Contents lists available at SciVerse ScienceDirect
Journal of Vocational Behavior
j ourna l homepage: www.e lsev ie r .com/ locate / jvb
From “work–family” to “work–life”: Broadening ourconceptualization and measurement☆
Jessica Keeney a,⁎, Elizabeth M. Boyd b, Ruchi Sinha c, Alyssa F. Westring d, Ann Marie Ryan e
a APTMetrics, 150 E. Ponce de Leon Ave., Suite 310, Decatur, GA 30030b Department of Psychology, Indiana University-Purdue University Indianapolis, 402 N. Blackford St., Indianapolis, IN 46202, USAc Organizational Behavior Area, Indian School of Business, Hyderabad, AP 500032, Indiad Department of Management, DePaul University, 1 E. Jackson Blvd. Chicago, IL 60604e Department of Psychology, Michigan State University, East Lansing, MI 48824, USA
a r t i c l e i n f o
☆ The research project described in this paper was fpresented at the annual conference for the Academy o⁎ Corresponding author at: Department of Psycholo
Article history:Received 22 September 2012Available online 27 January 2013
Despite frequent reference to “work–life” issues in the organizational literature, little theoretical orempirical attention has been paid to nonwork areas beyond family. The purpose of the researchdescribed here is to move beyond work–family conflict to a broader conceptualization andmeasurement of work interference with life. A measure of work interference with life across eightnonwork domains and two forms of interference (strain- and time-based) was developed andtested in two studies of 1811 and 3145 university alumni frommultiple organizations and diverseoccupations. In Study 1 evidence for the dimensionality of this measure is presented. In Study 2work interference with life demonstrated incremental validity above and beyond work inter-ference with family with respect to job satisfaction, turnover intentions, life satisfaction, andmental health. The results of relative importance analyses are presented for the same outcomes.This research has implications for designing more inclusive work–life policies and practices andpresents a new lens for understanding individual differences at the work–life interface.
Keywords:Work interference with lifeWork–family conflictLife domains
“My job causes me to cancel dates with friends, work late, miss my kids' activities, not be able to work out, not schedule doctorappointments. It affects all areas of my life because I'm either working long hours or too stressed to participate. Sometimes I try toprioritize one area that becomes important for a period of time… but it always seems to result in a backlog at work—whichresults in more stress, so I don't really enjoy the activity that is supposed to be rewarding.”– 42-year old Senior Vice President,Mother of two
The above quote from one of our study participants represents the realities of attempting to balance a demanding job and a full lifeoutside of work. Importantly, the quote suggests that work has the potential to interfere with many areas of nonwork life (e.g., health,friendships). However, over the past several decades, organizational researchers interested in the intersection between employees'work and personal lives have primarily focused on thework and family domains (e.g., Byron, 2005; Eby, Casper, Lockwood, Bordeaux, &Brinley, 2005). Attention to the work–family interface has been fueled by the changing nature of workplace demographics (e.g., morewomen are fully employed than ever before). While reducing work–family interference remains a valid and important concern, theliterature could benefit from a recognition of the diversity that exists in employees' pursuits outside of work.
unded by the Society for Human Resource Management Foundation. A previous version of this article wasf Management, Chicago, Illinois, August 2009.gy, 316 Physics Road, East Lansing, MI 48824, USA.ney), [email protected] (E.M. Boyd), [email protected] (R. Sinha), [email protected]
222 J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
We respond to numerous calls by organizational scholars to broaden the notion of work–family conflict to account fornonwork areas beyond family (Bellavia & Frone, 2005; Carlson & Kacmar, 2000; Crooker, Smith, & Tabak, 2002; Sturges & Guest,2004). Research on social identity suggests that there is a hierarchy of identities possessed by any individual (e.g., worker, parent,friend, volunteer), with some more important than others (McCall & Simmons, 1978). A broader approach is less presumptivethan traditional work–family studies about what the most important identities for individuals are, and allows for an examinationof the total hierarchy. Our purpose is to conceptualize a richer construct that is more representative of employees' experiences atthe intersection of work and life outside of work.
There is also a practical basis for examining work interference with life as opposed to work interference with family specifically.Many of the companies on Fortunemagazine's “100 Best Companies toWork For” have embraced a broader perspective in policies andprograms as work–life focused. Respect for a variety of employee needs is crucial in an increasingly diverse workforce (Wells, 2007).Childlessness among employees has been increasing, especially among femalemanagers (Wood&Newton, 2006). The Bureau of LaborStatistics reported that in 2004, 64% of theU.S.workforce does not have dependent children at home. Also, a large portion of employeesare single and live alone with some U.S. reports providing estimates as high as 40% (Casper, Weltman, & Kwesiga, 2007). Institutinghuman resource policies that potentially neglect or even disadvantage single or childless employees creates the risk of backlash(Casper, Eby, Bordeaux, Lockwood, & Lambert, 2007; Nord, Fox, Phoenix, & Viano, 2002; Ryan & Kossek, 2008). Not only has thedefinition of family for leave policies becomemore flexible, but practices such as allowing employees paid volunteer time or open-usesabbaticals are becoming more commonplace (Schramm, 2009). Despite the presence of these forward practices, however, theorganizational research literature, while beginning to adopt the term “work–life,” actually rarely expounds on and measures thisbroader conceptualization (Crooker et al., 2002). This disconnect between research and practice leaves HR professionals with lessguidance on how to effectively design, implement, and evaluate inclusive policies and programs.
Based on previous definitions of work–family conflict offered by Greenhaus and Beutell (1985), we define work interferencewith life (WIL) as difficulty participating in nonwork domains by virtue of participation in the work domain. This definition is focusedon a person's ability to fulfill their desired involvement in a domain and meets its obligations rather than their enjoyment of thedomain, which is seen as a potential consequence of WIL. We focus on only one direction of interference (work to life) as that hasbeen found to be stronger (Frone, 2003), as well as more feasibly influenced by organizations. While cognizant that “work” is apart of “life,” we adopt the term work interference with life in keeping with the common framing of policy and initiatives inorganizational settings. To support this broader conceptualization, the present article describes the development and validation ofa measure of work interference with life domains. We present the results from two studies in which we evaluate the internalstructure of the measure and demonstrate explanatory power beyond that of work–family conflict.
1. Prior measurement of WIL
We conducted a literature review for existing scales of work interference with life using PsycInfo and the following search terms:work–life, work/nonwork, work–home, andwork–personal life (eachwith conflict, balance, interaction, interference, integration).Wespecifically sought scales that measured a construct broader than work–family conflict. We included ‘balance’ in our search becausethe term is often used loosely (i.e., sometimes in place of conflict), but we did not review measures of balance that include aspects offacilitation or overall balance perceptions.
The first category of scales we found measure global perceptions of work demands interfering with personal life in general. Anexample is the scale developed by O'Driscoll, Ilgen, and Hildreth (1992), in which all items require respondents to make a globalassessment of howwork demands interferewith off-job activities (e.g., “I have to put off non-work things I would like to do because ofmywork requirements”). Another example of the global approach is the scale by Fisher, Bulger, and Smith (2009). In addition, severalauthors have modified established work–family conflict scales to assess global work–life conflict. At least three studies of work–lifeconflict have used the Kopelman, Greenhaus, and Connolly (1983) work–family conflict scale modified to include “friends” after“family” in certain items (Gutek, Searle, & Klepa, 1991).
The global perceptions approach does not assess the same construct as would be measured by asking about specific life domains(Diener, Emmons, Larsen, & Griffin, 1985). Domain-level measurement has several unique advantages. First, domain-based scalesprovide diagnostic information about specific aspects of life whereas global scales preclude any conclusions about which life domainsare affected. Individuals may experience interference betweenwork and one aspect of life (e.g., education), but not with other aspectsof life (e.g., friendships). Due to the diversity of individuals' nonwork interests, a global score for nonwork conflict is conceptuallyconfusing in that it may reflect conflict with one domain the individual views as particularly central, (e.g., family) or amental average.Furthermore, scales commonly used to measure global work–life conflict (e.g., Gutek et al., 1991) contain items that refer to “family/friends,” thereby dissuading respondents from considering other nonwork contexts.
Second, assessingwork interferencewith respect to other domains besides family can informmore inclusivework–life policies. Thesupports offered may be tailored to different groups of employees depending on which domains are most heavily impacted by theirwork demands. Employees seeking to earn an advanced degree may appreciate educational reimbursement, those with youngchildren may value on-site childcare, and others who desire more community involvement may welcome extra vacation days inexchange for volunteering.
