Spillover and CrossoverEffects of Work-FamilyConflict among Married andCohabiting Couples

Deniz Yucel1 and Beth A. Latshaw2

Abstract

The present study uses Wave 8 of the German Family Panel to test the spillover and crossover effects ofwork-family conflict on job satisfaction, relationship satisfaction, and mental health for individuals (actoreffects) as well as their spouses/partners (partner effects) in dual-earning couples. We further contributeby assessing whether the results vary by gender and union type. Results suggest that among married cou-ples, for job satisfaction, there are no gender differences in actor effects (but gender differences in partnereffects), and actor and partner effects remain distinct. For relationship satisfaction, there are no genderdifferences in actor or partner effects, but both effects remain distinct. For mental health, however, thereare gender differences in actor effects (but not in partner effects), and both effects remain distinct. Amongcohabitors, there are no differences in actor effects by gender, and adding in partner effects does not sig-nificantly improve the models predicting all three outcomes. Some results also suggest differences in rela-tionship dynamics between married and cohabiting couples.

Keywords

work-family conflict, spillover, crossover, job satisfaction, relationship satisfaction, mental health

INTRODUCTION

Work-family conflict is a topic of growing con-

cern in the twenty-first century as greater numbers

of dual-earning couples seek to balance their

responsibilities in these two domains. Greenhaus

and Beutell (1985:77) define work-family conflict

as “a form of inter-role conflict in which the role

pressures from the work and family domains are

mutually incompatible. . . . That is, participation

in the work (family) role is made more difficult

by virtue of participation in the family (work)

role.” This type of interrole conflict operates in

two distinct directions: One’s work role can hinder

one’s role in the family domain (work-to-family

conflict; WFC), or one’s family role can jeopar-

dize one’s role in the work domain (family-to-

work conflict; FWC). For example, having a dead-

line at work can affect one’s ability to attend

a child’s school play (WFC), whereas getting little

sleep due to caring for a newborn baby can affect

one’s ability to perform at a work meeting (FWC).

Existing literature suggests that both WFC and

FWC are correlated with a wide range of outcomes

(see e.g., Allen et al. 2000; Amstad et al. 2011;

Bakker, Demerouti, and Dollard 2008; Frone, Rus-

sell, and Barnes 1996; Gareis et al. 2009; Michel

et al. 2009; Ngo and Lui 1999). For example,

research finds negative associations between

1William Paterson University, Wayne, NJ, USA2Widener University, Chester, PA, USA

Corresponding Author:

Deniz Yucel, Department of Sociology, William Paterson

University, 300 Pompton Road, 465 Raubinger Hall,

Wayne, NJ 07470, USA.

Email: yuceld@wpunj.edu

Society and Mental Health2020, Vol. 10(1) 35–60

� American Sociological Association 2018DOI: 10.1177/2156869318813006

journals.sagepub.com/home/smh

WFC and FWC and job satisfaction (Allen et al.

2000; Bellavia and Frone 2005; Ford, Heinen,

and Langkamer 2007; Kossek and Ozeki 1998).

Likewise, there is evidence that both forms of

work-family conflict negatively correlate with

marital satisfaction (Chen and Li 2012; Matthews,

Conger, and Wickrama 1996; Voydanoff 2005)

and mental health indicators, such as depression

and psychological strain (Kelloway, Gottlieb,

and Barham 1999; Vinokur, Pierce, and Buck

1999). However, most studies to date have tested

the “spillover effects” of work-family conflict

using individual-level data (Amstad et al. 2011).

There has been much less in-depth examination

of “crossover effects” (Young, Schieman, and

Milkie 2014), particularly in terms of clarifying

the complex processes through which stress and

strain are transmitted across partners, resulting in

negative outcomes (e.g., declines in mental

health). In a prior work, Young et al. (2014)

accomplish this goal, becoming one of few studies

to fill this gap in the literature and thoroughly

examine the relationship between spouses’ WFC,

family stressors, FWC, and respondents’ mental

health. Further, they contribute by teasing out

the theoretical mechanisms by which the stress

process model (Pearlin 1999) explains the effects

of crossover and whether these dynamics might

differ for men and women.

We build on and extend Young et al.’s (2014)

work by using couple-level data and dyadic anal-

ysis to study the crossover effects of work-family

conflict, something few studies have done (Ham-

mer, Allen, and Grigsby 1997; Lu et al. 2016; Mat-

thews et al. 2006). These few existing studies have

small, nonrepresentative samples that typically

focus on specific occupations or outcomes, limit-

ing the robustness and generalizability of their

findings. Couple-level data are also important

because as Young et al. (2014:5) point out,

“spouses do not always have sufficient informa-

tion about the other.” This leads to a type of

bias Kenny and Acitelli (2001) call “assumed-

similarity bias,” where one assumes another’s

experience is similar to one’s own experience.

This type of bias might be especially present

among cohabitors, who are typically in less com-

mitted relationships of shorter durations (Brown

2000, 2003), perhaps making their reports of part-

ners’ behaviors less accurate or reliable because

they lack sufficient information about one another.

