labor market, which has fostered the literature about work–family balance, there is a highly increasing rate of active elderly workers, workers with a long-standing health problem or disability (LSHPD), single workers, and childless couples [ 12 , 13 , 14 ]. These workers have different needs and interests outside work. This situation places renewed importance on a key feature of the WLB: The importance that is attached to the many different life role changes from person to person [ 9 ]. Therefore, even if the family role remains central in nonworking life, it is important to recognize the value of other roles when conceptualizing and measuring the WLB [ 11 ]. The family may not be the most important part of the WLB in determining the positive outcomes of, for example, workers with chronic diseases for whom the management of health has great influence. From this perspective, Gragnano et al. [ 15 ] recently developed the concept and measure of the work–health balance (WHB), which is particularly relevant for elderly workers and workers with a LSHPD.

This study aims to contribute to the WLB research by comparing the relevance of other nonwork domains beyond family and considering the heterogeneity of the current labor force in studying the WLB. Specifically, we (a) investigate the perceived importance of other nonwork life domains beyond family, with a focus on health; (b) compare the influence of the WFB and the WHB on job satisfaction; and (c) examine how the effects of the WFB and the WHB on job satisfaction change according to different worker characteristics.

In subsequent sections of this article, we discuss the relationship between the WLB and the WFB, also considering different worker characteristics. We then introduce the concept of the WHB.

2. Theoretical Background and Hypotheses

2.1. specific nonwork life domains: family and health.

The field of study about the work–life balance has had difficulty in establishing a commonly agreed-upon definition of the WLB [ 16 ]. A plethora of different conceptualizations exist in the literature, and many researchers have tried to summarize them [ 9 , 10 , 16 ]. After a review of the conceptualizations of the WLB in the literature, Kalliath and Brough [ 16 ] proposed a definition of the WLB that we endorse. “Work–life balance is the individual perception that work and nonwork activities are compatible and promote growth in accordance with an individual’s current life priorities” (p.326). A recent review indicated that a better work–life balance fosters not only job satisfaction, job performance, and organizational commitment but also life and family satisfaction [ 10 ]. The work–life balance also reduces stress-related outcomes such as psychological distress, emotional exhaustion, anxiety, and depression [ 10 ].

Research on work and nonwork interactions dates back to the mid-twentieth century, e.g., [ 17 ], and the issue has gained increasing importance in the popular press since the 1990s [ 16 ]. Today, there exists an extensive and growing body of research about the work–life balance [ 18 ], and the topic is of even more concern than in the past considering the new flexible ways of managing work (e.g., agile working, smart working, activity-based working, and flexible working).

Researchers have highlighted that the field of research about the work–life balance is itself “unbalanced.” The majority of studies on the work–life balance have focused only on work and family roles, that is, on the work–family balance [ 6 , 9 , 10 , 11 ]. For example, Casper et al. [ 9 ] reviewed the conceptual definition of the balance in the academic literature and found that 66% of the definitions focused only on work and family. In their review, Chang et al. [ 7 ] found that the WLB was studied specifically, not in the form of the WFB, in only 9% and 26% of the quantitative and qualitative studies reviewed, respectively. As a result, the knowledge acquired over time about the predictors and consequences of the balance with work is based mainly on the work–family balance [ 1 , 10 ].

Different types of the work–family balance have been studied in the literature. A general classification distinguished four types of influence that can occur between work and family based on their direction and valence [ 19 ]. When the effect is negative from the family domain to the work domain, it is called the family-to-work conflict. When the effect is still negative but from the work domain to the family domain, it is called work-to-family conflict. When the effect is positive, it is called enrichment and can have the same two directions; therefore, there is family-to-work enrichment and work-to-family enrichment. The work–family balance has been extensively studied in its negative form, work–family conflict [ 19 ]. However, since the 2000s, the scientific community has begun to focus on its positive form, work–family enrichment [ 20 ].

Many researchers have called for a real expansion of the WLB concept, such that the second arm of the balance—life—is not confined to the family role [ 6 , 9 , 19 ]. The call for an expansion of the concept is not only theoretically grounded but also related to recent changes in the labor market. The identification of the WFB as an indicator of the WLB was relatively effective and useful in recent decades, when the greatest change in workplace demographics was the increase in the participation of women, and the management of family and work roles for working women and dual-earner couples, especially those with children, became a central issue within organizations. Currently, workplace demographics are more heterogeneous. In addition to the massive presence of woman in the labor market, we are also seeing an increase in the rate of active elderly workers, workers with an LSHPD, single workers, and childless couples [ 12 , 13 , 14 ]. It is clear that an exclusive focus on family has become at least reductive when considering the WLB [ 1 , 21 ].

The majority of the studies that have investigated the work–nonwork balance without an exclusive focus on the family domain have considered nonwork to be unspecific, i.e., they have considered nonworking life in general, including nonfamily and family domains [ 19 ]. However, the consideration of the specific nonwork domains is essential to a full comprehension of the dynamics that influence the work–life balance in the heterogeneous working population, that is, the different, specific nonwork domains will have different levels of importance and different effects in the determination of the work–life balance among workers with diverse characteristics and needs outside work [ 11 ].

Based on the quality of life literature [ 22 ], the multiple identity perspective [ 23 ], and Super’s [ 24 ] life-space theory of career development, Keeney et al. [ 11 ] identified eight nonwork domains of relevance in the WLB: education, health, leisure, friendships, romantic relationships, family, household management, and community involvement. The importance that individuals give to the different domains varies from person to person [ 11 ]. Moreover, the relative importance of these life domains is likely to change over time within the same person because of changes in interests and life circumstances [ 24 ]. Thus, it is crucial to understand whether the other nonwork domains are as important as family and under which circumstances the priorities change. Among the domains that were detected by Keeney et al. [ 11 ], there was health. This is relevant because to our knowledge, for the first time in work–life balance literature, it has been recognized that health management can conflict with work activity.

As stated, the relevance of health to the work life derives from an increase in the rate of workers with an LSHPD and elderly workers, both with a higher incidence of health problems. In 2017, 27.8% of the European Union (EU) workers reported an LSHPD, and 19% of the employed persons in the EU were 55 years of age or older [ 25 , 26 ]. There is, however, another reason that makes the health domain relevant even for “healthy” workers. A paradigm shift has occurred in the planning and delivery of healthcare. People are now expected to actively manage their healthcare. Theorizations in the field of public health and in medicine have indicated that it is strategic for healthcare systems to have informed patients who are more directly responsible for their health and care management [ 27 ]. This has been paired with an increasing focus on health promotion that is based, partly but strongly, on good individual healthy behaviors [ 28 ]. Therefore, the workers, not just the sick ones, must take on a somewhat active role in the health domain of life, which may be more or less compatible with the working role.

In light of this literature and considering the life domains defined by Keeney et al. [ 11 ], we hypothesized that family is still central in the WLB of workers but that the health domain also has an equally important role. Therefore, if the workers were asked directly:

Workers will indicate that the family and health domains are more important than the other life domains in the WLB process .

2.2. Consequences of Work–Family Balance: Job Satisfaction

Many studies have analyzed individual consequences of the different types of the work–life balance, and several meta-analyses have summarized the literature about the correlates of work–family conflict [ 29 , 30 , 31 , 32 ] and work–family enrichment [ 20 ]. Work–family conflict, in both directions, has been consistently found to be associated with work-related, family-related, and domain-unspecific outcomes. Specifically, among the many outcomes that are associated with work–family conflict in a statistically significant manner, the ones that were more strongly associated were organizational citizenship behavior, work-related and general stress, burnout and exhaustion, and job, marital and life satisfaction [ 29 ]. Far fewer studies exist for work–family enrichment, but by comparing the two extant bodies of literature, it is possible to note that the effect sizes of work–family enrichment are comparable to those of work–family conflict [ 20 , 29 ]. For simplicity and because more studies are needed about the relationship between work–family enrichment and conflict [ 33 ], which goes beyond the objectives of this research, we considered only the conflict, in both directions, in our study.

Among the literature considering work-related outcomes, job satisfaction has been the most studied variable [ 29 ]. Job satisfaction represents the extent to which workers like or dislike their job [ 34 ]. Job satisfaction is a central variable in organizational behavior research. Spector [ 34 ] ascribed its importance to three main reasons. Job satisfaction is an indicator of well-being and psychological health, it is related to many behaviors of the worker that are positive for the organization, and finally, it is a very useful indicator of organizational problems when its level is low. In fact, job satisfaction is highly related to burn-out, self-esteem, depression, anxiety and, to a lower extent, perceived physical illness [ 35 ]. It is consistently correlated with job performance [ 36 ] and with four dispositional traits predictive of job performance: self-esteem, generalized self-efficacy, locus of control, and emotional stability [ 37 ]. Job satisfaction has also been found to be a significant predictor of turnover and turnover intention [ 38 , 39 ].

Job satisfaction is also related to the work–family balance. The meta-analysis conducted by Amstad et al. [ 29 ] reported that the correlation with job satisfaction was stronger for work-to-family conflict (weighted mean correlation = −0.26) than for family-to-work conflict (weighted mean correlation = −0.13). Theoretically, the work–family balance affects job satisfaction because an incompatibility between two personally relevant roles creates negative states and feelings. Following the principle that when something threatens something else personally relevant, the first is appraised negatively with negative emotion [ 40 ], and a role that interferes with the fulfilment of another personally relevant role is negatively evaluated. Specifically, a negative evaluation of an individual’s job is formed (i.e., low job satisfaction) depending on the extent to which the job threatens the fulfillment of the family role [ 41 ]. This explanation justifies why family-to-work conflict has been found to have a lower correlation with job satisfaction than work-to-family conflict. In fact, provided that both conflict directions may generate a strain in both domains, the family-to-work conflict will generate a low family satisfaction—instead of a low job satisfaction—because the family role interferes with the work role, and the negative evaluation will be toward the source of the interference [ 41 ]. This was supported by the meta-analysis conducted by Amstad et al. [ 29 ], who found that work-to-family conflict was more strongly correlated with work-related outcomes than family-related ones and that the opposite was true for family-to-work conflict. Based on these premises, we hypothesized that:

Work-to-family and family-to-work conflict will be significantly and negatively related to job satisfaction.

The relationship between work-to-family conflict and job satisfaction will be greater than the relationship between family-to-work conflict and job satisfaction.

2.3. Consequences of Work–Health Balance

The present study aimed to expand the knowledge about the nonwork life domain other than family, specifically the health domain. Despite the importance of the life domain of health, the literature has not offered many studies that consider health in the WLB process or measurement instruments that are specifically designed for the purpose [ 42 ]. Considering the literature about job retention and the quality of working life among workers with an LSHPD [ 43 , 44 ], Gragnano et al. [ 15 ] conceptualized the work–health balance (WHB) as a state in which the worker feels able to effectively balance health and work needs, arising from the perception of how much the characteristics of one’s work are a barrier to health needs and counterbalanced by the evaluation of the helpfulness of the working environment to meet health needs.

Health needs are understood here in a broad sense, covering not only the care needs of workers with chronic illnesses or conditions but all the needs that a worker considers necessary to adequately care for his or her health. From the definition, a measure of the WHB has been developed. The WHB questionnaire measures three distinct constructs: work–health incompatibility, health climate and external support [ 15 ]. The first construct measures how much work commitments hamper the desired management of health. The last two constructs measure the helpfulness of the working environment for health needs. The health climate detects the extent to which workers perceive that management is truly interested in their employees’ health, whereas external support identifies the perception of the level of help available for health problems in the workplace in the form of support from the supervisor and work flexibility.

Studies have shown that elderly workers and workers with an LSHPD have more difficulties in reaching a good WHB [ 45 , 46 ]. In addition, it has been shown that among workers who stop working for cardiovascular diseases, the process of returning to work is faster for those who have a good WHB [ 47 ]. With low levels of the WHB, the rates of presenteeism, emotional exhaustion, workaholism and general psychological distress (GHQ) increase [ 15 , 48 ]. In contrast, a good WHB is associated with greater work autonomy, job engagement, and job satisfaction [ 15 , 49 , 50 , 51 ].

In the WHB, a good balance generates job satisfaction because the work role is not a threat to the management of health. A low level of work-to-family conflict generates job satisfaction because the work role is not a threat to the family domain. Because the two domains at risk are different, the proportion of the job satisfaction variance that is explained by the WHB is expected to not overlap, to a great extent, with the proportion that is explained by the work-to-family conflict. Moreover, in the current working context, characterized by a great heterogeneity of the contemporary labor force with a substantial proportion of elderly workers and workers with an LSHPD, as well as with the increasing spread of a health care system that is based on the active and informed role of patients, we expect the WHB to be as important as work-to-family conflict in shaping attitudes toward job and job satisfaction. Therefore, we hypothesized that:

The WHB will have a significant positive effect on job satisfaction.

The effect size of the WHB on job satisfaction will be at least as large as that of work-to-family conflict.

2.4. The Heterogeneity of the Labor Force and WLB

As stated before, the present study focuses on the problem of the limited consideration that has been given in the WLB literature to the heterogeneity of the contemporary labor force [ 8 ]. The current labor force is characterized not only by a greater female presence but also by an increasing rate of elderly workers, workers with an LSHPD, single workers, and childless couples [ 12 , 13 , 14 ], all with different needs and with a different levels of importance that are given to their various nonworking roles [ 1 ].

This last consideration is particularly relevant in the context of the WLB because the balance is not absolute; rather, it depends on the importance that is given by the worker to the various roles. Therefore, when studying the effect of the WLB on outcomes by using concepts and measures such as work-to-family conflict or the WHB, which measure the balance between a specific nonwork role and work, it is theoretically appropriate to expect that the studied effect will vary based on the importance that is given by the worker to the nonwork role under consideration. In other words, the perception of an imbalance between a specific nonworking role and work will have a negative effect on the outcome to the extent that the nonworking role in question is important for the worker.

Despite the centrality of individual priorities in the definition of the WLB [ 9 , 10 , 16 ], surprisingly few studies have explored how individual priorities moderate the effect of the WLB on outcomes [ 6 , 29 , 52 ], which is a symptom of the limited consideration of diversity in the labor force by the WLB literature [ 1 , 8 ]. Individual differences have been considered as predictors of differences in the level of balance [ 10 , 53 ] instead of as moderators of the effects of the balance on the outcomes. Crooker et al. [ 21 ] developed a theoretical framework that extensively considered differences in individual value systems as moderators, but this study was focused on the genesis of the WLB instead of its consequences.

In the present study, we considered four variables (i.e., age, gender, parental status, and work ability) that, according to the literature, moderate the relationship between the WFB and job satisfaction or, alternatively, the relationship between the WHB and job satisfaction. The hypothesis is that individual conditions and characteristics that increase (or decrease) the importance that is given by the worker to the family or health domain will increase (or decrease) the effect that the work–family balance or the WHB has on job satisfaction.

Gender has been studied in the WLB literature as a possible predictor of different levels of the work–family balance. The hypothesis has been that, since family responsibilities usually pertain more to women, women have worse levels of the work–family balance, but these studies have not consistently supported this hypothesis [ 54 ]. However, research has still indicated that there are significant disparities between men and women pertaining to the work–family balance [ 55 ]. There have also been studies that have indicated that women do value family more than men, and the opposite has been shown to be true for work [ 56 , 57 ]. This is consistent with other studies that have indicated a stronger effect of the work–family balance on job satisfaction [ 58 , 59 ] and negative emotional responses [ 60 ] for women. Based on these premises, we hypothesized that:

The negative effect of work–family conflict (work-to-family and family-to work) on job satisfaction will be stronger for women than for men.

Similarly, there is evidence that parents experience more problems with the work–family balance than workers without children (for a meta-analysis, see [ 61 ]). This is often because family-related demands are higher for parents [ 62 ]. However, we also sustain that the importance that is given to the family domain is higher for workers with children than for those without. Thus, we hypothesized that:

The negative effect of work–family conflict (work-to-family and family-to work) on job satisfaction will be stronger for workers with children than for those without.

Socioemotional selectivity theory (SST) [ 63 ] sustains that individuals have an intrinsic perception of the time left in their life—the future time perspective—and based on that, they adjust their preferences and behavior. A shortened future time perspective promotes the pursuit of short-term emotion-related goals, such as positive emotional and psychological well-being, and it devaluates long-term goals, such as the development of skills or career advancements [ 63 ]. In the WLB literature, SST implies that elderly workers, who have a shorter future time perspective, should consider family relationships more important than work [ 64 ]. Therefore, a high level of work-to-family conflict will affect elderly workers and their evaluation of job satisfaction more than younger worker. In line with this, Treadway et al. [ 65 ] found that, in the presence of a high work-to-family conflict, workers with a more constrained future time perspective experienced a lower continuance commitment than employees with a less shallow future time perspective.

The negative effect of work–family conflict (work-to-family and family-to-work) on job satisfaction will be stronger for elderly workers than for younger workers.

Because increasing age is associated with higher morbidity, (multiple) chronic conditions, and higher use of health services [ 66 ], the importance of the health domain is expected to be higher among elderly workers than younger workers. Therefore, we hypothesized that:

The positive effect of the WHB on job satisfaction will be stronger for elderly workers than for younger workers.

Finally, work ability is expected to play a role in association with the WHB. Work ability represents the perceived ability to do one’s job effectively and to continue to do so in the near future when considering personal health problems and resources [ 66 ]. Thus, in the life of workers with a low work ability, the health domain generally has more importance than workers with a high work ability because health is a current problem. Considering this, we hypothesized that:

The positive effect of the WHB on job satisfaction will be stronger for workers with a low work ability than for those with a high work ability.

3. Materials and Methods

3.1. sample and procedure.

The study involved workers of full age under an employment contract. Entrepreneurs and self-employed workers were excluded. We distributed the link to the online questionnaire with a brief description of the research through social networks (i.e., Facebook and LinkedIn), messaging applications, and email. To begin the assessment, the participants had to read and approve an informed consent form to freely decide whether to participate in the research. The informed consent provided informed about the aim of the study and the procedures to collect the data, and it ensured that there were no potential risks or costs involved. The research team assured the anonymity and confidentiality of the participants’ responses throughout the entire study process. The contact details of the researcher in charge were provided in the event of any further questions. The study was conducted in accordance with the ethical standards set by the Declaration of Helsinki and was approved by the Ethical Committee of the University of Milano-Bicocca (Prot.160-2014). The number of subjects that started the questionnaire was 350. However, the dataset used in the analyses contained 318 responses after excluding 32 questionnaires because they were substantially incomplete; that is, the subjects opened the online page of the questionnaire but did not answer any questions. These values represent a completion rate of 91%. All participants lived in Italy; 90% lived in northern Italy. Overall, 37%, 28%, and 35% of the respondents were between 20 and 30, 31 and 44, and 45 and 60 years old, respectively. The proportion of men and women, as well as people with and without children, was balanced in the sample (56% women and 58% with children). Among the 134 workers with children, 49%, 43%, and 8% of the respondents had one, two, and three or more children, respectively. The workers with one or more children under the age of twelve were 51%. Most of the respondents had a partner (76%) and at least an upper secondary school diploma (93%). Most of the participants worked full-time (85%) with an open-ended contract (79%) as a white-collar worker (72%). Table 1 presents detailed descriptive statistics of the sample.

Descriptive statistics of the sample (N = 318).

3.2. Measures

The sociodemographic information described above was provided by the respondents at the beginning of the online questionnaire.

Based on the instrument developed by Keeney et al. [ 11 ] to evaluate the importance in the WLB attached to the different life domains (family, health, household management, friendship, training activities, favorite leisure activities, and community involvement), respondents were asked “How important is it in your life to reconcile work with …? ”. The question was asked, changing the final part, for all of the seven domains of life considered. The response scale was a 10-point scale from 1 (not at all important) to 10 (extremely important).

