research paper about family conflict

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Antecedents and outcomes of work-family conflict: A mega-meta path analysis

Brian k. miller.

1 Department of Management, Texas State University, San Marcos, Texas, United States of America

Dawn Carlson

2 Department of Management, Baylor University, Waco, Texas, United States of America

K. Michele Kacmar

3 Department of Management, University of South Alabama, Mobile, Alabama, United States of America

Merideth Thompson

4 Department of Management, Utah State University, Logan, Utah, United States of America

Associated Data

All data can be found inside the paper in Tables ​ Tables1 1 and ​ and2 2 .

This study examines the mediating role of work-to-family conflict and family-to-work conflict between the Big Five personality traits and mental health thereby enhancing theoretical development based upon empirical evidence. Integrating Conservation of Resources theory with the self-medication hypothesis, we conducted a mega-meta analytic path analysis examining the relationships among employees’ Big Five traits, work-to-family conflict and family-to-work conflict, anxiety and depression, and substance use. We produced a ten-by-ten synthetic correlation matrix from existing meta-analytic bivariate relationships to test our sequential mediation model. Results from our path analysis model showed that agreeableness and conscientiousness predicted substance use via mediated paths through both work-to-family conflict and family-to-work conflict and sequentially through depression as well as through family-to-work conflict followed by anxiety. Extroversion and openness-to-experience had relatively weaker influences on substance use through work-to-family conflict, anxiety, and depression. Neuroticism was the strongest driver of the two forms of conflict, the two mental health conditions, and substance use. From this model it can be inferred that work-to-family conflict and family-to-work conflict may be generative mechanisms by which the impact of personality is transmitted to mental health outcomes and then to substance use when analyzed via a Conservation of Resources theory lens.

Introduction

The ever-growing body of research around work-to-family conflict began with the theoretical work [ 1 ] and has been followed by immense interest in its measurement, correlates, antecedents, and outcomes. Work-to-family conflict is a form of inter-role conflict where “participation in the work [family] role is made more difficult by virtue of participation in the family [work] role” [ 1 ] [p. 77]. Because employees face pressure from work and family simultaneously, demands in one role interfere with meeting the requirements in the other role thus resulting in conflict [ 2 , 3 ]. The definition implies a bi-directional feature of employees’ work and family lives, such that in some cases there is work-to-family conflict and in other cases it is family-to-work conflict [ 4 ]. This conflict is likely to have serious consequences for one’s roles in their family and at work.

With the development of valid instruments [ 2 , 5 – 7 ] research on the antecedents, correlates, and outcomes of work-to-family conflict (WFC) and family-to-work conflict (FWC) has grown in number and type. The important directionally different flow of conflict between these two major domains of life [ 8 ] results in WFC and FWC being only moderately positively correlated at .41 [ 9 ]. It is notable that work-family conflict takes unique bi-directional forms of WFC and FWC. The former is defined as when the work demands interfere with performing family responsibilities, while the latter is defined as when family demands interfere with the performance of work duties [ 4 ]. Examples of the former include work demands like forced overtime and dealing with rude customers. Examples of the latter include family demands like caring for sick children and marital strife. These two directions of conflict have enough unique variance to act as separate and stand-alone constructs because they only overlap by about 16% [ 9 ]. A large body of literature [ 2 , 5 , 9 ] has documented that WFC and FWC are theoretically distinct, are predicted by different factor, and result in different consequences [ 2 , 5 , 9 ]. Because these two forms of conflict often relate differently to other variables [ 10 , 11 ] such that they are not interchangeable.

The purpose of the current study is to link some antecedents of WFC and FWC with some outcomes of the two in a mediation model not previously examined. Although some primary studies have assessed the mediating role of WFC and/or FWC in some of these relationships, most focus on antecedents or on outcomes but not usually both. By our count there are at least 54 different antecedents and outcomes of WFC and/or FWC in published primary studies, many of which have been analyzed numerous times. This accumulation of the study of some of these relationships has led to meta-analyses of the relationships between WFC/FWC and variables such as personality traits [ 9 , 12 – 16 ], workplace policies [ 15 , 17 , 18 ], issues of home life [ 10 , 18 ], demographics [ 19 , 20 ], various forms of stress and strain [ 14 , 21 ], and psychological disorders and issues [ 22 ]. However, not every relationship examined in a WFC/FWC-based primary study has been meta-analyzed.

We assembled available meta-analytic effect sizes as a synthetic input correlation matrix to a path model that tests the mediating role of WFC and FWC in the relationship between personality and mental health tied together under one major theoretical framework. A synthetic matrix of all previously analyzed associations with WFC and FWC would require a 56-by-56 matrix consisting of 1540 unique off-diagonal meta-analytic effect sizes. The overwhelming majority of the cells of such a matrix have not been meta-analyzed. We integrate some of the loosely connected segments of the nomological network of WFC/FWC via our secondary use of meta-analytic data [SUMAD] [ 23 ] as we seek to connect some elements of the left hand side [i.e. antecedents] with other elements of the right hand side [i.e. outcomes] of the nomological network surrounding WFC/FWC. The advantage of our use of SUMAD in a path model is that it allows us to simultaneously examine numerous complex relationships based upon precise meta-analytic estimates of population parameters [ 23 ].

We make several contributions to the study of WFC using the theoretical framework of conservation of resources [COR] theory [ 24 ] supplemented by the self-medication hypothesis [Khantzian, 1987]. First, our model allows us to integrate the sometimes-disconnected fields of management, personality, clinical psychology, and public health based upon existing meta-analyses. Second, by applying COR theory [ 24 ], our study brings insight into WFC/FWC as a generative mechanism by which personality affects mental health. Third, by integrating COR theory [ 24 ] with the self-medication hypothesis [ 25 ] we empirically examine theoretical arguments in a nuanced, in-depth explanation of the mechanism underlying these relationships. Our study addresses this issue both theoretically and empirically by examining the sequential [serial] mediating effects of both WFC and FWC as well as two mental health disorders on the personality-substance use relationship. By providing scholars with a more comprehensive understanding of the proposed sequential mediating effects of WFC and FWC, we expand extant research and connect related but not often well-integrated areas of research. To be clear, there are likely a host of other mediators of the personality-to-mental-health relationship but the focus of this study is on the role of WFC/FWC.

Theoretical framework

Conservation of Resources [COR] theory [ 24 , 26 ], argues that individuals have a natural tendency to protect their valuable resources because their personal outcomes will be impaired if resource losses occur. There are four resources in COR theory: object resources, conditions, personal characteristics, and energy [ 24 ]. Personality traits are examples of personal characteristics that can aid stress resistance [ 24 , 27 ] and serve as key resources [ 24 , 27 – 29 ] in personal struggles. Specifically, self-discipline which is embodied in the personality trait of conscientiousness is a resource [ 27 ]. For example, a person high in conscientiousness may retreat and dig more diligently into their work duties as a response to distress and conflict at work. Compared with resources that are easily depleted such as energy and time, personality traits are examples of key resources that are theorized as relatively stable resources that “provide an explanation for why some people are better than others in coping with stressful circumstances” [p.550] [ 30 ]. Thus, certain personality traits can help one to cope effectively with challenging situations [ 31 ] such as incompatible work and family demands.

Personality plays a role in the allocation of one’s self to one’s problems and as such is likely to be relied upon as an antidote of sorts by persons experiencing conflict in the workplace. Because one’s resources are finite, individuals involved in multiple role requirements tend to experience substantial resource drain [ 1 , 32 , 33 ]. It is also well-known that personality predicts substance use [ 34 , 35 ] and the Big Five personality traits in particular [ 36 ] have a well-validated impact on substance use [ 37 – 39 ]. Unfortunately, the current literature presents a complex picture of these relationships. For example, neuroticism is consistently documented to be positively associated with substance use, but the other Big Five traits have been much less consistent in the prediction of substance use [ 38 , 40 – 44 ]. These inconsistent findings suggest the need for stronger theoretical links between the Big Five traits and substance use. In line with COR theory, we consider the Big Five traits as critical characteristics that impact employees’ WFC/FWC, which will further affect anxiety, depression, and substance use.

Nomological network

Left side of the nomological network.

The Big Five personality traits have been shown to influence both directions of conflict [ 12 , 45 , 46 ] and some traits play a preventive role in WFC [ 47 ]. Conscientious individuals tend to be determined, diligent, organized, and achievement-oriented [ 36 ]. The orderliness, self-discipline, and effectiveness of conscientiousness help employees effectively manage their time and simultaneous demands that arise between work and family domains, thereby triggering less WFC [ 46 , 48 – 50 ]. Agreeable individuals are cooperative, trusting, and soft-hearted [ 36 ] and are more likely to establish interpersonal bonds with colleagues and family members. These social connections help in handling work or family struggles and thus protect employees from possible conflict in either domain [ 12 , 51 ]. Openness-to-experience entails being creative, flexible, and open to new perspectives [ 52 ] and is likely to assist in problem solving or coping strategies for those who are facing simultaneous demands in both work and family roles, resulting in lower WFC. Extroverted individuals are talkative, sociable, and highly active [ 53 ]. Individuals with high extroversion normally perceive events positively [ 54 ] and are inclined to proactively look for specific solutions to challenges such as WFC [ 55 , 56 ]. Individuals with high agreeableness, conscientiousness, extroversion, and openness-to-experience deal better with the two-way demands of the work and family domains [ 46 , 55 ]. These four global traits are consistently negatively related to WFC.

However, neuroticism has an opposite effect on WFC and FWC compared to the other four traits. Neuroticism consists of the tendency to have low self-esteem, irrational perfectionist beliefs, and inferior emotional adjustments such as pessimismand being temperamental [ 54 , 57 ]. Individuals with high neuroticism are vulnerable to experiencing emotional turmoil and encounter negative life experiences [ 58 ]. Moreover, neurotic employees are more likely to feel worried or focus on negativity [ 59 ], leaving them with less of the calm and resilience that are necessary to accomplish their mutual work and family demands 59. Because this Big Five trait plays a role in maladaptive thoughts and behavior [ 60 ], neuroticism is positively related to WFC/FWC.

Right side of the nomological network

Work-family conflict has been found to affect anxiety and depression [ 47 , 61 – 65 ]. Such conflict results in “a negative state of being” (p. 355) [ 32 ], often manifesting itself in these two psychological disorders [ 14 , 63 , 66 , 67 ]. Anxiety in this study refers to clinically diagnosed generalized anxiety disorder (GAD), often characterized by excessive fear or worry that interferes with one’s daily activities [ 68 ]. Depression in this study refers to clinically diagnosed major depressive disorder (MDD), a common medical illness with the symptoms of profound sadness and loss of interest that negatively affect how one feels, thinks, and acts [ 68 ]. There is a well-documented body of research on the relationship between WFC/FWC and both anxiety and depression [ 14 , 47 , 63 , 64 , 69 – 72 ] supporting the notion that that both WFC and FWC are positively related to anxiety and depression.

Conflict at work or home also positively relates to employees’ substance use [ 66 , 70 , 73 – 76 ]. The United State loses more than $400 billion annually in low work productivity, absenteeism, increased health care expenses, law enforcement, and criminal justice costs [ 77 ] because of the use of psychoactive substances such as alcohol and illicit drugs [e.g., steroids, cannabis, stimulants, opioids, sedatives, and hallucinogens]. There were 19.7 million American adults engaged in substance use in 2017 [ 78 ]. The prevalence of substance use in the United States is both detrimental and costly to organizations [ 79 , 80 ] and therefore the importance of understanding factors that predict substance use cannot be understated. In this study, substance use refers to an excessive use of alcohol and/or a sub-clinical level of use of illicit drugs and/or abuse of prescription medication, none of which could be considered severe enough to rise to the level of a substance use disorder but all of which are likely to cause problems with one’s family life or work or both. We suggest that the self-medication hypothesis [ 25 , 81 ], which proposes that individuals sometimes attempt to alleviate the anxious or depressive symptomatology through the use of illicit substances [ 82 , 83 ], can help integrate these three outcomes of WFC/FWC still under the heading of COR. In sum, when individuals are at a resource loss state [depression and anxiety] they look to other resources (substances) to fill that void as a considerable number of studies have generally supported a positive relationship between anxiety, depression, and substance use [ 84 ]. For purposes of simplicity we hereafter refer to anxiety, depression, and substance use simply as mental health outcomes except when referring to specific hypotheses or model linkages or to properly differentiate them from each other or from other aspects of mental health.

