dispositional variables and work–family conflict

Dispositional variables and workfamily conict: A meta-analysis

Tammy D. Allen, Ryan C. Johnson, Kristin N. Saboe, Eunae Cho, Soner Dumani, Sarah EvansThe University of South Florida, Department of Psychology, USA

a r t i c l e i n f o a b s t r a c t

Article history:Received 2 March 2011Available online 15 April 2011

Meta-analysis was used to comprehensively summarize the relationship between dispositionalvariables and both directions of workfamily conflict. The largest effects detected were thoseassociated with negative affect, neuroticism, and self-efficacy; all were in expected directions.In general, negative trait-based variables (e.g., negative affect and neuroticism) appear to makeindividuals more vulnerable to workfamily conflict, while positive trait-based variables (e.g.,positive affect and self-efficacy) appear to protect individuals from workfamily conflict. Inaddition, the different dimensions of workfamily conflict (time, strain, and behavior)exhibited different patterns of relationships with several of the dispositional variables. Nomoderating effects were found for sex, parental status, or marital status. Results support thenotion that dispositions are important predictors of workfamily conflict.

2011 Elsevier Inc. All rights reserved.

Keywords:Workfamily conictPersonalityDispositions

Over the past several decades, industrial and organizational psychologists have become increasingly interested in examiningthe dispositional sources of a wide variety of work behaviors and attitudes. For example, research demonstrates that personalityvariables are linked with job satisfaction (e.g., Judge, Heller, & Mount, 2002), transformational and transactional leadership (e.g.,Bono & Judge, 2004), and job performance (e.g., Barrick & Mount, 1991; Kaplan, Bradley, Luchman, & Haynes, 2009). As such, it isno surprise that dispositional variables have also been investigated as a source of workfamily conict (e.g., Bruck & Allen, 2003;Carlson, 1999; Wayne, Musisca, & Fleeson, 2004).

Workfamily conict is dened as a form of interrole conict in which the role pressures from the work and family domainsare mutually incompatible in some respect (Greenhaus & Beutell, 1985, p. 77). It is grounded in theories of role stress andinterrole conict (Kahn, Wolfe, Quinn, Snoek, & Rosenthal, 1964). Current research distinguishes the direction of the conict. Thatis, family can interfere with work (FIW) and work can interfere with family (WIF; Mesmer-Magnus & Viswesvaran, 2005). Forpurposes of clarity, throughout the rest of this paper we use the term workfamily conict to refer to the workfamily conictliterature in general and use the termsWIF and FIWwhen referring to the specic direction of the conict (work-to-family versusfamily-to-work, respectively).

The purpose of the current article is to extend what is known about the association between dispositions and workfamilyconict. We believe that the lack of a more precise understanding of the full array of predictors of workfamily conict has stiedworkfamily research and practice. Theoretical models of the workfamily interface have failed to take into account the role ofdispositions and have focused primarily on situational demands (e.g., Ford, Heinen, & Langkamer, 2007; Frone, Russell, & Cooper,1992). Moreover, recommendations for practice have centered on the implementation of organizational practices such as exiblework arrangements (Hammer, Neal, Newsom, Brockwood, & Colton, 2005; Kossek, Lautsch, & Eaton, 2006). Although exible workarrangements can be advantageous to organizations in terms of absenteeism and productivity (e.g., Baltes, Briggs, Huff, Wright, &Neuman, 1999; Gajendran & Harrison, 2007), the benets to individuals in terms of averting workfamily conict have beenmixed (Allen & Shockley, 2009). It is possible that dispositional variables may be stronger determinants of workfamily conictthan are situational demands, yet they have received relatively much less research attention. A better understanding of the role of

Journal of Vocational Behavior 80 (2012) 1726

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dispositions as they relate to workfamily conict should be useful toward the identication of additional approaches tomanagingthe workfamily interface.