Two forms of the WLB were measured: the work–family balance and the work–health balance. The work–family balance was measured in the form of the work-to-family conflict (WFC—three items, α = 0.79) and family-to-work conflict (FWC—three items, α = 0.72) with the abbreviated version of the measure of work–family conflict [ 67 ]. Answers were given with a five-point Likert scale, from 1 (completely disagree) to 5 (completely agree). The work–health balance was measured with the Work–Health Balance Questionnaire [ 15 ], which was composed of three subscales: work–health incompatibility (WH—six items, α = 0.84), health climate (HC—five items, α = 0.92), and external support (ES—six items, α = 0.81). The total WHB score was calculated by subtracting WHI from the mean of HC and ES. Answers were given according to a five-point rating scale from 1 (completely disagree) to 5 (completely agree) for WHI and from 1 (never) to 5 (always) for HC and ES.

Work ability, the perceived ability to do one’s job effectively and to continue to do so in the near future when considering personal health problems and resources, was measured with the Work Ability Index (WAI) [ 68 ]. The index was calculated from seven factors (α = 0.79) for a total of 10 items with different rating scales.

Job satisfaction was measured with a single item that asked respondents to rate their overall satisfaction with their job on a 5-point scale from 1 (not at all satisfied) to 5 (fully satisfied). The reliability and validity of the single-item measure to assess job satisfaction has been established [ 69 ].

Harman’s single-factor test was adopted to check for a common method bias. The first factor explained 27% of the variance. Given that this fell below the threshold of 50%, the common method bias does not appear to have been a significant factor in this study. The results of the explorative factor analysis performed for the Harman single-factor test are available in the online Supplementary Materials of this article.

3.3. Data Analysis

All data analyses were performed by using R [ 70 ]. The different life domains were ordered according to the mean importance to the WLB that was attached to them by the respondents. Mean and standard deviations were provided for all the life domains. To test whether family and health domains were considered more important than the other life domains in the WLB (H1), the mean of the importance that was attached to health and family were compared to the mean of the importance that was attached to all the other life domains with a paired t-test. Even if no hypothesis was formulated specifically on this point, we explored whether the family and health domain were considered equally important. A paired t-test between the importance ascribed to family and to health was performed.

The hypotheses about the direction and effect size of work-to-family conflict, family-to-work conflict, and the WHB on job satisfaction (H2a,b and H3a,b) were tested with a multiple linear regression with job satisfaction as the dependent variable and work-to-family conflict, family-to-work conflict and the WHB as independent variables. To evaluate the relative importance of these predictors to the multiple regression model just described, we used the Lindeman, Merenda, and Gold’s metric (LMG) and reported the standardized β . The LMG expresses the squared semipartial correlation that was averaged across all possible ordering of the predictors. Since each order of predictors yields a different decomposition of the model sum of squares, the variance of the dependent variable that is explained by a predictor in a multiple regression varies according to the sequential order in which a predictor is entered into the model in relation to the other predictors. LMG averaged this value for all the possible orders of entry [ 71 ]. As a result, LMG considers both the predictor’s direct effect and its effect when combined with other predictors. Conversely, the standardized β represents only the incremental contribution of each predictor when combined with all remaining predictors [ 71 , 72 ].

This model, as well as the other following models, was controlled for age, marital status, and parental status. The control variables to be included were chosen with a backward model selection by the Akaike information criterion (AIC) from an initial model that included age, gender, education level, marital and parental status, job role, type of contract, and working hours. These preliminary analyses are available in the online Supplementary Material of this article.

Finally, the hypotheses about the moderation of the relation between the work–family balance and/or the WHB with job satisfaction (H4a–e) by individual characteristics (age, gender, parental status, and work ability) were tested with several models—one per moderator—with interaction effects. Continuous variables involved in the interaction were centered on the mean.

4.1. Perceived Importance of Family and Health Domain

The mean and standard deviation of the importance that is attached to the different life domains, ordered by their importance, are listed in Figure 1 .

Mean importance and standard deviation of the seven life domains.

The first paired t-test resulted in a significant difference in the mean of the importance that was attached to health and family (M = 9.27 and SD = 1.04) and those ascribed to the other life domains (M = 7.3 and SD = 1.32); t (317) = 25.7 and p < 0.001. This result supported H1a, that is, the health and family domains were considered to be more important than the other domains in the WLB.

Moreover, the second paired t-test resulted in a nonsignificant difference in the importance that is attached to health (M = 9.29 and SD = 1.18) and those attached to family (M = 9.25 and SD = 1.3); t (317) = 0.57 and p = 0.57. This exploratory analysis showed that health and family are life domains considered of equivalent importance in the WLB.

4.2. Consequences of Work–Family and Work–Health Balance on Job Satisfaction

Table 2 presents the result of the first model that tested the effects of work-to-family conflict, family-to-work conflict, and the WHB on job satisfaction (R 2 = 0.28, F (6/308) = 20.24, and p < 0.001).

Adjusted effects of work-to-family conflict, family-to-work conflict, and the work–health balance (WHB) on job satisfaction.

*** = p < 0.001; ** = p < 0.01; * = p < 0.05; 1 se = standard error.

The model resulted in a significant negative effect of work-to-family conflict and a nonsignificant effect of family-to-work conflict, thus partially supporting H2a. The LMG of work-to-family conflict on job satisfaction (LMG = 0.08) was eight times greater than that of family-to-work conflict (LMG = 0.01). Moreover, the former was statistically significant, while the other was not. These results fully supported H2b. Considering the effect of the WHB on job satisfaction, the model estimated a significant positive effect, supporting H3a. Moreover, the variance that was explained by the WHB (LMG = 0.16) was twice as much as the variance that was explained by work-to-family conflict (LMG = 0.08), supporting H3b.

4.3. Moderators of the Effects of Work–Family and Work–Health Balance

Table 3 reports models 1 and 2, which tested the moderating effect of gender and parental status, respectively.

Adjusted effects of work-to-family conflict, family-to-work conflict, and the WHB on job satisfaction.

*** = p < 0.001; ** = p < 0.01; * = p < 0.05; 1 In model 1, the moderator is gender (female); in model 2, the moderator is parental status (no children). Continuous variables in the interactions have been centered on the mean.

Model 1 (R 2 = 0.30, F (9/305) = 14.54, and p < 0.001) in Table 3 showed a significant negative interaction of gender with work-to-family conflict but no interaction with family-to-work conflict. The interaction indicates that the negative effect of work-to-family conflict on job satisfaction was stronger among women than among men. To facilitate the interpretation, the interaction effect is depicted in Figure 2 . This result partially supported H4a: The effect of the work–family balance, specifically of work-to-family conflict, on job satisfaction was stronger among women than among men.

Moderating effect of gender on the relationship between work-to-family conflict and job satisfaction.

Model 2 (R 2 = 0.31, F (8/306) = 17.46, and p < 0.001) in Table 3 again showed a significant interaction of work-to-family conflict with the moderator (i.e., parental support) but no interaction of the moderator with family-to-work conflict. The interaction indicates that the negative effect of work-to-family conflict on job satisfaction was stronger among workers with children than among those without. This interaction effect is depicted in Figure 3 . This result partially supported H4b: The effect of the work–family balance on job satisfaction, specifically of work-to-family conflict, is stronger among workers with children than among those without.

Moderating effect of parental status on the relationship between work-to-family conflict and job satisfaction.

Table 4 reports models 3 and 4, which tested the effects of two moderators—age and work ability, respectively. Model 3 (R 2 = 0.31, F (9/305) = 15.28, and p < 0.001) in Table 4 showed a significant interaction of age with work-to-family and family-to-work conflict but no interaction with the WHB.

*** = p < 0.001; ** = p < 0.01; * = p < 0.05; 1 In model 3, the moderator is age; in model 4, the moderator is work ability. Continuous variables in the interactions have been centered on the mean.

The interactions showed that the negative effect of work-to-family conflict on job satisfaction increased with age ( Figure 4 a), whereas family-to-work conflict appeared to have a positive effect for older workers ( Figure 4 b). These results again supported H4c only for work-to-family conflict, whereas they showed an unexpected positive effect of family-to-work conflict on job satisfaction among the elderly. In contrast, the results did not support H4d because the effect of the WHB on job satisfaction did not seem to increase with age.

( a ) Moderating effect of age on the relationship between work-to-family conflict and job satisfaction. ( b ) Moderating effect of age on the relationship between family-to-work conflict and job satisfaction.

Model 4 (R 2 = 0.33, F (8/306) = 18.18, and p < 0.001) in Table 4 showed a significant negative interaction between the WHB and work ability. The interaction showed that the positive effect of the WHB on job satisfaction decreased with the increase in work ability ( Figure 5 ). This result supported H4e: The positive effect of the WHB on job satisfaction increased with the decline in work ability.

Moderating effect of work ability on the relationship between the work–health balance and job satisfaction.

5. Discussion

This study aimed to verify the importance of different, specific nonwork domains in the work–life balance process, with a focus on family and health. We also investigated the impact of the work–family balance (in both directions) and the work–health balance on job satisfaction and how the heterogeneity of the current workforce modifies these relationships.

The results supported the first hypothesis. As hypothesized, when considering their work–life balance, the workers attached more importance to the health and family domains than to the other nonwork domains. A further analysis showed that the health and family domains were given similar importance. This result was the starting point of the entire study and justified the inclusion of the concept of the work–health balance. The workers rated family and health as 25% more important than the other nonwork life domain in their work–life balance. The fact that health was important as family is a relevant result, and it was found to be even more important when we analyzed the sample. Indeed, there were no apparent sample characteristics that made this sample more exposed to health issues than the general population. This fact suggests that researchers and companies should pay more attention to the health domain even for workers that are not affected by severe or chronic health conditions.

The second hypothesis concerned the effect of the work–family balance on job satisfaction. The work–family balance was supposed to affect job satisfaction, and work-to-family conflict was supposed to be more important than family-to-work conflict. The results supported this hypothesis and, consistent with other studies, the effect of family-to-work conflict on job satisfaction was smaller than that of work-to-family conflict and was statistically not significant [ 73 ]. This result can be explained in light of the appraisal theory [ 40 ]: If work threatens family life (work–life conflict), work will be negatively appraised; if family issues threaten work participation (family–work conflict), family, not the work, will be negatively appraised [ 41 ]. Consistent with a prior meta-analysis [ 29 ], these results support the “matching-hypothesis” (work-to-family conflict affects the work domain more, whereas family-to-work conflict affects the family domain more) as opposed to the “cross-domain hypothesis” (work-to-family conflict affects the family domain more, whereas family-to-work conflict affects the work domain more). Our study provides new evidence in this sense because the regression model was controlled for the work–health balance and because of the adoption of the LMG metric.

The third hypothesis investigated the effect of the WHB on job satisfaction and its importance relative to work–family conflict. As hypothesized, the WHB had a positive and statistically significant relationship with job satisfaction, and its importance was two times greater than that of work-to-family conflict. This result supports the usefulness of the specific instrument, the WHB questionnaire, and confirms the importance of filling the gap in the literature [ 42 ] by introducing the health domain into the concept of the work–life balance. Even if our results cannot be considered definitive in saying that the health domain is more important than the family domain in the genesis of job satisfaction, they clearly indicate that, when investigating or promoting work–life balance, considering the WHB is at least as important as considering the work–family balance. The common practice of considering the work–life balance as an issue that is related only to family is wrong and limits the possibility to explain work phenomena through the lens of the work–life balance.

The fourth hypothesis was related to the moderation of the effects of work–family conflict and the WHB by specific work characteristics (i.e., gender, parental status, age, and work ability) on job satisfaction. All three hypothesized moderators of the effect of work-to-family conflict on job satisfaction (i.e., gender, parental status, and age) were supported, whereas only one moderator of the family-to-work conflict effect (i.e., age) was sustained. Of the two hypothesized moderators (age and work ability) of the WHB effect on job satisfaction, only the interaction with work ability was supported.

In particular, the impact of work-to-family conflict on job satisfaction was greater for women (H4a), parent workers (H4b), and elderly workers (H4c). The reason for this moderation effect is likely due to the difference in salience of the family domain attached by the groups of workers. Women are likely to evaluate family as more central in their lives than men because of widespread cultural norms and gender-differentiated values [ 56 , 57 ]. Likewise, parents are likely to give more salience to family than people with no children because of cultural norms and, possibly, because of a “self-selection process” that brings people with a high salience of family to be more prone to parenthood than people with a low salience [ 62 , 74 ]. Given such result, it is possible, and should be tested in future studies, that being responsible for eldercare, beyond generally increasing the level of work-to-family conflict, also increases the impact of work-to-family conflict on job satisfaction. Finally, as implied by the socioemotional selectivity theory, elderly workers are likely to consider family relationships more important than younger workers because of a shorter future time perspective [ 64 ].

Given the theoretically coherent nonsignificant main effect of family-to-work conflict on job satisfaction, it was not surprising that the hypothesized moderators of its effects were not relevant. However, the moderation of the effect of family-to-work conflict on job satisfaction by age was significant and indicated that among older workers, a higher level of family-to-work conflict was related to higher job satisfaction. A further analyses showed that the effect of family-to-work conflict was nonsignificant among workers of 27 (the first quartile) and 38 years of age (the mean age), but this effect was statistically significant among workers of 49 years of age (the third quartile). The interpretation of this effect is hazardous with the data at hand. Further studies should investigate this effect while also considering the cross-sectional nature of our study. In fact, it is not possible to exclude that the found relationship was inverse. That is, older workers with higher job satisfaction perceived a higher family-to-work conflict because of a greater importance that is attached to the work domain than other elderly workers with lower job satisfaction.

Concerning the WHB, we hypothesized that its effect on job satisfaction was stronger among older workers (H4d) and workers with a lower WAI score (H4e). Since the interaction term was not significant in the case of age, H4d was not supported. Our results showed that a good WHB was associated with an equally high job satisfaction among all ages. We believe this is simply because, in our sample, the importance that was given to the health domain was not associated with age. This idea was supported by post hoc analyses that correlated the importance that was given by the workers to the health domain with their age, which resulted in a nonsignificant correlation ( r = −0.09, t = −1.62, and p = 0.11). We believe this result indicates that the health domain is crucial for both younger and older workers. There is the possibility that the WHB is a very important dimension at all ages—not only for elderly workers as originally intended [ 15 ]. In contrast, our results supported H4e. With the decline of the WAI, that is, with more health problems affecting job activity, the importance of the positive effect of the WHB on job satisfaction was increased. As proposed elsewhere [ 15 ], workers who are more vulnerable to health problems had a greater gain from their work situation with a good balance between health needs and work demands than healthy workers.

Overall, the results regarding the hypothesized moderators indicate that it is crucial to take into account the heterogeneity of the current workforce and to consider the specificity of different groups of workers when considering the WLB. From the outset, most definitions of the work–life balance have stressed the fact that it is not possible to identify an absolute optimal balance because it depends on the importance that the worker gives to the different domains of life [ 1 , 9 , 10 , 16 ]. Despite being theoretically clear, individual differences have been mainly overlooked in the WLB literature. Our study presents strong evidence that the issue must be considered, especially in light of the large presence of women, elderly individuals, people with an LSHPD, singles, and childless couples in the labor force [ 12 , 13 , 14 ].

The current study presents some limitations to consider when interpreting the results. First, the study design was cross-sectional. This limits our confidence in determining the cause and effect in the relationships between the considered variables. We based our considerations on a strong theoretical basis [ 10 , 29 ], but longitudinal studies are needed to replicate our findings.

Second, we adopted an online recruitment procedure that has the problem of a participant selection bias because of the self-selection of participants [ 75 ]. The online recruitment made our sample not representative of the entire working population, but this was beyond our intent. As explained by Landers and Behrend [ 76 ], when the aim is to test theoretically relevant hypotheses, as in our study, sample representativeness is less crucial than when a study aims to estimate the presence and the level of one or more variables in the workers’ population. Of course, our results must be replicated in other samples to increase their generalizability. By comparing our sample characteristics with data representative of the employees in north Italy [ 77 ] (data shown in the online Supplementary Material of this article), it is possible to note some differences in the proportions of job roles, type of occupations, and levels of education that are worth being mentioned. Specifically, like many studies in the WLB literature [ 7 ], in our sample, there was an over-representation of white-collar workers and an under-representation of blue-collar workers. There was an over-representation of clerical support workers and an under-representation of factory workers, skilled laborers, building workers, elementary occupations, and services and sale workers. Finally, the level of education of the sample was higher than in the general population of employees in north Italy. Given these specificities, it will be necessary to test whether the same results hold across samples with an appropriate representation of factory workers, skilled laborers, building workers, elementary occupations, and services and sale workers, as well as employees with a lower level of education.

Third, the measure of the importance that workers gave to the different life domains was based on the instrument of Keeney et al. [ 11 ], but the final instrument was created ad hoc for this study. Therefore, the measurement instrument may have biased the results regarding the importance of the different life domains. However, it should be considered that the questions that were posed to the participants were quite straightforward, and the values obtained for each domain were plausible and not extreme. Even if the instrument was not fine-tuned for exact comparisons, we believe it was appropriate for the aim of the study. The cited limitations warn against an unconditional generalization of the results of this study that, instead, have to be replicated with stronger research designs and other samples of workers.

6. Conclusions

The health issue has emerged in the organizational literature as a central topic. It no longer pertains to only small groups of workers with severe health problems. The changes in the labor force and of the patient’s role in the health system have made it impossible to consider the management of health as an exclusively nonworking activity. This study shows that workers are aware of the importance of the health domain for achieving a good work–life balance. Our results indicate health as a fundamental domain in the work–life balance dynamic that is as important as the family domain, if not more so. Researchers and practitioners should therefore consider the health domain in addition to the family domain when investigating the work–life balance.

By showing the differences in the effects of the work–family balance and the work–health balance on job satisfaction for different categories of workers, the present study demonstrates the importance of individual differences in the work–life balance process. That is, the balance between work and life is not absolute, but it is related to the importance that is given by the worker to the various domains. This relationship is of prominent importance in the current heterogeneous labor force.

Finally, our results provide evidence, to be replicated, that the importance of the work–health balance is not related to age, as previously believed; but only with the health condition.

Overall, this study is relevant for the work–life balance literature because, to the best of our knowledge, it is the first to consider the work–health balance. Moreover, it is one of the few studies that, through moderation analyses, investigates how the effect of the work–life balance on a relevant outcome changes according to workers’ characteristics.

Acknowledgments

We thank Martina Raimondi for her valuable assistance during the process of data collection and Zavagno D. for his help in proofreading the final changes made to the manuscript.

Supplementary Materials

The following are available online at https://www.mdpi.com/1660-4601/17/3/907/s1 , Table S1: Factor Loadings of the EFA performed for the Harman’s single factor test, Table S2: Percentage of variance explained by the factors, Table S3: Comparison of the characteristics of the sample with those of the population of employees in north Italy.

Author Contributions

Conceptualization, A.G. and M.M.; Methodology, A.G. and S.S.; Formal analysis, A.G.; Investigation, A.G. and M.M.; Data curation, A.G., M.M.; Writing—original draft preparation, A.G.; Writing—review and editing, S.S., M.M. and A.G.; Visualization, A.G. and S.S.; Supervision, M.M.; Project administration, M.M. All authors have read and agreed to the published version of the manuscript.

This research received no external funding. The APC was funded by the “Fondo di Ateneo” grant, from the University of Milano-Bicocca to M.M.

Conflicts of Interest

The authors declare no conflict of interest. The funder had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Work-life balance -a systematic review

Vilakshan - XIMB Journal of Management

ISSN : 0973-1954

Article publication date: 15 December 2021

Issue publication date: 31 July 2023

This study aims to systematically review the existing literature and develop an understanding of work-life balance (WLB) and its relationship with other forms of work-related behavior and unearth research gaps to recommend future research possibilities and priorities.

Design/methodology/approach

The current study attempts to make a detailed survey of the research work done by the pioneers in the domain WLB and its related aspects. A total of 99 research work has been included in this systematic review. The research works have been classified based on the year of publication, geographical distribution, the methodology used and the sector. The various concepts and components that have made significant contributions, factors that influence WLB, importance and implications are discussed.

The paper points to the research gaps and scope for future research in the area of WLB.

Originality/value

The current study uncovered the research gaps regarding the systematic review and classifications based on demography, year of publication, the research method used and sector being studied.