Third, it has been argued that people rely on their current mood state whenmaking global judgments as a means to simplify whatcould be an otherwise complex task to perform mentally. In contrast, domain-level measures simplify the process of formingjudgments. Respondents can base their judgments on domain-specific circumstances and criteria and are less likely to take cognitiveshortcuts tainted by transitory mood (Schwarz & Strack, 2003).
223J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
A few scales already exist that focus on assessing conflict between work and specific life domains. For example, Small and Riley(1990) examined work interference with marriage, parenthood, homemanagement, and leisure. Premeaux, Adkins, and Mossholder(2007) examined work interference with a similar subset of nonwork contexts: the spouse, parent, elder care, home care, and leisureroles. Both studies found that conflict experienced with these roles had differential relationships with work and family characteristicsand outcomes. For example, Small and Riley found that work interference with marriage correlated most strongly with reports ofmarital satisfaction, whereas work interference with parenthood correlated most strongly with the quality of the parent–childrelationship. Premeaux et al. found that number of children was only associated with work conflict with the spouse and parent roles;not with home, leisure, or elder roles. Both scales, however, have significant limitations. Small and Riley did not subject their scale tofactor analysis while Premeaux et al. included reverse coded enrichment items. Also, both scales exclude certain life domains (e.g.,community involvement and education).
We conclude that measures currently employed fall short of a comprehensive assessment of work–life interference. A newmulti-dimensional measure is needed that accurately assesses the interface between work and a full range of other domains in whichindividuals are commonly involved. An important issue to address at this point is that the entire set of life domainswill not be assumedto be relevant to all individuals. Rather, it is assumed that the set of life domains is comprehensive across people. That is, a givenindividual might participate in a different subset of life domains than another individual. Such an approach allows for more flexibilityand fewer assumptions regarding which domains are important. In the following sections we describe our conceptualization of workinterference with life and our proposed measurement approach.
2. Present conceptualization and proposed measurement
2.1. A life domains perspective
Our approach derives from the life domains orientation espoused by Swindle andMoos (1992), which is rooted in the quality of lifeliterature (Campbell, Converse, & Rodgers, 1976), themultiple identity perspective (Thoits, 1983), and Super's (1980) life-space theoryof career development. These bodies of research provide support for a key underlying assumption of our approach—that individualsare involved in domains other than family andwork and that they vary in the importance ascribed to these other domains. Life domainsare defined as the spheres of activity that make up a person's identity. Importantly, not all individuals occupy all life domains at anygiven point in time and, instead, may shift in and out of domains based on their interests and life circumstances (Super, 1980). Thus,variability across individuals in how “nonwork” is defined is to be expected and is planned for in our measurement approach.
The process by which perceptions of work interference are formed is assumed to be parallel in nature across life domains.According to role theory, interrole conflict results from competing expectations (Kahn,Wolfe, Quinn, Snoek, & Rosenthal, 1964). Socialpartners are anobvious source of expectations and are readily identifiable in thework domain (e.g., boss) and some contexts outside ofwork (e.g., familymembers, friends). For several life domains, however, expectationsmaybemostly or entirely internally derived. Thatis, in addition to social pressures, individuals also create their own expectations within domains based on personal beliefs andpreferences (Greenhaus & Beutell, 1985; Greenhaus & Powell, 2003). Failure to meet either externally or internally derivedexpectations set in any personally valued life domain (e.g., raising a family, volunteering in the community, maintaining physicalfitness) because of work demands should lead to perceptions of work interference with that domain.
The direction of interference depends on the domainwith stronger expectations, or fromwhich greater pressure originates (Frone,Russell, & Cooper, 1992; Greenhaus & Powell, 2003). Researchers have suggested that it is for this reason interference has often beenfound to be stronger in the work to family direction (Milliken & Dunn-Jensen, 2005). Managers are thought to be less forgiving thanfamily and are therefore given higher priority when there is competition for resources, resulting in higher work to family interference.A similar argument applies for other life domains outside of work. The consequences for failing to meet standards in these domains,whether due to stress or time constraints, are likely less severe compared to work (e.g., there may be low accountability to others forexercise or volunteering). The weaker punishments for not attending to these domains render their boundaries permeable andsusceptible to intrusions from work demands.
In considering howdomain importance relates to perceptions of interference,we take the position that the importance of a domainis factored into an individual's judgment of work interference with that domain. Highly valuing a domain may reduce the level ofinterference experienced (i.e., if individuals take preventative steps to protect the domains they valuemost) or intensify perceptions ofinterference that is beyond their control. Because domain importance is integral to forming perceptions of interference, it would beunnecessary and redundant to weight work interference with life domains by their respective importance when forming a compositeor when predicting outcomes. A similar position is taken by researchers of life satisfactionwho argue and find evidence to support theidea that people factor domain importance into their domain satisfaction ratings (Staples & Higgins, 1998).
2.2. Forms of interference
Adomain-based conceptualization of interference is intended to supplement othermeaningful distinctions that have characterizedthe study and measurement of interrole conflict. Work–family conflict measures consistently demonstrate a factor structure that isbased on three different forms of interference (Greenhaus & Beutell, 1985). Time-based interference refers to when time pressure fromone role prevents one from meeting expectations in other roles. Strain-based interference refers to when one role creates fatigue,tension, orworry thatmakes it difficult to fulfill other role expectations. Behavior-based interference refers towhen patterns of behaviorestablished in one role are incompatible with behavioral expectations in another role.
224 J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
Both time-based and strain-based interference readily apply to our conceptualization of work interference with life, as it can beargued that insufficient time and excessive stress are not conducive to participating in any life domain. However, we had a difficulttime transferring the current conceptualization of behavior-based work interference with family to other life domains. Compared tostrain-based and time-based interference, behavior-based interference has been investigated far less frequently in the literature(Carlson, Kacmar, & Williams, 2000; Premeaux et al., 2007). The incompatible behaviors are often assumed to be of an interpersonalnature (e.g., “do not helpme to be a better parent and spouse”, but not all life domains require social interaction). For these reasons, inaddition to a consideration of scale length, we chose to exclude behavior-based interference from our conceptualization andmeasure.
3. Item generation
A literature reviewwas conducted to identify relevant life domains for inclusion. Researchers have examinedwhat the primary lifedomains are for various reasons, such as to determine the domains that make up life satisfaction (Andrews & Withey, 1974; Frisch,Cornell, Villanueva, & Retzlaff, 1992), identify significant life domains for personal goals (Wadsworth & Ford, 1983), classify thecontexts in which stressful life events occur (Swindle & Moos, 1992), describe the life space of most people during the course of alifetime (Super, 1980), and uncover the dimensions underlying self-identity (Blais, Vallerand, Briere, Gagnon, & Pelletier, 1990). Toconsider a life domain for inclusion, it had to appear in most existing frameworks of life domains, be associated with a readilyidentifiable set of activities (e.g., domains such as “creativity” or “self-regard” were too abstract), and make sense in the context ofwork interference with life (e.g., “pensioner” was not applicable). Based on these criteria, eight life domains (described in Table 1)were included in the final measure: education, health, leisure, friendships, romantic relationships, family, household management, andcommunity involvement.
The goal of the item generation process was to create a set of item stems that would capture both time-based and strain-basedinterference and that could be easily tailored to reference different life domains. Having items written in a parallel manner acrossdomains was important to ensure similar operationalization of the construct space. We began generating items by consultingestablished scales of work–family and work–life conflict. Several existing items were modified to allow reference to specific lifedomains and to avoid exclusion of activities that take place outside thehome. For example, the Carlson et al. (2000) item “Due to all thepressures at work, sometimes when I come home I am too stressed to do the things I enjoy”was adapted to “Due to all the pressuresfromwork, sometimes I am too stressed to engage in health-related activities” (the relevant domain replaced “health” in other items).In addition to adapting existing items, several new items were created to ensure adequate content coverage.
4. Pilot study
The outcome of the above process was a set of ten item stems, five to measure time-based interference and five to measurestrain-based interference, which were completed by inserting the name of one of the eight life domains. In total then, the initial itempool consisted of 80 items. A pilot study was conducted to refine the item pool and ensure item comprehension. Data were collectedfrom54 individuals from several public settings including a train station, airport, and 5 k run/walk. Volunteering respondents receiveda luggage identification tag.