Accordingly, the current study has several objectives. We provide the rst comprehensive meta-analysis of dispositionalvariables and workfamily conict. In addition, we examine several moderators. Specically, we investigate the dimension ofconict (time, strain, or behavior) and demographic variables (sex, parental status, and marital status). Admittedly, thecontribution of our research is primarily empirical rather than theoretical. However, investigation of dispositional variablesassociated with workfamily conict has important implications with regard to further development of theoretical models.

Theoretical support for linking workfamily conict and dispositional variables

There are several theoretical reasons to expect relationships between workfamily conict and dispositions. One is based onresource drain theory (Rothbard, 2001; Staines, 1980). Resource drain theory posits that individuals have a limited amount ofresources to devote to various roles; thus, if one role requires a large amount of resources, performance in other roles will suffer.From a broad perspective, resources can be physical, psychological, or social features that aid in goal completion and/or demandreduction (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). Frone (2003) has suggested variables such as positive affect andextraversion may function as individual resources that allow individuals to cope with problems at work and home.

Differential exposure and differential reactivity are additional mechanisms that can explain the link between dispositions andworkfamily conict (Bolger & Zuckerman, 1995). The differential exposure perspective suggests that some individuals are morelikely to drift into highly stressful situations than are others. Dispositions can impact the environments that individuals choose forthemselves. For example, certain dispositional variables may predispose individuals to select supportive work environments and/or develop personal support networks that make it easier to manage work and family roles (Friede & Ryan, 2005). Differentialreactivity suggests that some individuals are more vulnerable to stressful situations than are others. The impact of stressfulsituations can also differ across individuals. Dispositional variables can determine whether the demands associated with work andfamily are deemed as manageable or as conicting (Friede & Ryan).

Brief summary of existing research

Given the connection betweenworkfamily conict and the stressorstrain literature, it is perhaps not surprising that negativeaffect and neuroticism have been themost frequently studied dispositional variables within theworkfamily literature. It has beenproposed that negative affect impacts how individuals perceive their jobs and other life experiences and is associated with reportsof stressors and strains (Spector, Zapf, Chen, & Frese, 2000). Multiple studies have shown that individuals with greater negativeaffect also report greater workfamily conict (e.g., Bruck & Allen, 2003; Carlson, 1999; Stoeva, Chiu, & Greenhaus, 2002).Similarly, neuroticism has been repeatedly linked to bothWIF and FIW (e.g., Grzywacz &Marks, 2000;Wayne et al., 2004). Severalstudies have examined all of the Big Five variables in relation to workfamily conict. Both Bruck and Allen (2003) andWayne etal. (2004) reported that agreeableness and conscientiousness related to workfamily conict. Specically, less agreeableindividuals reported greater workfamily conict, while more conscientious individuals reported less workfamily conict.Positive affect has also been negatively associated with both WIF and FIW (e.g., Karatepe & Uludag, 2008). In addition to affect-oriented variables, individual differences associated with self-concept (e.g., self-efcacy), control beliefs (locus of control), andpsychological resiliency (e.g., optimism) have been investigated in relation to workfamily conict (e.g., Aryee, Srinivas, & Tan,2005; Beauregard, 2006; Wallace, 2001).

Based on the aforementioned theory and research, in the current study we propose that dispositional variables that predisposeindividuals to negative exposures and reactions (e.g., negative affect, neuroticism, and Type A personality) will be associated withgreater WIF and FIW. Personality variables that serve as resources for individuals, predisposing them to positive exposures andreactions (e.g., positive affect, agreeableness, internal locus of control, extraversion, self-esteem, self-efcacy, and optimism), willbe associated with less WIF and FIW. Because our intent was to conduct a comprehensive study of dispositions and workfamilyconict, we also included other variables investigated in previous studies (e.g., openness to experience) but we pose no a prioritheoretically-based expectation that they relate to either direction of workfamily conict.