• Work-life balance
• Flexibility
• Individual’s ability to balance work-life
• Support system
• WLB policy utilization
• Societal culture

S., T. and S.N., G. (2023), "Work-life balance -a systematic review", Vilakshan - XIMB Journal of Management , Vol. 20 No. 2, pp. 258-276. https://doi.org/10.1108/XJM-10-2020-0186

Emerald Publishing Limited

Copyright © 2021, Thilagavathy S. and Geetha S.N.

Published in Vilakshan – XIMB Journal of Management . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

In this technological era, work is becoming demanding with changing nature of work and working patterns (Thilagavathy and Geetha, 2020 ). The proactive, aggressive and demanding nature of business with the intention of reaching the top requires active involvement and comprehensive devotion from the employees, thereby compromising their work-life balance (WLB) (Turanlıgil and Farooq, 2019 ). Research concerning the work-life interface has exploded over the past five decades because of the changing trends in the nature of gender roles, families, work and careers (Powell et al. , 2019 ). Researchers in this domain has published many literature reviews with regard to WLB. It is argued that the study of WLB remains snowed under by a lack of conceptual clarity (Perrigino et al. , 2018 ). Thus, research and theory only partially view the employees’ work-life needs and experiences.

How WLB is conceptualized in the past?

What are the factors that significantly influenced WLB?

In which geographical areas were the WLB studies undertaken?

Which sectors remain unstudied or understudied with regard to WLB?

Methodology

We systematically conducted the literature review with the following five steps, as shown in Figure 1 . The first step was to review the abstracts from the database like EBSCO, Science Direct, Proquest and JSTOR. The articles from publishers like ELSEVIER, Emerald insight, Springer, Taylor and Francis and Sage were considered. The literature survey was conducted using the search terms WLB, balancing work and family responsibility and domains of work and life between the period 1990 to 2019. This search process led to the identification of 1,230 relevant papers. Inclusion criteria: The scholarly articles concerning WLB published in the English language in journals listed in Scopus, web of science or Australian business deans council (ABDC) were included in this review. Exclusion criteria: The scholarly articles concerning WLB published in languages other than English were not taken into consideration. Similarly, unpublished papers and articles published in journals not listed in Scopus, web of science or ABDC were excluded.

In the second step, we identified the duplicates and removed them. Thus, the total number of papers got reduced to 960. Following this, many papers relating to work-life spillover and work-life conflict were removed, resulting in further reduction of the papers to 416. Subsequently, in the third step, the papers were further filtered based on the language. The paper in the English language from journals listed in Scopus, web of science or ABDC were only considered. This search process resulted in the reduction of related papers to 93. The fourth step in the search process was further supplemented with the organic search for the related articles, leading to 99 papers illustrated in Appendix Table 1 . In the fifth step, an Excel sheet was created to review the paper under different headings and the results are as follows.

Literature review

Evolution and conceptualization of work-life balance.

WLB concern was raised earlier by the working mothers of the 1960s and 1970s in the UK. Later the issue was given due consideration by the US Government during the mid of 1980. During the 1990s WLB gained adequate recognition as the issue of human resource management in other parts of the world (Bird, 2006 ). The scholarly works concerning WLB have increased, mainly because of the increasing strength of the women workforce, technological innovations, cultural shifts in attitudes toward the relationship between the work and the family and the diversity of family structures (Greenhaus and Kossek, 2014 ). The research works on WLB include several theoretical work-family models. Though the research on WLB has expanded to a greater extend, there are considerable gaps in our knowledge concerning work-family issues (Powell et al. , 2019 ).

Moreover, in studies where WLB and related aspects are explored, researchers have used different operational definitions and measurements for the construct. Kalliath and Brough (2008) have defined WLB as “The individual’s perception that work and non-work activities are compatible and promote growth in accordance with an individual’s current life priorities.” WLB is “a self-defined, self-determined state of well being that a person can reach, or can set as a goal, that allows them to manage effectively multiple responsibilities at work, at home and in their community; it supports physical, emotional, family, and community health, and does so without grief, stress or negative impact” (Canadian Department of Labor, as cited in Waters and Bardoel, 2006 ).

Figure 2 depicts the flowchart of the framework for the literature survey. It clearly shows the factors that have been surveyed in this research article.

Individual factors

The individual factors of WLB include demographic variables, personal demands, family demands, family support and individual ability.

Work-life balance and demography.

WLB has significant variations with demographic variables (Waters and Bardoel, 2006 ). A significant difference was found between age (Powell et al. , 2019 ), gender (Thilagavathy and Geetha, 2020 ) and marital status (Powell et al. , 2019 ) regarding WLB. There is a significant rise in women’s participation in the workforce (Jenkins and Harvey, 2019 ). WLB issues are higher for dual-career couples (Crawford et al. , 2019 ).

Many studies were conducted on WLB with reference to sectors like information technology (IT), information technology enabled services, Banking, Teaching, Academics and Women Employment. A few WLB studies are conducted among services sector employees, hotel and catering services, nurses, doctors, middle-level managers and entrepreneurs. Only very scarce research has been found concerning police, defense, chief executive officers, researchers, lawyers, journalists and road transport.

Work-life balance and personal demands.

High work pressure and high family demand lead to poor physical, psychological and emotional well-being (Jensen and Knudsen, 2017 ), causing concern to employers as this leads to reduced productivity and increased absenteeism (Jackson and Fransman, 2018 ).

Work-life balance and family demands.

An employee spends most of the time commuting (Denstadli et al. , 2017 ) or meeting their work and family responsibilities. Dual career couple in the nuclear family finds it difficult to balance work and life without domestic help (Dumas and Perry-Smith, 2018 ; Srinivasan and Sulur Nachimuthu, 2021 ). Difficulty in a joint family is elderly care (Powell et al. , 2019 ). Thus, family demands negatively predict WLB (Haar et al. , 2019 ).

Work-life balance and family support.

Spouse support enables better WLB (Dumas and Perry-Smith, 2018 ). Family support positively impacted WLB, especially for dual-career couples, with dependent responsibilities (Groysberg and Abrahams, 2014 ).

Work-life balance and individual’s ability.

Though the organizations implement many WLB policies, employees still face the problems of WLB (Dave and Purohit, 2016 ). Employees achieve better well-being through individual coping strategies (Zheng et al. , 2016 ). Individual resources such as stress coping strategy, mindfulness emotional intelligence positively predicted WLB (Kiburz et al. , 2017 ). This indicates the imperative need to improve the individual’s ability to manage work and life.

Organizational factor

Organizational factors are those relating to organization design in terms of framing policies, rules and regulations for administering employees and dealing with their various activities regarding WLB ( Kar and Misra, 2013 ). In this review, organizational factors and their impact on the WLB of the employee have been dealt with in detail.

Work-life balance and organizational work-life policies.

The organization provides a variety of WLB policies (Jenkins and Harvey, 2019 ). Employee-friendly policies positively influenced WLB ( Berg et al. , 2003 ). Further, only a few IT industries provided Flexi timing, work from home and crèches facilities (Downes and Koekemoer, 2012 ). According to Galea et al. (2014) , industry-specific nuance exists.

Work-life balance and organizational demands.

Organizations expect employees to multi-task, causing role overload (Bacharach et al. , 1991 ). The increasing intensity of work and tight deadlines negatively influenced WLB (Allan et al. , 1999 ). The shorter time boundaries make it challenging to balance professional and family life (Jenkins and Harvey, 2019 ). Job demands negatively predicted WLB (Haar et al. , 2019 ).

Work-life balance and working hours.

Work does vacuum up a greater portion of the personal hours (Haar et al. , 2019 ). This causes some important aspects of their lives to be depleted, undernourished or ignored (Hughes et al. , 2018 ). Thus, employees find less time for “quality” family life (Jenkins and Harvey, 2019 ).

Work-life balance and productivity.

Organizational productivity is enhanced by the synergies of work-family practices and work-team design (Johari et al. , 2018 ). Enhanced WLB leads to increased employee productivity (Jackson and Fransman, 2018 ).

Work-life balance and burnout.

WLB is significantly influenced by work exhaustion (burnout). Negative psychological experience arising from job stress is defined as burnout (Ratlif, 1988). Increased work and non-work demands contribute to occupational burnout and, in turn, negatively predict WLB and employee well-being (Jones et al. , 2019 ).

Work-life balance and support system.

Support from Colleagues, supervisors and the head of institutions positively predicted WLB (Ehrhardt and Ragins, 2019 ; Yadav and Sharma, 2021 ). Family-supportive organization policy positively influenced WLB (Haar and Roche, 2010 ).

Work-life balance and employee perception.

The employee’s perception regarding their job, work environment, supervision and organization positively influenced WLB (Fontinha et al. , 2019 ). Employees’ awareness concerning the existence of WLB policies is necessary to appreciate it (Matthews et al. , 2014). The employee’s perception of the need for WLB policies differs with respect to their background (Kiburz et al. , 2017 ).

Work-life balance and job autonomy.

Job autonomy is expressed as the extent of freedom the employee has in their work and working pattern ( Bailey, 1993 ). According to Ahuja and Thatcher (2005) , autonomy and flexibility enable employees to balance competing demands of work-life. Job autonomy will enhance WLB (Johari et al. , 2018 ).

Work-life balance and job satisfaction.

Job satisfaction is the driving force for task accomplishment and employees’ intention to stay (Brough et al. , 2014 ). Employees’ positive perception concerning their job enhances job satisfaction (Singh et al. , 2020 ; Yadav and Sharma, 2021 ). WLB and job satisfaction are positively correlated (Jackson and Fransman, 2018 ).

Work-life balance and organizational commitment.

Alvesson (2002) describes organizational commitment as a mutual and fair social exchange. WLB positively predicted organizational commitment (Emre and De Spiegeleare, 2019 ). Work-life policies offered by an organization lead to increased loyalty and commitment (Callan, 2008 ).

Work-life balance and work-life balance policy utilization.

The utilization of WLB policies (Adame-Sánchez et al. , 2018 ) helps meet job and family demands. Despite the availability of WLB policies, their actual adoption is rather small (Waters and Bardoel, 2006 ) and often lag behind implementation (Adame-Sánchez et al. , 2018 ).

Work-life balance and organizational culture.

Employees perceive WLB policy utilization may badly reflect their performance appraisal and promotion (Bourdeau et al. , 2019 ). Hence, seldom use the WLB policies (Dave and Purohit, 2016 ). The perception of the organization culture as isolated, unfriendly and unaccommodating (Fontinha et al. , 2017 ); a lack of supervisor and manager support and a lack of communication and education about WLB strategies (Jenkins and Harvey, 2019 ). This leads to counterproductive work behavior and work-family backlash (Alexandra, 2014 ). As a result, growing evidence suggests a dark side to WLB policies, but these findings remain scattered and unorganized (Perrigino et al. , 2018 ). Organizational culture significantly affects WLB policy utilization (Callan, 2008 ; Dave and Purohit, 2016 ).

Societal factors

Societal changes that have taken place globally and locally have impacted the individual’s lifestyle. In this modern techno world, a diversified workforce resulting from demographic shifts and communication technology results in blurring of boundaries between work and personal life (Kalliath and Brough, 2008 ).

Work-life balance and societal demands.

Being members of society, mandates employee’s participation in social events. But in the current scenario, this is witnessing a downward trend. The employee often comes across issues of inability to meet the expectation of friends, relatives and society because of increased work pressure. Societal demands significantly predicted WLB (Mushfiqur et al. , 2018 ).

Work-life balance and societal culture.

Societal culture has a strong influence on WLB policy utilization and work and non-work self-efficacy. Specifically, collectivism, power distance and gendered norms had a strong and consistent impact on WLB Policy utilization by employees (Brown et al. , 2019 ). Women’s aspiration to achieve WLB is frequently frustrated by patriarchal norms deep-rooted in the culture (Mushfiqur et al. , 2018 ).

Work-life balance and societal support.

WLB was significantly predicted by support from neighbors, friends and community members (Mushfiqur et al. , 2018 ). Sometimes employees need friend’s viewpoints to get a new perspective on a problem or make a tough decision (Dhanya and Kinslin, 2016 ). Community support is an imperative indicator of WLB ( Phillips et al. , 2016 ).

Analyzes and results

Article distribution based on year of publication.

The WLB studies included for this review were between the periods of 1990–2019. Only a few studies were published in the initial period. A maximum of 44 papers was published during 2016–2019. Out of which, 17 studies were published during the year 2019. In the years 2018, 2017 and 2016 a total of 12, 7 and 8 studies were published, respectively. The details of the article distribution over the years illustrate a rising trend, as shown in Figure 3 .

Geographical distribution

Papers considered for this review were taken globally, including the research works from 26 countries. American and European countries contributed to a maximum of 60% of the publications regarding WLB research. Figure 4 illustrates the contribution of different countries toward the WLB research.

Basic classification

The review included 99 indexed research work contributed by more than 70 authors published in 69 journals. The contribution worth mentioning was from authors like Allen T.D, Biron M, Greenhaus J. H, Haar J.M, Jensen M.T, Kalliath T and Mc Carthy A. The basic categorization revealed that the geographical distribution considered for this review was from 26 different countries, as shown in Figure 4 . The research was conducted in (but not limited to) countries like Africa, Australia, Canada, China, India, Israel, The Netherlands, Norway, New Zealand, Pakistan, Singapore, Sweden, Turkey, the USA and the UK. American and European countries together contributed to the maximum of 60% of publications. Further, the categorization uncovered that 7 out of the 99 journals contributed to 30% of the WLB papers considered for this review, clearly illustrated in Table 1 .

Methodology-based categorization of papers

The basic information like research methods, sources of data, the proportion of papers using specific methodologies were considered for methodology-based categorization. The categorization revealed that 27 out of 99 papers reviewed were conceptual and the remaining 72 papers were empirical. The empirical papers used descriptive, exploratory, explanatory or experimental research designs. Further, categorization based on the data collection method revealed that 69 papers used the primary data collection method. Additionally, classification uncovered that 57 papers used the quantitative method, whereas 11 papers used the qualitative approach and four used the mixed method. The most prominent primary method used for data collection was the questionnaire method with 58 papers, while the remaining 20 papers used interview (10), case study (5), experimental studies (3), daily dairy (1) or panel discussion (1).

Sector-based categorization of papers

The sector-based categorization of papers revealed that 41.6% (30 papers) of research work was carried out in service sectors. This is followed by 40.2% (29 papers) research in the general public. While one paper was found in the manufacturing sector, the remaining nine papers focused on managers, women, the defense sector, police and the public sector, the details of which are showcased in Table 2 .

Research gap

Individual factor.

The literature survey results demonstrated that the impact of employee education and experience on their WLB had not been examined.

The literature survey has uncovered that the relationship between income and WLB has not been explored.

The influence of domestic help on WLB has not been investigated.

Much of the research work has been carried out in developed countries like the US, UK, European countries and Australia. In contrast, very scarce research works have been found in developing countries and underdeveloped countries.

Not much work has been done in WLB regarding service sectors like fire-fighters, transport services like drivers, railway employees, pilots, air hostesses, power supply department and unorganized sectors.

A review of the relevant literature uncovered that studies concerning the individual’s ability to balance work and life are limited. The individual’s ability, along with WLB policies, considerably improved WLB. Individual strategies are the important ones that need investigation rather than workplace practices.

Kibur z et al . (2017) addressed the ongoing need for experimental, intervention-based design in work-family research. There are so far very scares experimental studies conducted with regard to WLB.

Organizational factor.

A very few studies explored the impact of the WLB policies after the implementation.

Studies concerning the organizational culture, psychological climate and WLB policy utilizations require investigation.

Organizational climates influence on the various factors that predict WLB needs exploration.

Societal factor.

The impact of the societal factors on WLB is not explored much.

Similarly, the influence of societal culture (societal beliefs, societal norms and values systems) on WLB is not investigated.

Discussion and conclusion

The current research work aspires to conduct a systematic review to unearth the research gaps, and propose direction for future studies. For this purpose, literature with regard to WLB was systematically surveyed from 1990 to 2019. This led to identifying 99 scientific research papers from index journals listed in Scopus, the web of science or the ABDC list. Only papers in the English language were considered. The review section elaborated on the evolution and conceptualization of WLB. Moreover, the literature review discussed in detail the relationship between WLB and other related variables. Further, the research works were classified based on the fundamental information revealed that a maximum of 44 papers was published during the year 2016–2019. The geographical distribution revealed that a maximum of research publications concerning WLB was from American and European countries. Further, the basic classification revealed that 7 out of the 69 journals contributed to 30% of the WLB papers considered for this review. The methodology-based classification unearthed the fact that 73% of the papers were empirical studies. Additionally, the categorization uncovered that 79% ( n = 57) of papers used quantitative methods dominated by survey method of data collection. Sector-based categorization made known the fact that a maximum of 41.6% of research work was carried out in the service sector. The research gaps were uncovered based on the systematic literature review and classifications and proposed future research directions.

Limitations

We acknowledge that there is a possibility of missing out a few papers unintentionally, which may not be included in this review. Further, papers in the English language were only considered. Thus, the papers in other languages were not included in this systematic review which is one of the limitations of this research work.

Implications

The discussion reveals the importance and essentiality of the individual’s ability to balance work and life. Consequently, the researchers have proposed future research directions exploring the relationship between the variables. WLB is an important area of research; thus, the proposed research directions are of importance to academicians. The review’s finding demonstrates that there are very scarce studies on the individual’s ability to balance work and life. This leaves a lot of scopes for researchers to do continuous investigation in this area. Hence, it is essential to conduct more research on developing individuals’ ability to balance work and life. There are a few experimental studies conducted so far in WLB. Future experimental studies can be undertaken to enhance the individual’s ability to balance work and life.

Flow chart of the steps in systematic review process

Framework for the literature review

Distribution of papers based on year of publication

Geographical distribution of papers across countries

Journals details

Table 1 List of papers included in the review

Adame-Sánchez , C. , Caplliure , E.M. and Miquel-Romero , M.J. ( 2018 ), “ Paving the way for competition: drivers for work-life balance policy implementation ”, Review of Managerial Science , Vol. 12 No. 2 , pp. 519 - 533 , doi: 10.1007/s11846-017-0271-y .

Ahuja , M. and Thatcher , J. ( 2005 ), “ Moving beyond intentions and towards the theory of trying: effects of work environment and gender on post-adoption information technology use ”, MIS Quarterly , Vol. 29 No. 3 , pp. 427 - 459 .

Allan , C. , O'Donnell , M. and Peetz , D. ( 1999 ), “ More tasks, less secure, working harder: three dimensions of labour utilization ”, Journal of Industrial Relations , Vol. 41 No. 4 , pp. 519 - 535 , doi: 10.1177/002218569904100403 .

Alvesson ( 2002 ), Understanding Organizational Culture , Sage Publications , London . 10.4135/9781446280072

Bacharach , S.B. , Bamberger , R. and Conely , S. ( 1991 ), “ Work-home conflict among nurses and engineers: mediating the impact of stress on burnout and satisfaction at work ”, Journal of Organizational Behavior , Vol. 12 No. 1 , pp. 39 - 63 , doi: 10.1002/job.4030120104 .

Bailey , T.R. ( 1993 ), “ Discretionary effort and the organization of work: employee participation and work reform since Hawthorne ”, Teachers College and Conservation of Human Resources , Columbia University .

Bardoel , E.A. ( 2006 ), “ Work-life balance and human resource development ”, Holland , P. and De Cieri , H. (Eds), Contemporary Issues in Human Resource Development: An Australian Perspective , Pearson Education , Frenchs Forest, NSW , pp. 237 - 259 .

Berg , P. , Kalleberg , A.L. and Appelbaum , E. ( 2003 ), “ Balancing work and family: the role of high - commitment environments ”, Industrial Relations , Vol. 42 No. 2 , pp. 168 - 188 , doi: 10.1111/1468-232X.00286 .

Bird , J. ( 2006 ), “ Work-life balance: doing it right and avoiding the pitfalls ”, Employment Relations Today , Vol. 33 No. 3 , pp. 21 - 30 , doi: 10.1002/ert.20114 .

Bourdeau , S. , Ollier-Malaterre , A. and Houlfort , N. ( 2019 ), “ Not all work-life policies are created equal: career consequences of using enabling versus enclosing work-life policies ”, Academy of Management Review , Vol. 44 No. 1 , pp. 172 - 193 , doi: 10.5465/amr.2016.0429 .