Themean age of respondentswas 44 years (SD=11) and 67% had a college degree or higher. Forty-eight percentwere female. Themarital status of the sample was: 19% single, 10% divorced, 2% widowed, 69%married. Fifty-six percent had spouses who also worked.Forty-eight percent had children living at home. The ethnic breakdown was: 85% Caucasian, 10% Hispanic, and 5% Asian. On averagethe respondents worked 44 h per week (SD=7).
Table 1Domain descriptions.
Health All activities to maintain your physical and mental health, such as exercising, going to the doctor and dentist, eating a balanced diet, ormeditation. May also include activities that you see as necessary to maintain a healthy appearance, such as getting a haircut or a manicure.
Family All activities with your family. This may include visiting/taking care of parents, spending time with a sibling, attending family functions,caring for a child (feeding or dressing, driving to and from daycare or medical appointments, parent–teacher meetings, etc.), or spendingtime with a pet. This does not include time spent alone with your significant other.
Householdmanagement
Activities to maintain a household, such as cleaning, grocery shopping, paying bills, making household repairs and improvements, or lawncare or arranging for these types of tasks to be performed by others. This does not include care for children or other dependents.
Friendships Any activities engaged in with friends (nonfamily members) outside of work. This may include going to the movies, sharing a meal,talking, or providing support for a friend with a problem.
Education Educational activities, such as reading job-related material not required by your work, completing class assignments for a degree programor certification, attending a seminar or conference, or taking courses for self-improvement. This does not include training or educationprovided by your employer on company time.
Romanticrelationship(s)
Going on dates or spending personal time with a significant other.
Communityinvolvement
Activities like volunteering, participating in political campaigns or fundraisers, or attending meetings (e.g., town hall or city council) orcommunity events.
Leisure Both active leisure, such as hobbies (e.g., gardening, car shows, vacationing) or playing/watching sports, and resting leisure, such as readingor watching T.V. at home
225J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
Descriptions were provided for each life domain (Table 1) to ensure that respondents understood the nature of activities thatwould qualify as participation in that domain. Consistent with the most well validated measure of work–family conflict to-date(Carlson et al., 2000) a five-point Strongly Disagree to Strongly Agree response scale was used.
Data analysis consisted of computing item means, variances, and inter-item correlations. A combination of psychometricproperties and discussions between co-authors about item content were used to select items for deletion. Items were dropped forone or more of the following reasons: low item-total correlation, low variance, high conceptual and empirical redundancy withanother item, and high correlation with an item from a different dimension (e.g., between a time-based and strain-based item). Asan example of the decision making process used, time-based interference had very high internal consistency for all domainssuggesting redundancy of item content; thus, one time-based item was eliminated that was highly correlated with another item(“I have to miss activities related to [domain] because of the amount of time I spend on work”). These revisions left six item stems,three to measure strain-based and three to measure time-based interference. The 48-item scale adapted to all eight domains isprovided in the Appendix A.
5. Study 1
The first study examines the factor structure of work interference with life. Past research has supported a multidimensional factorstructure of work-family conflict based on forms of interference (Carlson et al., 2000). Similarly we expect work interference with lifeto exhibit multidimensionality—both in terms of different domains and forms of interference (time-based and strain-based).Theoretically, these two factors (domain and form) should fully cross such that each form of interference can occur for each lifedomain. Because we are only studying one direction of interference, we propose a sixteen-factor model. For each of the eight lifedomains there will be two forms of interference (time and strain) thus leading to sixteen factors. To provide a stronger test of ourtheory and measurement we compare this sixteen-factor model with rival models, including a unidimensional model, a two-factormodel accounting for forms of interference only, and an eight-factor model accounting for life domains only.
H1. Work interference with life is best represented by a multidimensional structure that incorporates both forms of interferenceand the life domains with which work interferes.
The usefulness of domain-specific assessment of interference rests on the assumption that individuals can distinguish betweentargets of interference. While factor analysis can establish support for the distinctiveness of work interference with different lifedomains, differential relationshipswith other variables also serve as evidence for the validity of dimensions that are highly conceptuallyand empirically related (e.g., procedural and distributive justice; Colquitt & Shaw, 2005). We expect domain-specific measures of workinterference with life to be differentially related to satisfaction with various aspects of life. Work interference reduces the quantity orquality of involvement within a domain thereby making it difficult to meet personal standards within a domain, which may result inlower domain satisfaction (Pavot & Diener, 1993). For example, work-family conflict has been linked to fewer social activities in thefamily domain (Ilies, Schwind, & Heller, 2007) and work–school conflict is related to lower school performance (Butler, 2007). Supportfor this assertion is also evident in observed relationships betweenwork-to-family interference and family satisfaction (ρ=− .17; Allen,Herst, Bruck, & Sutton, 2000) and work-to-leisure interference and leisure satisfaction (r=− .23; Rice, Frone, & McFarlin, 1992).Judgments of satisfaction within a given life domain should be most strongly related to perceptions of work interfering with that samedomain. Similarly, work interference with a given life domain should be most strongly related to satisfaction within that same domain.
H2. Work interferencewith life and domain satisfaction aremore strongly negatively relatedwhen they aremeasuredwith respect tothe same life domain as opposed to different life domains.
6. Method
6.1. Participants and procedures
Participants were alumni of a large midwestern university. Out of 4142 individuals who received and viewed the invitation e-mail,60% (2485) accessed the survey and 45% (1865) completed the survey. The responses of 54 individuals who worked less than 25 h perweekwere discarded. The final sample of 1811 participants had the following characteristics: 46%male, 68.5%married or in a domesticpartnership, 61.1% dual earner, and 44%with one ormore children living at home. Themean agewas 38 years (SD=11.25). On average,respondents worked 46 h per week (SD=8.78). The ethnic breakdown was as follows: 90% Caucasian, 3.7% African American, 3.2%Asian, and 1.1% Hispanic. With respect to highest level of education, 49% held a college degree and 51% held a graduate degree.Participants represented diverse occupations—themost frequently reportedmajor SOC groupings weremanagement (33%), education,training, and library (12%), business and financial operations (8%), healthcare practitioners (8%), arts, design, entertainment, sports andmedia (7%), and architectural and engineering (6%). Participants were compensated with a $15 gift certificate to an online retailer.
6.2. Measures
The presentation order of themeasureswas counterbalanced across participants such that a randomhalf received items pertainingto the eight domains in one order and the other half received them in the opposite order.
226 J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
6.2.1. Work interference with lifeThe 48-itemmeasure of work interference with life was administered alongwith the eight domain descriptions (Table 1) repeated
throughout the survey for reference. The response scale was 1=Strongly disagree to 5=Strongly agree.Importantly, not all individuals are involved in all life domains. Ourmeasurewasdevelopedwith the intent that respondentswould
only complete those portions relevant to the domains in which they currently participate. Branching of the survey was programmedbased on responses to qualifying questions about domain involvement. Participants were asked how much of their time, in general,they spent participating in each of the life domains. Response options ranged from 1=None to 4=A great deal. Those who indicatedthat they spent “none” of their time in a domain did not receive those questions, whereas those who reported at least someinvolvement no matter how minimal received questions related to that domain.
6.2.2. Domain importanceRespondents were asked to rate the importance of each domain to them on a scale ranging from 1=Not at all important to
5=Very important.
6.2.3. Domain satisfactionThree modified items from the Satisfaction with Life Scale (SWLS; Diener et al., 1985) were used to measure satisfaction with life
domains. A sample itemwith domain names substituted for the blank is: “I am satisfied withmy ___.” The response scale ranged from1=Strongly disagree to 5=Strongly agree.
7. Results
Confirmatory factor analysis (CFA) was performed to evaluate the distinctiveness of the dimensions underlying the workinterferencewith life scale (LISREL 8.72, Jöreskog & Sörbom, 2005). Although exploratory factor analysis is often recommended for theearly stages of scale development, CFA was more appropriate in the present study for two reasons. First, CFA is preferable when aresearcher has strong theoretical or empirical evidence to specify alternative models a priori (Fabrigar, Wegener, MacCallum, &Strahan, 1999). We have presented theoretical arguments in favor of a domain-based approach to measurement and, furthermore,items were adapted from existing scales to clearly reference different life domains. Second, CFA permits tests of relative fit in additionto absolute fit (Fabrigar et al., 1999). A critical concern in Study 1 is the comparison of alternative measurement models.