Moderators

Several moderators are investigated in an exploratory manner. We focus on two groups of moderators, the dimensions ofworkfamily conict and demographics. The rst category of moderators relates to the different forms of workfamily conict. Asnoted previously, there are two directions by which workfamily conict ows (work interferes with family and family interfereswith work). In addition to direction, researchers also recognize multiple dimensions or types of conict. The most recognizeddimensional structure is that developed by Greenhaus and Beutell (1985). Greenhaus and Beutell posit that there are three typesof workfamily conict, time-based, strain-based, and behavior-based. Time-based conict happens when time spent on activitiesin one role impedes the completion of responsibilities in another role. Strain-based conict occurs when pressures from one roleinhibits the fulllment of obligations in another role. Lastly, behavior-based conict occurs when behaviors exhibited in one roleare incompatible or incongruent with behavior patterns needed in the other role.

The second set of moderators we investigate are demographic variables, which include sex, parental status, and marital status.These variables are among those most commonly studied in workfamily research. Sex in particular has been extensively

18 T.D. Allen et al. / Journal of Vocational Behavior 80 (2012) 1726

investigated in relation to work and family roles (Korabik, McElwain, & Chappell, 2008; Powell & Greenhaus, 2010). Although it iscommonly thought that because women tend to have greater family demands while men tend to have greater work demands,women experience greater FIW than do men and men experience greater WIF than do women, meta-analytic research nds verysmall effects associated with these relationships (Byron, 2005). The effects associated with parental status and workfamilyconict tend to bemore robust. That is, the number of children at home consistently relates to greater reports of bothWIF and FIW(e.g., Bruck & Allen; Byron, 2005; Carlson, 1999). With regard to marital status, members of a dual-earner couple are thought toexperience more workfamily conict than are members of a single-earner couple (e.g., Higgins & Duxbury, 1992), but meta-analytic research shows no difference between the two (Byron). Thus, we investigate sex, parental status and marital status asmoderators because it may be that, in combination with personality characteristics, demographic variables have an inuence. Forexample, the slight tendency for women to report greater FIW and for men to report greater WIF may be enhanced when coupledwith characteristics that predispose individuals to experience workfamily conict (e.g., neuroticism). More specically, therelationship between neuroticism andWIFmay be stronger among samplesmore highly dominated bymenwhile the relationshipbetween neuroticism and FIW may be stronger among samples more highly dominated by women.

Method

Literature search

We searched the PsycINFO database by coupling keywords for dispositions and workfamily. Dispositional keywords includedpersonality, trait, Eysenck 3 factor, Big 5 (and each dimension by different names; e.g., intellect, openness to experience,neuroticism, and emotional stability), negative affect, positive affect, Type A, locus of control, and optimism. Workfamilykeywords included workfamily conict, workfamily balance, workfamily interference, negative spillover, worklife conict,worklife balance, worknonwork conict, and worknonwork balance. We also contacted researchers in the workfamily area,reviewed the content of the Society for Industrial and Organizational Psychology and Academy of Management conference programsfrom the last ve years, and conducted manual searches of reviews of the literature (e.g., Eby, Casper, Lockwood, Bordeaux, &Brinley, 2005).

Inclusion criteria

To be considered for inclusion, the study had to examine the relationship between at least one of the dispositional variables andat least one directional form of workfamily conict. The study also had to include the information necessary to calculate acorrelation between the dispositional variable and workfamily conict. For studies that met the inclusion criteria but did notreport usable statistics, we attempted to obtain relevant data by contacting the study authors.

A total of 75 independent samples from 68 articles met the inclusion criteria.

Study variables

Workfamily conictIn most cases, authors reported an overall assessment of WIF or of FIW. When more than one dimension of WIF/FIW was

measured, but no higher level aggregate was included, we averaged the dimensions (e.g., time-based, strain-based, and behavior-basedWIF/FIW) using the formula provided by Hunter and Schmidt (1990, p. 457) that takes into account intercorrelations amongdimensions. Purely bidirectional/global measures of workfamily conict were excluded. To conduct the time-, strain-, andbehavior-based moderator analyses, we also coded effects between each of these dimensions and the dispositional variable whenavailable.

