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Well-Being in Life and Well-Being at Work: Which Comes First? Evidence From a Longitudinal Study

Dorota weziak-bialowolska, piotr bialowolski, pier luigi sacco, tyler j vanderweele, eileen mcneely.

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Edited by: Marissa G. Baker, University of Washington, United States

Reviewed by: Trevor K. Peckham, University of Washington, United States; Kyoung-Mu Lee, Korea National Open University, South Korea

*Correspondence: Dorota Weziak-Bialowolska [email protected]

This article was submitted to Occupational Health and Safety, a section of the journal Frontiers in Public Health

Received 2020 Jan 11; Accepted 2020 Mar 16; Collection date 2020.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Understanding reciprocal relationships between specific arenas in life and at work is critical for designing interventions to improve workplace health and safety. Most studies about the links between dimensions of well-being in life and at work have been cross-sectional and usually narrowly focused on one of the dimensions of the work-life well-being link. The issues of causality and feedback between life and work well-being have often not been addressed. We overcome these issues by measuring six aspects of well-being for both the work arena and life in general, using longitudinal data with a clear temporal sequence of cause and effect, and by explicitly accounting for feedback with potential effects in both directions. Nine hundred and fifty-four Mexican apparel factory workers at a major global brand participated in two waves of the Worker Well-Being Survey. Data on life satisfaction and job satisfaction, happiness and positive affect, meaning and purpose, health, and social relationships in life and at work were used. Lagged regression controlling for confounders and prior outcomes was employed. Sensitivity analysis was used to assess the robustness of the results to potential unmeasured confounding. For the relationships between life satisfaction and job satisfaction and between happiness in life and happiness at work effects in both directions were found. Nevertheless, indication of a larger effect of life satisfaction on job satisfaction than the reverse was obtained. For depression and meaning in life, there was evidence for an effect of life well-being on work-related well-being, but not for the reverse. For social relationships and purpose, there was evidence for an effect of work-related well-being on life well-being, but not the reverse. Relationships based on the longitudinal data were considerably weaker than their respective cross-sectional associations. This study contributes to our understanding of the nature of the relationship between aspects of well-being in the arenas of life and work. Findings from this study may facilitate the development of novel workplace programs promoting working conditions that enable lifelong flourishing in life and at work.

Keywords: well-being in life, well-being at work, health, job and life satisfaction, happiness, meaning and purpose in life and at work, social relationships

Introduction

Although the influence of work on occupational health and safety has been long recognized ( 1 ), importance of work for well-being has been gaining scientific attention only recently ( 2 – 6 ). The impact of employee health on work has been traditionally examined through the lenses of physical and mental disabilities that limit chances for performing certain jobs ( 7 – 9 ). Recently the topic of worker well-being has been gaining attention in the field of occupational health. The United States Centers for Disease Control and Prevention's National Institute for Occupational Safety and Health (CDC/NIOSH) launched in 2011 the Total Worker Health® program that integrates protection against work-related and health hazards with promotion of injury avoidance and illness prevention to advance worker well-being ( 10 – 12 ). The World Health Organization introduced the Model for Action, which advocates for workers' health, safety and well-being on and off the job ( 13 ). Similar conceptual idea, highlighting the importance of achieving living and working conditions that enable people to engage and thrive at work over their lives, lies behind the concept of sustainable work over the life course which was introduced in the European Union to help people maintain health, develop skills and achieve financial security, work–life balance, meaningful work, and sense of self-fulfillment in the workplace ( 14 ). These worker well-being promoting initiatives emerge in labor market policies ( 14 ) and are subsequently integrated into companies' strategies ( 12 , 15 ).

We argue that understanding the reciprocal relationships between well-being aspects at work and in life is critical to design policies to improve not only workplace health and safety but also employee satisfaction and well-being. Unfortunately, studies about the links between dimensions of well-being in life and at work have been usually narrowly focused on one of the dimensions of the work-life well-being link and additionally—have been mostly cross-sectional making causal inference implausible. The aim of this paper is to offer a more holistic outlook of the relationships between well-being at work and well-being in life by evaluating reciprocal relationships between six dimensions of well-being (such as life satisfaction, happiness, meaning, purpose, mental health, and social relationships) and their work-related counterparts while considering the bi-directional effects between work and life for each of the dimensions over time. This perspective contrasts with numerous well-being studies that not only limit well-being to a single life-related measure but also conceal the role of work as a driver for human flourishing and disregard the value of promoting flourishing in life to enhance flourishing at work. Consequently, in this article we hypothesize that for each of the six dimensions, significant reciprocal relationship between well-being in life and well-being at work can be established. In other words, we test a hypothesis that well-being while at work positively influences well-being in life and well-being in life is beneficial for well-being while at work.