In fact, most existing studies on couples have

focused exclusively on married partners, with little

emphasis being placed on other types of unions,

such as cohabitors (Symoens and Bracke 2015).

Young et al. (2014) conclude their work by

encouraging future researchers to more closely

examine variations in crossover effects among

married and cohabiting couples, particularly to

assess whether there are differences in mental

health outcomes due to differences across union

statuses. We extend their work by closely explor-

ing these differences here. We also shift our theo-

retical focus toward examining whether crossover

effects of work-family conflict on mental health

might vary for married and cohabiting couples

due to differences in the “cost of caring” (Kessler

and McLeod 1984) and apply life course perspec-

tive as a new theoretical lens to interpret differen-

ces in work-family conflict by union type. Further,

we examine the relationship between work-family

conflict and two other domain-specific outcomes:

relationship satisfaction (family) and job satisfac-

tion (work). In doing so, we assess the usefulness

of applying Amstad et al.’s (2011) theoretical

framework to better understand the consequences

of work-family conflict across multiple domains

of social life.

Accordingly, in the following, we examine the

actor effects (AEs) and partner effects (PEs) of

WFC and FWC on outcomes across three domains

(job satisfaction, relationship satisfaction, and

mental health) for dual-earning German couples.

We contribute to the literature in three ways. First,

we empirically explore the relationship between

WFC, FWC, and these three outcomes using

couple-level data and dyadic data analysis. Sec-

ond, our study tests whether there are gender dif-

ferences in AEs and PEs. Third, we assess whether

AEs and PEs vary by union type by comparing

married and cohabiting couples.

THEORETICAL FRAMEWORKS

The experience of work-family conflict is associ-

ated with negative outcomes in the well-being of

workers across multiple areas of social life. Fol-

lowing a theoretical model first proposed by Bel-

lavia and Frone (2005) and more recently adopted

by Amstad et al. (2011), these outcomes can be

grouped into three major domains: work-related

(e.g., burnout, satisfaction, and job performance),

family-related (e.g., satisfaction and strain in the

relationship), or domain-unspecific (e.g., mental

health, physical health, and life satisfaction). For

36 Society and Mental Health 10(1)

the purpose of this paper, we will focus on one

outcome from each domain: (1) job satisfaction

(work), (2) relationship satisfaction (family), and

(3) mental health (domain-unspecific).

Amstad et al. (2011) adopt two alternate

hypotheses for understanding the relationship

between work-family conflict and the domain-

specific outcomes: the cross-domain and the

matching hypotheses. The first hypothesis (Frone,

Russell, and Cooper 1992a) proposes that there is

a “cross-domain” relationship between work-

family conflict and outcomes such that WFC

should be more influential on family-related

domain outcomes (e.g., relationship satisfaction)

and FWC should more strongly affect work-

related domain outcomes (e.g., job satisfaction).

In other words, conflict that emerges in one

domain has a deleterious effect on well-being in

a separate domain of social life. Frone et al.

(1992a) theorized that when one role a person

occupies (e.g., teacher) interferes with another of

their roles (e.g., mother), this individual will strug-

gle to fulfill the responsibilities associated with

the latter role and become dissatisfied with this

receiving role as a result (e.g., lower family satis-

faction resulting from WFC).

The “matching hypothesis” suggests the oppo-

site possibility—WFC should more negatively

impact work-related domain outcomes, and FWC

should more harshly impact family-related domain

outcomes. Here, because the root of the conflict

lies in one domain, individuals are likely to expe-

rience declines in well-being within that same

domain. According to Amstad et al. (2011:153),

this matching hypothesis is rooted in the theoreti-

cal notion that a person’s “negative affective reac-

tions” and/or “strain reactions” to work-family

conflict (e.g., lowered satisfaction at work because

they are spending less time with their family) will

correspond to the domain where the conflict and

problems originate (e.g., increasing demands at

work). Thus, the theoretical underpinnings of the

matching hypothesis are rooted in what Shockley

and Singla (2011:864) refer to as “source attribu-

tion,” which also links back to appraisal theories

(Lazarus 1991) and the suggestion that “when

self-relevant roles are threatened, individuals

tend to appraise the source of the threat

negatively.”

Numerous empirical studies have tested the

efficacy of the cross-domain and matching

hypotheses (see e.g., Li, Lu, and Zhang 2013;

Luk and Shaffer 2005; Nohe et al. 2015; Shockley

and Singla 2011) in predicting work-family con-

flict itself as well as various work-, family-, and

domain-unspecific outcomes related to it. As

Amstad et al. (2011), Ford et al. (2007), and

Nohe et al. (2015) point out in their meta-analyses,

the cross-domain perspective has been more

“popular” in the existing literature; however, the

matching hypothesis has received more empirical

support. For example, Shockley and Singla

(2011) found that there is a stronger relationship

between WFC and job satisfaction as well as

between FWC and relationship satisfaction. Nev-

ertheless, some scholars (see e.g., Li et al. 2013)

have questioned the generalizability of applying

the matching hypothesis in non-Western nations

like China. Given the likelihood that work-family

conflict might vary across cultures and contexts,

we also seek to test the usefulness of the cross-

domain and matching perspectives in explaining

outcomes of WFC and FWC in Germany.