Simple mediation

In our overall test of the model, we focus on WFC and FWC as simple mediators of the relationships between personality with anxiety and depression as well as a sequential mediator in the relationship between personality, WFC/FWC, anxiety/depression, followed by substance use. Consistent with COR theory, the interference between work and family reflects resource depletion, as the time, strain, and behavioral interferences from one role drain the resources needed to complete duties in the other role [ 2 , 24 , 26 , 32 ]. Negative strain can take the form of anxiety and depression [ 64 , 69 , 75 ]. In particular, the personality traits of agreeableness, conscientiousness, extroversion, and openness-to-experience help employees effectively utilize their other resources [ 24 , 27 , 30 ] to manage the interference of WFC/FWC [ 12 , 45 , 59 ]. The reduced conflict further decreases the occurrence of psychological disorders such as anxiety and depression [ 62 , 63 ]. In contrast, employees with high neuroticism experience higher conflict, due to the fact that they are low in critical personal resources such as self-esteem and calmness that are needed to handle stressful role demands in work and family domains. Consequently, the higher level of WFC/FWC impairs employees’ well-being [ 24 ] by yielding higher levels of anxiety and depression. Thus, work-to-family and family-to-work conflict are generative mechanisms by which the influence of personality is linked to anxiety and depression. These arguments lead to our first set of hypotheses:

• Hypotheses 1a-d : Work-to-family conflict mediates the negative relationship between the Big Five traits of (a) agreeableness , (b) conscientiousness , (c) extroversion , and (d) openness-to-experience and anxiety .
• Hypothesis 1e : Work-to-family conflict mediates the positive relationship between the Big Five trait of (e) neuroticism and anxiety .
• Hypotheses 2a-d : Family-to-work conflict mediates the negative relationship between the Big Five traits of (a) agreeableness , (b) conscientiousness , (c) extroversion , and (d) openness-to-experience and anxiety .
• Hypothesis 2e : Family-to-work conflict mediates the positive relationship between the Big Five trait of (e) neuroticism and anxiety .
• Hypotheses 3a-d : Work-to-family conflict mediates the negative relationship between the Big Five traits of (a) agreeableness , (b) conscientiousness , (c) extroversion , (d) openness-to-experience and depression .
• Hypothesis 3e : Work-to-family conflict mediates the positive relationship between the Big Five trait of (e) neuroticism and depression .
• Hypotheses 4a-d : Family-to-work conflict mediates the negative relationship between the Big Five traits of (a) agreeableness , (b) conscientiousness , (c) extroversion , and (d) openness-to-experience and depression .
• Hypothesis 4e : Family-to-work conflict mediates the positive relationship between the Big Five trait of (e) neuroticism and depression .

The self-medication hypothesis [ 25 , 81 ] suggests that persons experiencing high anxiety or depression tend to engage in substance use, which serves a self-medicating role for reducing psychological disorders [ 84 – 86 ]. Building on COR theory [ 24 , 26 ] and the self-medication hypothesis [ 25 ], we contend that the psychological disorders of anxiety and depression mediate the relationship between WFC/FWC and substance use. That said, the inter-role conflict between work and family domains reflects resource depletion, with the resource drain in one domain leaving fewer resources needed to fulfill the requirements in the other domain [ 32 ]. The resource loss may generate strains in terms of higher levels of anxiety and depression to employees [ 14 , 65 , 70 , 75 ]. In turn, anxious or depressive employees are more likely to self-medicate with substances to reduce the symptoms of anxiety and depression [ 84 ]. At least two studies have previously suggested the sequential linkage from WFC to psychological disorders to substance use. For example, in a conceptual model regarding WFC and health outcomes, it was proposed that negative emotions (prevalent to both anxiety and depression) mediated the relationship between two directions of WFC and unhealthy behaviors such as substance use [ 47 ]. Work-to-family conflict was found to be positively associated with overall emotional distress, which further resulted in increased weekly alcohol consumption [ 76 ]. We suggest that anxiety and depression act as generative mechanisms by which the impact of work-to-family and family-to-work conflict are transmitted to substance use. Therefore, we next propose that:

• Hypothesis 5a-b : (a) Anxiety and (b) depression simultaneously mediate the positive relationship between work-to-family conflict and substance use .
• Hypothesis 6a-b : (a) Anxiety and (b) depression simultaneously mediate the positive relationship between family-to-work conflict and substance use .

Sequential mediation

Substance use can be partially explained by the sequential mediating effects of personality, WFC, FWC, and the psychological disorders of anxiety and depression. Guided by COR theory [ 24 , 26 , 27 , 87 ], we expect that individuals with high levels of the personality traits of agreeableness, conscientiousness, extroversion, and openness-to-experience will be able to effectively address the simultaneous pressures from work and family domains that are mutually incompatible [ 88 ], leading to a lower level of WFC and FWC [ 46 ]. In turn, employees with lower WFC and FWC are less likely to suffer anxiety or depression [ 63 ], which reduces the occurrence of substance use [ 81 ]. Conservation of resources theory [ 24 , 26 ] and the self-medication hypothesis [ 25 ] help explain the indirect effect between neuroticism and substance use. Neuroticism consists of characteristics such as insecurity, tension, and emotional instability that lead employees to be internally worried and made vulnerable by the stress of incompatible work and family demands [ 89 ]. The inefficiency of resource usage for coping with work and family challenges leads to a high level of WFC, which further increases the levels of anxiety or depression, as the stress of WFC gives rise to negative mental health consequences [ 75 ]. The sequential psychological resource loss, represented by anxiety or depression, may ultimately increase substance use [ 84 , 90 ] as employees tend to adopt illicit substance use to alleviate their psychological disorders [ 81 ]. In this sequence of effects, WFC/FWC, anxiety/depression sequentially mediate the relationship between personality and substance use. Lastly, we propose the following hypotheses:

• Hypotheses 7a-d : Work-to-family conflict followed by anxiety sequentially mediate the negative relationship between the Big Five traits of (a) agreeableness , (b) conscientiousness , (c) extroversion , (d) openness-to-experience and substance use .
• Hypothesis 7e : Work-to-family conflict followed by anxiety sequentially mediate the positive relationship between the Big Five trait of (e) neuroticism and substance use .
• Hypotheses 8a-d : Family-to-work conflict followed by anxiety sequentially mediate the negative relationship between the Big Five traits of (a) agreeableness , (b) conscientiousness , (c) extroversion , (d) openness-to-experience and substance use .
• Hypothesis 8e : Family-to-work conflict followed by anxiety sequentially mediate the positive relationship between the Big Five trait of (e) neuroticism and substance use .
• Hypotheses 9a-d : Work-to-family conflict followed by depression sequentially mediate the negative relationship between the Big Five traits of (a) agreeableness , (b) conscientiousness , (c) extroversion , (d) openness-to-experience and substance use .
• Hypothesis 9e : Work-to-family conflict followed by depression sequentially mediate the positive relationship between the Big Five trait of (e) neuroticism and substance use .
• Hypotheses 10a-d : Family-to-work conflict followed by depression sequentially mediate the negative relationship between the Big Five traits of (a) agreeableness , (b) conscientiousness , (c) extroversion , (d) openness-to-experience and substance use .
• Hypothesis 10e : Family-to-work conflict followed by depression sequentially mediate the positive relationship between the Big Five trait of (e) neuroticism and substance use .

Analytic technique

Typically, primary meta-analyses are on a few bivariate effects size at a time [ 91 ] although the development of meta-analytic structural equation modeling (MASEM) [ 92 , 93 ] has greatly aided in the understanding of how a cascade of variables relate to each other. Despite many primary studies on WFC/FWC using many different theoretical frameworks to explain the same relationship and certainly to explain different relationships even within the same primary study, we focus our analysis only on those model relationships that can be unified under COR theory as supplemented by the self-medication hypothesis and, of course, on relationships which are actually available as published meta-analyses. We refer to our approach as a mega-meta path analysis to differentiate it from a second-order or meta-meta-analysis that synthesizes two or more existing meta-analyses of the same bivariate relationship [ 94 , 95 ]. Ours is one of the first to rely exclusively on other researchers’ meta-analytic correlations rather than some primary study correlations of our own or of others combined with some meta-analytic correlations of our own or of others that are assembled into one complete input matrix suitable for analysis. To our knowledge, only one study [ 96 ] has assembled a synthetic correlation matrix solely from prior published meta-analyses to compare the predictive validity of different matrices on the same model.

Other researchers have assembled partial input correlation matrices from existing meta-analyses to supplement their own primary study effects or their own meta-analyses of other variable relationships. Several studies [ 17 , 97 – 99 ] have conducted meta-analyses for some cells in a correlation matrix and then supplemented missing cells not meta-analyzed in their own study with previously published meta-analytic correlations from other studies to test a path model. Others [ 15 ] filled their missing cells in their own primary single-sample study input matrix with meta-analytically derived correlations from other studies to test their model. The major advantage of our mega-meta analytic path analysis is that it allowed us to test a theoretical model not previously tested in any primary study [ 100 ]. Minor advantages include the fact that the bivariate components of the input matrix are: (1) based upon very large collective sample sizes, (2) based upon a large number of primary published studies, and (3) are sample size weighted and corrected for unreliability.

This required the construction of a 10-by-10 synthetic correlation matrix [ 96 ] with 45 unique off-diagonal meta-analytically derived correlations to be used as input to a structural equation modeling test. In some cells of the input matrix, more than one meta-analysis had been conducted on the same bivariate relationship which both facilitated and complicated the secondary use of meta-analytic data (SUMAD) [ 23 ]. The taxonomy of SUMAD [ 23 ] suggests that our use is a variation of the Type 4 variety which is a full-information MASEM (FIMASEM) [ 95 ]. The Type 4 variety addresses effect size heterogeneity or the variability in true score correlations in a population [ 101 ] by using bootstrapped samples built off of the cell correlation values and the standard deviation of those meta-analytic correlations to produce 80% credibility intervals for the paths and fit indices. However, it is implied [ 23 ] that both Type 3 which is a traditional MASEM [ 93 ] and Type 4 assume that only one meta-analytic correlation is available for each cell of the input correlation matrix. In most cases we have more than one meta-analysis per cell. However, in a simulation study [ 102 ] the FIMASEM technique [ 95 ] "…showed that bootstrap credibility intervals (CVs) work reasonably well, whereas test statistics and goodness of fit indices do not" thereby making the comparison of alternative models difficult. The focus of our study is on model fit as we seek to theoretically integrate rarely connected fields of research using prior validated bivariate relationships. Our study addresses effect size heterogeneity by capitalizing on the aforementioned complication of more than one meta-analytic value being available for most of the synthetic input matrix cells and therefore using MASEM on multiple permutations of our input matrices. The model tests are not nested within other models but rather the different meta-analytic input matrices allow us to test the same model with a variety of heterogenous meta-analytic correlations. The availability of different input matrices serves as a variation of the FIMASEM technique [ 95 ] such that we can compare input matrices that are known to be different rather than different models using the same singular input matrix for which the technique was designed [ 95 ] and which requires the standard deviations of the correlation cell values to produce bootstrapped results.

Literature search

To collect meta-analytically derived correlations, we searched three online databases (PsychInfo, ABI-Inform, and Web of Science) for meta-analyses of each of the necessary 45 bivariate relationships. We used the search term strings of "meta-analy* OR quantit* rev*" combined with variations of keywords like "work-family conflict," "work-family conflict," "WFC," "family-work conflict," "family work conflict," "FWC," "Big Five," "Five Factor model," "FFM," "conscientiou*," agreeabl*," "neuroti*," "emotional stab*," "openness-to-experience," "openness," "extraver*," "extrover*," "introver*," "anxiety," "anxious*," "depres*," "substance use," and "substance abuse." The search effort uncovered 5859 unique possible meta-analyses. After the removal of 1039 duplicates from the three databases there were 5253 articles that remained eligible for screening.

Article inclusion criteria

To be included in our study a meta-analysis had to meet four criteria: (1) it must have been written in English, (2) it had to be published in a peer reviewed scholarly journal, (3) it had to be a meta-analysis and not a primary study, and (4) it had to have reported an effect size for at least one of the 45 unique relationships necessary for our correlation matrix input. Three meta-analyses used the same unpublished dissertation [ 105 ] for their meta-analytic intercorrelations between the Big Five traits [ 109 – 111 ]. After coding them and comparing them to the dissertation [ 105 ] it was determined that all three correctly reported those correlations. In order to avoid duplication, the dissertation [ 105 ] was added to the coded studies list and the three published articles were removed. After all screening was completed, 12 meta-analyses were coded to fill 45 cells with 75 coded effect sizes. We used a PRISMA flow chart [ 112 ] to guide our collection of studies to code ( Fig 1 ).

The steps below were used to identify and select studies for coding.

Meta-analytic coding

The meta-analytic data extracted for analysis included: (1) type of corrected effect size (e.g. ρ , r , d , odds ratio [OR]), (2) corrected bivariate effect size, (3) total sample size reported [i.e. n ] in the meta-analysis, and (4) total number of independent samples reported (i.e. k ) in the meta-analysis. Eleven of the 45 cells were cross-coded by two of the authors. After a number of coding trials completed side-by-side, interrater agreement was perfect (See Table 1 for the coding results). The remaining 34 cells were then evenly split between the authors.

a Either converted from odds ratios or d -statistics.

Effect sizes reported in meta-analyses as Cohen’s d -statistic or as OR required transformation to correlations. Transformation from d to r is commonplace but from OR to r is not as straightforward. When the case/treatment and control groups are dissimilar in size, as they were in the meta-analyses coded here, it is recommended [ 113 ] that the values be transformed as an approximation of the tetrachoric correlation [ 114 ] which is preferred over a Pearson transformation [ 115 ] which requires equal marginal probabilities. Alas, none of the studies that computed meta-analytic effect sizes as odds ratios reported their outcomes as continuous variables, or had similar size samples in the cells of the contingency table, or had equal marginal probabilities so the OR values were transformed into an approximation of the tetrachoric correlation using the formula [ 114 ] below:

Creation of correlation matrices for input

As can be seen in the online supplementary materials, the 45 unique off-diagonal cells of the matrix had between 1 and 3 meta-analyses each that were coded. Thus, we had an impossibly large 120,932,352 different possible permutations of the input matrix. We ran three different matrices comprised of meta-analytic correlations that were not just a randomly assembled set of correlations serving as one of the over 120 million possible combinations. Our matrices were purposeful and were (a) the most recent meta-analyses in the cells under the assumption that these would be the most comprehensive, (b) the meta-analyses that had the largest individual number of subjects or largest n in each cell, and (c) the meta-analyses that had the largest number of samples used or largest k per cell. The other potentially viable but randomly assembled candidates of possible input matrices were not examined here. Because the model input effect sizes for the relationship between anxiety and substance use and between depression and substance use were meta-analyzed on longitudinal data some inference of causality can be inferred for these two pairs of variables. Personality is omnipresent, conflict is not usually episodic, and mental disorders usually take time to develop so they all tend to co-occur and temporal precedence is difficult to establish between them. However, our model and data imply that anxiety and depression temporally precede substance use thus lending some causality to an otherwise correlational model.