Brough , P. , Timm , C. , Driscoll , M.P.O. , Kalliath , T. , Siu , O.L. , Sit , C. and Lo , D. ( 2014 ), “ Work-life balance: a longitudinal evaluation of a new measure across Australia and New Zealand workers ”, The International Journal of Human Resource Management , Vol. 25 No. 19 , pp. 2724 - 2744 , doi: 10.1080/09585192.2014.899262 .

Callan , S.J. ( 2008 ), “ Cultural revitalization: the importance of acknowledging the values of an organization's ‘golden era’ when promoting work-life balance ”, Qualitative Research in Organizations and Management: An International Journal , Vol. 3 No. 1 , pp. 78 - 97 , doi: 10.1108/17465640810870409 .

Crawford , W.S. , Thompson , M.J. and Ashforth , B.E. ( 2019 ), “ Work-life events theory: making sense of shock events in dual-earner couples ”, Academy of Management Review , Vol. 44 No. 1 , pp. 194 - 212 , doi: 10.5465/amr.2016.0432 .

Dave , J. and Purohit , H. ( 2016 ), “ Work-life balance and perception: a conceptual framework ”, The Clarion- International Multidisciplinary Journal , Vol. 5 No. 1 , pp. 98 - 104 .

Denstadli , J.M. , Julsrud , T.E. and Christiansen , P. ( 2017 ), “ Urban commuting – a threat to the work-family balance? ”, Journal of Transport Geography , Vol. 61 , pp. 87 - 94 , doi: 10.1016/j.jtrangeo.2017.04.011 .

Downes , C. and Koekemoer , E. ( 2012 ), “ Work-life balance policies: the use of flexitime ”, Journal of Psychology in Africa , Vol. 22 No. 2 , pp. 201 - 208 , doi: 10.1080/14330237.2012.10820518 .

Dumas , T.L. and Perry-Smith , J.E. ( 2018 ), “ The paradox of family structure and plans after work: why single childless employees may be the least absorbed at work ”, Academy of Management Journal , Vol. 61 No. 4 , pp. 1231 - 1252 , doi: 10.5465/amj.2016.0086 .

Ehrhardt , K. and Ragins , B.R. ( 2019 ), “ Relational attachment at work: a complimentary fit perspective on the role of relationships in organizational life ”, Academy of Management Journal , Vol. 62 No. 1 , pp. 248 - 282 , doi: 10.5465/amj.2016.0245 .

Emre , O. and De Spiegeleare , S. ( 2019 ), “ The role of work-life balance and autonomy in the relationship between commuting, employee commitment, and well-being ”, The International Journal of Human Resource Management , Vol. 32 No. 11 , pp. 1 - 25 , doi: 10.1080/09585192.2019.1583270 .

Fontinha , R. , Easton , S. and Van Laar , D. ( 2017 ), “ Overtime and quality of working life in academics and non-academics: the role of perceived work-life balance ”, International Journal of Stress Management , ( in Press ).

Fontinha , R. , Easton , S. and Van Laar , D. ( 2019 ), “ Overtime and quality of working life in academics and non-academics: the role of perceived work-life balance ”, International Journal of Stress Management , Vol. 26 No. 2 , pp. 173 , doi: 10.1037/str0000067 .

Galea , C. , Houkes , I. and Rijk , A.D. ( 2014 ), “ An insider’s point of view: how a system of flexible working hours helps employees to strike a proper balance between work and personal life ”, The International Journal of Human Resource Management , Vol. 25 No. 8 , pp. 1090 - 1111 , doi: 10.1080/09585192.2013.816862 .

Greenhaus , J.H. and Kossek , E.E. ( 2014 ), “ The contemporary career: a work–home perspective ”, Annual Review of Organizational Psychology and Organizational Behavior , Vol. 1 No. 1 , pp. 361 - 388 , doi: 10.1146/annurev-orgpsych-031413-091324 .

Groysberg , B. and Abrahams , R. ( 2014 ), “ Manage your work, manage your life ”, Harvard Business Review , Vol. 92 No. 3 , pp. 58 - 66 , available at: https://hbr.org/2014/03/manage-your-work-manage-your-life

Haar , J.M. and Roche , M. ( 2010 ), “ Family-supportive organization perceptions and employee outcomes: the mediating effects of life satisfaction ”, The International Journal of Human Resource Management , Vol. 21 No. 7 , pp. 999 - 1014 , doi: 10.1080/09585191003783462 .

Haar , J.M. , Sune , A. , Russo , M. and Ollier-Malaterre , A. ( 2019 ), “ A cross-national study on the antecedents of work-life balance from the fit and balance perspective ”, Social Indicators Research , Vol. 142 No. 1 , pp. 261 - 282 , doi: 10.1007/s11205-018-1875-6 .

Hughes , R. , Kinder , A. and Cooper , C.L. ( 2018 ), “ Work-life balance ”, The Wellbeing Workout , pp. 249 - 253 , doi: 10.1007/978-3-319-92552-3_42 .

Jackson , L.T. and Fransman , E.I. ( 2018 ), “ Flexi work, financial well-being, work-life balance and their effects on subjective experiences of productivity and job satisfaction of females in an institution of higher learning ”, South African Journal of Economic and Management Sciences , Vol. 21 No. 1 , pp. 1 - 13 , doi: 10.4102/sajems.v21i1.1487 .

Jenkins , K. and Harvey , S.B. ( 2019 ), “ Australian experiences ”, Mental Health in the Workplace , pp. 49 - 66 . Springer , Cham .

Jensen , M.T. and Knudsen , K. ( 2017 ), “ A two-wave cross-lagged study of business travel, work-family conflict, emotional exhaustion, and psychological health complaints ”, European Journal of Work and Organizational Psychology , Vol. 26 No. 1 , pp. 30 - 41 , doi: 10.1080/1359432X.2016.1197206 .

Johari , J. , Yean Tan , F. and TjikZulkarnain , Z.I. ( 2018 ), “ Autonomy, workload, work-life balance, and job performance among teachers ”, International Journal of Educational Management , Vol. 32 No. 1 , pp. 107 - 120 , doi: 10.1108/IJEM-10-2016-0226 .

Jones , R. , Cleveland , M. and Uther , M. ( 2019 ), “ State and trait neural correlates of the balance between work-non work roles ”, Psychiatry Research: Neuroimaging , Vol. 287 , pp. 19 - 30 , doi: 10.1016/j.pscychresns.2019.03.009 .

Kalliath , T. and Brough , P. ( 2008 ), “ Work-life balance: a review of the meaning of the balance construct ”, Journal of Management & Organization , Vol. 14 No. 3 , pp. 323 - 327 , doi: 10.1017/S1833367200003308 .

Kar , S. and Misra , K.C. ( 2013 ), “ Nexus between work life balance practices and employee retention-the mediating effect of a supportive culture ”, Asian Social Science , Vol. 9 No. 11 , p. 63 , doi: 10.1016/j.soscij.2019.03.008 , doi: 10.5539/ass.v9n11p63 .

Kiburz , K.M. , Allen , T.D. and French , K.A. ( 2017 ), “ Work-family conflict and mindfulness: investigating the effectiveness of a brief training intervention ”, Journal of Organizational Behavior , Vol. 38 No. 7 , pp. 1016 - 1037 , doi: 10.1002/job.2181 .

Mushfiqur , R. , Mordi , C. , Oruh , E.S. , Nwagbara , U. , Mordi , T. and Turner , I.M. ( 2018 ), “ The impacts of work-life balance (WLB) challenges on social sustainability: the experience of nigerian female medical doctors ”, Employee Relations , Vol. 40 No. 5 , pp. 868 - 888 , doi: 10.1108/ER-06-2017-0131 .

Perrigino , M.B. , Dunford , B.B. and Wilson , K.S. ( 2018 ), “ Work-family backlash: the ‘dark side’ of work-life balance (WLB) policies ”, Academy of Management Annals , Vol. 12 No. 2 , pp. 600 - 630 , doi: 10.5465/annals.2016.0077 .

Phillips , J. , Hustedde , C. , Bjorkman , S. , Prasad , R. , Sola , O. , Wendling , A. and Paladine , H. ( 2016 ), “ Rural women family physicians: strategies for successful work-life balance ”, The Annals of Family Medicine , Vol. 14 No. 3 , pp. 244 - 251 .

Powell , G.N. , Greenhaus , J.H. , Allen , T.D. and Johnson , R.E. ( 2019 ), “ Introduction to special topic forum: advancing and expanding work-life theory from multiple perspectives ”, Academy of Management Review , Vol. 44 No. 1 , pp. 54 - 71 , doi: 10.5465/amr.2018.0310 .

Ratliff , N. ( 1988 ), “ Stress and burnout in the helping professions ”, Social Casework , Vol. 69 No. 1 , pp. 147 - 154 .

Singh , S. , Singh , S.K. and Srivastava , S. ( 2020 ), “ Relational exploration of the effect of the work-related scheme on job satisfaction ”, Vilakshan – XIMB Journal of Management , Vol. 17 Nos 1/2 , pp. 111 - 128 , doi: 10.1108/XJM-07-2020-0019 .

Srinivasan , T. and Sulur Nachimuthu , G. ( 2021 ), “ COVID-19 impact on employee flourishing: parental stress as mediator ”, Psychological Trauma: Theory, Research, Practice, and Policy. Advance Online Publication , doi: 10.1037/tra0001037 .

Thilagavathy , S. and Geetha , S.N. ( 2020 ), “ A morphological analyses of the literature on employee work-life balance ”, Current Psychology , pp. 1 - 26 , doi: 10.1007/s12144-020-00968-x .

Turanlıgil , F.G. and Farooq , M. ( 2019 ), “ Work-Life balance in tourism industry ”, in Contemporary Human Resources Management in the Tourism Industry , pp. 237 - 274 , IGI Global .

Waters , M.A. and Bardoel , E.A. ( 2006 ), “ Work-family policies in the context of higher education: useful or symbolic? ”, Asia Pacific Journal of Human Resources , Vol. 44 No. 1 , pp. 67 - 82 , doi: 10.1177/1038411106061510 .

Yadav , V. and Sharma , H. ( 2021 ), “ Family-friendly policies, supervisor support, and job satisfaction: mediating effect of work-family conflict ”, Vilakshan - XIMB Journal of Management , doi: 10.1108/XJM-02-2021-0050 .

Zheng , C. , Kashi , K. , Fan , D. , Molineux , J. and Ee , M.S. ( 2016 ), “ Impact of individual coping strategies and organizational work-life balance programmes on australian employee well-being ”, The International Journal of Human Resource Management , Vol. 27 No. 5 , pp. 501 - 526 , doi: 10.1080/09585192.2015.1020447 .

Further reading

Allen , T.D. ( 2012 ), “ The work and family interface ”, in Kozlowski , S.W.J. (Ed.), The Oxford Handbook of Organizational Psychology , Vol. 2 , Oxford University Press , New York, NY , pp. 1163 - 1198 .

Bell , A.S. , Rajendran , D. and Theiler , S. ( 2012 ), “ Job stress, wellbeing, work-life balance and work-life conflict among Australian academics ”, Electronic Journal of Applied Psychology , Vol. 8 No. 1 , pp. 25 - 37 .

Biron , M. ( 2013 ), “ Effective and ineffective support: how different sources of support buffer the short–and long–term effects of a working day ”, European Journal of Work and Organizational Psychology , Vol. 22 No. 2 , pp. 150 - 164 , doi: 10.1080/1359432X.2011.640772 .

Carlson , D.S. and Kacmar , K.M. ( 2000 ), “ Work-family conflict in the organization: do life role values make a difference? ”, Journal of Management , Vol. 26 No. 5 , pp. 1031 - 1054 , doi: 10.1177/014920630002600502 .

Clark , S.C. ( 2000 ), “ Work/family border theory: a new theory of work/family balance ”, Human Relations , Vol. 53 No. 6 , pp. 747 - 770 , doi: 10.1177/0018726700536001 .

Daipuria , P. and Kakar , D. ( 2013 ), “ Work-Life balance for working parents: perspectives and strategies ”, Journal of Strategic Human Resource Management , Vol. 2 No. 1 , pp. 45 - 52 .

Gregory , A. and Milner , S. ( 2009 ), “ Editorial: work-life balance: a matter of choice? ”, Gender, Work & Organization , Vol. 16 No. 1 , pp. 1 - 13 , doi: 10.1111/j.1468-0432.2008.00429.x .

Hirschi , A. , Shockley , K.M. and Zacher , H. ( 2019 ), “ Achieving work-family balance: an action regulation model ”, Academy of Management Review , Vol. 44 No. 1 , pp. 150 - 171 , doi: 10.5465/amr.2016.0409 .

Adame-Sánchez , C. , Caplliure , E.M. and Miquel-Romero , M.J. ( 2018 ), “ Paving the way for coopetition: drivers for work–life balance policy implementation ”, Review of Managerial Science , Vol. 12 No. 2 , pp. 519 - 533 , doi: 10.1007/s11846-017-0271-y .

Adame , C. , Caplliure , E.M. and Miquel , M.J. ( 2016 ), “ Work–life balance and firms: a matter of women? ”, Journal of Business Research , Vol. 69 No. 4 , pp. 1379 - 1383 , doi: 10.1016/j.jbusres.2015.10.111 .

Adame-Sánchez , C. , González-Cruz , T.F. and Martínez-Fuentes , C. ( 2016 ), “ Do firms implement work–life balance policies to benefit their workers or themselves? ”, Journal of Business Research , Vol. 69 No. 11 , pp. 5519 - 5523 , doi: 10.1016/j.jbusres.2016.04.164 .

Ahuja , M. and Thatcher , J. ( 2005 ), “ Moving beyond intentions and towards the theory of trying: effects of work environment and gender on post-adoption information technology use ”, MIS Quarterly , Vol. 29 , pp. 427 - 459 .

Alam , M. , Ezzedeen , S.R. and Latham , S.D. ( 2018 ), “ Managing work-generated emotions at home: an exploration of the ‘bright side’ of emotion regulation ”, Human Resource Management Review , Vol. 29 No. 4 , doi: 10.1016/j.hrmr.2018.12.002 .

Alexandra , B.T. ( 2014 ), “ Fairness perceptions of work−life balance initiatives: effects on counterproductive work behaviour ”, British Journal of Management , Vol. 25 , pp. 772 - 789 .

Allan , C. , O'Donnell . M. and Peetz , D. ( 1999 ), “ More tasks, less secure, working harder: three dimensions of labour utilization ”, Journal of Industrial Relations , Vol. 41 No. 4 , pp. 519 - 535 .

Allen , T.D. ( 2001 ), “ Family-Supportive work environments: the role of organisational perceptions ”, Journal of Vocational Behavior , Vol. 58 No. 3 , pp. 414 - 435 .

Antonoff , M.B. and Brown , L.M. ( 2015 ), “ Work–life balance: the female cardiothoracic surgeons perspective ”, The Journal of Thoracic and Cardiovascular Surgery , Vol. 150 No. 6 , pp. 1416 - 1421 , doi: 10.1016/j.jtcvs.2015.09.057 .

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Bell , A.S. , Rajendran , D. and Theiler , S. ( 2012 ), “ Job stress, wellbeing, work-life balance and work-life conflict among Australian academics ”, Electronic Journal of Applied Psychology , Vol. 8 , pp. 25 - 37 .

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Crawford , W.S. , Thompson , M.J. and Ashforth , B.E. ( 2019 ), “ Work-life events theory: making sense of shock events in dual-earner couples ”, Academy of Management Review , Vol. 44 No. 1 , pp. 194 - 212 .

Daipuria , P. and Kakar , D. ( 2013 ), “ Work-Life balance for working parents: perspectives and strategies ”, Journal of Strategic Human Resource Management , Vol. 2 , pp. 45 - 52 .

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Downes , C. and Koekemoer , E. ( 2012 ), “ Work-life balance policies: the use of flexitime ”, Journal of Psychology in Africa , Vol. 22 No. 2 , pp. 201 - 208 .

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Emre , O. and De Spiegeleare , S. ( 2019 ), “ The role of work–life balance and autonomy in the relationship between commuting, employee commitment and well-being ”, The International Journal of Human Resource Management , Vol. 32 No. 11 , pp. 1 - 25 , doi: 10.1080/09585192.2019.1583270 .

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Galea , C. , Houkes , I. and Rijk , A.D. ( 2014 ), “ An insider’s point of view: how a system of flexible working hours helps employees to strike a proper balance between work and personal life ”, The International Journal of Human Resource Management , Vol. 25 No. 8 , pp. 1090 - 1111 .

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Groysberg , B. and Abrahams , R. ( 2014 ), “ Manage your work, manage your life ”, Harvard Business Review , Vol. 92 No. 3 , pp. 58 - 66 .

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Haar , J.M. , Sune , A. , Russo , M. and Ollier-Malaterre , A. ( 2019 ), “ A cross-national study on the antecedents of work–life balance from the fit and balance perspective ”, Social Indicators Research , Vol. 142 No. 1 , pp. 261 - 282 , doi: 10.1007/s11205-018-1875-6 .

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Hirschi , A. , Shockley , K.M. and Zacher , H. ( 2019 ), “ Achieving work-family balance: an action regulation model ”, Academy of Management Review , Vol. 44 No. 1 , pp. 150 - 171 .

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Funding: This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.

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Work–Life Balance: Definitions, Causes, and Consequences

• Reference work entry
• First Online: 17 September 2022
• Cite this reference work entry

• Paula Brough 4 ,
• Carolyn Timms 5 ,
• Xi Wen Chan 6 ,
• Amy Hawkes 7 &
• Laura Rasmussen 7  

Part of the book series: Handbook Series in Occupational Health Sciences ((HDBSOHS))

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This chapter reviews the multiple definitions of work–life balance, including definitions focused on the equity of time spent in the work and non-work domains, satisfaction with performance/time spent in each domain, and the salience of each role for an individual. There is a general consensus that a preferred definition should focus on work– life rather than work- family , in order to include non-family responsibilities and demands, such as study or travel commitments. The chapter also discusses the common antecedents and consequences of work–life balance arising from both work and non-work domains. These include work demands and resources, family demands and resources, and personality antecedents including evidence associating psychological capital constructs with work–life balance. Finally, this chapter considers the future directions for work–life balance research, focusing on technological advancements (e.g., Fitbits) and individual levels of mindfulness and resilience. The chapter concludes by noting the increasing evidence linking employee appointments and retention with an organization’s positive work–life balance culture.

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Brough, P., Timms, C., Chan, X.W., Hawkes, A., Rasmussen, L. (2020). Work–Life Balance: Definitions, Causes, and Consequences. In: Theorell, T. (eds) Handbook of Socioeconomic Determinants of Occupational Health. Handbook Series in Occupational Health Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-31438-5_20

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Career Guide  14 March 2019

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Open Access

Ten simple rules to improve academic work–life balance

Contributed equally to this work with: Michael John Bartlett, Feyza Nur Arslan, Adriana Bankston, Sarvenaz Sarabipour

* E-mail: [email protected] (MJB); [email protected] (SS)

Affiliation Scion, Rotorua, New Zealand

Affiliation Institute of Science and Technology Austria, Klosterneuburg, Austria

Affiliation Future of Research, Pittsfield, Massachusetts, United States of America

Affiliation Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America

• Michael John Bartlett, 
• Feyza Nur Arslan, 
• Adriana Bankston, 
• Sarvenaz Sarabipour

Published: July 15, 2021

• https://doi.org/10.1371/journal.pcbi.1009124
• Reader Comments

Citation: Bartlett MJ, Arslan FN, Bankston A, Sarabipour S (2021) Ten simple rules to improve academic work–life balance. PLoS Comput Biol 17(7): e1009124. https://doi.org/10.1371/journal.pcbi.1009124

Editor: Scott Markel, Dassault Systemes BIOVIA, UNITED STATES

Copyright: © 2021 Bartlett et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was the product of volunteer time and the authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The ability to strike a perceived sense of balance between work and life represents a challenge for many in academic and research sectors around the world. Before major shifts in the nature of academic work occurred, academia was historically seen as a rewarding and comparatively low-stress working environment [ 1 ]. Academics today need to manage many tasks during a workweek. The current academic working environment often prioritizes productivity over well-being, with researchers working long days, on weekends, on and off campus, and largely alone, potentially on tasks that may not be impactful. Academics report less time for research due to increasing administrative burden and teaching loads [ 1 – 3 ]. This is further strained by competition for job and funding opportunities [ 4 , 5 ], leading to many researchers spending significant time on applications, which takes away time from other duties such as performing research and mentorship [ 1 , 2 ]. The current hypercompetitive culture is particularly impactful on early career researchers (ECRs) employed on short-term contracts and is a major driver behind the unsustainable working hours reported in research labs around the world, increases in burnout, and decline in satisfaction with work–life balance [ 6 – 10 ]. ECRs may also find themselves constrained by the culture and management style of their laboratory and principal investigator (PI) [ 11 – 12 ]. Work–life balance can be defined as an individual’s appraisal of how well they manage work- and nonwork-related obligations in ways that the individual is satisfied with both, while simultaneously maintaining their health and well-being [ 13 ]. Increasing hours at work can conflict with obligations outside of work, including but not limited to family care commitments, time with friends, time for self-care, and volunteering and community work. The increasing prevalence of technology that allows work to be out of the office can also exacerbate this conflict [ 14 , 15 ].