Spillover/Actor Effects

Existing research outlines two theoretical path-

ways through which work-family conflict affects

individuals and their partners. The first, spillover,

transpires when stressors in one domain generate

strain that is then transferred to another domain,

thereby affecting an individual’s well-being. It is

said to occur because of interrole conflict (Green-

haus and Beutell 1985) that arises when individu-

als occupy multiple social roles (e.g., employee

and mother), and it is linked to negative outcomes

in job satisfaction, relationship satisfaction, and

mental health (see e.g., Bellavia and Frone 2005;

Grzywacz, Almeida, and McDonald 2002; Grzy-

wacz and Bass 2003; Grzywacz and Marks 2000;

Michel et al. 2011). Negative spillover is fre-

quently explained using theoretical frameworks

such as the role-scarcity hypothesis (Edwards

and Rothbard 2000) and conservation of resources

theory (Hobfoll 1989). The role-scarcity hypothe-

sis suggests that individuals have a limited number

of resources, and thus, strain can develop when

multiple roles pull from the same resources. Sim-

ilarly, conservation of resources theory proposes

that individuals typically strive to achieve and

maintain their resources, and thus, strain can

develop when a disruption in one’s workplace or

family leads to an inability to balance roles and

protect resources in either domain, leading to

a decline in well-being. In addition, the stress

Yucel and Latshaw 37

process model (Pearlin 1999) suggests that when

someone experiences primary stressors at work

or at home, they can lead to secondary stressors

that heighten and/or proliferate conflict, affecting

mental health specifically.

These theories have been tested, and the prior

research highlighted here demonstrates that there

is a negative association between work-family

conflict and job satisfaction, relationship satisfac-

tion, and mental health. In the following, we

extend this literature and contribute by using

couple-level data to evaluate whether there are

gender and/or union status differences in the spill-

over and crossover effects of work-family conflict,

in both directions, on three outcomes that Amstad

et al. (2011) would classify as being “domain spe-

cific” (job satisfaction and relationship satisfac-

tion) and “domain unspecific” (mental health). In

doing so, we also more thoroughly assess the use-

fulness of applying Amstad et al.’s (2011) theoret-

ical framework to examine work-family conflict

across social contexts.

Gender Differences in Spillover/ActorEffects

The experiences of work-family conflict for men

and women have changed over time. In the United

States, men’s reports of work-family conflict have

increased consistently across the past three deca-

des, particularly for fathers in dual-earner mar-

riages (Aumann et al. 2011; Galinsky, Aumann,

and Bond 2011; Nomaguchi and Johnson 2009).

This could be due in part to recent changes in

both gender ideologies and gendered divisions of

paid and unpaid labor (Winslow 2005). Women’s

labor force participation has increased, and fathers

are also devoting more time to child care and

housework (Bianchi, Robinson, and Milkie 2006;

Galinsky et al. 2011). Despite this movement

toward greater equality, women are still more

likely to manage the care of children, and tradi-

tional male breadwinner expectations persist

(Bianchi et al. 2006; Nomaguchi and Johnson

2009; Schieman and Glavin 2008; Schieman, Gla-

vin, and Milkie 2009). Moreover, scholars have

critiqued the workplace for being resistant to shift-

ing away from the male breadwinner model,

thereby disadvantaging mothers (Ridgeway and

Correll 2004; Williams 2001) and increasing lev-

els of work-family conflict for fathers (Aumann,

Galinsky, and Matos 2011).

We draw on these recent trends as well as sev-

eral theoretical perspectives on gender to generate

predictions about how the AEs of work-family

conflict might vary for men and women. Accord-

ing to Ridgeway (2011), despite movement toward

egalitarianism in the time use among romantic

partnerships, gender inequality continues to persist

due to powerful traditional beliefs and expecta-

tions about gender that can quickly be used to

frame and organize social interactions. For exam-

ple, due to expectations surrounding the norms of

roles like wife and mother, women will likely feel

more responsibility over and invest more time in

the family domain, while men will feel more

responsibility over and invest more time in the

work domain (see e.g., Bakker et al. 2008; Brum-

melhuis et al. 2008; Voydanoff 2002). Accord-

ingly, one might expect that men are more likely

to experience the negative AEs of WFC (due to

cultural expectations surrounding their career

roles, making work a greater source of conflict),

while women are more likely to experience the

negative AEs of FWC (due to cultural expecta-

tions surrounding their family roles, making fam-

ily a greater source of conflict). For example,

women are more likely than men to see their

employee role as negatively competing with their

family responsibilities (Simon 1995), and frequent

work contact is correlated with greater levels of

guilt and distress for women but not men (Glavin,

Schieman, and Reid 2011).