Literature Review

One of the most examined relationships between well-being and work has been the one between subjective well-being (SWB) 1 and job satisfaction ( 16 – 19 ). This relationship has been subject to scrutiny over the past decades, with early contributions dating back to the 1950's ( 20 ). Previous studies, however, identified only a modest to moderate association between SWB and job satisfaction ( 16 , 19 ). Limited evidence, however, is available for the relationship between other dimensions of well-being in life and their counterparts related to well-being at work.

Many existing studies are also hardly conclusive due to serious methodological limitations. Most of the studies have been based on cross-sectional study designs ( 18 , 21 ), which rendered it impossible to establish any causal link. Limited longitudinal research carried out so far mainly focused on the relationship between the broad concepts of life satisfaction and job satisfaction without delving into its constituents [see ( 16 ) for a review] or work-life conflict ( 22 , 23 ), avoiding a scrutinized study of other aspects of well-being in the arena of life and work.

Theoretical and empirical lack of agreement on the directionality of the relationship between well-being and work further complicates the interpretation and assessment of the findings ( 16 ). For instance, the part-whole theory ( 24 , 25 ) posits that specific aspects of life (e.g., work) influence well-being, whereas the dispositional approach ( 26 , 27 ) claims that it is well-being that has a causal effect on specific aspects of life (e.g., work).

Additionally, regarding the directionality of the relationship, a heated dispute arose between proponents of the spillover approach, advocating for a reciprocal, positive relationship between specific aspects of life (e.g., work) and well-being ( 16 , 28 ), the compensation approach, assuming that dissatisfaction in one sphere is compensated by search for enrichment in the other (thus envisaging a negative relationship), and the segmentalist approach, making a case for a lack of relationships between the two areas ( 29 ). Current evidence is thus inconclusive and thus all hypotheses about the cause and the effect remain plausible.

The conceptual and operational definitions of well-being in life and well-being at work have been refined more recently as well. The definitions shifted from early characterizations in broad affective terms to more articulate, conceptually sharper ones ( 30 ), which provide relatively robust and consistent frameworks necessary for a scientific analysis ( 16 ). For example, consideration of job and life satisfaction is now combined in notions of employee well-being ( 31 – 33 ) and more well-being interventions are proposed to ensure that workers are both happy (or high in well-being) and productive (have high performance) ( 34 , 35 ).

However, the nature of the work-life link is still unclear. Despite strong evidence provided by Bowling et al. ( 16 ) that the effects are bi-directional and life satisfaction affects job satisfaction more than job satisfaction affects life satisfaction, the issue of the direction of causality and strength of bi-directional relations between dimensions of well-being at work and well-being in life remains fundamentally open and unexplored. Although recent research has extended our contextual knowledge about the possible effects on the job-life satisfaction relationship [for example the effects of: burnout ( 36 , 37 ), positive affect or negative affect ( 19 , 28 ), job importance ( 38 ), work-family conflict ( 19 , 28 ), work-life balance ( 39 , 40 ), workplace friendship ( 41 , 42 ), job insecurity ( 43 ), and even geographical remoteness ( 44 )], a more comprehensive approach—as advocated also by Neve et al. ( 2 ) is needed. However, it is worth noting that a distinction between workplace well-being from general well-being has been recently recognized ( 33 ). Still, limited evidence on how particular aspects of general well-being affect their counterparts while at work and vice versa is available.

Consequently, this paper offers the following contributions in this relatively under-explored direction. First, by carrying out a longitudinal analysis it provides more robust evidence on the causal relationships between job and life satisfaction. Second, by studying in depth other aspects of well-being in the work and life sphere, such as happiness ( 45 ), meaning ( 46 ), purpose ( 47 ), mental health ( 48 ) and social relationships ( 49 ), our results provide an innovative framework for the analysis of the job vs. life dimensions of well-being studied in the literature as well as evidence for their causal directionality.

Materials and Methods

Data source and sample size.