The academic system’s focus on publications and securing grant funding and academic positions instead of training, mentoring, and mental health has skewed the system negatively against prioritizing “The whole scientist” [ 5 , 16 ]. Research focused on the higher education sector has revealed that poor work–life balance can result in lower productivity and impact, stifled academic entrepreneurship, lower career satisfaction and success, lower organizational commitment, intention to leave academia, greater levels of burnout, fatigue and decreased social interactions, and poor physical and mental health, which has become increasingly prevalent among graduate students [ 1 , 17 – 22 ]. For instance, a recent international survey of over 2,000 university staff views on work–life balance found that many academics feel stressed and underpaid and struggle to fit in time for personal relationships and family around their ever-growing workloads [ 20 ]. These systemic issues are making it increasingly difficult to maintain an efficient, productive, and healthy research enterprise [ 23 ].

In the academic context, work–life balance needs to be examined with regard to spatial and temporal flexibility, employment practices, and employee habits. The need to improve work–life balance is recognized for researchers at all career stages [ 7 , 22 , 24 , 25 ]. While there is a growing literature providing specific strategies to cope with busy academic life [ 26 – 28 ], collating these disparate advice pieces into a coherent framework is a daunting task and few capture multifaceted advice by ECRs for ECRs. Departments and institutes need to contribute to improving research practices for academics at all levels on the career ladder [ 29 , 30 ]. PIs and mentors can promote healthier environments in their laboratories by respecting boundaries and providing individuals with greater autonomy over their own working schedule [ 11 , 12 , 31 – 33 ]. However, institutions do not typically prioritize work–life balance, leading to the loss of valuable talent in the research pipeline. The power dynamics within academia are evident now more than ever, with ECRs lacking agency at multiple time points and in controlling many aspects of their training. This may be especially true for trainees from underrepresented backgrounds, who face additional hurdles to their professional advancement in the current academic environment while attempting to maintain work–life balance. Furthermore, academia, in general, does not always value the aspects of a researcher’s job that the researcher finds important such as teaching, mentoring, and service. Thus, the experience of individual researchers regarding work–life balance will vary depending on multiple factors [ 34 – 39 ], including personal circumstances and satisfaction with aspects of life outside of work [ 40 ]. It is therefore unlikely that there is a “one size fits all” approach to effectively address work–life balance issues.

In order to support ECRs in maintaining work–life balance, institutions should support individualized strategies that are continually refined during their training. Here, drawing from our discussion as part of the 2019–2020 eLife Community Ambassador program and our experiences as ECRs, we examine the strategies individuals can adapt to strike a healthier balance between the demands of personal life and a career in research.

While many of the challenges junior academics face are systemic problems and will take a while to fix, some level of individual adjustment and planning may help ECRs more immediately and on an individual level. The rules presented here seek to empower ECRs to take action in improving their own well-being, while also providing a call to action for institutions to increase mechanisms of support for their trainees so they can thrive and move forward in their careers.

Rule 1: Long hours do not equal productive hours

One common reason for work–life imbalance is the feeling of lagging behind as a result of the present-day competitive nature of academia. This has led to incorrectly normalized practice of overwork, due to a sense of pressure from colleagues or ourselves, contributing to increasing mental health problems in academia [ 3 , 7 , 9 ]. On the other hand, keeping a balance sets one for higher productivity and creativity [ 41 ] and long-term satisfaction with work [ 17 , 18 ]. It is important to focus on the benefits of work–life balance on overall well-being and to accept that performing research and building a career in academia is a long process. Taking time off should not be associated with a feeling of guilt for not working at that moment. On the contrary, it should be seen as a necessity to have good health, energy, and motivation for the next return to work. A break can result in a boost to your productivity (rate of output) [ 42 ]. Studies show output of working hours to not increase linearly after a threshold and absence of a rest day to decrease output, as long hours result in errors and accidents, as well as fatigue, stress, and sickness [ 43 , 44 ]. It can be challenging to cut down on work hours when you feel that there is so much to get done. We also acknowledge that there are times when putting in long hours may be needed, for example, to meet a deadline; however, keeping this behavior constant might have more disadvantages than advantages in the long term.

Having flexibility in when and where you work can help you manage tasks and feel more balanced. It is important to discuss your needs with people at work and at home, in order to establish expectations and fit your lifestyle.

Rule 2: Examine your options for flexible work practices

Examine your relationship with your work, and try alternative schedules. Review your expected obligations, employer work hour rules, and offered benefits. Where possible, make use of modernization of work tools (such as remote work methods using digital technologies); working time is no longer exclusively based on in-person presence at the workplace, but rather the accomplishment of tasks [ 45 , 46 ]. The virtual office aspect can offer extensive flexibility in terms of time and location of work, reduce time spent traveling and commuting, and allow easier management of schedules and lives. Attending conferences online and giving invited talks, seminars, and interviews virtually can reduce fatigue and increase the time available for activities essential for your well-being [ 47 , 48 ]. Working remotely may not work for all or on many days of a week, but an overall reduction in travel is possible. In some instances, it may be difficult to know beforehand how much time you will be allocating to particular tasks in your new job, also some tasks such as fieldwork or labwork cannot be done remotely. Factor in workplace flexibility policies when looking at employment options and negotiating contracts. At the interview stage, ask your employer and prospective supervisor about flexible hours, options such as compressed workweeks, job sharing, telecommuting, or other scheduling flexibility to work in a way that best fits your efficiency and productivity. The more control you have over where and when you work, the less stressed you are likely to be. Once you know the options available to you, agree on a schedule based on your expectations and needs. Clear agreements on how and when to work are necessary to avoid conflict between work and nonwork obligations [ 45 ], so it is important to effectively communicate agreements with your managers, mentors [ 31 ], supervisors, colleagues, and also with your family. Having said this, in reality, ECRs may not always be able to negotiate salaries and benefits as conditions might be predetermined by an institution, a fellowship, or a PI’s strict expectations. Weigh the pros and cons of nonnegotiable job offers carefully. Remember that some constraints might be relaxed over time as your new employers build trust in you; therefore, continue the communication to find the best arrangements for your work.

As you try to reduce overworking and be more flexible with working arrangements, you will need to be very focused within the time frame that you have available. This is especially important as work–life balance boundaries become blurred if working from home. Setting boundaries is critical to success, as detailed below.

Rule 3: Set boundaries to establish your workplace and time

Setting spatial and temporal boundaries around your work is important for focusing on the task in hand and preventing work from taking over other parts of your life. When you are in the office and need to focus, make sure you can work in a quiet place where colleagues are unlikely to distract you. If you work in a shared office space, communicate with those around you to let them know your needs, or if you need complete silence, then consider working in a designated space for focused work. While working from home, some may struggle to disconnect from work, step away from screens, and set clear boundaries between digital and physical settings. Screen time needs to be managed so that remote workers do not blur the lines of work and life, as that can result in discouragement and burnout. Ask your coworkers to not demand your attention toward work after a certain time in the evening. Turn off email notifications outside of working hours. By setting boundaries, you will also set an example for your coworkers and mentees. When working at home, separating your workspaces from relaxation spaces can be helpful. This way, less clutter can decrease your stress levels, and a separated space can help you to draw a line between work and family. Even carving an area on a table dedicated to your work time can help with calm and work–life balance.

In order for your resulting work to be of high quality, diligence is key. In addition to being focused on your task, you should also establish a routine and prioritize your tasks, being able to then gain more control over your time. Learning to say no is also critical. Below we expand on these issues in the context of efficiency and productivity.

Rule 4: Commit to strategies that increase your efficiency and productivity

Many people use to-do lists and outline daily/weekly tasks, defining both work- and nonwork-related obligations that need to be accomplished. For nonwork responsibilities, devise a strategy with your family or those you live with to delegate tasks. Make sure responsibilities at home are clearly outlined and evenly distributed.

• Manage your time. Learning how to effectively manage your time and focus while at work is critical. Set a schedule to help in managing time, and do not forget to include buffer times between your plans, such as a coffee break with colleagues and a walk away from the bench or computer screen, to socialize and rest. Outside of busy periods, try to keep routines of work hours. Try time blocking, for example, check email and other social media (e.g., Slack) messages at specific times of the workday, and, if possible, arrange meetings at concentrated times during the day. This will maximize the amount of deep work that can be done during work hours. Sometimes, multitasking, for instance, running a few experiments at the same time or trying to work in between several meetings, may not result in great outcomes; have realistic plans and monotask if you find it better.
• Minimize decision fatigue. Decision fatigue refers to the deteriorating quality of decisions made by an individual after a long session of decision-making. Decision fatigue depletes self-control, which results in emotional stress, underachievement, lack of persistence, and even failures of task performance [ 49 ]. To reduce this, make the most important decisions first in your workday, and limit and simplify your choices.
• Collaborate. Workplace and home collaborations can take some of the load off and help in managing stress. Adjusting to teamwork or training a student may seem like extra commitments at the beginning, but, in the long run, they can help delegate some of the tasks on your calendar and help maintain a better work–life balance.
• Do not overcommit. Learn to say “no” [ 46 ]. Consider that accepting extra, low-impact tasks will sacrifice your nonwork time and may also take attention off your other important work appointments. Try to drop activities that drain your energy, such as nonessential meetings that do not enhance your life or career, and be efficient within this limited time with set goals.
• Discover your own strategies. Try to figure out what strategies work for you, and apply these to your life. Individuals respond differently to time of the day, physical conditions, and stress. Productivity may come with creative arrangements, and a high degree of organization may not work for everyone. Sometimes, improvisation and flexible schedules might be what you need.

As you begin to make decisions about the best way to manage your time, being strategic is key to prioritizing. You should aim to review your strategy and ability to stick to it often.

Rule 5: Have a long-term strategy to help with prioritization, and review it regularly

Having a long-term strategy that considers what you want to achieve and the timelines needed to get there can help with prioritization and deciding what to take on and what to say no to. This not only includes goals linked to your research career but also what is important to you outside of work, whatever this may be. When managing your work and nonwork tasks, see how well they align with your short- and long-term goals when you are deciding on the time and energy you need to allocate to attain them. With daily tasks, starting each day with the most important task, allocating the most productive hours to important tasks, as well as grouping similar tasks might help increase productivity and efficiency. A long-term look can help justify time spent on particular tasks, such as learning new skills, which might be taking extra time now but would help reduce stress in the long term. It is important to review your strategic goals and how well you are doing regularly, updating your strategy as needed. Consider using weekly time management charts to assess your task delegation retrospectively ( Fig 1 ). Have you been able to reach the goals you set? Did your time get taken up by other tasks? Did you use additional time to meet work goals at the expense of priorities outside of work? Are the goals you have set realistic and achievable, or do you need to make adjustments? If this appears overwhelming remember that your plans do not necessarily need to be detailed, simply keeping track of the hours spent working can be useful [ 26 ]. It is normal for priorities to change over time. Choose mentors that can help you achieve your short- and long-term goals, and consult with them regularly on your work–life balance strategies [ 31 ].

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

Dynamic, prospective, or retrospective weekly or monthly time management assessment charts can help researchers with improving their work–life balance by determining exactly how they spend their time. There are 164 hours in a week. Example hour allocation is shown here for academics across career stages [ 50 ]. Hours allocated will vary depending on the researcher’s disciplines (for instance, humanities versus life sciences or engineering) and circumstances such as end or beginning of semester, when approaching a deadline, or when a committee is busiest. Teaching responsibilities include course instruction and administration, including grading and evaluation. Family time includes interacting, dining, and performing housekeeping chores with family members. Research activities include performing research and literature review time. External service may include manuscript or grant reviewing and editorial tasks. Meetings may include lab/group meetings, departmental faculty meetings, or other council meetings. Self-care activities may include attending to one’s hobbies. Internal service includes department and university service. Weekends and public holidays are included in the weeks. Other tasks not included in this chart may be professional development, writing letters of recommendation, advising undergraduate students, faculty and student hiring/recruitment, marketing/public relations, fundraising, phone calls, reception/dinner, commute/travel, scheduling/planning, and reporting. ECR, early career researcher; MLCR, mid- to later career researcher; PI, principal investigator. Figure created using ggplot library in R [ 51 ].

https://doi.org/10.1371/journal.pcbi.1009124.g001

In order to do your best in life and work, you need to put yourself first. You can do that by paying attention to your eating and sleeping schedule and engaging in activities that will keep you physically healthy and stimulate your mind.

Rule 6: Make your health a priority

You are not only defined by your work. Spending time on self-care and relaxation is a necessity in life to maintain a healthy body and mind, leading to a fulfilling lifestyle. This, in turn, will enable you to achieve peak performance and productivity in the workspace.

• Eat a healthy diet. A balanced diet with emphasis on fresh fruits, vegetables, and lean protein enhances the ability to retain knowledge as well as stamina and well-being. An option could be keeping fruit baskets in your office with your colleagues.
• Get enough sleep. Lack of sleep increases stress, and associated fatigue is linked to poor work–life balance [ 52 ]. One potential way to improve sleep quality is to avoid using personal electronic devices, such as smartphones and tablets, during your personal and other nonwork times, particularly right before going to sleep as screen time is associated with less and poorer quality rest [ 53 , 54 ].
• Prioritize your physical and mental health. Set time aside for individual or group physical activities of your choice. Schedule specific times for social activities and exercise to unwind, by arranging ahead of time with others or signing up to regular classes, making the plans harder to cancel. Using the gym at your workplace during a break can freshen you. Or you can bike or jog to work if safe to have some daily exercise. Equally important is dedicated time for your mental health. Reading a book, listening to music, gardening, many other activities, or if you prefer, regularly talking to a therapist could help you disengage from work, enjoy other aspects of life, rest, process, and recharge.
• Try meditation or mindfulness exercises. Meditation can reduce stress and increase productivity [ 29 ]; it will help you focus your thoughts and develop more self-awareness. If you are aware of when and why you are stressed or exhausted, these feelings become a trigger for you to lean into a boundary such as taking a screen break, going for a walk, or simply resting your eyes for 15 minutes before jumping back into a task or meeting. You can do meditation or yoga at home for short intervals. Do what is realistic for your life at the time and what helps you along.
• Make time for your hobbies and relaxation. Set aside time each day for an activity that you enjoy [ 28 , 55 , 56 ]. Discover activities you can do with your partner, family, or friends—such as hiking, dancing, or taking cooking classes. Listen to your favorite music at work to foster concentration, reduce stress and anxiety, and stimulate creativity [ 57 ].

While your work is important, you will be much happier if you schedule some social time into your week. This is a simple need, and methods vary from person to person, but the common goal is to increase your sense of connection and belonging, satisfaction with life, and/or energy.

Rule 7: Regularly interact with family and friends

Your work schedule does not need to lead to loss of your personal relationships. Scheduling time off to meet in-person or interact online with your loved ones in advance will make it harder to cancel plans in favor of working longer. As an example of good practice, most parents, even in academia, need to schedule their time around family responsibilities, which actually obliges them to maintain a work–life balance; they typically do not overstay at work every day, take the weekends off, and use annual leave. Meeting with friends and family will provide a chance to reconnect with them and your shared values. If you live in a country different from your family and friends, it is important to keep in touch using online audiovisual call and chat technologies. Other ways to relax include taking walks with loved ones, being out in nature, or playing board games. Social downtime can help replenish a person’s attention and motivation, encourages productivity and creativity, and is essential to both achieve our highest levels of performance and form stable memories in everyday life [ 58 ].

In addition to spending time for yourself and with family and friends, engaging in activities that are important to you, even when these activities are demanding, can bring a needed sense of achievement and satisfaction.

Rule 8: Make time for volunteer work or similar commitments that are important and meaningful to you

Many find additional engagements outside of their day to day jobs both important and rewarding. These activities would not be considered hobbies or relaxation, examples may include volunteering for the local community (e.g., at pet shelters, food banks, and environmental efforts), regional and online communities (e.g., student advocacy groups), time on boards or committees outside of work (e.g., acting as treasurer or secretary of a club), and learning a new language when you have moved to a new place. Many ECRs enjoy taking their work one step forward to volunteer with organizations focused on the societal value or impact of their work. This can help expand your perspective as an ECR working on a particular research topic, by understanding the broader picture of what you are working on and why and giving it a human impact dimension. Others may opt to volunteer in activities that are entirely independent of their research, which can provide opportunities to clear your mind for a good period of time and boost your mood. Although these activities add extra work to your schedule, if they are important to you, then you might find it difficult to find balance without the sense of achievement and reward they bring. However, when under pressure from work and home, finding time for these activities can be challenging—remember that work–life balance needs to be continually reassessed; consider taking a break if you need to and revisiting these extra commitments at a better time.

In addition to advisors and departments, institutions can take measures to support ECRs and provide them with necessary resources to thrive. They should also create a culture where asking for help is encouraged, and support for the well-being of researchers exists at their institution.

Rule 9: Seek out or help create peer and institutional support systems

Support systems are also critical to your success, and building more than one will increase your chances of success and balance overall [ 59 ]. At work, join forces with coworkers who can cover for you—and vice versa—when family conflicts arise. At home, enlist trusted friends and loved ones to pitch in with childcare or household responsibilities when you need to work overtime or travel. Seek support in academic communities and organizations who are working on mental health and well-being. For instance, PhD balance is a community space for academics to learn from shared experiences, to openly discuss and receive help for difficult situations, and to create resources and connect with others [ 60 ]. Dragonfly Mental Health, a nonprofit organization, strives to improve mental health care access and address the unhealthy culture pervading academia [ 61 ]. Everyone may need help from time to time. If life feels too chaotic to manage and you feel overwhelmed, talk with a professional, such as a counselor or other mental health provider. If your employer offers an employee assistance program, take advantage of available services. Joining a support and peer mentorship group, such as graduate, postdoctoral or faculty Slack communities [ 31 ], or working parents seeking and sharing work–life balance strategies, provides at least two key advantages: an opportunity to vent to people who truly understand your experiences and the ability to strategize with a group about how to improve your situation. A combination of these steps will help researchers to improve their work–life balance.

Finally, if your ability to effectively implement the advice in Rules 1 to 8 is constrained by the culture in your lab or pressure from the academic system, seek support from mentors, and advocate for yourself and for the change you would like to see.