DispositionsThere has been some controversy in the literature over the use of broad measures such as the Big Five versus the use of more

narrow traits, with advocates on both sides (Ones & Viswesvaran, 1995; Schneider, Hough, & Dunnett, 1996). To provide the mostne-grained and comprehensive assessment of relationships, in all cases we kept the dispositional variables in their original formas explicitly measured in the primary studies from which the effects were drawn.

Demographic moderatorsSex was coded as the percentage of male participants from each sample. Parental status was coded as the percentage of parents

from each sample. Marital status was coded as the percentage of married participants in the sample.

Coding of studies

Each study was independently coded by two of the study authors who recorded sample sizes and correlations. Codingdiscrepancies were few, but when they did occur consensus was reached through discussion and re-examination of the data.

19T.D. Allen et al. / Journal of Vocational Behavior 80 (2012) 1726

Statistical procedures

Statistics were computed via the Comprehensive Meta-Analysis software package (Borenstein, Hedges, Higgins, & Rothstein,2005; Pierce, 2008). Our indicator of effect size across all primary studies and that used in the analyses was the correlationcoefcient. The random effects model was used.

Results

For each meta-analytic relationship, we report the total sample size across all studies (N), the total number of independentstudies associated with the reported relationship (k), and the sample-weighted correlation (rxy). We used the 95% condenceinterval to determine whether effect sizes were statistically signicant. Condence intervals that did not include zero weredeemed statistically signicant. To assess whether or not the studies could be assumed to reect a single population of effect sizes,we calculated the Q-value. A signicant Q-value indicates greater than chance variation in effect sizes, implying the presence ofmoderators (Aguinis et al., in press). Tau2 (2) was used to report the degree of between study variance. In terms of interpretingeffect sizes, an absolute value of .09 to .23 was regarded as small, .24 to .36 as medium, and .37 or higher as large (Cohen, 1988).

Main effects

Results are shown in Table 1.With regard toWIF, with the exception of openness to experience, proactive personality, and self-esteem, each of the effect sizes differed from zero. Small effect sizes were associated with agreeableness, conscientiousness,extraversion, locus of control, positive affect, and self-esteem. Medium effect sizes were found for negative affect, neuroticism,optimism, self-efcacy, and Type A. All effects were in expected directions. It should be noted that although the effect sizeassociated with self-esteem was considerable in magnitude (.18), the condence interval associated with the effect includedzero, suggesting considerable heterogeneity in the effects observed. Indeed, based on signicant Q-values, the presence ofmoderators was suggested for each of the relationships.

With regard to FIW, with the exception of locus of control, openness to experience, and self-esteem, each of the effect sizesdiffered from zero. Small effects were observed for agreeableness, conscientiousness, locus of control, positive affect, and self-esteem. However, the condence intervals associated with locus of control and self-esteem included zero. Moderate effects wereassociated with negative affect, neuroticism, and self-efcacy. All effects were in the expected direction. Based on signicant Q-values, the presence of moderators was suggested for each of the relationships with the exception of extraversion.

Weexamined thendings to determine if therewere signicant differences in effects betweenWIF andFIW. The difference in effectsize ranged from .01 to .07with an average effect size difference of .03. Moreover, the differences did not tend toward larger effects forone direction of workfamily conict versus the other. In general, the personality variables related similarly toWIF as they did to FIW.

Dimensions of workfamily conict

Separate analyses were conducted for each dimension of WIF and FIW where k3. Results for time, strain, and behavior areshown in Tables 2, 3 and 4, respectively. We note that these analyses are based on a small number of primary studies, thus thendings should be interpreted with caution.