The analysis builds on the first two waves of the Worker Well-Being Survey (WWBS), a tool designed to track workers' well-being, administered in the Levi Strauss & Co.'s supplier in Mexico. The first wave of the WWBS was administered in February 2017, and the second one in March 2018.

Workers completed surveys in a private space inside the factory on tablets either connected directly to secure servers via the internet or using an offline app. In this way, all information was kept confidential. During survey administration, groups of workers were released from their line positions (e.g., one production line at a time) to come to the survey stations. A communication campaign took place prior to survey activities to invite workers to participate in the survey. The results were reported in aggregate to workers and the factory after tabulation and analysis. The workers' decision to participate in the survey was voluntary and was not disclosed to management. All workers signed an informed consent. The study was approved by Harvard T.H. Chan School of Public Health Institutional Review Board.

Nine hundred fifty-four apparel workers participated in both waves of the WWBS. Descriptive statistics of the sample are presented in Table 1 . Data are available from the corresponding author upon request.

Descriptive characteristics of the sample.

In analyzing the relationships between life-related well-being factors and their job-related counterparts, we distinguished six aspects of well-being: (1) life satisfaction and job satisfaction, (2) happiness, (3) meaning, (4) purpose, (5) social relationships, and (6) mental health. Questions measuring the first five aspects originated from the flourishing index ( 50 – 52 ), while the question measuring health was adopted from the set of healthy days questions of the Health-Related Quality of Life instrument ( 53 ). For each well-being question a work-related counterpart was used. Specifically, questions from an adapted version of the Positive and Negative Affect Scale (PANAS) ( 54 ) referring to work domain, i.e., from the Job-Related Affective Well-Being Scale ( 55 ) were used, as well as a question about job satisfaction and meaning and purpose at work ( 56 , 57 ).

The full set of questions used to measure specific dimensions of well-being from both a life- and job-related perspective is presented in Table 2 . Table 3 presents descriptive statistics of the variables in the study. Correlation matrix of the measures is provided in Table A1 in the Appendix.

Job-related and out-of-job variables measuring well-being in life and well-being at work.

Descriptive statistics of the variables in the study.

Means and standard deviations are reported for variables measured on 0–10 response scale .

Control Variables

It has been empirically shown that relationship between well-being and job attitudes may be different depending on gender, age, and education ( 19 , 58 – 65 ) and together with job tenure, these variables are among the most commonly used as control variables in the organizational research ( 59 ). There is also evidence that marital status or having a family in general, especially in combination with a necessity of raising a child, is a discriminatory factor for happiness ( 66 ) and job attitudes ( 67 – 70 ). Similarly, caregiving to an elderly has a detrimental effect on well-being ( 71 , 72 ), health ( 73 ), and job satisfaction and other job attitudes ( 74 ). Additionally, there are theoretical foundations and supporting empirical evidence that job demand and job control correlate with mental health and job attitudes ( 75 , 76 ).

Consequently, in the analysis, we controlled for: (1) demographic variables: gender, age, marital status, education, having children below 18 at home, taking care of an elderly; and (2) job characteristics: job tenure, job demand (“I have too much work to do, to do everything well;” yes/no), job control (“I have a lot of say about what happens on my job;” yes/no), and work shift (day vs. otherwise).

In the longitudinal analysis, these variables were controlled at baseline in Wave 1, in order to ensure that they were confounders and not mediators. In the cross-sectional analysis, they were measured simultaneously with the exposure and outcome so as to compare results with the more rigorous longitudinal analyses.

Statistical Analysis

As the goal was to investigate a causal link between well-being in life and job-related well-being (i.e., how well-being in life influences job-related well-being and vice versa), longitudinal data was used and statistical approaches for modeling longitudinal data were employed. Contrary to analyses conducted on cross-sectional data, this approach offered more reliable causal evidence by virtue of the logical temporal sequence of cause and effect. However, as most of the empirical evidence in the field is based on cross-sectional data, we also ran secondary analysis on such kind of data, with the aim of assessing the level to which the relationship is inflated by the use of cross-sectional data.

The relationship was modeled using either linear regression model (for continuous outcomes), or logistic regression model (for dichotomous outcomes). With respect to dichotomous outcomes, odds ratios were reported; with respect to continuous outcomes, standardized regression estimates were provided to report standardized effect sizes.