Prior literature testing gender differences is not

consistent (Cinamon and Rich 2002). Some stud-

ies have found stronger negative AEs of WFC

for men than women (Frone et al. 1996), while

others have found that men are more affected by

FWC spillover and women are more affected by

WFC spillover (Amstad and Semmer 2011;

Symoens and Bracke 2015). Despite the inconsis-

tent literature, because men and women still dem-

onstrate unequal divisions of paid and unpaid

labor (Bianchi et al. 2006; Nomaguchi and

Johnson 2009; Sayer 2005) and traditional cultural

expectations about gender persist throughout

social interactions today (Ridgeway 2011), we

expect that the AEs of WFC will be stronger for

men than women, while the AEs of FWC will be

stronger for women than men (Hypothesis 1).

Crossover/Partner Effects

A second theoretical pathway called crossover

occurs at the couple level when the stress an

38 Society and Mental Health 10(1)

individual experiences from WFC or FWC is

transmitted to one’s partner, thereby affecting his

or her well-being. As Bakker et al. (2008:901)

explain, “Whereas [spillover] is an intraindividual

transmission of stress or strain, crossover is

a dyadic, interindividual transmission of stress or

strain.” Thus, conflict between work and family

roles not only affects individual actors but their

romantic partners. Westman (2001, 2006) elabo-

rates on this phenomenon by proposing three plau-

sible mechanisms of transmission across couples.

First, partners may feel one another’s stress and

strain because they tend to empathize with the per-

son they share a relationship with. Second,

because partners’ lives are so closely connected,

the strains experienced by one are often felt by

the other, simply by virtue of them sharing their

experiences, homes, and (often) children together.

Finally, strain can affect an individual’s partner

due to a decline in effective couple-level commu-

nication or social interaction that results from the

work-family conflict the partner experiences (see

e.g., Amstad and Semmer 2011; Bakker and

Demerouti 2009; Bakker et al. 2008; Matthews

et al. 2006; Young et al. 2014). Moreover, the

stress process model (Pearlin 1999) also suggests

that experiences of primary and secondary stres-

sors can exacerbate and/or proliferate conflicts,

thereby negatively affecting the mental health of

both individuals and their partners. Thus, the exist-

ing theoretical models and literature lead us to

expect significant PEs for WFC and FWC. Specif-

ically, due to crossover, those whose spouses have

higher WFC and FWC will report significantly

lower job satisfaction, relationship satisfaction,

and mental health (Hypothesis 2).

Gender Differences in Crossover/Partner Effects

As stated, we believe that the AEs of WFC will be

stronger for men and the AEs of FWC will be

stronger for women. Accordingly, if the effects

of WFC and FWC cross over to the partners of

these individuals, we anticipate that these out-

comes will also vary by gender. Because we

hypothesized that men are more likely to experi-

ence WFC due to persistent masculine breadwin-

ner ideologies, female partners will likely have

to compensate by investing even more time in

the family domain. Thus, we expect that PEs of

WFC will be stronger for women than men

(Baruch, Biener, and Barnett 1987; Niles and

Goodnough 1996; Rosenthal 1985).

Theoretical perspectives on gender socializa-

tion and empathy can be employed to generate

additional hypotheses about why the outcomes of

partners’ work-family conflict might also vary

for men and women, particularly in terms of men-

tal health consequences. For example, Symoens

and Bracke (2015) found that husbands’ WFC

had an impact on their wives’ mental health,

whereas wives’ WFC did not have a negative

effect on their husbands’ mental health. According

to Kessler and McLeod (1984) and Rosenfield and

Smith (2010), the relationships between empathy,

sensitivity, and femininity are transmitted to

women via gender socialization. As a result,

when individuals in a woman’s social network

experience conflict, women might have a height-

ened awareness of the conflict (Rosenfield and

Smith 2010) and experience greater levels of dis-

tress as a result (Kessler and McLeod 1984).

Thus, women are not necessarily more vulnerable

to stress related to work-family conflict but rather,

are socialized to internalize and empathize when

people they care about experience conflict (Simon

1998). Because of these connections between gen-

der socialization and empathy, we expect that the

PEs of FWC will also be stronger for women than

men (Hypothesis 3).

Finally, we expect that AEs and PEs will differ.

Unlike AEs, PEs are more likely to be indirect

because they require transmission across individu-

als and are more dependent on a variety of factors,

including how close partners are, how much time

they spend together, and their level of communica-

tion (see e.g., Kenny and Cook 1999; Westman

2001, 2006). Thus, we expect that AEs will gener-

ally be stronger than PEs (Hypothesis 4).

COMPARING MARRIED ANDCOHABITING COUPLES

As new family structures become more common,

particularly in the United States and Europe, it is

also increasingly important to compare the effects

of work-family conflict across unions. Further,

because our study tests whether AEs and PEs

vary between married and cohabiting couples, it

is critical to review general ways relationships dif-

fer across these two formations. First, research

suggests that cohabiting unions, compared to mar-

riages, are less institutionalized (Cherlin 2004;

Yucel and Latshaw 39

Yabiku and Gager 2009), leading to lower levels

of well-being for cohabitors (Soons, Kalmijn,

and Teachman 2009). In other words, the norms

governing the behavior of individuals who cohabit

are not as clearly delineated as they are among

spouses (Cherlin 2004). As a result, cohabiting

partnerships tend to be associated with lower lev-

els of relationship satisfaction and commitment as

well as a higher risk of dissolution (see e.g.,

Brown 2003, 2004; Brown, Manning, and Payne

2015).