Comparisons of the magnitude of effect sizes across the three dimensions revealed several interesting patterns. First, withregard to WIF, the effect size associated with agreeableness and behavior-basedWIF was appreciably larger than those associated

Table 1Meta-analytic effect sizes between personality variables and WIF/FIW.

WIF FIW

Personality variables N k Rxy Q 2 CI N k Rxy Q 2 CI

Agreeableness 4514 12 .17 20.58 .003 .22, .13 3901 9 .19 21.00 .005 .24, .13Conscientiousness 6427 21 .16 78.87 .011 .21, .11 4494 14 .20 43.33 .008 .25, .14Extraversion 5112 14 .09 26.36 .003 .14, .05 4849 13 .07 16.13 .001 .11, .04Locus of control 8140 13 .13 167.59 .025 .22, .04 5693 9 .09 88.54 .024 .19, .02Negative affect 6993 25 .32 118.70 .015 .26, .36 3035 15 .33 59.94 .017 .26, .40Neuroticism 9085 27 .31 117.58 .011 .27, .36 6566 20 .27 81.94 .011 .21, .32Openness to experience 4026 9 .02 27.53 .007 .09, .05 4026 9 .05 21.19 .005 .11, .01Optimism 1784 4 .29 8.13 .005 .38, .20 2 Positive affect 2223 10 .20 35.62 .014 .28, .11 1552 8 .22 17.99 .008 .30, .14Proactive personality 1385 4 .01 37.20 .047 .23, .21 2 Self-efcacy 1947 7 .24 28.37 .015 .34, .14 1314 7 .31 54.24 .045 .45, .15Self-esteem 836 5 .18 39.36 .055 .38, .03 653 4 .14 61.98 .125 .46, .22Type A 1321 4 .26 32.51 .041 .06, .44 2

Notes: Rxy = uncorrected mean sample weighted correlation, N = total sample size, k = number of independent samples, Q = Q statistic, 2 = between studyvariance, CI = 95% condence interval. pb .05.


with strain- or time-based WIF (difference of .13 across both). The effect size associated with neuroticism and strain-based WIFwas considerably larger than that associated with neuroticism and time-based WIF (difference of .19). With regard to FIW, theeffect sizes associated with neuroticism and strain-based FIW as well as behavior-based FIW were notably larger than the effectsize associated with neuroticism and time-based FIW (difference of .11 and .08, respectively).

While the differences between effect sizes involving overall WIF versus overall FIW were negligible, comparisons at thedimension level revealed several substantial differences. The effect sizes associated with conscientiousness were notably larger forFIW than for WIF with regard to time-based conict (difference of .15) and strain-based conict (difference of .13). Similarly theeffect sizes associated with agreeableness were considerably larger for FIW than for WIF with regard to time-based conict(difference of .08) and strain-based conict (difference of .10). Finally, the effect size associated with neuroticism andWIF strain-based conict was larger than that associated with neuroticism and FIW strain-based conict (difference of .10).

Demographic moderators

The regression approach based on the method of moments was used to test the demographic moderators. Separate regressionmodels were estimated using the percentage variables as predictors. If the percentage variable is a signicant predictor of themeta-analytic correlation coefcient examined, it indicates that the predictor (sex, parental status, or marital status) moderatesthat particular relationship. A relationship had to have been examined in a minimum of 10 independent samples to be included inthe tests for moderation. Results for sex, parental status, and marital status are shown in Tables 5, 6, and 7, respectively. Nosignicant moderating effects were found.

Discussion

The objective of the current study was to quantify the magnitude of the relationships between dispositional variables andworkfamily conict. Findings suggest that dispositions are important predictors of both WIF and FIW. Our results yield keyinsights into the dispositional variables that serve as risk factors as well as those that appear to serve a protective function againstworkfamily conict. Results also suggest variation in the relationships across the different dimensions of workfamily conict.