The relationship between work-related well-being factors and their out-of-work well-being counterparts for continuous outcomes was modeled as follows:

and for dichotomous outcomes as follows:

where i = 1,…, N, k = 1,…,6 .

Subscript i represents an individual, the variable WBW indicates one out of six ( k = 1,…,6) work-related well-being factors, WBL is one out of six well-being in life factors. X is a vector of control variables including the first wave ( T = 1) outcomes. α 1 reflects effects of an out-of-work well-being factor on a well-being at work outcome and β 1 shows the effects of a well-being at work factor on a well-being in life outcome. α 2 shows the association between control variables and the well-being at work outcome, β 2 shows the association between control variables and a well-being in life outcome. η i and ε i are disturbance terms.

Robustness of the results was ensured by performing the sensitivity analysis ( 77 ) and through the design of the study's procedure to account for the common method bias ( 78 ). Sensitivity analysis was applied to assess the extent to which an unmeasured confounder would need to be associated with both the exposure and the outcome to explain away the observed association ( 77 , 79 ). To this end, the E -value, which is a continuous measure of how robust the association is to potential uncontrolled confounders, was applied. The E -value is the minimum strength of association on the risk ratio scale that an unmeasured confounder would need to have with both the outcome and the primary exposure or independent variable, above and beyond the measured covariates, in order to explain away the observed association ( 77 ).

Regarding the common method bias, we accounted for it through the design of the study procedure ( 78 ). Specifically, although it was not feasible to account for a common rater and a common measurement context (as it was of crucial importance to get data from the same persons being in the same measurement context), we proximally and methodologically separated predictor, and outcome variables. Specifically, these variables were located in different sections of the questionnaire and different response scales were used, e.g., 4-point Likert scales, number of days, intensity scales, 0–10 Likert type scales (see Table 2 ), with different scale endpoints, and different verbal labeling. Additionally, the research team strived to ensure anonymity of respondents and reduce evaluation apprehension by (i) providing the choice to participate in the study and (ii) ensuring that participation would affect neither the employment conditions nor the employment status. Moreover, (iii) respondent might choose to not respond to any question(s) and (iv) withdraw without penalty at any time. Appropriate information about (i–iv) was conveyed in the communication campaign and also added to the invitation letter. Finally, the follow-up visits to the factories were conducted 1, 3 and 6 months after the survey administration and the individual interviews with selected workers were conducted to make sure that the workforce was not negatively affected by the participation in the study.

Analyses were performed using Stata 15.

The strength of the relationships based on the longitudinal data, controlling for prior outcome ( Table 4 ), was found to be in each case weaker—and in the case of purpose and close social relationships also insignificant—than the strength of associations revealed from the cross-sectional analysis ( Table 5 ). This suggests that evaluations based solely on cross-sectional data could over-estimate the actual strength of the relationships, which is consistent with previous research about job satisfaction and subjective well-being ( 16 ).

Effect sizes (standardized estimates [std. est.] and odds ratios [OR]) and 95% confidence intervals (in parentheses) for the relationships between job-related well-being factors and their out-of-job counterparts—longitudinal results.

Each regression was controlled for: job control, job demand, gender, age, education, marital status, number of children, taking care of an elderly, job tenure, and work shift .

p < 0.05 ,

p < 0.01 ,

p < 0.001 .

Effect sizes (standardized estimates [std. est.] and odds ratios [OR]) and 95% confidence intervals (in parentheses) for the association between job-related factors and their out-of-job counterparts—cross-sectional results.

The effect size of the influence of life satisfaction on job satisfaction was found to be higher (0.14) than the effect size of the influence of job satisfaction on life satisfaction (0.09). Happiness in life was found to influence feelings of happiness at work and it was also the case that feelings of happiness at work influence happiness in life (effect sizes could not be directly compared as the former was assessed with an odds ratio scale and the latter with a standardized difference scale). Therefore, for both relationships—life vs. job satisfaction and happiness in life vs. at work—there is evidence that the causal relations are bi-directional, despite having different strength in the two directions. Additionally, in terms of absolute strengths, causal links in the happiness sphere turn out to be considerably stronger than those in the satisfaction sphere.