Data analysis

The hypothesized model in Fig 2 was tested using each of the three aforementioned correlation matrices as input to Mplus 8.2 SEM software [ 116 ]. The maximum likelihood estimator function was used on the summary data. Unstandardized paths were not computed because the use of correlations without standard deviations or means for model variables served as the data input. Following well-known recommendations [ 93 ], the harmonic mean was used to determine the sample size of each of the three input matrices. Bootstrapping was used to estimate confidence intervals around path coefficients. The disturbance terms for work-to-family conflict and family-to-work conflict were allowed to correlate. Separately, the disturbance terms for anxiety and depression were also allowed to correlate. We then evaluated the indirect effects by constructing bias-corrected 95% confidence intervals [ 117 , 118 ].

The model of some antecedents and outcomes of work-family and family-work conflict.

The input matrix comprised of the most recently published meta-analytic correlations using the harmonic mean of 8942, shown in Table 2 , yielded better fit [χ 2 = 744.69***, df = 7, SRMR = .04, CFI = .93, RMSEA = .109 [90% C.I. = .102; .115] than the models run on the two other input matrices using different respective harmonic means [model with meta-analytic largest n : χ 2 = 2769.49***, df = 7, SRMR = .06, CFI = .84, RMSEA = .183 [90% C.I. = .177; .189] and the model with meta-analytic largest k : χ 2 = 2506.86***, df = 7, SRMR = .07, CFI = .85, RMSEA = .177 [90% C.I. = .171; .183] and was the focus of further analysis. The SRMR indicates excellent fit [ 119 ], the CFI indicates good fit [ 120 ], and the RMSEA shows poor fit [ 121 ] for the model using the most recent meta-analytic correlations as input. Overall, that model ran can be said to show adequate fit to the data and better fit than the models run on the other two input matrices. The fit indices and path coefficients detailed below are likely to be quite robust in that the average number of studies used in the meta-analyses in each cell was 20.56 thus exceeding the minimum recommendation of 10 per cell [ 91 ].

a Correlations are on bottom left side of matrix below the diagonal and standard deviations are on top right side above the diagonal. Harmonic mean = 8942. All non-zero correlations are significant at p < .001.

In post hoc tests using the FIMSEM technique [ 95 ] on our best fitting input matrix, which required the correlation matrix as well as the standard deviation matrix, we ran 500 bootstrapped samples. We found that the bootstrapped path coefficients were close approximations of our model test but that the fit indices were not reproduced well [ 102 ] nor were they meaningful. The interested reader can use the correlations and standard deviations in Table 2 to reproduce these FIMASEM results.

Simple mediation results

Hypotheses 1 through 6 predicted simple mediation. Results for these tests can be found in Table 3 . Hypotheses 1a through 1e all involved WFC as a mediator between each of the Big Five traits and anxiety. Because the path between WFC and anxiety was .00, the indirect paths from these traits through WFC to anxiety were also .00. Therefore, none of these five hypotheses were supported.

Note : WFC = work-to-family conflict; FWC = family-to-work conflict; CI = confidence interval.

***p < .001.

Hypotheses 2a through 2e all involved FWC as a mediator between the Big Five traits and anxiety. Hypothesis 2a, that FWC mediates the linkage from agreeableness to anxiety and was supported. Hypothesis 2b, that FWC mediates the linkage from conscientiousness to anxiety also was supported. Hypotheses 2c and 2d, about extroversion and openness respectively, were not supported. Finally, Hypothesis 2e, that FWC mediates the linkage from neuroticism to anxiety was supported.

Hypotheses 3a through 3e all involved WFC as a mediator between each of the Big Five traits and depression. Hypothesis 3a, that WFC mediates the linkage from agreeableness to depression was supported as was Hypothesis 3b about the linkage from conscientiousness to WFC to depression. and. Hypotheses 3c about extroversion was not supported nor was Hypothesis 3d about the linkage from openness to WFC to depression because the direct of the effect was opposite that predicted. Finally, Hypothesis 3e about the linkage from neuroticism to WFC to depression was supported.

Hypotheses 4a through 4e all involved FWC as a mediator between the Big Five traits and depression. Hypothesis 4a, which predicted a mediating effect of FWC for the agreeableness to depression relationship, was supported as was Hypothesis 4b, that predicted a mediating effect of FWC for the conscientiousness to depression relationship. Hypotheses 4c [extroversion] and Hypothesis 4d [openness] were not supported. Finally, Hypothesis 4e, which predicted a mediating effect for FWC for the neuroticism to depression relationship, was supported.

Hypotheses 5a and 5b were about the linkage from WFC through anxiety and depression, respectively, to substance use. Because the path between WFC and anxiety was .00, Hypothesis 5a was not supported. However, the indirect path through depression was significant offering support for Hypothesis 5b. Hypotheses 6a and 6b were about the linkages from FWC through both anxiety and depression to substance use. The indirect effects through anxiety and depression on the relationship between FWC and substance use were both significant providing support for Hypotheses 6a and 6b.

Sequential mediation results

The results for our tests of sequential mediation for Hypotheses 7a-10e can be found in Table 4 . Hypotheses 7a-e predicted sequential mediation between each of the Big Five personality traits one at a time and substance use through WFC and anxiety. None of these indirect effects were significant as the path between WFC and anxiety was .00, so Hypotheses 7a-e were not supported. Hypotheses 8a-e predicted sequential mediation between each of the Big Five personality traits one at a time and substance use through FWC and anxiety. Hypothesis 8a (agreeableness), 8b (conscientiousness), and 8e (neuroticism) were all supported. However, Hypotheses 8c (extroversion) and 8d (openness) were not supported. Hypotheses 9a-e predicted sequential mediation between each of the Big Five personality traits one at a time and substance use through WFC and depression. The hypotheses for agreeableness (9a), conscientiousness (9b), and neuroticism (9e) were all supported while Hypotheses 9c (extroversion) was not. Although significant results were found for Hypothesis 9d (openness), the indirect effect was not in the predicted direction and the confidence interval contained zero, therefore Hypothesis 9e also was not supported. Finally, Hypotheses 10a-e predicted sequential mediation between each of the Big Five personality traits one at a time and substance use through FWC and depression. These results followed the same pattern as the sequential mediation for anxiety and FWC in that Hypothesis 10a (agreeableness), 10b (conscientiousness), and 10e (neuroticism) were all supported while Hypotheses 10c (extroversion) and 10d (openness) were not. See Fig 3 for the statistical results of the mega-meta path analysis model test.

Path coefficients resulting from mega-meta path analysis. Note . Values in parentheses indicate direct paths from each trait to work-to-family conflict, depression, anxiety, and family-to-work conflict in that order. Paths > .020 are statistically significant. For clarity, the intercorrelations between the Big Five traits and the correlations between the disturbance terms for the endogenous variables are omitted.

a CI = confidence interval.

b WFC = work-to-family conflict.

c FWC = family-to-work conflict.

The goal of our study was to test part of the nomological network of WFC and FWC via a simultaneous investigation of some of their antecedents and outcomes that integrated the loosely connected fields of management, personality, clinical psychology, and public health research. Specifically, we examined the antecedent role of the Big Five personality traits in the prediction of the maladaptive behavior of substance use through the sequential mediation of WFC, FWC, clinical anxiety, and clinical depression. Consistent with COR theory [ 24 ], we hypothesized and found meaningful sequential mediation effects among the personality traits of agreeableness, conscientiousness, and neuroticism, with both WFC and FWC, and depression in the prediction of substance use. As expected, the results suggest that agreeableness and conscientiousness are key resources that one can utilize to reduce the incompatible role conflict between work and family domains [ 49 , 51 ], resulting in lower depression and further mitigating substance use. On the other hand, neuroticism greatly hinders one’s use of resources that then increase the propensity for WFC/FWC as well as contributes to depression and substance use. Due to dysfunctional emotional adjustments, sensitivity, and vulnerability to negative experiences [ 54 , 59 , 89 ], neurotic employees have fewer resources with which to manage incompatible work and family demands [ 46 ], leading to higher WFC, which in turn increases depression and substance use.

Regarding the mediating role of anxiety, family-to-work conflict but not work-to-family conflict, was a significant mediator linking agreeableness, conscientiousness, and neuroticism with anxiety and substance use. This is probably because of the different contexts of work-to-family conflict and family-to-work conflict. As work-to-family conflict is the interference from work into the family domain (e.g., having to reply to emails or work on projects during family time) that may require additional contextual resources, such as family member support [ 122 ] and supervisor support [ 16 ], to lower the levels of anxiety and substance use. As for neuroticism, the findings demonstrate that its indirect effect on substance use is channeled through work-to-family conflict, family-to-work conflict, anxiety, or depression to impact substance use. Moreover, our findings indicate that extroversion and openness-to-experience have weak or nonsignificant effects on substance use through WFC and anxiety or through depression. Taken together, this study suggests that personality, as a stable key resource [ 29 ], can facilitate or hinder WFC/FWC and mental health. Positive, or adaptive, traits like agreeableness and conscientiousness provide strength to overcome conflict in life and work. Negative, or maladaptive, traits like neuroticism detract from one’s ability to weather the storm of conflict and play a direct role in increasing conflict and mental health disorders. For some employees, adaptive traits can serve as a reliable buttress to the struggles of life at work and at home and the sometimes-inevitable blurring of the boundaries between the two.

Study strengths, limitations and future directions

This study has several strengths. First, we used large sample sizes based upon meta-analyses of hundreds of different primary published studies thus helping ameliorate second order sampling error. The overall number of participants in the meta-analyses of the relationships used to create our best fitting input correlation matrix was 1,213,933. However, it is likely that some participants were counted more than once as some correlations in each input matrix came from the same study and presumably were calculated from the same primary study participants. Second, most of the meta-analytically derived correlations were corrected for attenuation by the original meta-analysts thus more closely approximating population parameters. Third, the meta-analyses were collected from many top journals covering general psychology, general management, organizational behavior, human resource management, clinical psychology, and epidemiology. Finally, using COR theory [ 24 ], in conjunction with the self-medication hypothesis, we were able to theoretically integrate the left-hand side (i.e. antecedents) with the right-hand side (i.e. outcomes) of the WFC/FWC network that are usually explored separately. Integrating these seemingly disparate meta-analytic correlations from different fields of study serves as an effective comprehensive explanation for the modeled relationships. These strengths lend credibility to the findings reported here.

Our study is not without limitations. The socio-demographic variables such as type of work and organizational tenure related to work were not, and largely could not be, included in the study. The body of literature around the relationship between them and WFC/FWC is growing but meta-analyses do not exist for most work-related socio-demographic variables with WFC/FWC and definitely do not exist for the relationship between them and the two disorders and substance use. Like with meta-analyses in general there are many judgment calls [ 123 ] with which to contend when using a mega-meta path analytic framework. For example, we are limited by the way other scholars coded their variables in their meta-analyses. Given that some variables may have been dichotomized or truncated in other ways, future primary study researchers could include more nuanced measures of anxiety and depression, thus providing more accurate meta-analytic insights. Additionally, the use of discrete categories to describe mental disorders likely attenuated some model relationships. If only the severest of cases can be categorized as clinically anxious or depressed, then the relationship between these disorders and the other variables in the model were likely weaker here than they could be if anxiety and depression were measured on continuous scales. Thus, our model may actually underreport the strength of these relationships. We were also not able to test some seemingly logical model relationships because published meta-analyses could not be found between all such variables. For example, although we focused on the clinical forms of depression and anxiety we could not include substance use disorder in our model because meta-analyses do not exist between that construct and all nine other variables in our model. Instead we focused on sub-clinical substance use because that is what was available.

The mega-meta path analytic technique can be limited by the availability of existing meta-analyses. Another potential weakness is that of effect size heterogeneity [ 101 ] in that there were quite a range of meta-analytic values reported for the same relationship in different meta-analyses. For example, one meta-analysis [ 41 ] reported an odds ratio between agreeableness and substance use that was transformed into a correlation of .03. For that same relationship, another meta-analysis [ 38 ] reported a d -statistic that was transformed into a correlation of -.27. The heterogeneity of these effect sizes suggests one other related limitation: the transformation of odds ratios is only an approximation of a tetrachoric correlation and not a direct Pearson correlation of continuous measures. Additionally, we only tested three of the over 120 million possible permutations of the input correlation matrix that were possible. It is highly likely that more than one of the other possible matrices would fit our model even better than those which we tested.