In all CFA models, each item was specified to load on only one factor and factors were free to correlate. Results are presented inTable 2. In order to test the measure in its entirety, the CFA analyses were based only on the respondents who were involved in alldomains and completed all subscales; the sample size was accordingly reduced but still sufficiently large (N=566). For all models theχ2was statistically significant, rejecting the exact-fit hypothesis. However, this is not surprising given a large sample size,which iswhyadditional indices are informative. The one-factor model, representing the case of a general factor underlying all work interferencewith life responses, was clearly a poor fit to the data according to RMSEA, SRMR, and CFI (Hu & Bentler, 1999). Because themodels arenot nested, we also report the expected cross-validation index (ECVI) where themodel with the smaller ECVI is considered superior infit. Although the ECVI suggests that the two-factor (form-based) model was a better fit than the eight-factor (domain-based) model,both models had poor fit according to RMSEA and SRMR. In support of Hypothesis 1, the sixteen-factor (form- and domain-based)model provided a good fit to the data, as evidenced by an RMSEA of .05 (test of close fit, p=.76), SRMR of .03, and CFI of .99. The ECVIfor the sixteen-factor model was also well below that of the other models.
In support for the sixteen-factor model, the estimated item loadings were large and significant, as seen in Table 3. The correlationsbetween the latent factors ranged from .24 to .73 (see Table 4) and were moderate on average (.45). Time-based and strain-basedinterference correlated .60, on average across domains, which is similar in magnitude to that seen in established scales of workinterference with family (.58; Carlson et al., 2000). There appears to be greater distinction between domains for time-basedinterference (average correlation of .43) than for strain-based interference (average correlation of .59).
The relevant correlations to test Hypothesis 2 concerning relationshipswith domain satisfaction are presented in Table 5. Divergentvalidity is represented by the correlations between work interference with a domain and satisfaction with different domains and thecorrelations between satisfaction with a domain and work interference with other domains. The average of these correlations wasr=− .16. Convergent validities, represented by the correlations betweenwork interferencewith a given life domain and satisfaction inthat same life domain, were nearly twice as large, on average, at r=− .35. The convergent and divergent correlations were compared
Table 2Study 1 comparison of alternative confirmatory factor analysis models.
Note. N=566. All chi-square values were significant at pb .001. RMSEA=root-mean-square error of approximation; SRMR=standardized root-mean-squareresidual; CFI=comparative fit index; ECVI=expected cross validation index; C.I.=confidence interval.
Note. Maximum likelihood estimation was used to obtain parameters.
227J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
after transforming them to corresponding Fisher's Z statistics. Results showed that, in support of Hypothesis 2, work interferencewithlife and domain satisfaction are correlated more strongly when they are measured with respect to the same life domain,t(126)=−10.04, pb .001.
While the average pattern supports our prediction, leisure was somewhat of an anomaly. Although satisfaction with leisure wasbest predicted by time-based and strain-based work interferencewith leisure (rs=− .42 and−.39, respectively) its correlations withwork interference with other life domains were also quite high (r=− .27 on average). In fact, both forms of work interference withfamilywere better predictors of leisure satisfaction (rs=− .34 and− .33 for time-based and strain-based, respectively) than theywereof family satisfaction (rs=− .23 and− .24). One possible explanation for this finding is that family and leisure are not distinguishablein terms ofwork-to-life interference. However, work interferencewith family and leisure are correlated .49 and .59 for time-based andstrain-based, respectively, suggesting discrimination. Furthermore, post hoc analyses revealed that combining these two domainsresulted in worsened model fit. We speculate about alternative explanations for this finding in the discussion below.
For descriptive purposes, we report levels of involvement, domain importance and interference scalemeans in Table 6. Involvementvaried across domains with the lowest levels observed for community involvement and education. On average, family was rated as the
Note. Pairwise correlations are presented (N ranges from 902 to 1730). Correlations greater than |.05| are significant at pb .05 and correlations greater than |.07|=pb .01.
228 J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
most important domain, followed by romantic relationships and health. However, there was substantial between-person variance inimportance ratings, substantiating the assumption that individuals vary in the priority they attach to different domains.
8. Discussion
The findings from Study 1 extend the work–family literature in three important ways. First, the descriptive data obtained ondomain involvement and importance affirms that employees are commonly involved in domains other than family, and by limitingmeasurement to family researchers riskmissing out on other meaningful targets of interference. Second, the results provide evidencethat individuals are able to distinguish between work interference with family and work interference with other life domains. Ameasurement model with factors based on life domains showed substantially better fit than models collapsing across domains.Furthermore, thework interferencewith life dimensions demonstrated differential relationshipswith other variables in a theoreticallymeaningful pattern. An anomalous finding was that all dimensions were strong predictors of leisure satisfaction. One explanation isthat leisure is the domain that is cut down on the most to satisfy obligations in other life domains. It is also possible that workinterference with other life domains such as family produces stress that interferes with one's ability to engage in satisfying leisure.
The third contribution is that we were able to replicate the dominant measurement framework for work–family conflict(i.e., distinguish between time-based and strain-based interference) for all of the life domains investigated. This findingsupports the idea that work interference takes the same form regardless of which life domain is affected. The implication isthat, though there is evidence for the distinctiveness of domain-based dimensions, it is also appropriate to refer to an overallabstraction of work interference with life. Such an abstraction would be meaningless if interference took a completelydifferent form depending on which life domain is involved. Study 1, therefore, provided evidence for work interference withlife as a coherent multidimensional construct.
Table 6Study 1 domain involvement, domain importance, and work interference with life domains.
Involvement Importance M (SD) Time-based WID M (SD) Strain-based WID M (SD)
Note. WID=work interference with domain. Involvement is reported as percentage of sample who reported being involved in a domain. Importance and WID ratings(ranging from 1 to 5) were provided only by individuals involved in the domain.
229J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
9. Study 2
Study 2 examines the theoretical correlates of work interference with life. In addition to building evidence for constructvalidity, our goal more generally is to illustrate the usefulness of measuring work interference with life as opposed to amore narrow definition of conflict. We intend to demonstrate that measuring work interference with life domains adds value(i.e., incremental prediction) beyond that provided by measuring work–family conflict. We also explore the relative value ofmeasuring work interference with respect to each of the life domains in the prediction of personal and work-relatedoutcomes.
A wide array of outcomes have been proposed and associated with work–family conflict. Work interference with family hasbeen linked to lower job satisfaction and higher turnover intentions (Allen et al., 2000), presumably because individualsattribute the cause of interference to aspects of their job or work environment (Frone, 2000; Shockley & Singla, 2011). Workinterference with family is also viewed as impacting perceived quality of life and acting as a general stressor; it has beenassociated with lower life satisfaction, increased physical symptoms of poor health, and increased depression (Allen et al.,2000). One might argue that work interference with life domains, in general, would be a better predictor of these broad-natured outcomes thanwork interference with family, specifically. This is due to the specificity matching principle (Cronbach &Gleser, 1957), according to which specific outcomes are best predicted by narrow predictors, whereas general outcomesrequire a broader predictor or set of predictors. Individual well-being depends on the ability to meaningfully participate in alllife domains in which one is involved including but not limited to family (Cantor & Sanderson, 2003). Similarly, when one isforming a judgment of job satisfaction and deciding whether to quit one's job, work interference with family life may be oneconsideration, but onemight also consider the available time and energy one's current job leaves to exercise, pursue hobbies, orsocialize with friends.
Preliminary evidence suggests that work interference with life is negatively related to job outcomes and well-being. Globalperceptions of work–life conflict are associated with higher incidence of depression, anxiety, and psychological strain, as wellas lower job satisfaction and organizational commitment (Fisher et al., 2009; Grant-Vallone & Ensher, 2001; Huffman,Youngcourt, Payne, & Castro, 2008; O'Driscoll et al., 1992; Siegel, Post, Brockner, Fishman, & Garden, 2005). However, it has yetto be shown that there is incremental validity in measuring a broader construct space than work–family conflict. The workinterference with life measure developed in Study 1 is well-suited to testing hypotheses of incremental validity. The dimen-sionality is such that the construct can be partitioned into work interference with family and work interference with domainsother than family. We therefore hypothesize:
H3. Work interference with life domains other than family explain additional variance in job satisfaction, turnover intentions, lifesatisfaction, and mental health, above and beyond the variance explained by work interference with family.