For the remaining variables, however, the evidence suggests that the causal relations may be unidirectional, with the actual links emerging from the life to the job sphere or the other way around, depending on the specific dimension. Depression was shown to increase the probability of feeling depressed at work, but reports of feeling depressed at work were not found to increase probability of feeling depressed in general. Similarly, meaning in life was found to have an impact on meaning in job, but the reverse relationship was not found to be significant. Conversely, feeling purposeful at work was found to increase purpose in life but not the other way around. We also found evidence that feeling close to people at work contributes to a sense of improved social connections in life; however, the reverse relationship was not supported by our results. We provide some further exploration of the potential reasons for these uni-directional associations in the discussion.

Sensitivity Analysis for Unmeasured Confounding

The E-values calculated for the longitudinal results ( Table 6 ) indicate that most of the estimated associations were relatively robust to unmeasured confounding, which provides some further evidence of causality for those outcomes. The influence of job satisfaction on life satisfaction, and the relationship in the opposite direction, were moderately robust to potential unmeasured confounding. Only an unmeasured confounder that would be associated with both job satisfaction and life satisfaction by a risk ratio of 1.383 (the effect of job satisfaction on life satisfaction) and 1.536 (the effect of life satisfaction on job satisfaction), above and beyond the measured confounders, could explain away the observed association between life satisfaction and job satisfaction; weaker confounding could not. Confounders associated with both the outcome and exposure by risk ratios of 1.5-fold to 2-fold each would be required to explain the relationship between life and job: happiness, purpose, meaning, and friends, also pointing to relatively strong evidence of robustness to confounding for the link between life and job-related outcomes. An even stronger confounder would be necessary to explain away the relationship between depression in life and depression at work. The strength of association of this hypothetical confounder would have to reach at least 4.664 in terms of risk ratios, with both depression at work and depression in life in the model; and even to reduce the 95% confidence interval to include the null would require an unmeasured confounder association with both depression in life and depression at work by risk ratios of 2.2-fold each having already adjusted for all measured confounders.

E -values for significant longitudinal effect measures and for corresponding CI limits.

E-values are reported only for significant estimates. E-values indicate the strength of unmeasured confounding that would be necessary to invalidate the observed relationship and thus are not of interest when the measured effect is not significant .

Discussion and Conclusions

The results contribute to our understanding of the nature of the relationship between job satisfaction and life satisfaction, as well as between other dimensions of well-being in life and well-being at work. Generally, job satisfaction and happiness, but also purpose, and social connections while at work were found to influence their out-of-job counterparts 1 year later. With regard to the reverse direction, life satisfaction and happiness, but also depression and meaning in life were found to influence the work-related counterparts 1 year later. Thus, only for life satisfaction and happiness was there an evidence for effects running in both directions, confirming our research hypothesis about the reciprocal benefits between well-being in life and well-being at work. Other relationships were more unidirectional but not always necessarily indicative of an impact of work on life—the directionality more often acknowledged in the literature.

Our results are in some ways intuitive, but nonetheless they call for further scrutiny. Regarding happiness and life satisfaction, causal links in the happiness sphere in absolute terms turn out to be significantly stronger than those in the satisfaction sphere. This may be due to the fact that happiness, as a construct, also includes elements of coping resources and positive emotions ( 80 ), potentially eliciting more immediate connections between the work and life spheres. However, the feedback loops we found are in line with the two competing theoretical models of well-being: the bottom-up (situational) model and top-down (dispositional) model ( 27 ). The bottom-up model of well-being assumes that well-being is a sum of small pleasures. This implies, in turn, that life satisfaction and happiness may be situational and thus influenced by job satisfaction and positive affect while at work, respectively. Instead, according to the top-down model, each person tends to experience things in a particular, positive or negative way, thus well-being is dispositional ( 81 ). This is reflected in the way in which all life experiences are perceived, and in particular this implies that well-being is projected onto other variables. Specifically, the impact of life satisfaction on job satisfaction and of happiness in life on happiness while at work are anticipated. Consequently, life satisfaction and happiness may be both the cause (as in the top-down model) and the effect (as in the bottom-up model) of job satisfaction and positive affect while at work, respectively. This conclusion has been already made by other scholars, based on empirical evidence ( 82 , 83 ) and on theoretical considerations conceptualized as the spillover model of well-being ( 18 , 84 , 85 ).