Rule 10: Open a dialogue about the importance of work–life balance and advocate for systemic change

Spreading awareness and promoting good practice for managing work–life balance are essential toward shifting the prevailing culture away from current excellence at any cost practices. While major change is only likely to come about with a coordinated shift in the way that research laboratories, institutions, publishers, funders, and governments assess research endeavors at a broadscale, there is much that can be done at smaller scales to improve the culture at institutions and within labs [ 62 ]. Leverage the support of communities that empower ECRs to participate in advocating for the importance of mental well-being in academia through research and programs (see Rule 9). Discussions on work–life balance can also be initiated through seminars and courses. You can ask for, or if you plan to get more involved, organize workshops and training in your institute for ECRs. Another way to encourage collective work–life balance could be to host activities such as family and employee sports, outdoor movies, or picnic events encouraging family-friendly time and team building. Advocate for policies in your workplace that can help reduce conflict between work and other responsibilities, for example, childcare services or pet-friendly workspaces. To advocate at larger scales, you can join graduate/postdoctoral researcher associations, unions, or work councils to actively pursue work–life balance–friendly policies and employment contracts at institutes and through funding agencies. For instance, institutions and funding agencies that do not encourage the traditional gender roles allowing both men and women to take family leave, see better work–life balance, and reduced work–life conflict [ 63 , 64 ]. If the culture in your research lab constrains your ability to manage your work–life balance in a way you find satisfactory, shifting departmental and institutional attitudes and policies can put pressure on PIs to build a more supportive work culture via steps outlined elsewhere [ 11 , 12 , 31 – 33 ]. Although organizational culture cannot be changed overnight, changes in policy can go a long way in creating a culture that aids work–life balance in the academic workplace [ 62 – 64 ].

Conclusions

Most academic jobs come with flexible working hours, which can be advantageous when researchers attempt to balance the competing obligations in their lives. Yet, ECRs typically work significantly longer than the normal working hours of academic employment contracts [ 65 ]. How researchers spend their time has major impacts on their well-being, productivity, and professional scale of impact and those of their mentees, family, colleagues, and institutions in the short and long term. Academic culture has normalized and ignored overworking often at the expense of a social life, or of even greater concern, at the expense of researchers’ health and well-being. It is important for all academic researchers, institutions, and funding agencies to credit service and administrative activities, to acknowledge difficulties in satisfying work- and nonwork-related obligations in academic careers, and support diverse strategies to attain work–life balance [ 29 , 30 ]. It is imperative to examine work–life balance practices by ECRs, suggest improvements, and integrate these into employment and promotion offers. Here, we provided recommendations for ECRs to improve management of the balance between their professional and personal lives, but striking a healthy work–life balance is not a one-shot deal. Managing work–life balance is a continuous process as your family, interests, and work life change. Working long hours does not equate to working better. Regularly examine your priorities—and, if necessary, make changes—to ensure you stay on track. Ultimately, for the benefit of researchers and the important work that they do, both individuals and institutions need to make health and well-being a priority.

Acknowledgments

The authors thank Inez Lam of Johns Hopkins University for valuable comments on an earlier version of the manuscript. We also thank the facilitators of the 2019–2020 eLife Community Ambassador program.

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• Research article
• Open access
• Published: 16 July 2020

Work-life balance and self-reported health among working adults in Europe: a gender and welfare state regime comparative analysis

• Aziz Mensah 1 &
• Nicholas Kofi Adjei 2 , 3  

BMC Public Health volume  20 , Article number:  1052 ( 2020 ) Cite this article

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The pressing demands of work over the years have had a significant constraint on the family and social life of working adults. Moreover, failure to achieve a ‘balance’ between these domains of life may have an adverse effect on their health. This study investigated the relationship between work-life conflict and self-reported health among working adults in contemporary welfare countries in Europe.

Data from the 6th European Working Conditions Survey 2015 on 32,275 working adults from 30 countries in Europe were analysed. Multivariate logistic regression models were used to examine the associations between work-life balance and self-reported health among men and women. We further used a 2 stage multi-level logistic regression to assess variations in self-reported health among welfare state regimes by gender.

The results showed a strong association between work-life conflict and poor self-reported health among working adults in Europe (aOR = 2.07; 95% CI: 1.93–2.23). However, the magnitude of the effect differed slightly by gender (men: aOR = 1.97; 95% CI: 1.78–2.18 vs women: aOR = 2.23; 95% CI: 2.01–2.47). Furthermore, we found variations in the relationship between work-life conflict and poor self-reported health between welfare states regimes. The association was found to be weaker in the Nordic and Southern welfare states than the Liberal, Conservative, and Central Eastern European welfare states. Although the associations were more consistent among men than women in the Conservative welfare states regime, we found higher associations for women than men in the Southern, Nordic, Liberal, and Central Eastern European welfare states.

Conclusions

This study provides evidence of some variations in the association between work-life conflict and poor self-reported health among men and women across welfare states regimes in Europe. The results demonstrate the need for governments, organizations and policymakers to provide conducive working conditions and social policies for working adults to deal with competing demands from work and family activities.

Peer Review reports

Introduction

The changing patterns of work over the years have had a significant constraint on both the family and the social life of working adults [ 1 ]. With the limited 24 h’ time resource available in a day, working adults may be confronted with many challenges, including deadlines to meet targets, financial obligations, and pressing family responsibilities. These situations may create role conflict, which can affect the level of involvement in their work, family and social life [ 2 , 3 , 4 ]. Some scholars suggest that higher demands from household activities make it difficult to balance work and family life [ 2 , 3 ]. A recent study on work-life conflict among employees in Europe revealed a work-life ‘imbalance’ among employees in Europe [ 5 ]. This phenomenon has partly been attributed to an increase in the involvement of women in the labour force and the rising involvement of men in performing housework, including child care and family chores [ 6 , 7 ]. The Evidence further suggests that time allocated by men to housework activities has increased over time [ 8 , 9 ], while female participation in the labour market has also increased over the years [ 10 ]. Work-life conflict may arise when there is a role conflict in the satisfaction of work and family life [ 11 ], and failure to achieve a ‘balance’ between these domains may have an adverse effect on working adults’ health [ 5 , 12 , 13 ].

Work-life conflict among employees is known to be related with many health problems, including poor physical health [ 14 , 15 , 16 ], poor-self reported health [ 15 , 17 ], psychological distress [ 14 , 18 ], poor mental health [ 19 , 20 , 21 ] and life dissatisfaction [ 22 ]. However, work-life conflict and health outcomes may differ by gender due to the unequal distribution of work-related roles [ 23 , 24 , 25 , 26 , 27 ]. For example, some previous studies found a positive relationship between work-life conflict and poor self-reported health among working women than men [ 25 , 26 , 27 ], while other studies suggest similar outcomes between men and women [ 5 , 28 ]. In a longitudinal study among working adults in Sweden, Leineweber et al. [ 27 ] found an association between work-life conflict and suboptimal self-reported health among working women than men. Similarly, Eek and Axmon [ 26 ] found that women in relationship with unequal distribution of work and family activity reported a higher level of fatigue, stress, and physical symptoms than those in relationship with equal distribution of responsibility. In contrast, Kinnunen and his colleagues [ 28 ] found no evidence of gender difference in the association between poor work-life balance and health outcomes such as life satisfaction and well-being.

Gender, work life balance, and welfare policies

Gender plays a key role in understanding how work and other domains of life are distributed and performed [ 29 ]. The term is not static but rather a phenomenon where identity is continuously renegotiated [ 30 , 31 ]. Evidence suggests that traditional and societal expectation of behaviour differs between men and women [ 32 , 33 ], where women are responsible for caregiving (family activities) and other household activities, while men assume the primary role for paid work activities [ 10 , 34 ]. For example, using time use data, Aliaga [ 35 ], Hagqvist [ 36 ] and Adjei et al. [ 37 ] indicated that women spent more time on family activities than men, while men spent more time on paid work activities than women. Similarly, research conducted by Boye [ 38 ] revealed that about 40% of working-age women are not engaged in paid work activities as compared to men (1.5%). The study further showed that women spend about 13 h more on unpaid work per week as compared to men. Hochschild [ 39 ] argued that although women’s contribution and participation in paid work activities have dramatically increased over the years, it has not been accompanied by a proportionate measure of increase in time allocation to unpaid work by men. Women continue to spend more time on household activities as compared to men [ 40 ]. However, recent studies suggest that women have reduced their time and involvement in unpaid work while men have increased the amount of time devoted to unpaid work activities [ 9 ], especially child care [ 8 , 9 ]. Kan et al. [ 41 ] argued that the change in the reduction of time spent on household activities by women could be attributed to the increase of women in the labour market rather than a change of ideology among men in the performance of household activities.

The rational view proposed that work-family conflict will increase when there is an increase in the amount of time spent on both work and family activities [ 32 ]. This phenomenon has been attributed to role strains [ 42 ]. In their study, Frone et al. [ 15 ] noted that long working hours, psychological involvement in work, inflexible working time arrangement, lack of clarity of work function, and role overload are indicators that influence work-life conflict among employees. There have been many studies on gender and work-life conflict [ 33 , 43 , 44 ]; however, the findings from these studies are inconclusive and contradicting [ 45 ]. While some studies found higher work-life conflict among women than men [ 33 , 43 , 44 ], few studies failed to demonstrate any significant difference among men and women [ 46 , 47 , 48 ]. In a cross-sectional study in the UK, Emslie et al. [ 46 ] found that both white-collar men and women employees in the Bank have the same level of work-family interference. Similarly, Schiemann et al. [ 47 ] found no gender difference in work-life conflict among higher status workers in Canada. These authors attributed their findings to the egalitarian gender role balance that suggest that the level of expectation in terms of sharing financial and family responsibilities is similar for men and women [ 47 ]. Nonetheless, using longitudinal data from the German Socio-Economic Panel Study (SOEP), Busch-Heizmann and Holst [ 44 ] found a higher prevalence of interference between work and family life among working women than men in Netherland. Gutek et al. [ 33 ] attributed some of the reasons to the fact that women still retain their primary role of performing care and other household activities even when they are confronted with higher job demands. Men, on the other hand, are more satisfied when they devote more time and effort to paid work- than household activities [ 49 ]. Ngo and Lui [ 45 ] also suggested that work- life conflict is higher among women due to limited control over conflicting domains of life. It has also been established that women who are affected by work-life conflict may experience higher forms of stress and other adverse health outcomes than men [ 33 , 43 ].

Gender inequality in work-life conflict has also been linked with socio-economic policies that exist within countries [ 50 ]. According to Gornick [ 51 ], extensive parental leave, support for childcare and elderly care, strong labour regulation, and universal health service that exist within countries are factors that may influence interference between work and family life. The development of welfare policies may also be rooted in historical, social, and economic development that exist in a country [ 52 ]. Hence, there may be variations among countries in terms of generosity, focus, and goals of social and welfare policies [ 53 ]. Contemporary welfare policies may be classified into five distinct regimes, namely, Nordic (social democratic), Liberals (Anglo-Saxon), Conservative (Corporatist), Southern Europe, and Central Eastern Europe (CEE) [ 54 ]. Esping-Andersen [ 53 ] described countries in the Nordic welfare states regime as having policies that are ‘encompassing,’ where the level of social support is generous and universal. This type of welfare system encourages dual-earner family roles, extensive support to single parents, and a regulated labour market, which allows more women to participate in the labour market [ 55 ]. In addition, there is provision for publicly funded child and elderly care services [ 55 , 56 ], and extensive paid parental leave days for working women and men [ 57 ]. Liberal welfare states, on the other hand, are characterized by a strong male-breadwinner model with childcare primarily provided by a private venture with low state support [ 58 ]. These countries are also characterized by weak employment regulations and less generous state provision of social services and benefits [ 53 , 59 ]. Conservative welfare states are characterized by traditional male breadwinner family models and have strong labour market laws to regulate employment [ 53 ]. In this regime type, families bear the responsibility for primary social welfare benefits [ 59 ], and most working mothers engage in part-time or secondary jobs without good economic remuneration [ 60 ]. In the Southern European welfare states regime, social benefits are much lower [ 59 , 61 ] as compared to the Conservative welfare states regime. Moreover, care services are largely provided by family, friends, and volunteers. Familialism is stronger in this regime type [ 39 ], and there are gender roles, where men are known to be ‘breadwinners’ and women as ‘caregivers’ [ 39 ]. The CEE welfare states are also characterized by the dual-earner family model but weak trade unions and labour regulations [ 62 ], and a traditional division of housework [ 63 ].

Welfare policies may influence work-life balance and might subsequently have an effect on health outcomes [ 5 , 14 , 15 , 64 ]. Countries with more generous social policies such as quality child care service, extensive parental leave, and generous social benefits may influence the magnitude of the association between work-life conflict and health-related outcomes [ 5 , 64 , 65 ]. For instance, Artazcoz and his colleagues [ 64 ] could not find any evidence that work-life conflict and poor self-reported health among working adults in northern Europe, where many generous welfare policies exist, but the study found an association between work-life conflict and poor health in Conservative and Southern European welfare states with less generous welfare benefits. In contrast, Hagqvist and his colleagues [ 12 ] noted that Nordic countries may show higher association between work-family conflict and low well-being as compared to countries with a more traditional family model in Europe.

A plethora of studies on work-life balance and health status have been based on a single country [ 25 , 41 , 66 ]. Still, only a few studies have focused on cross-country variation in welfare state typologies as well as gender differences [ 9 , 67 ]. To the best of our knowledge, no previous study has used a more comprehensive cross-country sample as the underlying conceptual structure for making a comparison. Hence, this study seeks to contribute to a deeper understanding of the gender difference in the relationship between work-life conflict and poor self-reported health among working adults in Europe. In addition, we analyse whether these effects vary across different welfare state regimes in Europe. By drawing on the theoretical relationship that exists between work-life conflict and self-reported health, the following research questions will be addressed:

Is there a relationship between work-life conflict and poor self-reported health among working adults in contemporary welfare states in Europe?

Does the relationship between work-life conflict and poor self-reported health differ by gender?

To what extent do these relationships vary by welfare state regimes among men and women in Europe?

This study was based on the 6th European Working Conditions Survey (EWCS 2015), conducted by the European Foundation for the Improvement of Living and Working Conditions. The EWCS survey data covered 35 countries in Europe. This includes EU28 countries, two countries from the European Free Trade Association (Norway and Switzerland), and five potential EU candidates’ countries (Albania, the Former Yugoslav Republic of Macedonia, Turkey, Serbia, and Montenegro). The target population of the survey was working adults who were between the ages of 15 years and above. The EWCS adopted a multistage, stratified, random sample in selecting the target population in each country. The target sample size for most countries was 1000, however, because some countries had larger workforce than others, the sample size varied [ 68 ]. For instance, the target sample size was increased to 1200 for Poland, 1300 for Spain, 1400 for Italy, 1500 for France, 1600 for UK, and 2000 for both Germany and Turkey. Furthermore, the European Foundation for the Improvement of Living and Working Conditions (Eurofound) also offered opportunity for countries to top-up their sample size. This opportunity was taken up by Belgium, Slovenia, and Spain which allowed them to increase their sample size to 2500, 1600, and 3300 respectively. Each country was stratified by region and the degree of urbanization. Primary sampling units (PSU) were randomly selected with probability proportional to size in each of the stratum. A random sample of household or individuals were further selected from each PSU [ 68 ]. A total of about 44,000 respondents were selected for a face-to-face interview in their respective households.

We restricted our analysis to working adults aged 16–64 years who were non-retired, not full-time homemaker, not a full-time student, and nondisabled. Respondents who refused to answer specific questions or do not know answers to specific questions were also excluded from the analysis. We also limited our study to 30 countries in Europe (i.e., the EU 28 countries, Switzerland and Norway). Missing responses were excluded because they accounted for less than 2% of the sample size. In the final analysis, we included a total of 32,275 participants.

Self-reported health, our outcome variable of interest, was measured using the question, “How is your health in general?” Responses were rated from 1 (very good), 2 (good), 3 (fair), 4 (bad), 5 (very bad). Self-reported health has been shown to be a good proxy for measuring health status and a reliable technique as a predictor of mortality [ 69 ]. To avoid much-skewed distribution of responses [ 70 ], we dichotomized the responses as done in previous studies [ 5 , 64 , 71 , 72 ]. Respondents who answered very good and good were categorized as having “good self-reported health”, while those who answered fair, bad, and very bad were categorized as having “poor self-reported health”. Our approach for dichotomizing the responses for the self-reported health was supported by existing research which mentioned that when five multiple options are available for a respondent to choose, the response that falls in the middle is closer to the negative responses as compared to the positive responses [ 73 ].

Work-life balance, our primary exposure of interest, was measured with the following question: “In general, how do your working hours fit in with your family or social commitments outside work?” Responses were: very well, well, not very well, and not at all well. To aid interpretability of our study, we further dichotomized the answers as good work-life balance (“very well” or, “well”) and poor work-life balance or work-life conflict (“not very well”, or “not at all well”).

The working characteristics of respondents were measured based on the Standard Industrial classification (NACE), sector, years of service, working arrangement, form of employment, type of employment, and weekly hours. NACE was classified into four categories (agriculture, industry, service, and other). Sector of employment was classified into five categories (private, public, joint private-public, NGO, and other). Shift work was measured with the question, “do you work shifts?” The responses were grouped as “Yes” or “No”. Working arrangement was categorised as (set by company, can choose between fixed schedule, flexible working time, working time is determined by self). We dichotomized the type of employment (employee and self-employed). Working hour was divided into five categories (30 h and below, 31–40 h, 41–50 h, 51–60 h, 60 h +). Regarding welfare regime types, we grouped countries according to common welfare state regime features. This study adopted Ferrera [ 74 ] and Bambra and Eikemo [ 75 ] classification of welfare typologies: Nordic (Sweden, Denmark, Finland, and Norway), Conservative (Austria, Belgium, France, Germany, Netherland, Luxembourg, and Switzerland), Liberals (United Kingdom and Ireland), Southern Europe (Greece, Spain, Italy, Portugal, Cyprus, and Malta), and Central and Eastern Europe (CEE) (Estonia, Lithuania, Hungary, Czech Republic, Poland, Latvia, Romania, Slovakia, Slovenia, Bulgaria, and Croatia).

Demographic characteristics including gender (male and female), household size, and age, marital status (single or widowed, married or cohabiting), and living with child (yes, no) were further explored. Socio-economic position was measured by education and occupation. Education was categorized in accordance with the International Standard Classification of Education-2011 (early childhood, primary, lower secondary, upper secondary, post-secondary, short cycle tertiary, bachelor, master, doctorate). The measurement of occupation was in line with the International Standard Classification of Occupation-08 (managers, armed forces, professionals, technicians and associate professionals, clerical support workers, agricultural workers, plant and machine operators, and elementary occupations).

Analytical strategy

Descriptive statistics were used to describe the study population. Furthermore, a bivariate test was performed on the measured variables by gender. We adopted a chi-square test for categorical variables [ 76 ], and a point biserial correlation test for continuous variables [ 77 ]. Variables that were significantly associated with the outcome variable were selected to estimate the odds ratios. In order to determine the association between self-reported health and work-life balance, a multivariate logistic regression was applied, adjusting for socio-economic position, working conditions, and demographic characteristics. Odds ratios and 95% confidence interval for all models estimated were presented for analysis. In addition, we estimated the Variance Inflation Factor (VIF) to test for multicollinearity of the independent variable and the covariates. The VIF is a more superior technique in determining collinearity [ 78 ]. According to O’Brien [ 78 ], a threshold value of VIF < 10 is an indication of low multicollinearity or non-existence of multicollinearity. Due to the clustering nature of the sample, we extended our multivariate logistic regression to a multi-level logistic regression to examine variations between welfare regimes and by gender. A two-stage multi-level logistic regression was applied with individual working adults nested within welfare state regimes. This was done across welfare state regimes, where the strength of the associations was compared. Furthermore, we estimated the median odds ratio (MOR) and the variance partition coefficient (VPC). The VPC is the percentage of variation that may occur in higher levels (welfare state regimes) [ 79 ]. Similarly, the MOR quantifies the level of variations that may exist between countries in Europe [ 5 ]. If the MOR is equal to 1, then there is no variation between countries across welfare state regimes, however, if the MOR is larger than 1, then there is a variation between countries in Europe [ 80 ]. All analyses were performed using Stata V14 [ 81 ] and done separately for men and women.