Conclusion and practical implications

In conclusion, we designed this research to connect some of the antecedents and outcomes of the nomological network surrounding work-to-family and family-to-work conflict. These two forms of conflict are mediators of the relationship between personality and mental health. We found that the three personality traits of agreeableness, conscientiousness, and neuroticism worked through the mediating mechanisms of work-to-family conflict and family-to-work conflict with depression as well as through family-to-work conflict and anxiety to play mediating roles in their relationship with substance use. Thus, this research supports the notion that the work-family interface may play a critical role in understanding why employees experience adverse mental health outcomes and engage in substance use.

We suggest that organizations take kinder note of employees facing difficulties at work or at home and that they appropriate funding for employee assistance programs to address mental health and substance use problems. Many of the types of issues giving rise to $400 billion in annual losses to businesses in the U.S. [ 77 ] are the result of mental health issues and/or substance use and abuse. The loss to businesses is not only financial but interpersonal as the spill-over effect of idiosyncratic problems of one worker may unintentionally affect another worker as the cascade of despair infects the organization. Given the rise in interest in personality testing by managers in the workplace we recommend that those employees with an identifiably aberrant combination of traits (e.g. extremely low agreeableness and extremely high neuroticism) be given an opportunity to receive wise counsel from supervisors regarding interpersonal interactions with coworkers and customers. However, the relative unmalleability of personality traits makes such trait levels particularly difficult to ameliorate but the encouragement of self-awareness can likely be beneficial. To facilitate such self-awareness, we recommend training in emotional intelligence which helps employees build skills devoted to helping them be aware of and manage the emotions of themselves and others. The goal of a business organization should be not only to earn a profit but to develop its people to their fullest human capacity.

Supporting information

S1 checklist, acknowledgments.

A previous version of this manuscript was accepted in reduced form and with a different title to be presented at the annual conference of the Academy of Management in Vancouver, British Columbia, Canada in 2020. However, the conference was cancelled due to COVID-19.

Funding Statement

The authors received no specific funding for this work.

Data Availability

• PLoS One. 2022; 17(2): e0263631.

Decision Letter 0

12 Jan 2022

PONE-D-21-39844Antecedents and Outcomes of Work-Family Conflict:  A Mega-Meta Path AnalysisPLOS ONE

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Reviewer #1: I appreciate the opportunity to review this article. The authors conducted a mega-meta analytic path analysis examining the relationships among Big Five traits, work-to-family conflict and family-to-work conflict, anxiety and depression, and substance use.

In my opinion the objective is relevant and the selection of variables and the theoretical models are also well founded.

The methodology is complex and allows responding to the objectives set.

However, there are some doubts related to the definition of some variables and the methodology used.

- I think that the constructs “work-to-family conflict and family-to work conflict” should be defined more extensively in the introduction.

- In the discussion some traits are considered as adaptive and one trait as maladaptive. However, the Big Five Traits Model is a normal personality model. According to the model, no trait is maladaptive in itself, but it will depend on the context or environment in which the person is and the influence of other variables. Is neuroticism considered a maladaptive trait in the context of the interpretation of the results?

- I understand that only clinical cases of anxiety and depression with a clinical diagnosis have been considered. Is that correct? Could any diagnostic category be considered of both types of disorders?

- When describing the Article Inclusion Criteria, it is not clear what the reasons were for excluding the 115 articles from the last step of Figure 1.

- Although I am not an expert in mega-meta

analytic path analysis, I think that as described by the authors, the working method can be followed without difficulty.

- I think that within the limitations it should be included that the influence of sociodemographic variables and variables related to work (type of work, years of dedication, occupational risks, temporality) have not been considered.

- Practical implications should be included. According to the results, what strategies could be implemented to reduce work-to-family conflict and family-to-work conflict? How to prevent them? Could it be predicted through the personality profile?

In summary, I think it is an interesting study that uses a complex methodology; however, there are some aspects that should be clarified.

Reviewer #2: Thank you very much for this opportunity to read this interesting study. Although, the paper is highly interesting and worth publishing, I have some remarks and questions.

I would have wanted stronger theoretical and conceptual background in the introduction.

For example, to clarify what is the difference of WFC and FWC? And why they need to be considered separately?

Why anxiety, depression and substance use were selected as outcomes?

Could the relationship go other way around? I mean could it be that anxiety, depression and/or substance use affect WFC and/or FWC?

In table 3, 2e Neuroticism-> FWC-> Anxiety, should the effect be positive, instead of -.02***? The 95% confidence intervals are positive

Is 3a in the same table correct effect?

Now there are quite many analyses. Did you use e.g. Bonferroni correction for the p-values?

I was wondering, have you tested e.g. to combine WFC and FWC to a common conflict measure and run the analyses with it? As e.g. Byron 2005 (your reference number 10) shows that coping styles and skills have quite similar relations with both WFC and FWC, and I think personality traits might behave similarly. What comes to your reference number 11, it considers positive side of work-family interface, not conflict, what you concentrate on, so I don’t think it is the best one for your purposes.

I would ask the same with anxiety and depression, such as have you tried to combine these to general mood or mental health measure and run the analyses with it?

Do these combinations affect the effect sizes? Or to the model fit indexes?

RMSEA shows poor fit, is that a reason to be concerned?

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Author response to Decision Letter 0

18 Jan 2022

Response to Reviewers of PLOS-D-21-39844

Reviewer #1 Comments:

1. I appreciate the opportunity to review this article. The authors conducted a mega-meta analytic path analysis examining the relationships among Big Five traits, work-to-family conflict and family-to-work conflict, anxiety and depression, and substance use. In my opinion the objective is relevant and the selection of variables and the theoretical models are also well founded. The methodology is complex and allows responding to the objectives set. However, there are some doubts related to the definition of some variables and the methodology used.

Authors' Response: We thank the reviewer for these comments and address them one-by-one below in a numbered fashion.

2. I think that the constructs “work-to-family conflict and family-to work conflict” should be defined more extensively in the introduction.

Authors' Response: Thank you for your suggestion. We elaborate as suggested on the definitions of work-to-family conflict and family-to-work conflict on newly inserted lines 46-60 into the second paragraph of our paper:

"With the development of valid instruments [2, 5, 6, 7] research on the antecedents, correlates, and outcomes of work-to-family conflict (WFC) and family-to-work conflict (FWC) has grown in number and type. The important directionally different flow of conflict between these two major domains of life [8] results in WFC and FWC being only moderately positively correlated at .41 [9]. It is notable that work-family conflict takes unique bi-directional forms of WFC and FWC. The former is defined as when the work demands interfere with performing family responsibilities, while the latter is defined as when family demands interfere with the performance of work duties [4]. Examples of the former include work demands like forced overtime and dealing with rude customers. Examples of the latter include family demands like caring for sick children and marital strife. These two directions of conflict have enough unique variance to act as separate and stand-alone constructs because they only overlap by about 16% [9]. A large body of literature [2, 5, 9] has documented that WFC and FWC are theoretically distinct, are predicted by different factors, and result in different consequences [2, 5, 9]. Because these two forms of conflict often relate differently to other variables [10, 11] they are not interchangeable."

3. In the discussion some traits are considered as adaptive and one trait as maladaptive. However, the Big Five Traits Model is a normal personality model. According to the model, no trait is maladaptive in itself, but it will depend on the context or environment in which the person is and the influence of other variables. Is neuroticism considered a maladaptive trait in the context of the interpretation of the results?

Authors' Response: We appreciate this request for clarification and hope that our response is not pedantic in any way. Our understanding of the Big Five follows. The traits in the model are construed as a spectrum which ranges from very low to very high levels of each trait. Some of the traits are known by their polar opposite endpoint name. For example, agreeableness could be referred to (but rarely is) as "disagreeableness" if the need arose. Such a need might be in the explanation of its positive relationship with Anti-Social Personality Disorder (ASPD). Alternatively, ASPD is negatively correlated with trait agreeableness.

The negative relationship between agreeableness scores and ASPD would likely make agreeableness adaptive in some cases. Low scores on agreeableness, or alternatively construed as high scores on disagreeableness, would make it somewhat maladaptive. It is the same trait, it just matters from which direction it is measured. We are quite certain that the reviewer already knows this but wanted to make sure that our understanding of the Big Five traits matches that of the reviewer.

Now we directly address the reviewer's issue. For many years, the trait of Emotional Stability was known as Neuroticism which is likely a holdover of Eysenck's two factor model of personality. When the trait is measured such that high scores on it indicate high levels of neuroticism and therefore low levels of emotional stability then in some contexts it can be maladaptive in its behavioral, cognitive, and affective outcomes. In the studies coded in the meta-analyses gathered for use in this paper the meta-analysts tended to measure that Big Five trait as neuroticism which is negatively related to most favorable outcomes and positively related to most maladaptive outcomes like WFC, FWC, depression, anxiety, and substance use. We found that in the context of the work-family interface, neuroticism is strongly related to all five. We consider this to be evidence of its maladaptive nature.

Methodologically, we would only need to reverse the sign of the model relationships and we would have results of an opposite but equal magnitude. In that case all Big Five Traits in our model would be negatively related (adaptive) to the various hypothesized outcomes in our model. We are happy to go back and reverse the signs to accomplish this but theoretically it weakens our argument about Conservation of Resources Theory which helps the reader understand the importance of neuroticism in the prediction of maladaptive outcomes like depression, anxiety, and substance use. We hope this helps explain our thinking and we thank the reviewer for this comment.

4. I understand that only clinical cases of anxiety and depression with a clinical diagnosis have been considered. Is that correct? Could any diagnostic category be considered of both types of disorders?

Authors' Response: Yes, only clinically diagnosed cases were considered because that was all that was available in the published meta-analyses used as part of the synthetic input correlation matrix for this study. In those meta-analyses, different meta-analytically derived values for different directional influences of WFC and FWC on depression and anxiety were available. Meta-analytic effect sizes do exist for depression and anxiety in the antecedent prediction of WFC and FWC. To our knowledge none considered sub-clinical levels of depression and anxiety. Our study can only be thought of as truly cross-sectional we opted for the meta-analytic values of WFC and FWC as truly and timely precursors of depression and anxiety to lend a modicum of causality to the model. However, these are not consistent with the field of research surrounding WFC/FWC which developed along the lines of clear and distinct antecedents of conflict and clearly theoretical outcomes of conflict. We noted our lack of the ability to infer causality as a limitation in the original submitted version of our study which we still include and can be found on the newly numbered lines 391-396 and make sure to limit any notion of causality.

5. When describing the Article Inclusion Criteria, it is not clear what the reasons were for excluding the 115 articles from the last step of Figure 1.

Authors' Response: Thanks for the opportunity to explain this. We excluded those studies because they were meta-analyses on relationships other than the 45 necessary for input into our synthetic correlation matrix. We have changed the verbiage in two of the boxes in the flow chart to be more transparent. Instead of one box stating "Records excluded (n = 4087)" we rewrote it as "Non-meta-analyses excluded (n = 4087)". These records were excluded because they merely referenced a meta-analysis and were not meta-analyses in and of themselves. To directly address the reviewer's point, we also rewrote "Full text articles excluded (n = 115)" as "Irrelevant meta-analyses excluded (n = 115)". In our search we uncovered many meta-analyses that only referenced WFC and/or FWC and the Big Five or the psychological outcomes in our model. These 115 studies did not meta-analyze any of our focal relationships. We also found a typographical error in the text on line 345 where we deleted "606" and typed in "1039" to match the flow chart.

6. Although I am not an expert in mega-meta analytic path analysis, I think that as described by the authors, the working method can be followed without difficulty.

Authors' Response: Thanks very much! It is indeed a complicated method so we tried very hard to make it understandable.

7. I think that within the limitations it should be included that the influence of sociodemographic variables and variables related to work (type of work, years of dedication, occupational risks, temporality) have not been considered.

Authors' Response: We thank the reviewer for this suggestion. We added the following to lines 543-548:

" The socio-demographic variables such as type of work and organizational tenure related to work were not, and largely could not be, included in the study. The body of literature around the relationship between them and WFC/FWC is growing but meta-analyses do not exist for most work-related socio-demographic variables with WFC/FWC and definitely do not exist for the relationship between them and the two disorders and substance use."

8. Practical implications should be included. According to the results, what strategies could be implemented to reduce work-to-family conflict and family-to-work conflict? How to prevent them? Could it be predicted through the personality profile?

Authors' Response: We thank the reviewer for this opportunity to add to our paper. On lines 586 -601 we have added the following:

"We suggest that organizations take kinder note of employees facing difficulties at work or at home and that they appropriate funding for employee assistance programs to address mental health and substance use problems. Many of the types of issues giving rise to $400 billion in annual losses to businesses in the U.S. [77] are the result of mental health issues and/or substance use and abuse. The loss to businesses is not only financial but interpersonal as the spill-over effect of idiosyncratic problems of one worker may unintentionally affect another worker as the cascade of despair infects the organization. Given the rise in interest in personality testing by managers in the workplace we recommend that those employees with an identifiably aberrant combination of traits (e.g. extremely low agreeableness and extremely high neuroticism) be given an opportunity to receive wise counsel from supervisors regarding interpersonal interactions with coworkers and customers. However, the relative unmalleability of personality traits makes such trait levels particularly difficult to ameliorate but the encouragement of self-awareness can likely be beneficial. To facilitate such self-awareness, we recommend training in emotional intelligence which helps employees build skills devoted to helping them be aware of and manage the emotions of themselves and others. The goal of a business organization should be not only to earn a profit but to develop its people to their fullest human capacity."