For depression, it was shown that depression in life increases the probability of feeling depressed at work, but reports of feeling depressed at work were not found to increase probability of feeling depressed in general. Depression in life is likely to manifest itself at work as its symptoms are neither temporarily limited to the periods spent out-of-work nor spatially confined to the non-working environment. However, depression at work may depend on very context-specific conditions that do not necessarily reflect a more general susceptibility to depression. In particular, the evidence on the effects of workplace stressors [e.g., prolonged job strain ( 86 , 87 ), increased job demand ( 88 , 89 ) and limited job control ( 90 , 91 )] on the development of depression is moderate but the level of exposure to stressors that seems to be generally needed to cause depression still requires further investigation ( 86 , 92 , 93 ).

Meaning in life was found to have an impact on meaning in one's job, but the reverse relationship was not corroborated. Thus, no support was found for the assertion by Steger and Dik ( 94 ), Duffy and Sedlacek ( 95 ), and Allan et al. ( 46 ) that meaning at work translates into greater meaning in life. Instead, our findings were in line with the top-down theory of subjective well-being ( 27 ) or the dispositional approach ( 26 , 27 ), according to which global well-being translates into domain-specific well-being.

Specifically, meaning refers to overall relatedness in a larger sense, such as coherence and significance of one's experiences, whereas, purpose mainly refers to pursuit and aspiration of certain ends ( 57 , 96 ). The one-directional causal links that we found seem to conform to intuition—with meaning, the more existential dimension, being driven by the life sphere, whereas purpose, the more goal-oriented dimension, being driven by the work sphere. This result appears to be in line with the findings of Steger and Dik ( 94 ), who report that both experiencing a calling and seeking life meaning are predictors of life meaning.

Similar to other studies ( 41 , 42 ), we also found evidence that feeling close to people at work contributes to improved social connection in life. This finding corroborates Rumens' [( 97 ), p. 1149] assertion that “workplace friendships contribute to human flourishing.” However, the reverse relationship was not supported by our results. This is again a result that conforms to intuition, as social connection at work will contribute to one's overall social well-being, but relationships outside of the workplace do not necessarily make workplace friendships any more likely. Additionally, social connection in the workplace may call for a more demanding social adaptation compared to the life sphere since, in the work environment, people have less control over the choice to associate with certain people or not, compared to their own out-of-work social environment, and the emotional control tasks in the former case are consequently more demanding ( 98 ). Additionally, it is natural that social relationships from work can spread (spill-over) into the life domain, while relationships from life are confined in the life domain. Despite recognition and effectiveness of word-of-mouth as a recruitment source ( 99 , 100 ), one cannot expect to be able to often influence the hiring decisions of one's employer based on non-work-related friendship.

In contrast to the majority of other studies, we used longitudinal data thus making a substantial adjustment for confounding and control for work and life characteristics, which are known to correlate with aspects of both well-being at work and well-being in life. Although cross-sectional analyses [both ours and those of other authors; see e.g., ( 19 )] suggest presence of moderate to strong bidirectional relationships, our longitudinal results provide evidence for potential effects in both directions, with effect sizes of roughly equal magnitude only for the relationships of life satisfaction-job satisfaction, and happiness at work-happiness in general/life. This confirms the findings of the meta-analysis of the relationship between job and life satisfaction conducted by Bowling et al. ( 16 ) on 11 (eight published and three unpublished) longitudinal studies, which may be more valid as they account for the logical and temporal sequence of cause and effect and for prior levels of outcomes. Moreover, our results here also suggest that only unidirectional effects exist concerning meaning, purpose, mental health, and social connectedness. Although the Worker Well-Being Survey was designed to target working adults and examine worker well-being, it must be also noted that our sample of Mexican manufacturing workers may reflect specific social conditions and cultural inclinations. Different samples, covering jobs with different characteristics and professional profiles, or taken in different geographical and socio-cultural contexts, might yield different results. The literature shows that cross-country variation in the dimensions, which are the object of this study, should be expected, with a possibly prominent role played by the local level of social capital ( 101 – 103 ). Likewise, work-related stress varies significantly across occupations ( 104 , 105 ), and therefore—although we controlled for job demand and job control, which are well-known correlates of work-related stress and burnout ( 75 , 76 )—one can expect this source of variation to affect the relationship between well-being at work and in life. Consequently, there should be caution as to the generalizability of our results, and more research for different job profiles and in different geographical contexts should be carried out to gain a deeper insight. To this end, in particular, relatively more research effort should be directed toward longitudinal rather than cross-sectional studies, in order to improve our understanding of the structure of the causal relations between the work and life spheres of the other related variables of interest.