Second, cohabitation can have different mean-

ings to those who enter into the arrangement. For

some, it is more akin to being single than married

(Rindfuss and VandenHeuvel 1990), while for

others, it is mostly a short-term precursor to mar-

riage or even a substitution for marriage (Heuve-

line and Timberlake 2004). In the United States

today, cohabitation continues to be primarily

short-lived and is very rarely viewed as a substitu-

tion for marriage (Smock and Manning 2004).

Cohabitors continue to receive far fewer rights

and legal protections than married couples. In

addition, despite the fact that the majority of cou-

ples will cohabit prior to first marriages, few

cohabiting unions are long term in duration, and

cohabitation is more common among individuals

with a lower socioeconomic status (Brown et al.

2015).

While cohabitation has increased in all Euro-

pean countries in recent decades, the highest rates

are found in Germany, Austria, and Norway

(Perelli-Harris et al. 2014). In German-speaking

countries, cohabitation is primarily viewed as

a younger stage in the life course that tends to occur

before marriage and children. In addition, cohabita-

tion is associated with having greater levels of free-

dom and an ability to explore self-fulfillment,

sometimes with multiple partners. Similar to the

United States, German cohabitors have very few

legal rights or responsibilities (Gassen and Perelli-

Harris 2015; Le Goff 2002). Still, differences exist

within Germany. In the Western region, cohabitors

generally desire to marry and associate marriage

with financial stability and plans to have children.

In contrast, East German cohabitors express a lower

desire to marry, see fewer differences between

cohabitation and marriage, and interpret having

children with someone as being more serious than

marriage (Perelli-Harris et al. 2014).

Based on this literature, we expect that AEs

and PEs will vary between married and cohabiting

couples in Germany. Very few studies have tested

these differences among union types. Symoens

and Bracke (2015) predicted that FWC would

cause greater spillover strain for cohabiting indi-

viduals than married individuals because married

men and women have more committed, secure

relationships and thus will not feel their well-being

is threatened if they must devote more time to

work. Cohabitors, who are more prone to relation-

ship uncertainty, are therefore at greater risk of

well-being declines resulting from FWC (see

e.g., Knobloch and Knobloch-Fedders 2010; Kno-

bloch, Miller, and Carpenter 2007). In contrast, the

same study hypothesized that WFC would have

more consequential PEs for married couples because

greater devotion and investment in one’s family

among married partners equates to more negative

outcomes in well-being when conflict arises.

While Symoens and Bracke (2015) ultimately

found no differences in AEs and PEs for cohabit-

ing and married couples, we draw on their study to

make our own predictions here. Due to higher lev-

els of commitment, relationship closeness, and

intimacy among married people as well as the

increased emphasis on freedom and self-fulfill-

ment among cohabitors, we infer that married

spouses will be more affected by both the WFC

and FWC of their partners. In opposition, because

cohabiting unions are not as committed or as likely

to last over the long term, we infer that cohabitors

will be less affected by the WFC and FWC of their

partners. In other words, as Westman (2001, 2006)

explains, negative PEs are transmitted because of

the empathy, shared connection, and support cou-

ples experience by virtue of being in longer-term,

more committed relationships. Because cohabitors

likely feel less commitment, connection, and sta-

bility, the negative AEs of WFC and FWC might

seem more pronounced in the absence of a strong

support system from their partners.

Finally, we can also draw on differential vul-

nerability theories to generate predictions about

how the consequences of work-family conflict

vary by marital status. According to this perspec-

tive, unmarried individuals are likely more vulner-

able to experiencing distress related to the conse-

quences of strain and conflict between work and

family roles (see e.g., Pearlin and Johnson 1977;

Simon 1998). In other words, marriage can serve

as a protective barrier to the higher risks unmar-

ried individuals face (e.g., isolation and financial

hardship). Thus, we expect that AEs will be stron-

ger among cohabiting couples and PEs will be

stronger among married couples (Hypothesis 5).

40 Society and Mental Health 10(1)

MATERIALS AND METHODS

This study uses Wave 8 of the German Family

Panel (pairfam), which focuses on partnership

and family dynamics in Germany and is funded

by the German Research Foundation (Bruderl

et al. 2017; Huinink et al. 2011). The survey, first

launched in 2008–2009, collects data from

a national, random sample of 12,402 anchor per-

sons as well as their spouses and partners annually.

Questions about work-life balance were only

asked in Waves 6 and 8.1 This study focuses on

the more recent wave and is limited to married

and cohabiting couples where both spouses/part-

ners are employed (1,043 married and 323 cohab-

iting couples).