While the above hypothesis concerns the value added by measuring nonfamily domains, for measure development purposes it isalso useful to draw conclusions about the incremental validity of the new scale in its entirety. In particular, it is important todemonstrate enhanced predictive ability beyond existing measures. Based on the same rationale provided for Hypothesis 3, weexpected that the work interference with life measure would explain additional variance beyond an established work-family conflictscale.
H4. Work interference with life explains additional variance in job satisfaction, turnover intentions, life satisfaction, and mentalhealth, above and beyond the variance explained by an established work-to-family conflict scale.
10. Method
10.1. Participants and procedures
Alumni were recruited from a midwestern university, excluding invitees from Study 1. Of the 9837 individuals who received andviewed the invitation e-mail, 4023 (41%) accessed the survey and 3234 (32%) completed the survey. Responseswere dropped from 89individuals who were not employed at least 25 h per week. The final sample (n=3145) was 48% female, 71% married or partnered,61% dual earners, 43%with children living at home, andwith amean age of 46 years (SD=12). Respondentsworked 47 h perweek onaverage. The sample was primarily Caucasian (91%) with other participants identifying as African American (3%), Asian (2.5%), orHispanic/Latino (1%). The highest level of education achievedwas a college degree for 41% of the sample and a graduate degree for theremaining 59%. In return for participating, all respondents were entered into a drawing for one of nine MP3 players.
10.2. Measures
10.2.1. Work interference with lifeThe 48-item scale developed in Study 1 was used to measure work interference with life. Participants only completed items
pertaining to the life domains in which they were involved, and the same qualifying questions from Study 1 were used to determinedomain involvement. The dimensionality of the scale was cross-validated in the present sample. The 16-factor structure fit the datawell, χ2 (960, N=1148)=3285.34, pb .01, SRMR=.02, RMSEA=.05, CFI=.99.
Table 7Descriptive statistics and intercorrelations among study 2 variables.
Note. All correlations at |.05| and greater are significant at pb .01. Coefficient alphas are presented along the diagonal. WIF=work interference with family as measured by Carlson et al. (2000). Sex: 0=men, 1=women; Married/partnered: 0=no, 1=yes; Child at home: 0=no, 1=yes.
230J.K
eeneyet
al./JournalofV
ocationalBehavior82
(2013)221
–237
231J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
10.2.2. Work interference with familyIn addition to measuring work interference with family as a dimension of our work interference with life scale, we administered
Carlson et al.'s (2000) validated scale. A sample items is “I have to miss family activities due to the amount of time I must spend onwork responsibilities.” Similarly to the work interference with life scale, participants indicating they spent no time in the familydomain did not complete this measure.
10.2.3. Job satisfactionParticipants provided self reports of job satisfaction using three items from Brayfield and Rothe (1951). A sample item is, “I feel
fairly well satisfied with my present job.” The response scale ranged from 1=Strongly disagree to 5=Strongly agree.
10.2.4. Life satisfactionOverall life satisfaction was measured using the 3-item Satisfaction with Life Scale (Diener et al., 1985). A sample item is “I am
satisfied with my life.” The response scale ranged from 1=Strongly disagree to 5=Strongly agree.
10.2.5. Turnover intentionsIntentions to quit were measured using three items: “I frequently think of quittingmy job.” “I am planning to search for a new job
during the next 12 months,” and “If I get another job that pays aswell, I will quit this job.” The response scale ranged from 1=Stronglydisagree to 5=Strongly agree.
10.2.6. Mental healthParticipants completed the 12-item General Health Questionnaire (Goldberg, 1978). They were asked to rate the extent to which
they had recently experienced a number of psychological symptoms. A sample item is “lostmuch sleep over worry”. Response optionsranged from 1=More so than usual to 4=Much less than usual or from 1=Not at all to 4=Much more than usual depending on theitem.
10.2.7. ControlsWe included several variables that could influence the study results (Byron, 2005; Eby et al., 2005): one or more children at home
(0=no, 1=yes), sex (0=male, 1=female), relationship status (0=single, 1=married or partnered), and number of hours worked.
11. Results
The means, standard deviations, and intercorrelations of the variables are shown in Table 7. In general across the eight domains,ratings of time-based work interference tended to be higher than strain-based work interference. There was considerable variabilityacross domains in levels of time-basedwork interference, with the highest ratings for leisure, health, and family. Levels of strain-basedwork interferencewere similar across domains, though slightly higher for health and romantic relationships.Women had significantlyhigher work interference than men for 14 of the 16 domains (see Table 7; significant correlations between sex and dimension scoresranged from r=.06 to .17). The largest such differences were for strain-based interference with health (d=.34), leisure (d=.33),household management (d=.32), friendships (d=.31), and romantic relationships (d=.30). Consistent with past research (Eby etal., 2005), employees with children at home andmarried or partnered employees had more work interference with family comparedto childless employees (d=.44 and .27 for time-based and strain-based, respectively) and single employees (d=.32 and .15 fortime-based and strain-based, respectively).
11.1. Incremental validity
Hypothesis 3 concerns the incremental prediction of outcomes (job satisfaction, turnover intentions, life satisfaction, andmental health) above and beyond that afforded by work interference with family. A hierarchical regression was conducted foreach outcome with control variables entered in Step 1, the work interference with family subscale in Step 2, and the workinterference with domains other than family subscales in Step 3 (see Table 8). In order to include all of the subscales, the analysiswas performed using data from respondents who were involved in all domains. For all outcomes, the addition of the non-familydimensions provided a significant increment in variance explained (between 4.2 and 9.7%), supporting Hypothesis 3.
Hypothesis 4 addresses incremental validity over an established work interference with family scale. The same hierarchicalregressions as above were conducted, but with the Carlson et al. (2000) work-to-family conflict scale in Step 2 and all of the newlyconstructed work interference with life subscales in Step 3 (see Table 8). Similar levels of incremental prediction were obtained(between 3.2 and 8.1%) supporting Hypothesis 4.
11.2. Supplemental analyses: Relative importance
An analysis of incremental validity is well suited to demonstrating that the new measure of work interference with life is tappingunique variance, butmay not fully demonstrate the value added by the non-family dimensions. A comparison of predictors, particularlywhen they are correlated, is best addressed through the use of relativeweights analysis, which has been recommended as a supplementto hierarchical regression when evaluating the usefulness of a newmeasure (LeBreton, Hargis, Griepentrog, Oswald, & Ployhart, 2007;
Table 8Incremental validity in study 2.
ΔR2
Job satisfaction Turnover intentions Life satisfaction Mental health
Non-family subscales over family subscaleStep 1 Control variables: sex, marital/partner, children, hours worked .031⁎⁎ .051⁎⁎ .015⁎⁎ .013⁎
Step 2 Work interference with family subscale .105⁎⁎ .083⁎⁎ .102⁎⁎ .198⁎⁎
Step 3 Work interference with non-family subscales .094⁎⁎ .080⁎⁎ .042⁎⁎ .097⁎⁎
Work interference with life over work interference with familyStep 1 Control variables: sex, marital/partner, children, hours worked .031⁎⁎ .053⁎⁎ .015⁎⁎ .013⁎
Step 2 Work interference with family (Carlson et al., 2000) .139⁎⁎ .111⁎⁎ .123⁎⁎ .228⁎⁎
Step 3 Work interference with life .076⁎⁎ .062⁎⁎ .032⁎⁎ .081⁎⁎
Note. Because of missing data, N ranged from 1393 to 1396.⁎ pb .01.
⁎⁎ pb .001.
232 J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
Tonidandel & LeBreton, 2011). Relativeweights analysis (Johnson, 2000) transforms a set of predictors into a new set of variables thatare as highly related to the original set as possible yet orthogonal to one another. The end result is an estimate of a predictor's relativeimportance (epsilon), defined as its contribution to R2, considering both its unique contribution and its contribution in the presence ofother predictors. This value is often rescaled into a percentage of the variance explained (i.e., percentage of R2, LeBreton et al., 2007).
We conducted a relative weights analysis with the same outcomes used previously (job satisfaction, turnover intentions,life satisfaction, and mental health) and the work interference with life dimensions and control variables as predictors. Thedata analyzed were from respondents involved in all domains. The relative weights are provided in Table 9. Notably, no lifedomain was a superior predictor of all outcomes, and the pattern of results varied according to whether the dependentvariable was specific to work or personal well-being. The strongest predictors of job satisfaction and turnover intentions werestrain-based and time-based work interference with education. In contrast, strain-based interference with romanticrelationships and leisure were among the strongest predictors of life satisfaction and mental health. Another noteworthyobservation is that no life domain accounted for the majority of explained variance for any outcome. Work interference withfamily, for example, accounts for less than 15% of the explained variance for any outcome (a figure obtained by summing therescaled weights for strain-based and time-based work interference).