We hope that we did not get too flowery in our language but we feel passionate about this set of implications and hope that they meet the reviewer's expectations.

9. In summary, I think it is an interesting study that uses a complex methodology; however, there are some aspects that should be clarified.

Authors' Response: We thank the reviewer for the insightful comments and suggestions and hope that we have adequately addressed them.

Reviewer #2 Comments:

1. Thank you very much for this opportunity to read this interesting study. Although, the paper is highly interesting and worth publishing, I have some remarks and questions.

Authors' Response: We thank the reviewer for these suggestions, comments, and concerns and address them point-by-point below.

2. Introduction. I would have wanted stronger theoretical and conceptual background in the introduction. For example, to clarify what is the difference of WFC and FWC? And why they need to be considered separately?

Authors' Response: Thank you. Per your suggestion, we clarified the differences of WFC and FWC in the introduction and also explained why the two dimensions of work-family conflict need to be considered separately. The revised sentences can be found on the newly inserted lines 46-60 in the second paragraph of our paper:

Thus, following the existing literature, we consider the two variables separately in the study.

3. Why anxiety, depression and substance use were selected as outcomes? Could the relationship go other way around? I mean could it be that anxiety, depression and/or substance use affect WFC and/or FWC?

Authors' response: We heavily considered running alternative models such as that. The fit of such a model would be exactly the same as our hypothesized model and the paths would likely only differ by the smallest of margins. It is true that mental disorders and substance use intuitively cause conflict at home and at work but the meta-analytic effect sizes gathered for use in this paper were computed on primary studies that largely had the intent of conflict being antecedent to the disorders. Thus, in the area of research around FWC and WFC depression, anxiety, and substance use have most often been studied as outcomes of FWC and WFC. Our paper is designed to strategically combine extant research from the growing field of WFC and FWC. We, in essence, combine the right half (i.e. antecedents ) and the left half (i.e. outcomes) of hundreds of studies of WFC and FWC based in our paper upon a unifying theory. Also, because our model can truly only be thought of as cross-sectional, because the nature of the meta-analytic results gathered for inclusion in our input matrix were calculated without any inference of directionality by the original meta-analysts. As we developed our model we scoured the databases for all primary studies of the antecedents and outcomes of WFC and FWC. We found a total of 56 different variables that neatly fell into either category. Alas, only the most oft-studied antecedent and outcome relationships had been meta-analyzed so we could not create a synthetic 56x56 matrix without relying on single primary studies. Additionally, some of the left-hand meta-analyses just did not combine well with some of the right-hand meta-analyses under any one or two particular theories. In essence, the field is a hodge-podge of loosely connected studies that share a central focus of WFC and FWC and largely based upon cross-sectional primary studies combined into non-directional effect sizes in meta-analyses.

4. Results. In table 3, 2e Neuroticism-> FWC-> Anxiety, should the effect be positive, instead of -.02***? The 95% confidence intervals are positive. Is 3a in the same table correct effect?

Authors' Response: Oops. We apologize for this error in our results table. Thanks for the very keen eye for detail!

5. Now there are quite many analyses. Did you use e.g. Bonferroni correction for the p-values?

Authors' Response: We did not need to adjust for the many tests because we used structural equation modeling to test the model for fit and all model relationships for their relationships in one fell swoop. Consider, for example, a regression model with 2, or 5, or even 50 predictors. Each regression coefficient is already corrected for the propensity for Type I error in the model test. This might be a little off-note but there is some growing acknowledgement that when using meta-analytically derived effects that are corrected for measurement error as part of the meta-analysis one can refer to the path model test as a structural equation model test because such tests also correct for measurement error. Regardless of if we consider ours a structural equation model test or a path model test control of Type I error is an inherent part of the underlying algorithm.

6. I was wondering, have you tested e.g. to combine WFC and FWC to a common conflict measure and run the analyses with it? As e.g. Byron 2005 (your reference number 10) shows that coping styles and skills have quite similar relations with both WFC and FWC, and I think personality traits might behave similarly. What comes to your reference number 11, it considers positive side of work-family interface, not conflict, what you concentrate on, so I don’t think it is the best one for your purposes.

Authors' Response: We did not combine WFC and FWC because the two variables are theoretically and empirically different, as shown in previous studies (Amstad et al., 2011; Mesmer-Magnus & Viswesvaran, 2005; Shockley & Singa, 2011; Whitely & England, 1977). Consistent with existing research on the theoretical difference, we tested WFC and FWC separately in the model. Our findings indicate that WFC and FWC have different mediating effects linking Big Five personality and mental health outcomes. It should also be noted that we cannot combine two meta-analytically derived correlations. Recall that we did not do the meta-analyses ourselves and thus could not recode the primary studies for any that combined both forms of conflict into one construct. We would also need nine more correlations of the combined form of WFC/FWC with each antecedent and outcome in the model. These statistics just do not exist.

We cited reference number 11 (Byron, 2005) to show that WFC and FWC are different from other work-family constructs such as work-family enrichment. There are positive sides to the work-family interface such as work-family enrichment which is a field still growing and likely to grow more in the future and thus be meta-analyzed and ripe for inclusion in a mega-meta. We would, of course, be happy to remove this citation per your request.

7. I would ask the same with anxiety and depression, such as have you tried to combine these to general mood or mental health measure and run the analyses with it? Do these combinations affect the effect sizes? Or to the model fit indexes?

Authors' Response: Similar to our response above, these statistics just do not exist in the meta-analytic literature surrounding WFC and FWC. As above, if they existed, we would need a meta-analytic effect size between the combination of depression and anxiety (two disorders that often are comorbid) and every other variable in the model. Thus, if only one or two such meta-analyses existed we would have a very, very simple model as most cells in the 10x10 synthetic input matrix would be empty.

8. RMSEA shows poor fit, is that a reason to be concerned?

Authors' Response: It is our understanding that the RMSEA is sensitive to model complexity. Our serial mediation model is likely more complex than most. We are pleased that, as we noted in our paper, the SRMR is excellent and the CFI indicates good fit. We hope the excellent SRMR sort of offsets the poor RMSEA, but as with all supplemental fit indices that is a judgment call. If our model had been a simple model with five exogenous predictor variables (the Big Five traits) in the prediction of five endogenous outcome variables (WFC, FWC, depression, anxiety, and substance use) our RMSEA would likely have been better. However, such a simple model belies the extant literature on WFC and to some extent does not give fodder for our use of Conservation of Resources Theory. If all fit indices were poor we would have found some evidence that researchers of the antecedents of WFC and other researchers of the outcomes of WFC might be examining incompatible segments of the nomological network surrounding WFC. We are happy to add more text about the poor RMSEA if the reviewer insists but we hope that the reader will recognize the excellent and good fit of the other indices.

Reviewer 3 Comments:

1. The authors should pay attention to small errors in the text.

Authors' Response: We apologize for the errors and have made the following corrections:

Line 47: Replaced the brackets with parentheses around the acronym

Line 48: Replaced the brackets with parentheses around the acronym

Line 83: Replaced "[Oh, 2020] with "[23]"

Line 85: Corrected the spelling of "supplemented"

Line 146: Replaced "...pessimism, and temperamentalism" with "...pessimism and being temperamental"

Line 179: Replaced the brackets around "[substances]" with parentheses

Line 345: Replaced "606" with the correct difference value of "1039"

Line 336: This line appeared twice due to adding text previous to it. We have now renumbered the lines from line 340 onward

Lines 392-394: Replaced brackets around "a", "b", and "c" with parentheses

Lines 491-503: Replaced brackets around trait names (e.g. agreeableness) and hypothesis numbers with parentheses

Lines 564-565: Replaced brackets with parentheses where appropriate

2. Please provide bibliographic references in all parts of the introduction. You cannot affirm something if it is not based on literature.

Authors' Response: In the five paragraphs comprising the introduction section we have 23 sentences. Twelve of the sentences have bibliographic citations. In that section there are 25 citations. The sentences without citations are summary sentences built upon previous sentences with the referenced sources such as line 44-45: "This conflict is likely to have serious consequences for one's roles their family and work." Most of the other sentences without citations are explaining the purpose of the study and how we assembled our input correlation matrix. We are not sure where we might need additional references but would be happy to do so with further guidance.

3. Please summarize or improve the introduction. It is very long and there are parts that are not understood. It must be more specific and fit the objectives and hypotheses of the study.

Authors' Response: Our introduction section is only five paragraphs long with three of them devoted to the purpose of the study, how "data" were collected/assembled, and the contributions of the study. We respectfully disagree that it should be any shorter than it already is without skipping vital information for the reader. We hoped to show the reader why we wanted to do the research, how it was going to be conducted, and how we hoped to make a contribution to the literature. We are happy to remove some small bits if they can be directly specified.

4. Regarding the structure of the Introduction section, I would suggest presenting objectives and hypotheses after adequately stating the background and justification rather than in reverse or mixed order for clarity reasons.

Authors' Response: We think that perhaps the reviewer is suggesting changes to the Theoretical Framework section rather than the Introduction section. Our model is rather complicated by its nature as a serial mediation model. We hoped to "walk the reader through" the model by proceeding left to right, that is, from antecedents to mediators to outcomes. Given the very large number of hypotheses we very much prefer to discuss one part of the model and then give its hypotheses then followed by a discussion of the next part of the model and its hypotheses, etc. this sort of piecemeal procedure from left to right also serves our stated purpose of joining the left hand side of the nomological network (see the heading in line 126) with the right hand side (see line 153). We are willing to put all hypotheses at the end of the Theoretical Framework section but they will take up almost three entire pages of text. We think that might be a bit overwhelming to the reader so we hope to stay with the current arrangement.

5. Please discuss the potential theoretical and clinical implications of your work deeply.

Author's Response: We thank the reviewer for this suggestion but are hesitant to discuss clinical implications. We have lines 517-551 where we discuss the findings within the Theory of Conservation of Resources. For example lines 529-533 reads as follows: "Due to dysfunctional emotional adjustments, sensitivity, and vulnerability to negative experiences [54, 59, 89], neurotic employees have fewer resources with which to manage incompatible work and family demands [46], leading to higher WFC, which in turn increases depression and substance use." However, we have added a section on practical implications to lines 612-627. Our paper's central focus is work-related. The main constructs are WFC and FWC. The personality trait antecedents are measured using instruments designed to measure personality in sub-clinical populations. Admittedly our study does use variables like clinical depression, clinical anxiety, and sub-clinical substance use but it is not a clinical paper, per se. As we state a few times in the paper we used variables that existed, that were found in previous meta-analyses on variables related to WFC/FWC, and could not use variables for which the necessary statistics did not exist. We hope the reviewer understands and we respectfully suggest that such additions to the paper are not in its best interest.

Submitted filename: Response to Reviewers.docx

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Article contents

Conflict in family communication.

• John P. Caughlin John P. Caughlin University of Illinois at Urbana Champaign
•  and  Emily Gerlikovski Emily Gerlikovski University of Illinois at Urbana Champaign
• https://doi.org/10.1093/acrefore/9780190228613.013.1465
• Published online: 22 November 2023

Conflict is a common experience in families. Although conflicts can be intense, most conflicts in families are about mundane issues such as housework, social life, schoolwork, or hygiene. Families’ negotiations over even such mundane topics, however, have important implications. Through conflicts with other family members, children typically first learn about managing difficulties with others, and the skills they learn in such conflicts are important to their social lives beyond their families. Yet poorly managed conflicts that become more intense or personal can undermine the well-being of families and family members. Family conflicts are extremely complex, and understanding them requires analysis at multiple levels, including examining the individual family members, dyads and larger groups within the family, and the sociocultural context in which families are embedded. At the individual level, family members’ conflict behaviors (e.g., exhibiting positive affect vs. negative affect), conflict skills (e.g., whether they are able to resolve problems), and cognitions (e.g., whether they make generous attributions about other family members' intent during disputes) all are important for understanding the impact of family conflicts. Examining conflict from the dyadic and polyadic levels recognizes that there are important features of conflict that are only apparent with a broader perspective. Dyadic and polyadic constructs include patterns of behavior, conflict outcomes that apply to all family members involved, and beliefs shared by family members. There are also particular types of relationships within families that have salient conflicts which have drawn considerable scholarly attention, such as parent–child or parent–adolescent conflicts, conflicts between siblings, marital conflicts, and conflicts between co-parents. In addition, families experience various transitions, and the life course of families influences conflict. Some key periods for conflict are the early years of marriage, the period of launching children and empty nest, and a family member navigating the end of life. Finally, family conflicts occur in a larger sociocultural context in which societal events and conditions affect family conflict. Such contextual factors include broad social structures (e.g., societal-level power dynamics between men and women), financial conditions, different co-cultural groups within a country, cross-cultural differences, and major events such as the COVID-19 pandemic that have direct effects on families and also elicit dramatic social responses that affect families. Despite the complexities, it is important to understand family conflict because of its implications for the health and well-being of families and family members.