On average, among the couples in the sample,

wives are approximately 38, and husbands are

approximately 41 years old, while female and

male cohabitors are around 29 and 31, respec-

tively. Approximately 49 percent of the married

men and 54 percent of the married women com-

pleted upper education,2 whereas 57 percent of

the cohabiting men and 64 percent of the cohabit-

ing women completed upper education. On aver-

age, married couples have been married for 11

years, and cohabiting couples have been together

for 4 years. Among cohabiting couples, around

27 percent have plans to get married. Table 1

presents detailed descriptive statistics for the cou-

ples in our sample and the full list of variables.

Dependent Variables

In this study, the three dependent variables are job

satisfaction, relationship satisfaction, and mental

health. Job satisfaction is measured by one indica-

tor: “How satisfied are you with school, education

and career?”3 The answer categories range from

0 (very dissatisfied) to 10 (very satisfied). This

item was highly skewed, and therefore, a log trans-

formation of the variable was used. Higher num-

bers indicate greater levels of job satisfaction.

Relationship satisfaction is also measured by one

item: “All in all, how satisfied are you with your

relationship?”4 The answer categories range from

0 (very dissatisfied) to 10 (very satisfied). This

item was also highly skewed; therefore, a log

transformation of the variable was used.5 Higher

numbers indicate greater levels of relationship sat-

isfaction. Finally, mental health is measured using

six indicators. Respondents are asked: “In the

following list you see a number of statements

that people can use to describe themselves. Please

read each statement and indicate from among the

four answers the one that corresponds to the way

you feel in general. (1) My mood is melancholy.

(2) I am happy. (3) I am depressed. (4) I am sad.

(5) I am in desperation. (6) My mood is gloomy.”6

The answer categories range from 1 (almost never)

to 4 (almost always). The factor loadings of these

six items range from .60 to .75 and .58 to .71 for

married and cohabiting couples, respectively,

which all exceed the threshold level of .50 (Hair

et al. 2006). Cronbach’s alpha scores for men

and women are .78 and .83, respectively (for mar-

ried couples), and .78 and .81, respectively (for

cohabiting couples), indicating high internal reli-

ability. After reverse coding the second item, sum-

ming these six items, and taking the average of the

summed score, higher numbers indicate lower lev-

els of mental health.

Independent Variables

This study uses two main independent variables:

WFC and FWC. To measure WFC, respondents

are asked:

(1) Because of my workload in my job,

vocational training, or university education,

my personal life suffers. (2) Even when I

am doing something with my friends, part-

ner, or family, I must often think about

work. (3) After the stress of work, I find it

difficult to relax at home and/or to enjoy

my free time with others. (4) My work pre-

vents me from doing things with my friends,

partner, and family more than I’d like.

Each item ranges from 1 (not at all) to 5 (abso-

lutely).7 The factor loadings of these four items

range from .65 to .86 and .62 to .82 for married

and cohabiting couples, respectively. Cronbach’s

alpha scores for men and women are .75 and .82,

respectively (for married couples), and .75 and

.81, respectively (for cohabiting couples), indicat-

ing high internal reliability. After summing these

five items and taking the average to create a scale,

higher scores indicate greater levels of WFC.

To measure FWC, respondents are asked:

(1) Because I am often under stress in my

private life, I have problems concentrating

Yucel and Latshaw 41

Tab

le1.

Des

crip

tive

Stat

istics

for

allVar

iable

s.

Mar

ried

Couple

s(N

=1,0

43)

Cohab

itin

gC

ouple

s(N

=323)

Var

iable

Nam

eR

ange

Mea

n/P

roport

ion

SDM

ean/P

roport

ion

SD

Dep

enden

tva

riab

les

Fem

ale

job

satisf

action

1–3

1.8

3.8

31.9

1.8

4M

ale

job

satisf

action

1–3

1.8

6.8

11.8

1.8

3Fe

mal

ere

lationsh

ipsa

tisf

action

1–3

2.1

8.8

52.2

5.8

3M

ale

rela

tionsh

ipsa

tisf

action

1–3

2.2

2*

.84

2.1

1*

.82

Fem

ale

men

talhea

lth

1–3.8

31.5

3***

.43

1.7

1***

.51

Mal

em

enta

lhea

lth

1–3.3

31.4

9**

.42

1.5

7**

.40

Indep

enden

tva

riab

les

Fem

ale:

Work

-to-f

amily

confli

ct1–5

2.2

0***

.99

2.7

0***

1.0

0Fe

mal

e:Fa

mily

-to-w

ork

confli

ct1–5

1.6

6*

.78

1.7

6*

.70

Mal

e:W

ork

-to-f

amily

confli

ct1–5

2.5

2.8

92.5

1.8

9M

ale:

Fam

ily-t

o-w

ork

confli

ct1–5

1.6

5.6

41.7

0.6

6C

ontr

olva

riab

les

Rel

atio

nsh

ipdura

tion

(log)