12. Discussion
By expanding measurement of work interference with life to include additional domains beyond family we are able toimprove our prediction of personal well-being and work-related outcomes. This was demonstrated by the results of theincremental validity analyses and was bolstered by the results of the relative weights analysis, which apportioned themajority of variance explained in outcomes to domains other than family. Both sets of results suggest that work–familyconflict scales would be deficient measures of work interference with life because there is unique and meaningful constructvariance associated with other life domains. A different measurement approach, such as the one taken in the present study, isneeded to more fully capture the construct as relevant to a workforce with diverse life circumstances. These results extendthe work–life literature by showing that family life is not the only aspect of employees' personal lives that can be impinged onby work, and that interference with other aspects can be equally detrimental to employee morale, retention, and generalwell-being.
Interestingly, despite the relatively lower importance attributed to education compared to other domains, workinterference with education emerged as an important predictor of work-related outcomes. A common reason for employeesto pursue continuing education is for professional advancement (Spannard, 1990). It would be a frustrating situation for anemployee if promotional opportunities hinge on furthering his or her education but work demands are making it difficult todo so, which could result in reduced job satisfaction and intent to quit. It is also possible that the casual relationship isreversed. A person dissatisfied in his or her job and planning on leaving may pursue further education to a greater degree inpreparation for changing careers.
Table 9Relative importance of work interference with life dimensions in study 2.
Dependent variable
Job satisfaction turnover intent Life satisfaction Mental health
Note. WI=work interference. (t)=time-based. (s)=strain-based. Because of missing data, N ranged from 1397 to 1398. eps=epsilon. %Var=rescaled weightcalculated as epsilon/R2.
233J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
13. General discussion
While the construction of a valid measure is a contribution in and of itself, the contribution of this research is more than thedevelopment of a new measure. Moving from work–family to work–life research requires a shift in our conceptualization and ourtheories. The aim of this research was not to measure the same construct better—the Carlson et al. (2000) scale is a perfectlyacceptable measure for the purpose of focusing on work and family. Instead, our intent was to expand a construct space. Whereasthe conceptualization of the basic nature of interference remained the same (i.e., based on role theory), thinking of individuals'nonwork lives as multi-faceted required an integration of the life domains literature. We believe we identified a useful startingpoint for future research with a broad and, what the results suggest is, a sufficiently distinct set of life domains for investigation.
13.1. Practical implications
An advantage of a domain-based measure of work interference with life is the ability to obtain information on the recipientdomains of interference from work (i.e., an evaluation of which domains experience interference and to what extent). Similar tothe manner in which clinical researchers have found the assessment of psychological health in terms of domains more useful fortargeting areas for change (Frisch et al., 1992; Lent, Singley, & Sheu, 2005), companies may find the assessment of workinterference with specific domains helpful for developing and evaluating initiatives. The decision of where an organization shouldfocus its resources may be aided by an assessment of domain-level interference levels broken down by demographic groups. Forinstance, whereas employees with children may have higher levels of work interference with family (as found in this study),younger employees may have higher levels of work interference with education. Thus, solutions for “work–life balance”may varyacross segments of employees. This research supports the idea of organizations tailoring work–life programs to support the needsof all employees, not just those with spouses and children. By instituting policies that appeal to a wider range of employees,organizations can build a more inclusive workplace and may enhance perceived organizational support (Casper, Eby, Bordeaux,Lockwood, & Lambert, 2007). Furthermore, when blanket solutions for work–life balance (e.g., reduce workload) are not feasible(e.g., because a company is short-staffed), solutions targeted toward specific problems may help.
13.2. Strengths and limitations
Methodological strengths of this research include the use of two large employee samples, respondents from diverse occupations, andmeasuring two forms of interference (time-based and strain-based). Nevertheless, there are limitations worthmentioning. Because datawere collected via self-report there are potential concerns for commonmethod bias.We do believe self-report was themost appropriatemethodology for the set of variables examined.While familymembers could potentially provide reports ofwork interferencewith certainaspects of a person's life, it would be unreasonable to expect them to understand how that person feels about all aspects (e.g., health,
234 J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
friendships, etc.). Furthermore, it is perceptions ofwork interferencewith life that aremost relevant to outcomes, such as how individualsview their jobs. There are characteristics of ourwork interferencewith lifemeasure thatmake it less susceptible to someof the biases thatunderlie commonmethod effects. First, a person'smood at the time of filling out a survey can bias responses (Podsakoff, MacKenzie, Lee,& Podsakoff, 2003) and domain-based measurement is less conducive to mood bias than global measurement as described earlier.Second,we tookproactivemeasures to reduce commonmethodbias based on suggestions in the literature (Podsakoff et al., 2003). Sets ofitemswere counterbalanced to reduce the effects of itemordering. Also, the fact that the surveywas anonymous reduces the potential forevaluation apprehension and socially desirable responding. Finally, the fact that we were able to differentiate between domains andforms of interference in confirmatory factor analysis suggests our measure has construct validity, which serves as evidence againstsubstantial common method variance (Conway & Lance, 2010).
A second limitation concerns the cross-sectional nature of the data collection. Although the relationships hypothesized rely ontheories of a causal nature, we cannot establish causality based on the research design. It is possible, for example, that those whoare low in mental health are likely to perceive their lives more negatively and respond more negatively to the work interferencewith life measure. We did collect data in Study 1 on trait negative affectivity, analysis of which (not detailed in this paper)suggested the relationships between work interference with life and the proposed outcomes are not accounted for by traitnegative affect. After controlling for trait negative affect, the work interference with life dimensions explained 11, 15, and 12% ofthe variance in life satisfaction, job satisfaction, and turnover intentions, respectively, compared to 19, 20, and 17% of varianceexplained before controlling for negative affectivity. Nevertheless, future research can utilize longitudinal research designs tobetter elucidate causal relationships.
Finally, although our sample was diverse according to occupations and several demographic criteria (e.g., age, gender, presence ofchildren in the home), we were not inclusive in all respects. For example, all participants were highly educated and the majority wereCaucasian. As such, our results may not be generalizable to people of all backgrounds.
13.3. Future research directions
The present research identifies several potentially fruitful directions for future studies. First, our findings support the idea that workinterferencewith life ismultidimensional, yet there aremultiplemodels ofmultidimensional constructs for researchers to consider (Law,Wong, &Mobley, 1998). Our results are consistentwith a formativemodel (i.e., similar to the sum-of-facets approach to job satisfaction).Formative constructs are defined by a combination of their dimensions, which can be but are not required to be correlated. An individualcan have low interference of work with one life domain yet still have high interference with other life domains and high interferenceoverall. In contrast, our results suggest that a latent construct model would be inappropriate, because dimensions are presumed to beinterchangeable indicators of an overall construct. However, another model of work interference with life construct that is compatiblewith our findingswould be a profilemodel. For example, individuals could be characterized according towhetherwork interferencewithfamily is highest and interference with all other domains relatively low, versus high interference across all domains, or low interferenceacross all domains.
Second, our research points to a potential explanation for inconsistent findings with regard to gender differences in work–familyconflict levels (Eby et al., 2005). A consideration of life domains other than family may help understand this issue. Women in our studytended to report higher work interference with life, with the largest such differences (with effect sizes of .30 or greater) observed forstrain-based interference with health, leisure, household management, friendships, and romantic relationships. The effect sizes fortime-based and strain-based interference with family were not as large (d=.13 and .19, respectively). It is possible that many workingwomen still see the “second shift” of caring for families as their duty (Hochschild & Machung, 1989), leaving less energy available foractivities in other domains. Thus, while they may not necessarily report high interference with family, they nonetheless might reporthigher interference levels with other nonwork domains. We have concerns about the construct validity of work–family conflict scalesthatmix items specific to familywith items referring to nonworkmore generally (e.g., “personal interests”, Kopelman et al., 1983; “thingsI enjoy”, Carlson et al., 2000). Such scales could at least partially account for the discrepant findings with respect to gender differences.