• parent–adolescent relationships
• adolescents
• family communication

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The Work–Family Conflict: Evidence from the Recent Decade and Lines of Future Research

• Published: 12 August 2020
• Volume 42 , pages 4–10, ( 2021 )

Cite this article

• José Alberto Molina 1 , 2  

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This contribution adopts an economic perspective to summarize what we learned in the last decade about the work–family conflict (WFC) and, primarily, where we go from here. On the basis of recent labor, demographic and socio-economic changes, and the use of both data and economic methods, we have identified a number of important topics. First, the relationship between the WFC and the kinds of family, with specific attention to motherhood/fatherhood. Later, the interrelations between the WFC and spousal problems or different satisfaction issues. We then analyze the implications of the WFC for policy and benefit issues, and, finally, the relationship between the WFC and dispositional characteristics. The future of the research should first address the limitations of the existing literature. The complete lack of longitudinal data makes it impossible to derive causal effects, with only correlations being possible. Another future avenue is the elaboration of cross-cultural papers. An interesting topic to be covered is to focus on the couple, rather than the individual, with different couples by race, religion…having implications for intra-family negotiation. Another line is to examine intergenerational issues that arise as a consequence of the delay in the nest-leaving of children and, at the same time, the presence of grandparents in the home.

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Acknowledgements

This paper was partially written while the author was Visiting Fellow at the Department of Economics of Boston College (US), to which he would like to express his thanks for the hospitality and facilities provided. This paper has benefited from funding from the Regional Government of Aragón (Project S32_17R).

This paper has benefited from funding from the Regional Government of Aragón (Project S32_17R).

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Molina, J.A. The Work–Family Conflict: Evidence from the Recent Decade and Lines of Future Research. J Fam Econ Iss 42 (Suppl 1), 4–10 (2021). https://doi.org/10.1007/s10834-020-09700-0

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How perceived organizational politics cause work-to-family conflict? Scoping and systematic review of literature

• Sumbol Fiaz   ORCID: orcid.org/0000-0003-3042-0332 1 &
• Muhammad Azeem Qureshi 1  

Future Business Journal volume  7 , Article number:  5 ( 2021 ) Cite this article

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Work–family conflict is a subject of interest for researchers in the field of organizational behavior for decades because of its negative impact on an individual’s life. The existing literature identified that workplace stressors contribute to work–family conflict and Perceived Organizational Politics emerged as an aversive workplace stressor. From empirical pieces of evidence, it is observed that perceived organizational politics and work–family conflict are indirectly associated with each other, and their impact on employees is unavoidable. To explore this uncovered relationship, at first, this study used a keywords co-occurrence network mapping approach and found that perceived organizational politics and work–family conflict are associated with each through various workplace variables. Further, with the help of a scoping review identify those specific variables, and, lastly, a systematic review approach used to identify a mechanism of how these identified variables form an association between perceived organizational politics and work–family conflict. Based on the findings of the systematic review, this study proposed a conceptual framework that extends the existing literature by providing new insight into concepts of perceived organizational politics by linking it with work–family conflict. This study introduced a novel way to develop a conceptual framework by linking three distinct approaches of research. In the last, this study proposed recommendations for future research.

Introduction

Work–family conflict is the most debated construct in the field of organizational behavior that has gotten the central attention of researchers due to its negative consequences related to the workplace [ 47 , 111 ]. Facing conflict at work and family domain is a burning issue for which employees mostly complain. Conflict in one domain ultimately affects the other domain. Employees are more concerned about keeping it balanced because of its impacts on their efficiency and wellbeing [ 88 ]. Work–family conflict is strongly associated with an employee’s wellbeing [ 101 ]. While wellbeing depends on the state of emotions, positive emotions satisfy whereas negative emotions disturb wellbeing [ 48 , 137 ] and strongly associated with individuals’ behavior. Employees experience several behaviors in the workplace that impacts their emotions. In the domain of organizational behavior, Perceived Organizational Politics is the most dominant and influencing work-related negative factor that impacts the employees’ behavior [ 114 ]. It is a general phenomenon in all organizations that are usually perceived negatively and results in undesirable or harmful outcomes such as stress that is one of the most prominent outcomes [ 29 , 44 , 78 , 144 ].

Experience is an outcome of an individual’s evaluation of specific phenomena or events [ 102 ]. Employees on this basis of their experience define organizational politics as cynical and manipulative phenomena, they describe it as an evil behavior that employees strategically show to get the things done for their benefit by disturbing the organization’s functions [ 38 , 41 , 45 , 51 , 79 , 90 ] and also risking the wellbeing of other employees and organization [ 70 ]. When employees experience organizational politics they think themselves as a victim who has to suffer due to others’ self-serving behavior. Consequently, this situation evokes negative emotions [ 128 ]. Employees spend most of their time at the workplace [ 87 ]. Therefore, work-related circumstances govern their emotions and behavior, experience of adverse events at the workplace predict the negative emotions and cause stress [ 96 ] that ultimately impacts the wellbeing of the employee.

Work and family are the most important factors in almost every individual’s life. When the occurrence of stress due to participation in one domain become a constrain and makes it challenging to fulfill the requirement of other domain this known as work–family conflict (WFC) [ 54 ]. Work–family conflict has been a subject of interest in the field of organizational behavior for decades, a constant increase in its body of literature raising the importance of work–family conflict [ 120 ]. Currently, it has gotten remarkable attention from researchers due to its negative consequences for work and family domain [ 47 , 111 ]. Existing research demonstrated that negative work-related factors such as stress predict work–family conflict [ 14 ] while Perceived organizational politics (POP) is identified as one of the most dominant and influencing negative aspects of the work environment [ 78 , 80 ]. POP is an uncovered work-related factor that affects both the personal and professional lives of employees and causes WFC. To prevent this uncovered cause of WFC, it is required to identify how POP causing WFC. There is an extensive number of studies explored the consequences of perceived organizational politics related to the work domain. There is no significant predictive model for understanding how POP impacts the WFC. It is a clear research gap that needs to be addressed.

To strengthen of above argument that there are factors indirectly causing the relationship of POP and WFC, with the help of VOSviewer software [ 142 ] this study also created the keyword co-occurrence network to map out all variables that have been studied in the field of POP and WFC. VOSviewer is a software tool that creates a map based on network data retrieved through search engines or databases. Microsoft Academic (MA) database was used with VOSviewer software. MA is a huge database that allows downloading already segmented citation contexts [ 19 ]. Key terms used to get the search data were Perceived Organizational Politics. The map-based on keywords occurrence network, generated through option, “title and abstract network”. This function of VOSviewer retrieved the keywords that appear in the title, abstract, and citation context [ 146 ]. The setting of VOSviewer was done in such a manner that it captured all the key variables that occurred in abstracts and titles, at least four times. Full counting of words was applied. From the retrieved keywords, before generating the map, irrelevant keywords that were not described as variables in the literature such as structural equation modeling, mediators, moderators, negative relation, were manually excluded. As argued Fig.  1 shown that the concept of POP is linking with all the work domain variables that are getting the effect of or affecting POP. This map supports our argument that existing researches focused on only work-related outcomes of POP.

Variables related to POP

The same procedure has been followed with the key term work-to-family conflict , to map out the most highlighted variables that explored or examine concern to work-to-family conflict. Figure  2 reflects the variable network concerning WFC. Map 2 highlighted all the variables that have been studied in the field of WFC. From the analysis of both maps shown in Figs.  1 and 2 , it can be seen that many identical variables are related to POP and WFC at the same time such as job stress, emotional intelligence, turnover intention. So, it can be argued that some of the outcome variables of POP are antecedents of WFC. Since we did not specify the key terms as an antecedent and outcome, therefore, we are unable to distinct that either linked variables are antecedents or outcomes. To address this issue and identify the specific factors that link these two vast domains of organizational behavior, i.e., POP and WFC, the present study conducted a scoping review. The purpose of the scoping review is to find out the identical variables that are outcomes of WFC and also antecedents of WFC. And also describe the reason for considering those identified variables.

Variables related to WFC (WFC is not highlighted in the above figure, because it is used in studies with different terms, i.e., work-to-family conflict, wtfc, work–family interference, work–family conflict)

Scoping review

For this study, the scoping review aims to establish a comprehensive review of published literature and identify the key variables that can predict the relationship between OP and WFC. The scoping review is conducted by following the advanced framework of Arksey and O’Malley described in Scoping studies: Advancing the Methodology [ 82 ]. The methodology of scoping studies is based on six systematic phases shown in Fig.  3 .

Process of Scoping Review

Defining research question

WFC is a subject of interest for researchers. It is a cyclic process; conflicts at one domain trigger the conflicts at other domains. Findings of studies revealed that the predictors of work-to-family conflicts are similar across the world [ 6 ]. Factors associated with the workplace severely impact employees’ lives than on family-related factors [ 35 , 64 , 138 ]. POP is one of the significant aspects of a workplace that influences employees’ personal and professional life. Both factors of organizational behavior are indirectly related to each other. The scope of this review is to identify:

What are the factors that bridge the association of perceived organizational politics and work–family conflict?

Identifying the relevant studies

To address the research question, this study considered that all the related studies reported the consequences of perceived organizational politics and antecedents of work–family conflicts. The literature search was conducted with the intent to find out the variables that bridge these two broad research areas of organizational behavior. For this purpose, this study employed the search databases, i.e., Elsevier BV, Sage Publication, Wiley Online, Springer nature, American psychological Association, Taylor and Francis., JSTOR, Frontiers Media S.A., Emerald, INFORMS, The Academy of Management, NCBI, MDPI, Public Library of Science, Cambridge University Press, EBSCO host, SSRN, PsycINFO and IEEE Xplore, to get all the relevant research articles, book sections, and dissertations (M.Phill. & Ph.D. level). This study developed two search terms for literature search are:

Consequence OR Outcomes OR relationship of OR Impact of AND Organizational Politics OR Perception of organizational politics, Office politics OR Political behavior at workplace OR Politics at the workplace.

Antecedents OR Predictors OR Sources of OR impact on AND work–family conflict OR work–life conflict OR work–family interference OR work-to-family conflict.

Studies containing any of these described keywords were selected. Similar search terms were used for all the databases.

Study selection

By following [ 82 ] guidelines for scoping review, established a team of three researchers included two independent reviewers and one arbitrator. The study selection process based on inclusion and exclusion criteria is carried out by two independent reviewers to maintain transparency and avoid uncertainty about the outcomes of the review. The same reviewers defined the inclusion and exclusion criteria for the studies that have been considered for this review with mutual understanding. In case of disagreement while selecting studies got consultation from an arbitrator to resolve the dispute and to determine the final participation. Studies indicating the outcome variables or consequence of POP and preceding variables of WFC retained. Inclusion and exclusion criteria for study selection shown in Table  1 .

The searched citations are managed through open-source citation management software Zotero. The study selection process of identified studies is shown in Fig.  4 PRISMA Flow diagram.

PRISMA flow diagram—scoping review

Charting the data

Data charting is a process at which both the reviewers collectively extract the required information from the selected studies to address the research question. Data extracted through Data Charting Form (DCF), developed with the mutual consultation of reviewers. Before starting the data charting, reviewers conducted a pilot test of established DCF on randomly selected five studies to validate that the data charting approach is appropriate for achieving the aim of scoping review. After the pilot test, DCF has refined accordingly. The data extracted in a qualitative manner, which was analyzed through the content analysis approach. Retained studies were separately analyzed to obtain the outcome variables of POP and anteceding variables of WFC. An arbitrator critically reviewed the extracted data. Following are the data items retrieved from the selected studies

Study characteristics (Author name, Journal name, year of publication, study design, population and sample size)

The objective of the study

Examine or identified variables as (antecedents of WFC and Outcomes of POP)

Findings/results/conclusion of the study

Collating, summarizing, and reporting results

Extracted data were organized by using Microsoft excel. Separate word files created of antecedents of WFC and outcome variables of POP. Manually identified the similar variables from both the separated files. Burnout, Emotional intelligence, Job involvement, Negative Affectivity, Psychological wellbeing, Perceived Organizational Support, and Social support are variables identified from literature through scoping review that may support the relationship between POP and WFC by acting as mediator or moderator. Afterword conducted a content analysis to describe the results of the scoping review.

From the search results, one research has identified that examined the impact of POP other than the work domain. A study conducted by Zhu and Li [ 154 ], based on ecological system theory [ 21 ] and boundary theory [ 9 ], examined the influence of POP on WFC. They hypothesized that WFC is an outcome of workplace environmental situations that are stressors. They consider POP as a workplace stressor that harms the boundary of work and family domain and makes it difficult for individuals to perform the family role. In line with the stimulus-responses model, they also hypothesized that organizational cynicism (Attitude) mediate (bridge) the relationship between OP (stimulus/event) and WFC (response). Little literature support was found for their research model therefore it identified as detailed research that needs to address. In this section as first defined the identified variables. Secondly, based on the content analysis of the findings of retained studies this section described the reason for considering these identified variables for further study.

Psychological health issues harm individuals’ life [ 104 ]. Burnout is a major psychological health problem around the world. It is a prolonged human response against the chronic emotional and interpersonal stressors on the job, which is expressed through exhaustion, cynicism, and professional inefficacy [ 94 , p. 351]. Burnout is an outcome of workplace stressors that prevent employees from achieving their organizational related goals and expectation [ 110 ]. Whereas POP highlighted as a workplace stressor [ 22 , 152 ] and a strong predictor of burnout [ 78 , 91 ]. From the analysis of studies, it has been identified that when an employee perceive the workplace as political, it affects the psychological health of employee that intensify the burnout [ 16 , 37 ]. Burnout is a dominant workplace factor that has a strong tie with the health and wellbeing of employees [ 94 , p. 351]. It has a detrimental impact on employees’ family and professional life [ 129 ]. Studies have identified a positive association between WFC and burnout. Studies predict burnout as a consequent factor that happens due to WFC [ 25 , 46 ]. Although burnout is identified as a common variable through analysis current literature has not found any strong literature support for burnout as an antecedent of WFC due to which this study has not considered Burnout for further examination.