–2.4

8to

5.7

54.5

4***

.99

.82***

1.3

0Pre

sence

of

pre

schoolch

ildre

nin

the

house

hold

0–1

.33***

—.1

6***

—Fe

mal

ew

ork

hours

1–70

28.3

3***

12.0

137.5

1***

9.8

4M

ale

work

hours

1–85

43.6

2***

9.0

941.4

9***

10.1

1Fe

mal

elo

wer

educa

tion

0–1

.08

—.0

6—

Fem

ale

inte

rmed

iate

educa

tion

0–1

.38**

—.3

0**

—Fe

mal

eupper

educa

tion

0–1

.54***

—.6

4***

—M

ale

low

ered

uca

tion

0–1

.16***

—.0

8***

—M

ale

inte

rmed

iate

educa

tion

0–1

.35

—.3

4—

Mal

eupper

educa

tion

0–1

.49**

—.5

7**

—Fe

mal

enat

ional

ity

0–1

.95**

—.9

8**

—M

ale

nat

ional

ity

0–1

.96

—.9

7—

Fem

ale

inco

me

(log)

4.3

2–9.1

07.0

1**

.70

7.1

6**

.60

Mal

ein

com

e(log)

5.7

0–9.3

97.7

6***

.48

7.4

1***

.53

Couple

lives

inEas

tG

erm

any

0–1

.33

—.3

5—

Pla

ns

toge

tm

arri

ed(f

or

cohab

itin

gco

uple

s)a

0–1

——

.27

—

Not

e.T

he

indic

ators

of

the

dep

enden

tva

riab

lear

eco

ded

soth

athig

her

score

sin

dic

ate

grea

ter

job

satisf

action

and

rela

tionsh

ipsa

tisf

action

and

wors

em

enta

lhea

lth.

a Pla

ns

toge

tm

arri

edw

asas

ked

toco

hab

itin

gco

uple

sin

the

surv

ey.T

her

efore

,th

ere

isno

info

rmat

ion

for

mar

ried

couple

s.*p

\.0

5.**p

\.0

1.***p

\.0

01

(tw

o-t

aile

dte

sts)

.

42

on my work. (2) Because of my personal

schedule, I often lack time to do my work.

(3) The time I need for my partner, family,

and friends keeps me from being more

involved in my job, vocational training, or

university education. (4) Conflicts in my

personal life reduce my work performance.

Each item ranges from 1 (not at all) to 5 (abso-

lutely). The factor loadings of these four items

range from .61 to .87 and .62 to .83 for married

and cohabiting couples, respectively. Cronbach’s

alpha scores for men and women are .74 and .78,

respectively (for married couples), and .74 and

.76, respectively (for cohabiting couples), indicat-

ing high internal reliability. After summing these

five items and taking the average to create a scale,

higher scores indicate greater levels of FWC.

Control Variables

This study also uses several other variables that

have been shown to be associated with our inde-

pendent and/or dependent variables (Bruck, Allen,

and Spector 2002; De Simone et al. 2014; Min-

notte, Minnotte, and Bonstrom 2015; Roehling,

Jarvis, and Swope 2005; Schieman et al. 2009;

Voydanoff 2005, 2007; Yucel 2017a, 2017b): edu-

cation, nationality, work hours,8 income, marriage

(relationship) duration,9 the presence of preschool-

aged children in the household, plans to marry in

the future (for cohabiting couples), and whether

the individual lives in the East or West Germany.10

Analytical Strategy

This study follows the same analytical approach of

prior research (Yucel 2017a; Yucel and Gassanov

2010). The actor-partner interdependence model

(APIM) framework is used, and dyadic data anal-

ysis is carried out using structural equation model-

ing (SEM) in AMOS 22.0. As part of dyadic data

analysis, first, the AEs and PEs for our two main

independent variables, WFC and FWC,11 are

tested. Next, using chi-square difference tests,

this study tests the gender differences in AEs

and PEs between men and women and whether

AEs and PEs are equal to each other. The relative

fits of these nested models in SEM are compared.

If the difference in chi-square between uncon-

strained models (i.e., coefficients are estimated

separately for both genders and for both types of

unions) and constrained models (i.e., coefficients

are constrained to be equal for both genders and

for both types of unions), the unconstrained model

is preferred. However, if there are no differences,

the constrained models with pooled estimates are

preferred (Kenny and Cook 1999). Finally, to

test whether AEs and PEs vary between married

and cohabiting couples, multigroup analyses are

used (see Results section for details).

RESULTS

Descriptive Findings

Descriptive findings for all variables are displayed

in Table 1. There are no differences between mar-

ried men (women) and cohabiting men (women) in

terms of their reports of job and relationship satis-

faction; however, cohabiting men and women are

significantly more likely than married men and

women (respectively) to have worse mental

health. There are no differences in reports of

WFC and FWC between cohabiting and married

men; however, cohabiting women are more likely

to report WFC and FWC than married women.

Cohabiting couples also have significantly shorter

relationships than married couples, while spouses

have significantly more preschool-aged children

than cohabitors.