Our third and final suggestion for future research is to study work–life enrichment. While researchers have begun examiningwork–family enrichment (Carlson, Kacmar, Wayne, & Grzywacz, 2006), the synergies of work and life, more generally, have yet tobe studied and constitute a promising area for future research. A broader scope of activities outside of work implies moreopportunity for gains from work to be applied elsewhere. Likewise, involvement in domains other than family should provideincremental gains to the work domain. For example, employees who are involved in multiple roles outside of work are not onlyhealthier but tend to have better managerial skills (Ruderman, Ohlott, Panzer, & King, 2002). Ensuring that employees are able toengage in personal pursuits increases the possibility that they will gain skills that can be applied to the workplace (Edwards &Rothbard, 2000).
13.4. Conclusion
The results of the present research demonstrate that work interference with life can be conceptualized as a multidimensionalconstruct on the basis of two properties: the form of interference (e.g., time-based) and the life domain implicated (e.g., communityinvolvement). Our research suggests that a broader construct space thanwork–family conflict indeed exists. Importantly, the addition ofdomains other than family provides incremental validity with respect to employee well-being and work attitudes. Relative weightsanalysis demonstrated that work interference with each of the eight life domains identified in this study was an important predictor ofone or more outcomes.
235J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
Appendix A
Work interference with life domains scale items
1. The time I spend on work cuts into the time I'd like to spend on my health.a
2. The amount of time my work takes up makes it difficult to find enough time for my health.b
3. My work keeps me from health-related activities more than I would like it to.c
4. After engaging in work activities, I am often too frazzled to focus on my health.c
5. Due to all the pressures from work, sometimes I am too stressed to engage in health-related activities.c
6. Stress from work makes it harder for me to be fully involved in my health.d
7. The time I spend on work cuts into the time I'd like to spend on my family.8. The amount of time my work takes up makes it difficult to find enough time for my family.9. My work keeps me from my family more than I would like it to.10. After engaging in work activities, I am often too frazzled to focus on my family.11. Due to all the pressures from work, sometimes I am too stressed to engage in family-related activities.12. Stress from work makes it harder for me to be fully involved in my family.13. The time I spend on work cuts into the time I'd like to spend on household management.14. The amount of time my work takes up makes it difficult to find enough time for household management.15. My work keeps me from household management more than I would like it to.16. After engaging in work activities, I am often too frazzled to focus on household management.17. Due to all the pressures from work, sometimes I am too stressed to engage in household management.18. Stress from work makes it harder for me to be fully involved in household management.19. The time I spend on work cuts into the time I'd like to spend on friendships.20. The amount of time my work takes up makes it difficult to find enough time for friendships.21. My work keeps me from friendships more than I would like it to.22. After engaging in work activities, I am often too frazzled to focus on friendships.23. Due to all the pressures from work, sometimes I am too stressed to engage in activities related to friendships.24. Stress from work makes it harder for me to be fully involved in friendships.25. The time I spend on work cuts into the time I'd like to spend on my education.26. The amount of time my work takes up makes it difficult to find enough time for my education.27. My work keeps me from my education more than I would like it to.28. After engaging in work activities, I am often too frazzled to focus on my education.29. Due to all the pressures from work, sometimes I am too stressed to engage in education activities.30. Stress from work makes it harder for me to be fully involved in my education.31. The time I spend on work cuts into the time I'd like to spend on romantic relationship(s).32. The amount of time my work takes up makes it difficult to find enough time for romantic relationship(s).33. My work keeps me from romantic relationship(s) more than I would like it to.34. After engaging in work activities, I am often too frazzled to focus on romantic relationship(s).35. Due to all the pressures from work, sometimes I am too stressed to engage in activities related to romantic relationship(s).36. Stress from work makes it harder for me to be fully involved in romantic relationship(s).37. The time I spend on work cuts into the time I'd like to spend on community involvement.38. The amount of time my work takes up makes it difficult to find enough time for community involvement.39. My work keeps me from community involvement more than I would like it to.40. After engaging in work activities, I am often too frazzled to focus on community involvement.41. Due to all the pressures from work, sometimes I am too stressed to engage in community involvement.42. Stress from work makes it harder for me to be fully involved in community involvement.43. The time I spend on work cuts into the time I'd like to spend on leisure activities.44. The amount of time my work takes up makes it difficult to find enough time for leisure activities.45. My work keeps me from leisure activities more than I would like it to.46. After engaging in work activities, I am often too frazzled to focus on leisure activities.47. Due to all the pressures from work, sometimes I am too stressed to engage in leisure activities.48. Stress from work makes it harder for me to be fully involved in leisure activities.
a This item stem was adapted from Kopelman et al. (1983).b This item stem was adapted from Netemeyer, Boles, and McMurrian (1996).c These item stems were adapted from Carlson et al. (2000).d New item.
References
Allen, T. D., Herst, D. E. L., Bruck, C. S., & Sutton, M. (2000). Consequences associated with work-to-family conflict: A review and agenda for future research. Journalof Occupational Health Psychology, 5, 278–308.
Andrews, F. M., & Withey, S. B. (1974). Developing measures of perceived life quality: Results from several national surveys. Social Indicators Research, 1, 1–26.Bellavia, G. M., & Frone, M. R. (2005). Work–family conflict. In J. Barling, E. K. Kelloway, & M. R. Frone (Eds.), Handbook of work stress. Thousand Oaks, CA: Sage
Publications.Blais, M. R., Vallerand, R. J., Briere, N. M., Gagnon, A., & Pelletier, L. G. (1990). Significance, structure, and gender differences in life domains of college students. Sex
Roles, 22, 199–212.Brayfield, A. H., & Rothe, H. F. (1951). An index of job satisfaction. The Journal of Applied Psychology, 35, 307–311.Butler, A. B. (2007). Job characteristics and college performance and attitudes: A model of work–school conflict and facilitation. The Journal of Applied Psychology,
92, 500–510.
236 J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
Byron, K. (2005). A meta-analytic review of work–family conflict and its antecedents. Journal of Vocational Behavior, 67, 169–198.Campbell, A., Converse, C. E., & Rodgers, W. L. (1976). The quality of American life. New York: Sage.Cantor, N., & Sanderson, C. A. (2003). Life task participation and well-being: The importance of taking part in daily life. In D. Kahneman, E. Diener, & N. Schwarz
(Eds.), Well-being: The foundations of hedonic psychology (pp. 230–243) New York: Sage.Carlson, D. S., & Kacmar, K. M. (2000). Work–family conflict in the organization: Do life role values make a difference? Journal of Management, 26, 1031–1054.Carlson, D. S., Kacmar, K. M., Wayne, J. H., & Grzywacz, J. G. (2006). Measuring the positive side of the work–family interface: Development and validation of a
work–family enrichment scale. Journal of Vocational Behavior, 68, 131–164.Carlson, D. S., Kacmar, K. M., & Williams, L. J. (2000). Construction and initial validation of a multidimensional measure of work–family conflict. Journal of
Vocational Behavior, 56, 249–276.Casper, W. J., Eby, L. T., Bordeaux, C., Lockwood, A., & Lambert, D. (2007). A review of research methods in IO/OB work–family research. The Journal of Applied
Psychology, 92, 28–43.Casper, W. J., Weltman, D., & Kwesiga, E. (2007). Beyond family-friendly: The construct and measurement of singles-friendly work culture. Journal of Vocational
Behavior, 70, 478–501.Colquitt, J. A., & Shaw, J. C. (2005). How should organizational justice be measured? In J. Greenberg, & J. A. Colquitt (Eds.), Handbook of organizational justice