The effect sizes associated with negative affect and neuroticism were robust in relation to both WIF and FIW, suggesting thatthey may serve as risk factors predisposing individuals to report workfamily conict. Negative affect/neuroticism has long beenimplicated in the stressorstrain process (Watson, Pennebaker, & Folger, 1987). Negative emotional reaction patterns such asemotional distress, tendency to worry, and hypervigilance, all of which reect negative affect, have been associated with a wide

Table 2Meta-analytic effect sizes between personality variables and time-based WIF/FIW.

Time-based WIF Time-based FIW


Agreeableness 953 3 .12 4.25 .004 .21, .02 953 3 .20 7.26 .008 .31, .08Conscientiousness 1797 6 .15 13.52 .006 .22, .07 953 3 .30 7.24 .008 .40, .18Extraversion 1244 4 .03 .50 .000 .08, .03 953 3 .07 1.27 .000 .13, .01Locus of control 1168 4 .03 3.23 .000 .09, .03 877 3 .09 .19 .000 .15, .02Negative affect 1347 5 .16 16.56 .013 .04, .27 1 Neuroticism 1244 4 .20 10.15 .008 .10, .29 953 3 .18 11.21 .015 .03, .32Openness to experience 953 3 .02 10.37 .013 .16, .13 2


Table 3Meta-analytic effect sizes between personality variables and strain-based WIF/FIW.

Strain-based WIF Strain-based FIW


Agreeableness 953 3 .12 .47 .000 .19, .06 953 3 .22 6.25 .007 .33, .11Conscientiousness 1797 6 .16 17.33 .009 .25, .08 953 3 .29 3.19 .002 .37, .22Extraversion 1244 4 .03 .98 .000 .09, .02 953 3 .01 5.68 .006 .12, .10Locus of control 1605 4 .19 20.57 .015 .32, .06 1 Negative affect 2195 8 .21 58.67 .029 .08, .33 1 Neuroticism 1244 4 .39 22.85 .022 .25, .51 953 3 .29 5.76 .006 .19, .39Openness to experience 953 3 .09 9.33 .012 .22, .05 953 3 .15 7.08 .008 .27, .03Positive affect 1024 3 .27 7.89 .011 .40, .13 1

Notes: Rxy = uncorrected mean sample weighted correlation, N = total sample size, k = number of independent samples, Q = Q statistic, 2 = between studyvariance, CI = 95% condence interval. p b.05.


range of dysfunctions including depression, psychosomatic complaints, and poor coping (e.g., O'Brien & DeLongis, 1996). What isless clear is the process that explains this link. Judge, Erez, and Thoresen (2000) have argued that negative affect is likely to becorrelated with actual and subjective differences between stressors and strains. Along these lines, research is needed to helpdetermine if observed relations between negative affect/neuroticism and workfamily conict reect differential reactions ordifferential exposure. That is, do individuals higher in negative affect/neuroticism over-report the occurrence of workfamilyconict due to heightened perceptions of stressors and strains, supporting the differential reaction perspective, or are those higherin negative affect/neuroticism more genuinely vulnerable to conicting work and family demands, supporting the differentialexposure perspective (Bolger & Zuckerman, 1995).

The dimension results provide some tentative initial insights into this issue. The ndings generally suggest that relationshipsinvolving neuroticism were weakest in magnitude for time-based conict and strongest in magnitude for strain-based conict.These ndings can be interpreted to support the differential reaction hypothesis in that strain-based conict seems more inlinewith reacting to the stress associated with managing multiple roles while time-based conict seems more closely tied to exposureto environmental demands. However, as noted, these associations are speculative and require further research that candisentangle objective and subjective experiences of workfamily conict.