General distribution and sample characteristics

Table  1 provides information on the general descriptive statistics of working men and women of the 6th EWCS 2015. The mean age across welfare states regimes was quite similar among men and women. We observed good work-life balance among working men to be higher in the Nordic welfare states regime (85.6%), followed by the Conservative welfare states regime (82.0%). Women in the Nordic welfare states regime also had the highest (86.9%) frequency of good work-life balance, followed by the Conservative welfare states regime (85.1%). Furthermore, the highest proportion of poor work-life balance was reported among men (23.5%) and women (19.0%) in the Southern welfare states. In general, we found higher proportions of poor work-life balance among men than women across welfare states regimes. Regarding self-reported health, some gender differences were observed across welfare states. We observed the highest percentage of good self-reported health among men (84.8%) and women (87.2%) in the Liberal welfare states as compared to the other welfare states. In contrast, both working men (23.8%) and women (27.0%) in the CEE welfare states reported the highest poor self-reported health. In general, women reported slightly higher levels of education than men across the welfare states regimes. Also, the frequency of engaging in shift work was higher among women than men, particularly in the CEE welfare states regime (men: 24.8% vs women: 30.0%). Men were more likely to have their working time determined by themselves as compared to women in all the welfare states regimes. On the other hand, women frequently had their working time arrangements set by their companies. The results further revealed that men had long working hours and higher occupational status than women across all welfare states regimes.

Bivariate analysis

The results of the bivariate analysis between self-reported health and the measured variables are shown in Table  2 . The bivariate analysis showed a significant association between work-life balance and self-reported health for both working men and women. Age was positively associated with self-reported health (men ( r  = 0.213) vs. women ( r  = 0.207)). We, however, found a negative but low correlation between household size and self-reported health for both men ( r  =  − 0.056 ) and women ( r  =  − 0.057). Marital status was found to be significantly associated with self-reported health for women, but not men. Meanwhile, a significant association was found between type of employment and self-reported health among men but not women. Overall, there were similar patterns of associations between measured variables and self-reported health among men and women.

The results for the VIF’s are shown in an additional file supplied in the table: S 1 and S 2 . We compared the VIF’s of all the measured variables by gender. The maximum VIF for working men was 2.16, and the mean VIF was 1.45. For working women, the maximum VIF was 2.01, and the mean VIF was 1.33. The VIF estimated for men and women were quite similar. In fact, the estimated VIF’s were less than 2.5, which meets the threshold [ 78 ], for non-existence of multicollinearity.

Multivariate analysis

Table  3 provides information on the multivariate logistic regression. After adjusting for socio-economic factors, working characteristics, and demographic characteristics, the results showed a significant association between poor work-life balance and poor self-reported health among working adults (aOR = 2.07; 95% CI: (1.93–2.23)). We also found a significant association between poor work-life balance and self-reported health for both men (aOR = 1.97; 95% CI: (1.78–2.18) and women (aOR = 2.21; 95% CI: (1.99–2.45)). However, the magnitude of the association differs slightly among men and women.

Multilevel logistic regression

Table  4 shows the country variation that exists in the relationship between poor self-reported health and work-life conflict. We used a two-stage multilevel logistic regression to assess variations that exist between welfare states regimes. After controlling for socio-economic positions, working characteristics, and demographic characteristics, the multilevel models showed a significant relationship between work-life conflict and poor self-reported. However, the magnitude of the associations differs slightly across welfare states regimes. For instance, we found the association to be slightly higher for women than men in the Nordic (men: aOR = 1.77; 95% CI: (1.26–2.47) vs women: aOR = 1.92; 95% CI: (1.37–2.69)), Liberal (men: aOR = 2.23; 95% CI: (1.55–3.21) vs women: aOR = 2.39; 95% CI: (1.51–3.78)), Southern (men: aOR = 1.65; 95% CI: (1.36–2.00) vs women: aOR = 2.02; 95% CI: (1.64–2.48)), and CEE welfare states (men: aOR = 1.91; 95% CI: (1.59–2.30) vs women: aOR = 2.29; 95% CI: (1.92–2.73)), but slightly higher for men than women in the Conservative welfare states (men: aOR = 2.62; 95% CI: (2.17–3.17) vs women: aOR = 2.42; 95% CI: (2.00–2.94)). While the largest odds between work-life conflict and poor self-reported health among men were found in the Conservative welfare states, the Liberal and the CEE welfare states, the smallest association was observed in the Southern European welfare states followed by the Nordic welfare states. Among women, the highest association was found in the Liberal and Conservative welfare states, while, the lowest association was observed in the Nordic welfare states regime.

Overall, we found small variation in the association between poor work-life balance and poor self-reported health between countries in Europe (men: MOR = 1.18 vs women: MOR = 1.29), and the percentage of variations were slightly higher for women (VPC = 2.07%) than men (VPC = 0.9%).

To the best of our knowledge, this is the first study to examine gender and welfare state regime differences in the relationship between work-life conflict and self-reported health among working adults with a comprehensive cross-country sample in Europe. The descriptive results revealed that working men in Europe had poor work-life balance than women in the Nordic, Conservative, Liberal, Southern, and CEE welfare states. We found the highest proportion of good work-life balance in the Nordic welfare states regime, while the highest proportion of poor work-life balance was found in the Southern European welfare states regime. More importantly, the result showed that poor work-life balance, as measured in the EWCS 2015 was strongly associated with poor self-reported health among working adults in Europe. However, the magnitude of the association was slightly higher for working women than men. Furthermore, we observed slight variations in the association between poor work-life balance and poor self-reported health across welfare states regimes in Europe. While the largest association between poor work-life balance and poor self-reported health for both men and women were observed in the Liberal welfare states and the Conservative welfare states, the smallest association was found in the Nordic and Southern welfare states.

Work-life balance and health

Prior evidence that examined work-life conflict among men and women showed inconsistent findings [ 5 , 33 , 43 , 44 , 45 ]. Overall, our study found a higher frequency of poor work-life balance among men than women across welfare states regimes in Europe. This finding is consistent with a study conducted by Jansen et al. [ 82 ], who found evidence that men are most affected by work-life conflict as compared to women. While working men and women in the Nordic (men = 85.6% vs. women = 86.9%) and the conservative (men = 82.0% vs. women = 85.1%) welfare states reported the highest proportions of good work-life balance, the highest proportion of poor work-life balance among men and women were found in the Southern (men = 23.5% vs women = 19.0%), CEE (men = 19.1% vs women = 15.3%), and Liberal (men = 19.0% vs women = 15.4%) welfare states. These findings were partly in agreement with the findings of the 2010 European Working Conditions Survey by Lunau et al. [ 5 ]. They found a higher prevalence of poor work-life balance among working men and women in the Southern, CEE, and Former Soviet Union welfare states. Juxtaposing our results to the findings by Luanu et al. [ 5 ] revealed that poor work-life balance among employees in Europe appears to have reduced over time, perhaps, due to improvement in working conditions for employees [ 83 ].

Our results further revealed a strong association between poor work-life balance and poor self-reported health among working adults in Europe. This finding is in congruence with other studies that found a negative association between poor work-life balance and self-reported health [ 5 , 41 , 66 , 84 ]. For instance, a systematic review by Allen, Herst, et al. [ 66 ] suggest that poor work-life balance was associated with poor health outcomes including psychological strain, depression, burnout, stress, and substance abuse. Likewise, research conducted among workers in Korea indicated that poor work-life balance was positively associated with poor health outcomes such as fatigue, general health, mental health, sickness absenteeism, musculoskeletal diseases, and work-related risks to health and safety [ 41 ]. This adverse relationship can partly be explained by the multiple role engagement and overload of demands and responsibilities among working adults [ 43 ].

Regarding gender, while some studies suggest that there is no difference in the relationship between work-life conflict and poor self-reported health among men and women [ 5 , 28 ], few studies noted higher adverse health outcomes among women than men [ 25 , 26 , 27 ]. Our findings from the multivariate analysis indicated that there is a negative relationship between work-life conflict and self-reported health among men and women in contemporary welfare states in Europe, consistent with prior studies [ 5 , 25 , 26 , 27 ]. However, there is a slight difference in the strength and magnitude of the association, where the association is slightly higher among women than men. This outcome has been attributed to behavioural norms and societal expectations for men and women [ 33 ], and differential exposure to multiple role engagement and overloads, pressures of family, work demands, and social commitment [ 43 ]. While women are expected to devote more time to family roles such as housekeeping, elderly care, and child care, men are expected to engage more in paid work activities [ 10 , 34 , 35 , 36 , 38 , 85 ]. This finding was evident in our study as the proportion of weekly working hours was higher among men than women, even though women reported higher levels of education than men in Europe. This unequal distribution of work-related activities (i.e. paid work and housework) may partly explain the gender work-life “imbalance” [ 25 , 26 ] and adverse health outcomes, especially among women [ 27 ].

In terms of the variations between welfare states, the two-stage multilevel logistic regression showed a higher magnitude in the association between poor work-life balance and poor self-reported health for both men and women in the Liberal welfare states regime, where there is a strong male breadwinner tradition, minimal social policies, and poorly regulated labour market [ 58 , 59 ]. Meanwhile, the magnitude of the association for both genders in the Conservative welfare states regime was slightly higher than the Nordic, Southern, and the CEE welfare states. Women had higher associations between poor work-life balance and poor self-reported health in this welfare states than men. We speculate that the presence of weak employment regulation and weak unions may allow for strict managerial control, which may increase job pressure and job insecurity [ 86 ]. In addition, the weak provision of social benefits for ‘child and elderly care’ [ 58 ] may exert pressure on women than men when combining care, household activities, and work demands [ 64 ].

Similar to other studies [ 13 , 64 , 87 ], we found a negative relationship between poor work-life balance and self-reported health for both men and women in the Conservative welfare states regime which is characterised by traditional breadwinner model and strong labour laws which regulate the labour market [ 53 , 74 ]. Surprisingly, working men and women in the Conservative welfare states regime had the highest magnitude regarding the association between poor work-life balance and poor self-reported health. There is some evidence that women who live in Conservative welfare states report poorer health status than men due to poor work-life balance [ 87 ]. In contrast, our findings suggest a slightly higher magnitude in the association for men than women. These gender differences may probably be due to temporary contracts [ 88 ], as well as part-time employment for women as compared to men [ 60 ], which may provide women with more time resources to deal with competing demands than men [ 12 , 13 ]. Further, we found a lower association between poor work-life balance and poor self-reported health for working adults in the Nordic welfare states regime than the Conservative, Liberal, and CEE welfare states. This may partly be attributed to the generous and encompassing social policies including child care for pre-school, universal health care, elderly care, and long parental leave days that exist in the Nordic welfare states [ 53 , 55 , 56 , 57 ], which may contribute to lower levels of work-life conflict and consequently better self-reported health [ 5 , 12 , 13 ]. However, poor work- life balance was slightly associated with poor self-reported health among women than men in the Nordic welfare states. The slight gender difference in the association may be related to the so-called “parallel ideals” that exist in the Nordic countries where equality is important; yet societal and cultural expectation of women as caregivers still exist [ 12 , 64 , 89 ]. Surprisingly, we found weaker associations between poor work-life balance and poor self-reported health among working adults in the Southern European welfare states as compared with Conservative and Liberal welfare states, especially among men. This is very striking considering the fact that Southern welfare states are characterized by minimal social welfare benefits than the conservative welfare state [ 64 ]. In view of the above discussion, and based on the median odds ratios (MOR) and the variance partition coefficients (VPC) that were estimated in the two-stage multi-level logistic regression, our findings suggested that the effect size of work-life balance on health status may vary between welfare states in Europe, particularly, among women than men. Nonetheless, the magnitude of the variation between welfare state regimes that was identified in our study were quite marginal.

In order to address the issue of work-life conflict among working adults in the welfare states in Europe, countries must design, and implement effective industrial relation laws, legislation, and policies that can effectively protect the health and safety of working adults [ 90 , 91 ]. The existing laws and regulation can also be effectively enforced through agencies, where labour inspectorate can oversee the enforcement of existing labour protection laws and work-life policies such as work time arrangement, paid parental leave days, and child and elderly care. Furthermore, welfare states should establish strong state institutions and judicial systems to serve as mediators that can assist workers and employers in the resolution of disputes [ 90 ]. For example, there must be well-functioning labour court, special tribunal and arbitration system which is easily accessible for workers and employers to address disputes pertaining to work and family life [ 90 ]. Finally, governments must encourage and strengthen frequent tripartite negotiation between welfare states and its representatives, employers, trade unions, and other stakeholders to dialogue on the implementation and sustainability of family-friendly policies [ 90 , 91 ].

Limitation and strength

Although the findings of this research are in line with previous research and empirical reviews, there are some conceptual limitations that need to be addressed. Firstly, the measure of work- life balance by the EWCS 2015 was assessed by using only one question on “whether working hours fit in with family or social commitments”. Although work-family fit serves as an important proxy in dealing with issues of work-life balance, it lacks the theoretical basis in describing how the dimensions of work-life conflict and facilitation operate together in shaping the individual and organization [ 92 ]. Greenhaus and Beutell [ 3 ] noted that work-life conflict can be measured through different dimensions such as time, strain, and behaviour based conflict. However, the EWCS 2015 only captured the time conflict dimension and not strain and behaviour-based conflict. As suggested by Choi and Kim [ 41 ], future studies should combine both the work-life balance measurement in the EWCS to the OECD measurement of work-life balance to form one comprehensive question that includes all the dimensions. Secondly, we used self–reported health as the outcome variable. This subjective measure has been linked with heterogeneity problems [ 93 , 94 ], where people living in different locations, and with different socio-economic status, family demographic status, and gender may adopt different thresholds in assessing their health [ 94 ]. Nevertheless, self-reported health has been shown to be an accurate measure and a strong predictor for mortality [ 95 ]. Thirdly, our findings were based on cross-sectional data, which makes it difficult to make definitive conclusions on the direction of the relationship between work-life balance and health status among employees [ 96 ]. Notwithstanding these limitations, this study is the first to provide a comprehensive overview of the relationship between work-life conflict and self-reported health according to welfare state regime typology.

We conclude that poor work-life balance is associated with poor self-reported health among working adults, particularly among working women than men in Europe. However, the magnitude and strength of these associations slightly differ across countries in different welfare states regimes. This study thus serves as the baseline for policymakers and stakeholders to fully understand the need to help reduce pressing demands from life domains. Organizations must also create good working atmosphere and flexible working time to deal with issues of jobs strain in order to reduce health problems.

Availability of data and materials

The data used for this study comes from European Foundation for the Improvement of Living and Working Conditions. Detailed information on the survey design and characteristics are provided on the https://www.eurofound.europa.eu/surveys/european-working-conditions-surveys/sixth-european-working-conditions-survey-2015 homepage.

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Additional file 1: table s1.

Variance Inflation Factor (VIF) of measured variables by men. Table S2 Variance Inflation Factor (VIF) of measured variables by women.

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Mensah, A., Adjei, N.K. Work-life balance and self-reported health among working adults in Europe: a gender and welfare state regime comparative analysis. BMC Public Health 20 , 1052 (2020). https://doi.org/10.1186/s12889-020-09139-w

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How Researchers Handle Work-Life Balance

Work-life balance, especially for careers in science, is more challenging than it sounds. Maintaining a balance between work and life represents a culmination of patience, self-discipline, and boundary-setting. It is common for researchers to suffer from mental health issues due to working significantly longer-than-normal working hours without making satisfactory progress. A 2022 Nature survey found that 70% of graduate students work more than 40 hours per week, and that 68% have difficulty maintaining a good work-life balance ( Woolston, 2022 ). And, according to Nature’s 2021 salary and Job survey , nearly half (45%) of scientists across all career stages reported signs of burnout and overwork ( Woolston, 2021 ).  

Although organizational skills are crucial if you choose to start a career in science ( Bartlett et al, 2021 ), many days it is impossible to work only eight hours or to avoid work on some weekends. To an extent, this is acceptable in a field like biological sciences where we work with living organisms. However, devoting seven days a week frequently might result in researchers’ having mental health struggles like anxiety, burnout syndrome, and depression ( Powell, 2016 ). It has been observed that students in academia are particularly affected by mental health issues due to uncertainty in their future jobs, and the need to obtain results that can be published ( Powell, 2017 ).  

Many young researchers find it difficult to have an active life outside the lab because they sacrifice their free time to meet the demands of the next experiment planned, an upcoming conference, or to work on a paper. However, disconnecting from work will increase creativity and productivity at the workplace. Many scientists say that their leisure time improves their research by boosting their confidence, sharpening their minds, and releasing stress.  

Family obligations, together with scientific research and teaching, have taken a toll on the mental health of academic mothers and female scientists who wish to create a family. Women shoulder more of the childcare responsibilities in a family ( Cohut, 2017 ), and one cannot be brilliant at taking care of everything at the same time if the family load is not equally shared. This unbalanced situation, paired with the demands of a career in scientific research, may lead to women developing mixed feelings about pursuing scientific research as a career. In a recent study   on a time-use survey of 19,905 academics, it was found that all academic parents reported a reduction in time spent on research per day ( Deryugina, 2021 ). This reduction of time spent on research is greater for academic mothers than fathers, especially during the Covid-19 pandemic.  

The common solutions that could be taken to ease work-life balance could be:  

• Improve organizational skills.  
• Take short breaks from daily bench work in the laboratory.  
• Set boundaries to have free time to develop our leisure activities.  
• Try not to schedule work during the weekends unless it is necessary.  
• Socialize and have a support network of either friends with different work backgrounds or family.   
• Fight for our rights. Better scholarships, longer and fair maternity leaves, flexible schedules, and sometimes improving mental health is just a matter of improving work conditions.  

Supervisors are key to encouraging healthy work-life balance in the lab by promoting self-care habits among their mentees and being role models themselves. Support systems for care-giver parents, especially women in academic science, need to be prioritized by institutions and agencies so that they continue to have a thriving, diverse workforce in place. Such practices of compassion, care, and equity will eventually lead to a healthy work-life balance for many.   

References  

• Bartlett MJ, Arslan FN, Bankston A, Sarabipour S. 2021. Ten simple rules to improve academic work-life balance. PLoS Comput Biol. 17(7):e1009124. doi:10.1371/journal.pcbi.1009124. http://dx.doi.org/10.1371/journal.pcbi.1009124 .  
• Cohut M. 2017 Oct 10. Women “spend more time on housework, childcare than men.” Medical News Today. [accessed 2023 Feb 6]. https://www.medicalnewstoday.com/articles/319687 .  
• Deryugina T, Shurchkov O, Stearns J. 2021. COVID-19 disruptions disproportionately affect female academics. Cambridge, MA: National Bureau of Economic Research.  
• Powell K. 2016. Young, talented and fed-up: scientists tell their stories. Nature. 538(7626):446–449. doi:10.1038/538446a. [accessed 2023 Feb 6]. https://www.nature.com/articles/538446a .  
• Powell K. 2017. Work–life balance: Break or burn out. Nature. 545(7654):375–377. doi:10.1038/nj7654-375a. [accessed 2023 Feb 6]. https://www.nature.com/articles/nj7654-375a .  
• Woolston C. 2021. How burnout and imposter syndrome blight scientific careers. Nature. 599(7886):703–705. doi:10.1038/d41586-021-03042-z. [accessed 2023 Feb 6]. https://www.nature.com/articles/d41586-021-03042-z .  
• Woolston C. 2022. Stress and uncertainty drag down graduate students’ satisfaction. Nature. 610(7933):805–808. doi:10.1038/d41586-022-03394-0. [accessed 2023 Feb 6]. https://www.nature.com/articles/d41586-022-03394-0 .  

______________________________________________

About the Authors:

Indrani Kakati Baruah  is a postdoctoral researcher mother and a 2023 Plantae Fellow , wishing to connect with researchers around the globe and impart knowledge through communicating innovative research and wants to inspire and motivate young girls to take up science and never give up. You can find her on Twitter at @indranikb .

Eva Maria Gomez Alvarez is a PhD student in Agrobiodiversity working in Italy  and a 2023 Plantae Fellow . She studies cereal genetics and microbiome, and during her free time, she likes to play the flute, run and read feminist books. You can find her on Twitter at @eva_ga96 .

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Job Satisfaction at a High Thanks to Work/Life Balance Strides

Female employees less satisfied, job switchers happiest

​Pandemic concerns, persistent inflation, burnout and more have wreaked havoc on employee well-being in recent years—but thanks to gains in pay, benefits and work/life balance, workers are actually happier than they have been in decades.