Our study made use of observational data. Most of the results presented in this study proved to be relatively robust to potential unmeasured confounding beyond a considerable number of measured potential confounders already included in the analyses. Thus, the evidence for causality was further strengthened. However, the results may still be subject to unmeasured confounding by personality, core self-evaluations, such as self-esteem, self-efficacy, locus of control and emotional stability ( 106 , 107 ), as well as goal self-concordance ( 108 ). However, our sensitivity analysis indicates that, for an unmeasured confounder to explain the effect of the observed associations, it would have to be associated with both job-related and out-of-job well-being factors by a risk ratio equal in magnitude to at least 1.383, while in order to explain away the relationship between general depression and work-related depression an unmeasured confounder related to both measures of depression by more than four on the risk-ratio scale would be required.

We used two waves of data, which let us control for the baseline outcomes. However, future research should consider replicating the results using more waves of data to control also for the baseline exposure. Such analysis will provide further evidence for the robustness of our results.

Finally, in the analyses we relied on single item measures of well-being dimensions. Although it is a common practice to use multi-item measures in such a case, we argue that long instruments—despite the advantages of conceptual richness—are inferior to short instruments in studies focusing on a vast array of topics. Workers' well-being study measures well-being along with physical and psycho-social working conditions, work safety and occupational health, job burden, job autonomy, job resources, work-family conflict, and others. In such a setting, a less time-consuming instrument may be beneficial. By being short enough for practical use in the workplace, it facilitates company's efforts to improve the worker well-being ( 32 ). Criticism of short instruments—especially those with one item per domain—relates to elevated Type 1 and Type 2 error probabilities [see ( 109 )] for evidence in the personality studies). Yet, such instruments can still be found in psychology ( 110 , 111 ), educational psychology ( 112 ) and organizational behavior ( 113 ), among others. In the well-being field, it is worth noting that the United Kingdom Office for National Statistics—to avoid excessive costs and to enable widespread use—since 2011 includes a set of only four well-being questions in the UK National Survey ( 114 ).

In sum, we concede that work is just one arena to enhance well-being, however, given the amount of time spent at work across our lifetimes, seemingly a powerful one. Therefore, understanding the well-being ecosystem for impact areas and reciprocal relationships in life and at work is important to finding ways to intervene. Without this holistic view, the leverage points for optimizing well-being may be invisible or inadequate by an overemphasis or attribution to one sphere of influence only.

Data Availability Statement

The datasets generated for this study are available on request to the corresponding author.

Ethics Statement

The studies involving human participants were reviewed and approved by Harvard T. H. Chan School of Public Health Institutional Review Board. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

DW-B developed the study concept, contributed to data analysis and interpretation of the result, drafted the manuscript and approved the final version of the manuscript. PB contributed to data analysis and interpretation of the result, drafted the manuscript and approved the final version of the manuscript. PS contributed to interpretation of the results, drafted the manuscript and approved the final version of the manuscript. TV contributed to interpretation of the results, revised the manuscript and approved the final version of the manuscript. EM developed the study design, revised the manuscript and approved the final version of the manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

1 SWB is defined as either a cognitive or affective evaluation of life, and is usually assessed for life as a whole, or for specific facets (e.g., life at work).

Funding. This study was supported by the Robert Wood Johnson Foundation under the grant No. 74275 Building a Culture of Health: A Business Leadership Imperative and by the Levi Strauss Foundation under the grant Follow up of Well-being measures in Mexico, China, Cambodia, and Sri Lanka.

Zero-order correlation matrix of the variables in the study (at T = 1).

p < 0.001 ,

p < 0.05 .

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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 .

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Further reading

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Acknowledgements

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

Conflict of interest: The authors declare that they have no conflict of interest.

Data availability: The data that support the findings of this study are available on request from the corresponding author.

Compliance of ethical standard statement: The results reported in this manuscript were conducted in accordance with general ethical guidelines in psychology.

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Work–Life Balance: Definitions, Causes, and Consequences

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• First Online: 17 September 2022
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• Paula Brough 4 ,
• Carolyn Timms 5 ,
• Xi Wen Chan 6 ,
• Amy Hawkes 7 &
• Laura Rasmussen 7  

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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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