• Emotional intelligence

Emotional intelligence is an ability to rational or unbiased identification of emotions, perceive emotions based on reality, understanding their true meaning, and manage them accordingly [ 97 , 98 ]. Emotional intelligence is a strength of character that allows individuals to control emotions [ 122 ]. POP is all about the individual’s perception of certain behaviors as apolitical. Due to not having emotional and intellectual skills, employees perceive certain behaviors in an organization as political, which swings the employees’ emotions [ 37 , 131 ]. While WFC is a resultant phenomenon of individuals’ negative behavior. EI has identified as a bulbous variable in the study of POP that varies the intensity POP. Findings of the studies have revealed that emotional intelligence enhances individual emotional and intellectual capacity, lets him accurately identify the behaviors, and acts accordingly [ 37 , 63 , 89 ]. Similarly, studies related to WFC also highlighted EI as a factor that is strongly associated with WFC [ 69 , 81 ]. Since the study found this variable as a factor that may predict the relationship between POP and WFC so it will be considered for further research to define its role.

Job involvement

Job involvement is referred to as a psychological attachment of individuals with their job, and their personality well described by his nature of current work [ 85 , 116 ]. A person with high job involvement would be highly concern with the job matter and put extra time and effort into a job [ 68 ]. Findings of the review identified job involvement as a consequent variable of OP and antecedent of WFC. Results of studies indicated that POP has an adverse impact on job involvement [ 117 ]. Perception of OP decreases the level of job involvement. When employees perceive the workplace as political or perceive political behavior at the workplace, it lowers their involvement in a job [ 11 , 18 , 117 , 130 ]. In the meantime, job involvement has also been identified as a strong predictor of WFC [ 27 ]. High job involvement increases the employees’ concentration toward job due to which employees pay less attention toward the performance of a role in the family domain that causes the WFC [ 59 , 99 , 111 ]. Although job involvement is found as a shared variable, the role of this variable is contrary. From the analysis of retained studies, it revealed that job involvement is not a factor that may lead POP to WFC. POP lowers employee job involvement [ 117 ], which may reduce the chances of WFC. Whereas high job involvement reduces negative perception about POP. Based on the above-described analysis, role of the job involvement seems ambiguous; therefore, this study neglected the construct job involvement to consider as a possible mediator or moderator in the relationship of POP and WFC.

• Negative affectivity

Negative affectivity (NA) is a mental health outcome [ 126 ]. It is a dispositional tendency at which individual experiences various states of negative mood [ 147 ]. It is described as an aversive, undesirable or uncomfortable state of emotions and self-concept at which a person feels anxiety, worry, depression fear, or anger [ 28 , 71 , 119 , 148 ]. The literature described its positive association POP [ 140 ]. Employees who perceive the workplace environment as political their level of negative affectivity is high. Because POP consider as negative workplace factor and it induces insecurity within employees as a result employees feel NA. Consequently literature also showed a positive association between NA and WFC, employees who experience NA due to workplace stressors they more likely to encounter WFC [ 132 ]. Hence NA is identified as a stimulus that bridges the relation of POP and WFC therefore NA is considered for further study.

• Psychological wellbeing

In the research of behavioral interventions, psychological wellbeing (PWB) has been used as an outcome variable that is affected due to adverse events [ 150 ]. Psychological wellbeing is defined as a presence of positive psychological adjustment indicators such as positive emotions, happiness, high self-esteem, life satisfaction, and absence of psychological maladjustment indicators such as negative emotions and psychopathological symptoms [ 62 ]. The emotional stability of an individual predicts PWB. POP is a negative workplace factor that disturbed the stability of emotions [ 79 ] and harms the psychological wellbeing of employees [ 141 ]. Employees with unstable psychological wellbeing due to workplace problems fail to perform their family roles and as result encounter the work–family conflict [ 101 ]. From an analysis of the scoping review, PWB has also identified as a variable that may lead POP to WFC and it is necessary to identify in what manner PWB would participate while causing this relation. Therefore, this study retained PWB for further systematic review.

• Perceived organizational support

Eisenberger et al. [ 39 ] described perceived organizational support (POS) as an employee’s perception that his organization value his contribution and care for his wellbeing. Employee perceives that the organization will support him whenever needed to carry on the job effectively and to deal with a stressful situation [ 118 ]. POS is workplace support. Positive perception about organizational support encourages an employee to concern for organizational welfare and objective [ 40 ]. It strongly predicts the employee’s orientation toward the organization and work, employee performance, and wellbeing [ 76 ]. In contrast, the perception of OP demotes employees associated with the organization but high POS will permit employees to perceive their workplace or workplace behavior as political [ 17 , 58 , 121 ]. POS impacts the employees’ behavior and works attitude [ 23 , 26 ]; meanwhile, POS is inversely associated with WFC [ 55 , 75 ]. The findings of the scoping review found a negative association between both the variables POP and WFC with POS. Hence from these findings, it is not clear how POS predicts this relation and it needs to be identified.

• Social support

From the analysis of retained studies, we have identified a construct of social support that has frequently been examined. Social support is an instrumental or emotional aid from work or family domain which intends to secure or enhance the wellbeing [ 95 , 136 ]. Social support is broadly classified into two categories, i.e., perceived social support and received social support [ 139 ]. Findings of the studies have shown a strong association of received social support from family, supervisor, coworkers, and friends with WFC [ 57 , 59 , 66 ]. When employees experience conflict in either work or family domain upon receiving social support from work or the family domain conflict alleviates [ 49 , 134 ]. Similarly when employees perceive workplace politics that causes stress and made them realize to get harm at that time provision of social support will reduce the adverse effects of POP that may harm his wellbeing [ 58 , 144 ]. Based on the above literature support, it can be said that social support not only enables employees to overcome the WFC but also a barrier for harming the impact of POP. It is reasonable for this study to further explore the way through which social support participates in the relationship between POP and WFC. Although findings of the scoping review identified both dimensions of social support, i.e., work and family, but through the content, analysis is found that only work-related dimensions of social support reduce the aftermaths of POP [ 144 ]. Therefore, this study is considered an only work-related dimension of social support.

From the above analysis, this study has identified the variable that can predict the relationship between POP and WFC, i.e., Emotional intelligence, Negative Affectivity, Psychological wellbeing, Perceived Organizational Support, Workplace Social support. To find out how these identified variables determine the path of OP toward the WFC and to get an in-depth understanding of this hypothesized relation, it is required to analyze and synthesize existing literature critically. Due to this purpose, this study proceed to conduct a systematic review.

Systematic literature review

As the objective of this study is to explore the relationship between POP and WFC. In this study, scoping review helped to identify the variables and how these are related to POP and WFC, but findings are not enough to define the relation of these variables with each other. To conclude the findings of the scoping review and formulate, the comprehensive model to describe the way through which identified variables predict the relationship of POP and WFC systematic review for this study conducted.

The systematic review has been conducted by following the guidelines of Pollock and Berge [ 112 ]. According to their guidelines, the procedure for conducting systematic review consists of six consecutive phases, namely (i) clarify research aims and objectives, (ii) performing literature search (finding relevant research), (iii) data collection/extraction, (iv) assess the quality of studies, (v) synthesize evidence and (vi) interpret findings.

Clarifying the aim and objectives

Defining a research objective.

POP and WFC are two of the critical and significant concepts of organizational behavior. Through an extensive search, it has found that these factors highly influencing the organizational and personal life of employees. To cope with any conflicting matter, it is necessary to have an in-depth understanding of it. Although from the findings of two approaches, i.e., Network map and Scoping review, it is proved that POP and WFC are related to each other through specific work-related factors but there is no predictive significant model available to understand and described this relationship. Therefore, the objective of this systematic review is to define the role of all the variables to establish a comprehensive conceptual model.

Formulating eligibility criteria

This study included all the empirical studies with qualitative, quantitative, or mixed—methodology and books published in the English language reporting relationship between identified variables through scoping review since their inception. The search for the dissertation was also made to include all the published pieces of evidence. Manuscripts that provide evidence related to the research objective, either positive or negative, were considered. All the published studies and books in which any of these variables separately studied, their relationship has been examined with other variables, examine as a mediating or moderating variable, findings showing an insignificant relationship among identified variables, studies other than the English language, not considered for this research excluded. Conference proceedings, publications with poor quality, and not published in curated journals/databases include thesis and dissertation excluded. To attain the generalizability of this review, all the studies are conducted for employees with chronic illness, patients, pregnant women, employees with physical/intellectual disabilities excluded because the mental state and environmental conditions of these employees are different from general employees and finding of these studies may impact the original findings. Grey literature was also excluded.

Literature search

Defining search strategy.

The search considered databases that publish studies specific to organizational behavior and industrial/organizational/business psychology. The literature search conducted by using the following electronic databases: Elsevier BV, Sage Publication, Wiley Online, Springer nature, American psychological Association, JSTOR, Frontiers Media S.A., Emerald, The Academy of Management, Public Library of Science, Cambridge University Press, ERIC, EBSCO host, SSRN, PsycINFO, Taylor & Francis, ProQuest theses & dissertations, NCBI, IEEE Xplore. For an adequate literature search, it required to use broad search terms, i.e., keywords and free text words [ 115 ], The search terms used in this study for literature search are Negative Affectivity AND Emotional Intelligence AND/OR Psychological Well - being/wellbeing AND/OR Perceived Organizational Support AND/OR Social support. Studies containing any of these described keywords were selected. Similar search terms were used for all the databases. Social support is a multidimensional construct, and it has observed that most of the studies used a keyword “ social support ” as a whole so instead of pointing its dimension that has considered in the study. To include all the relevant studies or evidence, this study used a search term “ Social Support.”

A vast number of studies have been conducted in connection with the identified variables. Peer-reviewed publications, book sections, thesis, and dissertation have been identified through the electronic databases. Additional publications search through search engines, i.e., Google Scholar, Microsoft Academic Search, and Crossref, by using keywords described in the search strategy. Overall, 468 studies have identified in which 229 studies retrieved from database search and 246 studies identified through manual search via a search engine, i.e., Google scholar. Details of studies retrieved from databases are shown in Table  2 .

Selection of abstract and full-text article

As per Chocrane guideline [ 50 ], selection of abstract and full-text articles was carried out by two independent reviewers to reduce bias while selecting and interpreting the content. Differences and disputes while selecting articles were discussed and resolved by the arbitrator. Studies that meet the above-described eligibility criteria were selected. Search results are managed by using free and open-source reference management software Zotero to keep an adequate record of developing a proper PRISMA flowchart.

Eligibility of identified studies based on predefined inclusion criteria initially evaluated through abstract and introductory sections of studies, i.e., study type, language, impact factor/HEC recognized journal. Two hundred forty-four studies have initially excluded (with reason) that were not meeting any of the inclusion criteria. Afterward, reviewed 231 full-text studies and an additional 196 studies excluded with documented reasons. Detailed characteristics of excluded studies are presented in the PRISMA flow diagram (Fig.  5 ).

PRISMA flow diagram–systematic review

Data extraction

Data extracted from the selected studies by adopting a data extraction form of Cochrane collaboration [ 32 ]. General information of article, i.e., title, author, publication year and journal name, the objective of the research, study design, statistical techniques, results, and conclusion extracted from selected studies. Required information of all the retained studies presents through textual description and tabulation. Detailed characteristics and extracted data of included studies are presented in the table.

Quality assessment

Quality assessment of all the selected studies is the key phase of systematic review because findings of review depend on it [ 112 ]. Quality assessment is a process through which the researcher evaluates the strength of the body of evidence and establishes the transparency of findings for systematic review [ 145 ]. The quality of all the selected studies has been assessed by using the MMAT critical appraisal tool [ 61 ]. This tool/checklist was designed to appraise and describe the methodological quality of five categories of studies, i.e., qualitative, quantitative, mixed-method study, randomized control trials, and non-randomized control trials. According to the evaluation criteria, the researcher required to provide a detailed article for each defined criteria. Studies that were not clear about any of the defined criteria have excluded. In this study, the quality of the selected studies assessed while extracting the data. Overall, 16 studies have been assessed as low quality: detailed quality characteristics of included studies presented in the table.

Analyze and synthesize evidence

After data extraction, analysis and synthesis are another vital phases of a systematic review. An analysis is a process through which the researcher examines the characteristics of individual studies, identifies its related component, and extracts the possible reasoning [ 20 ]. Whereas synthesis is a process that brings together the findings of all the included studies and establishes a knowledge that cannot be interpreted through the findings of individual study [ 34 ]. Extracted data are analyzed and examine through narrative synthesis. A narrative synthesis is an approach of systematic review which described as a process of exploring the relationship within and between the studies [ 8 ]. Popay et al. [ 113 ] identified four key elements for the narrative synthesis process, i.e., developing a theoretical model, developing a preliminary synthesis of findings of included studies, exploring relationships within and between the studies, and assessing the robustness of synthesis. According to the guideline, it is not mandatory to follow these elements sequentially for conducting narrative synthesis. These could be done iteratively.

Narrative review

Developing a theoretical model.