Our ndings indicate that several dispositional characteristics may help protect individuals from workfamily conict.Specically, positive affect, internal locus of control, self-efcacy, and optimism appear to help individuals avert conicting workand family demands. These variables may be associated with the development of the psychological resiliency needed to help copewith the challenges of competing work and family demands. These ndings also suggest that psychological capital may play a rolein managing work and family. Psychological capital is an emerging construct that consists of the state-like positive resources ofefcacy, hope, optimism, and resilience (Luthans, Avolio, Avey, & Norman, 2007). It has been related to employee attitudes,behavior, performance, and well-being (e.g., Avey, Luthans, Smith, & Palmer, 2010; Norman, Avey, Nimnicht, & Pigeon, 2010). Aline of research investigating workfamily conict and psychological capital seems worthwhile in that psychological capital isconsidered open to development and thus potentially amenable to training.

Agreeableness and conscientiousness were also robustly related to both WIF and FIW, particularly to time- and strain-basedFIW. Agreeableness may be helpful in garnering resources such as the support of friends, family members, and coworkers. This isimportant in that such support has consistently been related to less workfamily conict (e.g., Byron, 2005). Given thatconscientiousness has been associated consistently with performance across a wide variety of jobs (Barrick & Mount, 1991), itseems likely that more conscientious individuals also possess the skills to better manage time, multiple role responsibilities andconicts.

Limitations

Several limitations of this study require discussion. The ndings should be viewed within the context of the limitationsassociated with the primary research aggregated in this study. Most of the primary studies are based on cross-sectional research

Table 4Meta-analytic effect sizes between personality variables and behavior-based WIF/FIW.

Behavior-based WIF Behavior-based FIW


Agreeableness 953 3 .25 .64 .000 .31, .19 953 3 .24 4.51 .004 .33, .15Conscientiousness 1797 6 .22 15.64 .007 .30, .13 953 3 .27 9.73 .012 .40, .13Extraversion 953 3 .05 6.34 .007 .17, .06 953 3 .05 4.43 .004 .14, .05Negative affect 1347 5 .25 22.42 .019 .12, .38 1 Neuroticism 953 3 .25 28.90 .043 .01, .46 953 3 .26 24.51 .036 .05, .49Openness to experience 953 3 .13 4.57 .004 .22, .03 2


Table 5Percentage of male participants in study sample as a moderator of effect size.

WIF FIW

Personality variables k B 2 k B 2

Agreeableness 11 .00059 .00383 9 Conscientiousness 19 .00046 .01205 12 .00203 .00844Extraversion 13 .00042 .00165 12 .00012 .00161Locus of control 13 .00308 .01509 9 Negative affect 24 .00051 .01504 15 .00120 .01750Neuroticism 26 .00096 .01161 19 .00202 .01132

Notes: k = number of independent samples, B = unstandardized regression coefcient, 2 = between study variance.


designs. Although our characterization of dispositional variables as predictors of workfamily conict is theoretically sound, giventhe limitations associated with cross-sectional designs, caution is needed regarding the inferences drawn. Another issue is thatmost of the primary studies are based on self-report data that was used for both the predictor and outcome variables. This raisesconcerns regarding the potential for common source bias to inuence the size of the relationships observed. In the interest of beingcomprehensive, we kept the dispositional variables in their original form as opposed to aggregating to higher-level Big Fivevariables. Along these lines, we included variables for which there were few primary studies. The small number of primary studiesin some cases raises concerns regarding second-order sampling error. However, such reporting also helps demonstrate whereadditional primary research is needed.

Implications for practice and theory

Not withstanding these limitations, our ndings have implications for both theory and practice. From an applied perspective,training may be offered that helps individuals develop effective skills and strategies for managing work and family. Most practiceimplications with regard to the reduction of workfamily conict have been directed at changing the situation throughimplementation of practices such as exible work arrangements. The effect sizes observed in the current study are considerablylarger than those found for exible work practices. For example, the meta-analytic effect size associated with exibility and WIFhas been estimated at .01 while that associated with FIW has been estimated at .04 (Mesmer-Magnus & Viswesvaran, 2006).Clearly approaches are needed that simultaneously take into account changes that can bemade in thework environment aswell asindividual dispositions. The implementation of family-supportive work practices without consideration of employee dispositionaldifferences may be inhibiting our ability to fully understand the potential benets of such practices.