(pp. 113–152) Mahwah, NJ: Lawrence Erlbaum.Conway, J. M., & Lance, C. E. (2010). What reviewers should expect from authors regarding common method bias in organizational research. Journal of Business
and Psychology, 25, 325–334.Cronbach, L. J., & Gleser, G. C. (1957). Psychological tests and personnel decisions. Urbana: University of Illinois Press.Crooker, K. J., Smith, F. L., & Tabak, F. (2002). Creating work–life balance: A model of pluralism across life domains. Human Resource Development Review, 1,
387–419.Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality Assessment, 49, 71–75.Eby, L. T., Casper, W. J., Lockwood, A., Bordeaux, C., & Brinley, A. (2005). Work and family research in IO/OB: Content analysis and review of the literature
(1980–2002). Journal of Vocational Behavior, 66, 124–197.Edwards, J. E., & Rothbard, N. P. (2000). Mechanisms linking work and family: Clarifying the relationship between work and family constructs. Academy of
Management Review, 25, 178–199.Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological
Methods, 4, 272–299.Fisher, G. G., Bulger, C. A., & Smith, C. S. (2009). Beyond work and family: A measure of work/nonwork interference and enhancement. Journal of Occupational
Health Psychology, 14, 441–456.Frisch, M. B., Cornell, J. C., Villanueva, M., & Retzlaff, P. J. (1992). Clinical validation of the quality of life inventory: A measure of life satisfaction for use in treatment
planning and outcome assessment. Psychological Assessment, 4, 92–101.Frone, M. R. (2000). Work–family conflict and psychiatric disorders: The National Comorbidity Survey. The Journal of Applied Psychology, 85, 888–895.Frone, M. R. (2003). Work–family balance. In J. C. Quick, & L. E. Tetrick (Eds.), Handbook of occupational health psychology (pp. 143–162) Washington, DC:
American Psychological Association.Frone, M. R., Russell, M., & Cooper, M. L. (1992). Antecedents and outcomes of work–family conflict: Testing a model of the work–family interface. The Journal of
Applied Psychology, 77, 65–78.Goldberg, D. (1978). Manual of the General Health Questionnaire. Windsor, England: National Foundation for Educational Research.Grant-Vallone, E. J., & Ensher, E. A. (2001). An examination of work and personal life conflict, organizational support, and employee health among international
expatriates. International Journal of Intercultural Relations, 25, 261–278.Greenhaus, J. H., & Beutell, N. J. (1985). Sources of conflict between work and family roles. Academy of Management Review, 10, 76–88.Greenhaus, J. H., & Powell, G. N. (2003). When work and family collide: Deciding between competing role demands. Organizational Behavior and Human Decision
Processes, 90, 291–303.Gutek, B. A., Searle, S., & Klepa, L. (1991). Rational versus gender role explanations for work–family conflict. The Journal of Applied Psychology, 76, 560–568.Hochschild, A. R., & Machung, A. (1989). The second shift. New York: Viking.Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation
Modeling, 6, 1–55.Huffman, A. H., Youngcourt, S. S., Payne, S. C., & Castro, C. A. (2008). The importance of construct breadth when examining interrole conflict. Educational and
Psychological Measurement, 68, 515–530.Ilies, R., Schwind, K. M., & Heller, D. (2007). Employee well-being: A multilevel model linking work and non-work domains. European Journal of Work and
Organizational Psychology, 16, 326–341.Johnson, J. W. (2000). A heuristic method for estimating the relative weight of predictor variables in multiple regression. Multivariate Behavioral Research, 35,
1–19.Jöreskog, K. G., & Sörbom, D. (2005). LISREL 8.72. Chicago: Scientific Software International.Kahn, R. L., Wolfe, D. M., Quinn, R. P., Snoek, J. D., & Rosenthal, R. A. (1964). Organizational stress: Studies in role conflict and ambiguity. New York: Wiley.Kopelman, R. E., Greenhaus, J. H., & Connolly, T. F. (1983). A model of work, family, and interrole conflict: A construct validation study. Organizational Behavior and
Human Performance, 32, 198–215.Law, K. S., Wong, C., & Mobley, W. H. (1998). Toward a taxonomy of multidimensional constructs. Academy of Management Review, 23, 741–755.LeBreton, J. M., Hargis, M. B., Griepentrog, B., Oswald, F. L., & Ployhart, R. E. (2007). A multidimensional approach for evaluating variables in organizational
research and practice. Personnel Psychology, 60, 475–498.Lent, R. W., Singley, D., & Sheu, H. (2005). Social cognitive predictors of domain and life satisfaction: Exploring the theoretical precursors of subjective well-being.
Journal of Counseling Psychology, 52, 429–442.McCall, G. J., & Simmons, J. L. (1978). Identities and interactions: An examination of human associations in everyday life. New York: Free Press.Milliken, F. J., & Dunn-Jensen, L. M. (2005). The changing time demands of managerial and professional work: Implications for managing the work–life boundary.
In E. E. Kossek, & S. J. Lambert (Eds.), Work and life integration: Organizational, cultural, and individual perspectives (pp. 43–59) Mahwah, NJ: Erlbaum.Netemeyer, R. G., Boles, J. S., & McMurrian, R. (1996). Development and validation of work–family conflict and family–work conflict scales. The Journal of Applied
Psychology, 81, 400–410.Nord, W. R., Fox, S., Phoenix, A., & Viano, K. (2002). Real-world reactions to work–life balance programs: Lessons for effective implementation. Organizational
Dynamics, 30, 223–238.O'Driscoll, M. P., Ilgen, D. R., & Hildreth, K. (1992). Time devoted to job and off-job activities, interrole conflict, and affective experiences. The Journal of Applied
Psychology, 77, 272–279.Pavot, W., & Diener, E. (1993). Review of the satisfaction with life scale. Psychological Assessment, 5, 164–172.Podsakoff, S. B., MacKenzie, S. B., Lee, J., & Podsakoff, N. P. (2003). Method biases in behavioral research: A critical review of the literature and recommended
remedies. The Journal of Applied Psychology, 88, 879–903.Premeaux, S. F., Adkins, C. L., & Mossholder, K. W. (2007). Balancing work and family: A field study of multi-dimensional, multi-role work–family conflict. Journal
of Organizational Behavior, 28, 705–727.Rice, R. W., Frone, M. R., & McFarlin, D. B. (1992). Work–non-work conflict and the perceived quality of life. Journal of Organizational Behavior, 13, 155–168.Ruderman, M. N., Ohlott, P. J., Panzer, K., & King, S. N. (2002). Benefits of multiple roles for managerial women. Academy of Management Journal, 45, 369–386.Ryan, A. M., & Kossek, E. E. (2008). Work–life policy implementation: Breaking down or creating barriers to inclusiveness? Human Resource Management, 47,
295–310.Schramm, J. (2009). Work turns flexible. HRMagazine, 54, 88.
237J. Keeney et al. / Journal of Vocational Behavior 82 (2013) 221–237
Schwarz, N., & Strack, F. (2003). Reports of subjective well-being: Judgmental processes and their methodological implications. In D. Kahneman, E. Diener, & N.Schwarz (Eds.), Well-being: The foundations of hedonic psychology (pp. 61–84) New York: Sage.
Shockley, K. M., & Singla, N. (2011). Considering work–family interactions and satisfaction: A meta-analysis. Journal of Management, 37, 861–886.Siegel, P. A., Post, C., Brockner, J., Fishman, A. Y., & Garden, C. (2005). The moderating influence of procedural fairness on the relationship between work–life
conflict and organizational commitment. The Journal of Applied Psychology, 90(1), 13–24.Small, S. A., & Riley, D. (1990). Toward a multidimensional assessment of work spillover into family life. Journal of Marriage and the Family, 52, 51–61.Spannard, J. A. (1990). Beyond intent: Reentering college to complete the degree. Review of Educational Research, 60, 309–344.Staples, D. S., & Higgins, C. A. (1998). A study of the impact of factor importance weightings on job satisfaction measures. Journal of Business and Psychology, 13,
211–232.Sturges, J., & Guest, D. (2004). Working to live or living to work? Work/life balance early in the career. Human Resource Management Journal, 14, 5–20.Super, D. E. (1980). A life-span, life-space approach to career development. Journal of Vocational Behavior, 16, 282–298.Swindle, R. W., & Moos, R. H. (1992). Life domains in stressors, coping, and adjustment. In W. B. Walsh, K. H. Craik, & R. H. Price (Eds.), Person-environment
psychology: Models and perspectives (pp. 1–33) Mahwah, NJ: Erlbaum.Thoits, P. A. (1983). Multiple identities and psychological well-being: A reformulation and test of the social isolation hypothesis. American Sociological Review, 48,
174–187.Tonidandel, S., & LeBreton, J. M. (2011). Relative importance analysis: A useful supplement to regression analysis. Journal of Business and Psychology, 26, 1–9.Wadsworth, M., & Ford, D. H. (1983). Assessment of personal goal hierarchies. Journal of Counseling Psychology, 30, 514–526.Wells, S. J. (2007). Are you too family friendly? HRMagazine, 52, 35–40.Wood, G. J., & Newton, J. (2006). Childlessness and women managers: ‘Choice’, context, and discourses. Gender, Work and Organization, 13, 338–358.