The development of a theoretical model for synthesis is referred to as developing the “theory of change” to report the systematic review [ 113 ]. It is an element of a systematic review as a whole that defines the objective of the review and it needed to be done before synthesis, and it further contributes while interpreting the review’s findings [ 8 , 113 ]. By following this guideline, this study described the objective of the systematic review above and in this section focused on three elements of the synthesis process.

Developing a preliminary synthesis of findings of included studies

This step aimed to conduct an in-depth analysis of retained studies to find out how the association among considered variables has been established and examined in different studies. For this purpose, required information of all the retained studies, extracted with the help of an adapted data extraction form [ 32 ] and present through textual description and tabulation.

Assessing the robustness of the synthesis

This step is referred to as the methodological quality of all the retained primary studies because the strength of synthesis of the literature depends on this step [ 113 ]. The trustworthiness of synthesis based on methodologies employed to assess the quality of included and measures that have taken to minimize the bias. As mentioned above, all sequential performance of key elements is not necessary; it can be rearranged according to the study. In the present study, description of inclusion and exclusion and techniques to assess the methodological quality of retained studies is a preliminary step of systematic review before proceeding for synthesis that has been described and done. Therefore, to avoid repetition, this element has not been considered here.

Exploring relationships within and between the studies

At this phase, the researcher describes how the relationship among the variables has been identified or examines across the studies. One of the basic description and tabulation relationships among variables has been concluded and hypothesized to develop the conceptual framework of the study.

In line with the objective of a systematic review synthesis of the literature aimed to develop a conceptual framework for the study by analyzing the role of each identified variable and review their association with each other. From the results and conclusions of retained studies, identified relationship among variable has discussed as follows

Perceived organizational politics, negative affectivity, and psychological wellbeing

Negative affectivity is the combination of different unstable emotional states such as anxiety, depression, sadness, and unpleasant mood [ 28 , 71 , 119 ]. It is an emotional response to the experience of unpleasant events or the environment. According to affective events theory, employees’ experience at the workplace about certain events or environments shapes their attitudes and behavior [ 149 ]. Experience depends on perception; employees judge and interpret their experience based on perception. Organizational politics is a perceived phenomenon that shapes employees’ work-related attitudes and behaviors [ 1 ]. As OP is perceived as a negative workplace factor that impacts employees’ emotions and negative affectivity has been identified as an outcome emotional state of employees that occurs due to POP [ 140 ]. Negative affectivity is strongly predicted by negative experiences and it is highly associated with the individual’s physical and psychological health [ 53 ]. Perceived organizational politics evokes the negative affectivity that harms the physical and psychological health of employees.

Similarly, employees’ psychological wellbeing also depends on their perception and the way they appraise a particular situation [ 106 ]. When employees perceive certain situations positively, it enhances their PWB and vice versa. Studies described that psychological wellbeing has a negative association with negative emotions that occurs due to a negative work environment or condition [ 133 ]. When employees perceive workplace events negatively, they experience anxiety, depression, and unpleasant emotions that, as a consequence, harm their psychological wellbeing. From the analysis of retained studies, it has identified that perception of OP causes the negative affectivity that, as a result, affects the psychological wellbeing of employees. Negative affectivity channels the negative impact of POP on the psychological wellbeing of employees. Employees’ psychological wellbeing is also highly associated with WFC, higher PWB reduces the WFC [ 2 , 3 , 105 ]. Stable PWB enables employees to happily participate in both domains of life, i.e., work and family domain. Employees with deteriorated psychological wellbeing due to work role or negative workplace environment pay less attention to their family role that causes WFC. In light of the above arguments, it can be argued that negative affectivity and psychological wellbeing sequentially mediate the relationship between POP and WFC.

Emotional intelligence, negative affectivity, and psychological wellbeing

Emotional intelligence allows an individual to perceive and interpret certain events and react accordingly correctly. It is highly associated with positive emotion and has an inverse relation with negative affectivity [ 13 , 42 , 86 ]. Satisfaction or happiness level of emotionally intelligent employees is high because they can neglect negative emotions and prolong the positive/pleasant state of emotions [ 42 , 56 ]. PWB is a pleasant or satisfied state of mind [ 125 ]. Emotional intelligence controls the negative affectivity by lowering its symptoms such as aggression and anger [ 56 ]. The theory of Salovey and Mayer [ 124 ] claims that emotional intelligence positively predicts the PWB of employees because it holds the flow of negative emotions and nourishes optimism [ 12 , 30 , 33 , 127 ]. The finding of studies has also shown that emotional intelligence moderates the impact of negative emotions that occurs due to negative experience [ 43 , 77 ]. High emotional intelligence increases the level of PWB by reducing stress, which is a component of negative affectivity [ 42 ]. The presence of emotional intelligence enables an individual to overcome adverse effects. It protects and predicts the psychological wellbeing of employees [ 5 , 12 , 67 , 93 , 100 , 123 ]. Based on the findings of studies, it can be conceptualized that emotional intelligence acts as a moderating variable that alleviates the impact of negative affectivity and safeguards the psychological wellbeing of employees.

Perceived organizational support, negative affectivity, and psychological wellbeing

The occurrence of negative affectivity and stability of psychological wellbeing is associated with the cognitive abilities of individuals [ 84 , 143 ]. Cognitive ability is referred to as individuals’ mental capability to perform various psychological activities. A negative experience of employees at the workplace induces negative emotions and interrupts their psychological wellbeing [ 10 ]. Nevertheless, their perception that their organization as supportive reduces the occurrence of various negative work-related emotions such as anxiety, depression, and job insecurity, and raise positive feelings within them [ 24 ]. When employees sense a particular environment or behaviors at the workplace as political and as an unjust that may cause the loss in terms of pay, appraisal, and performance in front accountable authority, it arises the negativity and affects the PWB of employees. However, in the meantime, their perception that the organization is supportive for them, values them, and will never let them suffer from injustice, alleviates the negative consequences of employees’ perception about OP and protect PWB [ 107 ]. Studies described POS as a cognitive factor that relieves the negative impact of employees’ perceptions about OP [ 23 , 36 ]. It is positively associated with employees’ PWB [ 103 ]. Employees’ perception of their organization as supportive when they will have conflict at the workplace, it reduces anxiety, depression, and fatigue [ 92 ]. POS is an organizational construct that acts positively to enhance the PWB [ 108 , 151 ]. Findings of retained literature have not highlighted the association between POS and negative affectivity, but from the support of the above-described literature, it can be argued that POS has a moderating impact on the relationship between POP and PWB.

Workplace social support, negative affectivity, and psychological wellbeing

Emotions and perceptions are psychological factors of individuals that drive their attitudes, behaviors, and actions [ 65 ] p.10). Psychological factors refer to the measure that relates psychological phenomena to the social environment [ 60 ]. These factors occur and escalate within individuals but have an influencing impact of external factors such as social support [ 136 ]. It influences the experience of negative and positive emotions [ 4 ]. Individuals having social support experience positive emotions and pleasant mood [ 15 ]. The presence of social support mitigates the impact of negative and perception and emotions such as stress [ 7 ]. From the findings of studies, it has been identified that social support is positively associated with psychological wellbeing [ 5 , 31 , 52 , 135 ]. According to social support theory, the presence of social support reduces the negative impact of stressful events and protects the psychological and physical health of individuals. Perception of OP is itself a workplace stressor that induces negative emotions and affects the PWB of employees. The presence of social support from coworkers at the workplace reduces the negative impact of POP [ 144 ]. The literature identified that the workplace social support enhances the PWB of employees [ 109 ] and shelters it from the effect of adverse, stressful events, and workplace stressor [ 105 ]. This study identified only a single study that denied the importance of emotional intelligence concerning the PWB [ 13 ]. In the light of the above arguments, it can also be hypothesized that workplace social support acst as a moderator in such a manner that it reduces the intensity of POP and protects the employees PWB.

Studies also identified employees with high emotional intelligence are more inclined toward getting social support from the concerned domain [ 7 , 73 , 74 , 83 ] to protect the PWB from stress [ 153 ].

Based on the above synthesis and hypothesized relationships, the conceptual model for further examination is shown in Fig.  6 .

Conceptual framework

Perceived organizational politics is known as a critical workplace factor. Existing literature highlighted several insights of POP in which most of the researchers examined and extended the existing model of POP proposed by Ferris and Kacmar [ 45 ]. These studies only identified the work-related possible outcomes of POP to understand this phenomenon. This study aimed to examine the existing literature to explain its relationship with a critical non-work-related factor, i.e., WFC.

This study introduced a new insight by systematically combining three literature review approaches to develop a novel conceptual framework. At first, with the help bibliographic co-occurrence network map, this study proved an argument that there are variables that predict the relationship between POP and WFC. But the findings of the bibliographic co-occurrence network map are not enough to identify those specific variables. Therefore, this study is required to conduct a scoping review. Through the scoping review approach, this study comprehensively reviewed all published literature related to antecedents of WFC and outcomes of POP. At first, this study identified the variables that can translate the impact of POP toward WFC. Then through a content analysis, this study further explores and defines those identified variables and also explains the manner through which these variables can logically predict the relationship between POP and WFC. For the variables, no logical literature support was available were ignored. The result of the scoping review revealed five variables that predict the relationship of POP and WFC, i.e., emotional intelligence, negative affectivity, psychological wellbeing, workplace social support, and perceived organizational support. The findings of the scoping review were not sufficient enough to explain how these variables related to each other and form a mechanism through which POP can cause the WFC.

To define the relationship of identified variables with each other and describe how these variables build the relationship of POP and WFC, this study conducted a systematic review. Through this, another comprehensive literature review approach this study proposed hypothesis and formulated a conceptual framework. The findings of the systematic review offered theoretical reasoning to logically define the occurrence of each relationship in the framework. Each identified relation was strongly supported by theories but overall hypothesized mediating mechanism receives support from the conservation of resource (COR) theory. According to theory loss of resources cause stress and harms PWB, employee perceive organizational politics as an unjust behavior at the workplace that can cause loss of resource in term of benefits receiving or will receive at the workplace. This sense of resource due to POP induces negative affectivity in employees [ 72 , 140 ] that harms their PWB [ 106 ]. Due to deteriorated PWB, employees fail to participate in the family domain and experience WFC [ 101 ]. Furthermore review also identified that the presence of social support at work, the higher level of emotional intelligence, and perception about the organization as supportive eliminate the spillover of POP toward WFC.

The findings of this study articulated a new area of inquiry in the field of organizational behavior. It also provided new insight for conducting systematic review by systematically combining three approaches to answer the research objective. This is the first study that assesses the relationship between POP and WFC based on scoping and systematic review and presented a new framework by reviewing all the previous research. This research approach may be adopted for conducting a systematic review according to the research objective. Furthermore, the findings of this study are relevant enough to consider a new area for future research. This model can empirically examine to assess the validity and predictive power of the model and also find that if the proposed relationships are consistent over time.

Availability of data and materials

The data that support the findings of this study are available at would be provided upon request.

Data availability

The data sets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

conservation of resource

data charting form

emotional intelligence

microsoft academy

negative affectivity

organizational citizenship behavior

organizational politics

perceived organizational politics

perceived organizational support

psychological wellbeing

work-to-family conflict

workplace social support

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Acknowledgements

First and foremost, all praise to Almighty Allah, the most gracious and the most merciful for the blessing, wisdom health, and strength to carry out this exciting and challenging M.Phill. journey. I would like to express my profound gratitude to my supervisor for his kind support, supervision, and guidance throughout this journey. I am thankful to him for helping me. Also, I wish to thank my beloved Mother and my dearest Sister for their encouragement, continuous support, and prayers.

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Fiaz, S., Qureshi, M.A. How perceived organizational politics cause work-to-family conflict? Scoping and systematic review of literature. Futur Bus J 7 , 5 (2021). https://doi.org/10.1186/s43093-020-00046-5

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Master of Social Work Clinical Research Papers

A systematic review of the effects of family conflict: focusing on divorce, infidelity, and attachment style.

Jacob B. Borst , St. Catherine University

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Clinical research paper

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Master of Social Work (M.S.W.)

Social Work

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David Roseborough., Ph.D., LICSW

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In this systematic review, I explored the topic of family conflict, focusing on the conflicts of infidelity and divorce, and how these conflicts affect attachment style. The literature review provided information showing that family conflicts may increase the likelihood of children committing at-risk behaviors, have negative impacts on attachment style, and may even influence the success of future relationships. Positive outcomes can also occur from family conflict such as leaving an abusive environment or gaining secure attachment figures such as a stable stepparent. A focused literature search found 25 articles and two books that provided information regarding the effects of family conflict in this area. This research showed that trust and stable friendships during conflict impact attachment style and mitigate against the potentially negative effects of family conflict. Another theme found throughout the research was that there are generational patterns of conflict and that children often learn their behaviors from the generations before. The research supported the theme that attachment style can change over time and that when conflict arises it is important to develop effective repair techniques when communicating with others such as romantic partners or children involved in the family conflict. Lastly, children and adults can be highly adaptive and resilient when experiencing family conflicts and that strength may decrease negative implications such as higher likelihood of relational struggles and patterns of negative conflict.

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Borst, Jacob B.. (2015). A Systematic Review of the Effects of Family Conflict: Focusing on Divorce, Infidelity, and Attachment Style. Retrieved from Sophia, the St. Catherine University repository website: https://sophia.stkate.edu/msw_papers/426

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THE CAUSES OF CONFLICTS WITHIN FILIPINO FAMILIES AND THEIR RESOLUTION STYLES

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