From a theoretical perspective, our ndings underscore the importance of including dispositional variables in models of theworkfamily interface. Some evidence exists that dispositional variables can contribute unique variance toward the explanation ofworkfamily conict beyond family and work situational variables (Carlson, 1999). Dispositions likely play the role of commonantecedent in predicting reports of work stressors, family stressors, and workfamily conict (Frone, 2003; Stoeva et al., 2002).Expanded theoretical models are needed that recognize the interplay between individual and situational variables.

Future research

The ndings pave the way for a variety of additional future research directions. As research on dispositions and workfamilyconict continues to develop it will be important to identify moderating variables. Our results indicated that the majority of therelationships investigated are likely moderated. However, we found no evidence that the demographic factors we examined act asmoderators. Research investigating personsituation interactions seems a potentially fruitful area for future research. Forexample, there is some evidence that the relationship between demands and FIW is stronger for individuals higher in negativeaffect than for those lower in negative affect (Stoeva et al., 2002).

Our review and analyses revealed several dispositional variables that have received little study but appear promising. Forexample, optimism showed a moderate in magnitude relationship with WIF, but this relationship was based on only four studies.Moreover, we were not able to analyze the relationship between optimism and FIW due to the fact that only two primary studies

Table 6Percentage of parents in study sample as a moderator of effect size.

WIF FIW


Conscientiousness 15 .00090 .00763 11 .00119 .00802Extraversion 14 .00017 .00143 12 .00022 .00176Negative affect 18 .00166 .01066 11 .00245 .01320Neuroticism 23 .00020 .01388 17 .00086 .01280

Notes: k = number of independent samples, B = unstandardized regression coefcient, 2 = between study variance.

Table 7Percentage of married participants in study sample as a moderator of effect size.

WIF FIW


Conscientiousness 18 .00007 .01271 11 .00154 .01010Extraversion 13 .00167 .00180 11 .00029 .00231Negative affect 18 .00276 .01059 11 .00248 .01532Neuroticism 22 .00152 .01326 17 .00224 .01087

Notes: k=number of independent samples, B=unstandardized regression coefcient, 2=between study variance.


could be located. In addition, further research at the dimension level of workfamily conict is needed. Our dimension results werebased on a small number of studies, but suggest that the type of workfamily conict makes a difference in the relationshipsobserved. As noted previously, dimension research may also yield insight into the process by which dispositions relate to theexperience of workfamily conict.

The current study summarizes knowledge regarding the relationship between dispositions and workfamily conict. In futurestudies, it would also be useful to examine the relationship between dispositions and the positive side of the workfamilyinterface. In our search of the literature we detected only a handful of such studies (e.g., Wayne et al., 2004). It seems likely thattraits such as positive affect and optimism predispose individuals to experience positive spillover between work and family roles.

In conclusion, the present study provides the rst comprehensive meta-analysis of relationships between dispositionalvariables, both directions of workfamily conict, and moderators. Results suggest small to moderate effect sizes overall. Theresults help demonstrate which variables play a more or less important role in reports of workfamily conict and thus meritfurther research attention. Further research of this nature is needed to fully understand the underpinning of workfamily conict.

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Dispositional variables and workfamily conflict: A meta-analysisTheoretical support for linking workfamily conflict and dispositional variablesBrief summary of existing researchModeratorsMethodLiterature searchInclusion criteriaStudy variablesWorkfamily conflictDispositionsDemographic moderators

Coding of studiesStatistical procedures

ResultsMain effectsDimensions of workfamily conflictDemographic moderators

DiscussionLimitationsImplications for practice and theoryFuture research

References

dispositional variables and work–family conflict

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