New data out from The Conference Board, a research organization, shows that overall job satisfaction among U.S. workers—particularly those who recently changed jobs—hit its highest levels on record last year. Overall, 62.3 percent of U.S. workers were satisfied in 2022—up from 60.2 percent in 2021 and 56.8 percent in 2020 and the highest level recorded since The Conference Board started conducting its annual job satisfaction survey in 1987.

"With unemployment at record lows, it's a seller's market for labor, and U.S. workers are reaping the rewards," said Eren Selcuk, senior economist at The Conference Board.

The Conference Board's annual survey , which asked workers about 26 components of their jobs, including work/life balance, health benefits, leave policies, retirement plans, workload and leadership—finds that every aspect of work has improved since the previous year's survey. The largest jump from 2021 to 2022 was work/life balance, which grew 5.8 percentage points to reach 60.1 percent in 2022.

Caitlin Duffy, director in the Gartner HR practice, said she's not surprised that job satisfaction has increased over the past few years, as the COVID-19 pandemic "had a seismic impact on the dynamics of the talent market."

"As organizations have shifted toward more remote-work models and adoption of hybrid/remote jobs became more mainstream, employees gained unprecedented access to expanded opportunities," she said. "Many were no longer constrained by geographic availability of open roles and had the freedom to pursue jobs in a wider range of locations, which increased the probability of finding a role that best fit their interests and preferences."

The data comes as employers make advances in efforts to boost employee satisfaction. Employees have reeled from social and health stressors in the past few years, and employers are working to keep them put as many employees left for other opportunities in 2021 and 2022.

In tandem with rising employee expectations, employers have turned to more mental health benefits, flexible schedules, remote work opportunities and bigger pay increases. Recent data from consulting firm Mercer , for instance, found that employers are shelling out bigger pay boosts to employees in 2023 than they have in years.

Allan Schweyer, principal researcher of human capital at The Conference Board, said the results "reveal that once workers are paid competitively, a strong workplace culture is the most important factor for keeping workers."

"Leaders gain the most by offering flexible, hybrid work arrangements and by emphasizing work experience and culture factors such as interesting work, reasonable workloads and opportunities for career growth," he said.

However, The Conference Board's survey reveals a significant happiness gap between men and women in the workplace. Women are significantly less satisfied than men across almost all 26 job satisfaction components surveyed, with large gaps appearing in job security, promotion policy, bonus plans, and compensation and benefits, including pay, sick day policy, vacation policy and health plans. This means, the report's authors wrote, that "firms need to be more conscious and intentional about achieving pay equity and addressing gender gaps across numerous other factors of satisfaction."

Contrasting Data

Some of the findings from The Conference Board appear to be good news for organizations—but they run in contrast to other recent reports. Benefits firm MetLife, in its annual employee benefits report out in March, found that while overall job satisfaction increased year over year to 69 percent in 2023 from 66 percent in 2022, job satisfaction registered its second-lowest score in a decade. MetLife also found that employees' satisfaction with their benefits fell to 61 percent in 2023, down from 64 percent in 2022, reaching its lowest point in the past decade. MetLife's survey of some 2,840 benefits leaders and 2,884 full-time employees also revealed sharp declines in employees' overall well-being, particularly in financial and mental health.

Missy Plohr-Memming, senior vice president for national accounts sales and group benefits at MetLife, told SHRM Online in March that one likely reason for the decline in benefits and jobs satisfaction is higher employee expectations in the wake of significant financial and mental health struggles. "While employers have made efforts to expand their benefits offerings, they simply have not been able to meet employees' evolving expectations quickly enough," she said.

Job changes may account for some of the stark difference. The Conference Board, in its findings, highlighted and surveyed workers who switched jobs recently. Workers who voluntarily left their organizations and found new jobs since the pandemic began were the most satisfied among all workers, the survey found.

Compared to workers who had not left for another job, workers who had recently moved to another organization experienced significantly higher satisfaction—a difference in the double digits in percentage points—in aspects such as pay, bonuses, educational and job training programs, and mental health benefits. That's likely a result of the tight labor market, which has left employees able to leave for higher pay, better perks and more desired working arrangements.

Record-high inflation is leaving the majority of employees dissatisfied with their pay despite rising salaries, Duffy noted, so it makes sense that some employees who left for a significant pay boost at other organizations might feel more satisfied with their jobs.

It's also important to note that The Conference Board survey of 1,680 workers was conducted in November 2022. Since that time, layoffs and benefits cuts have been become increasingly common as recession fears grow.

"Looking ahead, the short recession that many anticipate in 2023 may temporarily ease labor shortages," The Conference Board's report noted. "We see some signs of softening labor markets with job openings and voluntary quits declining over the last few months after record highs in March 2022. Declining worker mobility could reduce job satisfaction in the coming 12 to 24 months. In the medium and long term, however, changing demographics and restricted immigration will likely expand skill and talent shortages."

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Balancing Your Research with Your Life

The Science Mission Directorate (SMD) recognizes the importance of balancing one’s work with the requirements of one’s family, friends and personal physical and mental health. This web page is offered to inform SMD-funded researchers about NASA-provided wellness resources and leave options that may be available.

This is SMD’s first effort at summarizing the resources and flexibilities available to its funded researchers. Please help us improve this page by sending suggestions, questions and feedback to: [email protected] .

Options and resources vary depending on your relationship to NASA, as well as the accommodations offered by your employer. The information below is divided into four categories: 1) researchers whose work is supported through NASA grants or cooperative agreements, also known as Federal Assistance awards; 2) NASA civil servants; 3) NASA Contractors; and, 4) NASA Postdoctoral Program (NPP) Fellows.

Your first step, regardless of your relationship to NASA, should be to contact your institution’s Office of Sponsored Programs, Human Resources or Human Capital Office to determine your employer's policies. NPP Fellows should contact their NPP Center Representative.

1) Researchers supported by NASA grants or cooperative agreements

Most of the flexibilities available to those whose work is supported by NASA grants and cooperative agreements are addressed in the US Code of Federal Regulations, Title 2, Part 200 (2 CFR 200) which is the common, US Government-wide guidance on grants and cooperative agreements. In the context of family-friendly and medical leave, the relevant section is Section 431(b), Leave , which is usually cited as “§200.431(b) Leave”.

NASA’s implementation of these Federal standards is enumerated in the Grant and Cooperative Agreement Manual (GCAM) . Your institution’s policies and NASA’s implementation of 2 CFR 200 determine whether costs associated with family or medical accommodations are allowed to be charged to your NASA-issued grant or cooperative agreement. Some commonly asked questions about the allowability of costs are:

• May a NASA grant's period of performance be extended for researchers who take a leave of absence due to dependent-care or other responsibilities?

As stated in the GCAM, award recipients are allowed to initiate one no-cost extension (NCE) on their own. So, a recipient could initiate an NCE, on their own for any reason, including a personnel absence. Subsequent NCEs require prior approval by NASA and need to be justified — especially if the amount of unspent funds is large. Personnel absence due to life events may be used as part of this justification. NASA will determine if extending the award is in the Agency’s best interest.

In accordance with 2 CFR§200.308, Revisions of budget and program plans, if a key person disengages from a grant for more than 3 months or reduces their efforts by 25% or more for any reason, then the recipient must obtain prior approval of the disengagement or effort reduction from a NASA Grant Officer and not by your Program Officer.

• May grant recipients use award funds for dependent-care expenses?

Dependent-care expenses are only allowable when the PI’s institution has a written policy in place that allows the institution to pay for employees’ dependent care. If the institution has such a policy in place, then the institution could charge those costs to a NASA award as either fringe benefits or indirect costs.

• May grant funds be used for dependent travel or childcare at conferences?

2 CFR 200.475, Travel costs, notes that temporary dependent-care costs beyond regular dependent-care that are the direct result from travel to conferences are allowable. Travel costs for dependents is unallowable, except for travel with a duration of six months or more with prior approval from NASA. Moreover, these dependent care costs and travel costs are allowable only if they are consistent with the institution’s own travel policy.

• May grant funds be used to pay for employee leave taken for dependent-care responsibilities?

When it comes to questions of employee leave for dependent care or dependent-care costs, those benefits and expenses are only allowable if the institution allows for them in their written policies. If the institution has policies regarding these benefits, they can charge them as fringe benefits or indirect costs to a NASA award.

• May institutions request supplemental funding or to change a current budget to support additional personnel to sustain research when the PI is on family leave?

NASA has the discretion to provide additional funds on a case-by-case basis. SMD, however, has not established a centralized source of funding for these supplements. Please contact your NASA Program Officer to inquire as to the availability of funds. Formal requests must come from your institution’s sponsored projects office and include a budget with a narrative. Note that prior approval for changes to the budget for these costs can only be given by a NASA Grant Officer and not by your Program Officer.

2) NASA Civil Servants

NASA has implemented leave programs that work in coordination with one another to provide flexibility to NASA employees who are experiencing a personal or family medical emergency. For more information about these programs visit the Leave Programs website . NASA civil servants should direct questions about leave and other work-life balance options to their Center’s respective Human Resources Office (HRO). A list of Center Human Resources Office Sites are available through the HR Portal.

Each NASA Center also offers Employee Assistance Programs (EAP) that provide voluntary, confidential, short-term, and free mental health/wellness support. All Civil Service Personnel are eligible and encouraged to explore EAP.

3) NASA Contractors

At some Centers, on-site contractors are also eligible for some Employee Assistance Program (EAP) services. At Centers where Contractors are not eligible for EAP, some services are still available. Contractor employees are encouraged to ask their employers which EAP benefits their employers may make available. Some NASA contractors’ EAP resources may be listed on the EAP for Contractors page accessible from the Employee Assistance Program (EAP) website.

4) NASA Postdoctoral Program ( NPP ) Fellows

NPP Fellows are neither employees of NASA nor the NPP Contractor. However, published NPP policies accommodate prolonged absences and are accessible via the Obligations of the Appointment page .

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Meditation: a simple, fast way to reduce stress.

Meditation can wipe away the day's stress, bringing with it inner peace. See how you can easily learn to practice meditation whenever you need it most.

If stress has you anxious, tense and worried, you might try meditation. Spending even a few minutes in meditation can help restore your calm and inner peace.

Anyone can practice meditation. It's simple and doesn't cost much. And you don't need any special equipment.

You can practice meditation wherever you are. You can meditate when you're out for a walk, riding the bus, waiting at the doctor's office or even in the middle of a business meeting.

Understanding meditation

Meditation has been around for thousands of years. Early meditation was meant to help deepen understanding of the sacred and mystical forces of life. These days, meditation is most often used to relax and lower stress.

Meditation is a type of mind-body complementary medicine. Meditation can help you relax deeply and calm your mind.

During meditation, you focus on one thing. You get rid of the stream of thoughts that may be crowding your mind and causing stress. This process can lead to better physical and emotional well-being.

Benefits of meditation

Meditation can give you a sense of calm, peace and balance that can benefit your emotional well-being and your overall health. You also can use it to relax and cope with stress by focusing on something that calms you. Meditation can help you learn to stay centered and keep inner peace.

These benefits don't end when your meditation session ends. Meditation can help take you more calmly through your day. And meditation may help you manage symptoms of some medical conditions.

Meditation and emotional and physical well-being

When you meditate, you may clear away the information overload that builds up every day and contributes to your stress.

The emotional and physical benefits of meditation can include:

• Giving you a new way to look at things that cause stress.
• Building skills to manage your stress.
• Making you more self-aware.
• Focusing on the present.
• Reducing negative feelings.
• Helping you be more creative.
• Helping you be more patient.
• Lowering resting heart rate.
• Lowering resting blood pressure.
• Helping you sleep better.

Meditation and illness

Meditation also might help if you have a medical condition. This is most often true if you have a condition that stress makes worse.

A lot of research shows that meditation is good for health. But some experts believe there's not enough research to prove that meditation helps.

With that in mind, some research suggests that meditation may help people manage symptoms of conditions such as:

• Chronic pain.
• Depression.
• Heart disease.
• High blood pressure.
• Irritable bowel syndrome.
• Sleep problems.
• Tension headaches.

Be sure to talk to your healthcare professional about the pros and cons of using meditation if you have any of these or other health conditions. Sometimes, meditation might worsen symptoms linked to some mental health conditions.

Meditation doesn't replace medical treatment. But it may help to add it to other treatments.

Types of meditation

Meditation is an umbrella term for the many ways to get to a relaxed state. There are many types of meditation and ways to relax that use parts of meditation. All share the same goal of gaining inner peace.

Ways to meditate can include:

Guided meditation. This is sometimes called guided imagery or visualization. With this method of meditation, you form mental images of places or things that help you relax.

You try to use as many senses as you can. These include things you can smell, see, hear and feel. You may be led through this process by a guide or teacher.

• Mantra meditation. In this type of meditation, you repeat a calming word, thought or phrase to keep out unwanted thoughts.

Mindfulness meditation. This type of meditation is based on being mindful. This means being more aware of the present.

In mindfulness meditation, you focus on one thing, such as the flow of your breath. You can notice your thoughts and feelings. But let them pass without judging them.

• Qigong. This practice most often combines meditation, relaxation, movement and breathing exercises to restore and maintain balance. Qigong (CHEE-gung) is part of Chinese medicine.
• Tai chi. This is a form of gentle Chinese martial arts training. In tai chi (TIE-CHEE), you do a series of postures or movements in a slow, graceful way. And you do deep breathing with the movements.
• Yoga. You do a series of postures with controlled breathing. This helps give you a more flexible body and a calm mind. To do the poses, you need to balance and focus. That helps you to focus less on your busy day and more on the moment.

Parts of meditation

Each type of meditation may include certain features to help you meditate. These may vary depending on whose guidance you follow or who's teaching a class. Some of the most common features in meditation include:

Focused attention. Focusing your attention is one of the most important elements of meditation.

Focusing your attention is what helps free your mind from the many things that cause stress and worry. You can focus your attention on things such as a certain object, an image, a mantra or even your breathing.

• Relaxed breathing. This technique involves deep, even-paced breathing using the muscle between your chest and your belly, called the diaphragm muscle, to expand your lungs. The purpose is to slow your breathing, take in more oxygen, and reduce the use of shoulder, neck and upper chest muscles while breathing so that you breathe better.

A quiet setting. If you're a beginner, meditation may be easier if you're in a quiet spot. Aim to have fewer things that can distract you, including no television, computers or cellphones.

As you get more skilled at meditation, you may be able to do it anywhere. This includes high-stress places, such as a traffic jam, a stressful work meeting or a long line at the grocery store. This is when you can get the most out of meditation.

• A comfortable position. You can practice meditation whether you're sitting, lying down, walking, or in other positions or activities. Just try to be comfortable so that you can get the most out of your meditation. Aim to keep good posture during meditation.
• Open attitude. Let thoughts pass through your mind without judging them.

Everyday ways to practice meditation

Don't let the thought of meditating the "right" way add to your stress. If you choose to, you can attend special meditation centers or group classes led by trained instructors. But you also can practice meditation easily on your own. There are apps to use too.

And you can make meditation as formal or informal as you like. Some people build meditation into their daily routine. For example, they may start and end each day with an hour of meditation. But all you really need is a few minutes a day for meditation.

Here are some ways you can practice meditation on your own, whenever you choose:

Breathe deeply. This is good for beginners because breathing is a natural function.

Focus all your attention on your breathing. Feel your breath and listen to it as you inhale and exhale through your nostrils. Breathe deeply and slowly. When your mind wanders, gently return your focus to your breathing.

Scan your body. When using this technique, focus attention on each part of your body. Become aware of how your body feels. That might be pain, tension, warmth or relaxation.

Mix body scanning with breathing exercises and think about breathing heat or relaxation into and out of the parts of your body.

• Repeat a mantra. You can create your own mantra. It can be religious or not. Examples of religious mantras include the Jesus Prayer in the Christian tradition, the holy name of God in Judaism, or the om mantra of Hinduism, Buddhism and other Eastern religions.

Walk and meditate. Meditating while walking is a good and healthy way to relax. You can use this technique anywhere you're walking, such as in a forest, on a city sidewalk or at the mall.

When you use this method, slow your walking pace so that you can focus on each movement of your legs or feet. Don't focus on where you're going. Focus on your legs and feet. Repeat action words in your mind such as "lifting," "moving" and "placing" as you lift each foot, move your leg forward and place your foot on the ground. Focus on the sights, sounds and smells around you.

Pray. Prayer is the best known and most widely used type of meditation. Spoken and written prayers are found in most faith traditions.

You can pray using your own words or read prayers written by others. Check the self-help section of your local bookstore for examples. Talk with your rabbi, priest, pastor or other spiritual leader about possible resources.

Read and reflect. Many people report that they benefit from reading poems or sacred texts and taking a few moments to think about their meaning.

You also can listen to sacred music, spoken words, or any music that relaxes or inspires you. You may want to write your thoughts in a journal or discuss them with a friend or spiritual leader.

• Focus your love and kindness. In this type of meditation, you think of others with feelings of love, compassion and kindness. This can help increase how connected you feel to others.

Building your meditation skills

Don't judge how you meditate. That can increase your stress. Meditation takes practice.

It's common for your mind to wander during meditation, no matter how long you've been practicing meditation. If you're meditating to calm your mind and your mind wanders, slowly return to what you're focusing on.

Try out ways to meditate to find out what types of meditation work best for you and what you enjoy doing. Adapt meditation to your needs as you go. Remember, there's no right way or wrong way to meditate. What matters is that meditation helps you reduce your stress and feel better overall.

Related information

• Relaxation techniques: Try these steps to lower stress - Related information Relaxation techniques: Try these steps to lower stress
• Stress relievers: Tips to tame stress - Related information Stress relievers: Tips to tame stress
• Video: Need to relax? Take a break for meditation - Related information Video: Need to relax? Take a break for meditation

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• Meditation: In depth. National Center for Complementary and Integrative Health. https://nccih.nih.gov/health/meditation/overview.htm. Accessed Dec. 23, 2021.
• Mindfulness meditation: A research-proven way to reduce stress. American Psychological Association. https://www.apa.org/topics/mindfulness/meditation. Accessed Dec. 23, 2021.
• AskMayoExpert. Meditation. Mayo Clinic. 2021.
• Papadakis MA, et al., eds. Meditation. In: Current Medical Diagnosis & Treatment 2022. 61st ed. McGraw Hill; 2022. https://accessmedicine.mhmedical.com. Accessed Dec. 23, 2021.
• Hilton L, et al. Mindfulness meditation for chronic pain: Systematic review and meta-analysis. Annals of Behavioral Medicine. 2017; doi:10.1007/s12160-016-9844-2.
• Seaward BL. Meditation. In: Essentials of Managing Stress. 5th ed. Jones & Bartlett Learning; 2021.
• Seaward BL. Managing Stress: Principles and Strategies for Health and Well-Being. 9th ed. Burlington, Mass.: Jones & Bartlett Learning; 2018.

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7 Least Stressful College Degrees That Can Help You Earn Well

By Roshni Chakrabarty

Choosing a college degree can be daunting, especially when considering stress levels; however, certain fields offer financial stability with lower stress environments.

Computer science offers high earning potential in software development, data analysis, and cybersecurity, with manageable stress levels.

1. COMPUTER SCIENCE

Education degrees offer rewarding careers in teaching and counseling, providing opportunities to positively impact students' lives with manageable stress.

2. EDUCATION:

Environmental science degrees provide opportunities in conservation and sustainability, focusing on environmental stewardship with lower stress levels.

3. ENVIRONMENTAL SCIENCE:

Library science degrees lead to careers in library management and information science, offering a quiet and intellectually stimulating environment with low stress.

4. LIBRARY SCIENCE:

Studying statistics leads to careers in data analysis and market research, focusing on numerical data analysis with manageable stress.

5. STATISTICS:

Accounting offers careers in financial analysis and taxation, known for stability and manageable stress levels.

6. ACCOUNTING:

Architecture graduates secure rewarding careers as architects, urban designers, or sustainable design consultants, making significant impacts on the built environment while earning competitive salaries.

7. NUTRITION:

Choosing a college degree in these fields can lead to financially rewarding careers with minimized stress and a healthy work-life balance, ensuring a fulfilling future.