Multivariate Analyses

Consistent with the approach in Yucel and Gassa-

nov (2010) and Yucel (2017a), multivariate analy-

ses proceed in five steps. Results for married cou-

ples are displayed in Tables 2 through 4, while

Table 5 presents the final models for cohabiting

couples across all three dependent variables.

Tables showing the full models for cohabiting

couples can be provided on request.

Married Couples

First, we test if there are any AEs between

respondents’ WFC, FWC, and their reports of

job satisfaction, relationship satisfaction, and men-

tal health. As shown in the first model (Model 1)

of Tables 2 through 4, significant AEs emerge.

For both husbands and wives, those with higher

WFC (b = –.094, p \ .001; b = –.065, p \ .001

for husbands and wives, respectively) report sig-

nificantly lower job satisfaction. Higher FWC is

Yucel and Latshaw 43

Tab

le2.

Pre

dic

tive

Model

of

Job

Satisf

action

among

Mar

ried

Couple

s(N

=1,0

43

Couple

s).

Model

1Te

stin

gfo

rA

ctor

Effec

ts

Model

2Te

stin

gfo

rG

ender

Diff

eren

ces

inA

ctor

Effec

ts

Mo

del

3T

est

ing

for

Part

ner

Eff

ects

Model

4Te

stin

gfo

rG

ender

Diff

eren

ces

inPar

tner

Effec

ts

Model

5Te

stin

gfo

rD

iffer

ence

sin

Act

or

and

Par

tner

Effec

ts

b(S

E)

b(S

E)

b(S

E)

b(S

E)

b(S

E)

Indiv

idual

-lev

elac

tor

effe

cts

Work

-to-f

amily

confli

ctW

:–.1

18***

(.032)

H:–.2

00***

(.031)

–.1

60***

(.023)

–.1

58***

(.023)

–.1

58***

(.023)

–.1

02***

(.016)

Fam

ily-t

o-w

ork

confli

ctW

:–.1

21***

(.038)

H:–.1

09**

(.042)

–.1

10***

(.028)

–.1

08***

(.028)

–.1

09***

(.028)

–.0

42*

(.020)

Indiv

idual

-lev

elpar

tner

effe

cts

Work

-to-f

amily

confli

ctW

:.0

00

(.031)

H:

–.0

94**

(.033)

–.0

46*

(.023)

–.1

02***

(.016)

Fam

ily-t

o-w

ork

confli

ctW

:–.0

01

(.037)

H:

.043

(.044)

.023

(.028)

–.0

42*

(.020)

Chi-sq

uar

e10.6

71*

14.4

50*

5.9

96*

10.4

56*

47.9

32***

df4

62

46

Com

par

ativ

eFi

tIn

dex

.97

.97

.97

.97

.97

Root

mea

nsq

uar

eer

ror

of

appro

xim

atio

n.0

4.0

4.0

4.0

4.0

5R

2(w

ives

).1

0.1

1.1

2.1

2.0

9R

2(h

usb

ands)

.11

.10

.09

.20

.09

Not

e.T

his

study

also

contr

ols

for

the

follo

win

gva

riab

les:

mar

ital

dura

tion,w

ork

hours

,ed

uca

tion,nat

ional

ity,

inco

me,l

ivin

gin

Eas

tor

Wes

tG

erm

any,

and

hav

ing

pre

schoolch

ildre

nliv

ing

inth

ehouse

hold

.H

igher

score

sin

dic

ate

grea

ter

job

satisf

action.B

est-

fitting

model

ishig

hlig

hte

din

bold

.W

=w

ives

;H

=husb

ands.

*p

\.0

5.**p

\.0

1.***p

\.0

01

(tw

o-t

aile

dte

sts)

.

44

Tab

le3.

Pre

dic

tive

Model

of

Rel

atio

nsh

ipSa

tisf

action

among

Mar

ried

Couple

s(N

=1,0

43

Couple

s).

Model

1Te

stin

gfo

rA

ctor

Effec

ts

Model

2Te

stin

gfo

rG

ender

Diff

eren

ces

inA

ctor

Effec

ts

Model

3Te

stin

gfo

rPar

tner

Effec

ts

Mo

del

4T

est

ing

for

Gen

der

Dif

fere

nces

inP

art

ner

Eff

ects

Model

5Te

stin

gfo

rD

iffer

ence

sin

Act

or

and

Par

tner

Effec

ts

b(S

E)

b(S

E)

b(S

E)

b(S

E)

b(S

E)

Indiv

idual

-lev

elac

tor

effe

cts

Work

-to-f

amily

confli

ctW

:–.0

53

(.032)

H:–.0

75*

(.032)

–.0

63**

(.023)

–.0

68**

(.023)

–.0

68**

(.023)

–.0

56**

(.018)

Fam

ily-t

o-w

ork

confli

ctW

:–.1

68***

(.037)

H:–.2

13***

(.043)

–.1

85***

(.028)

–.1

94***

(.029)

–.1

94***

(.029)

–.1

32***

(.022)

Indiv

idual

-lev

elpar

tner

effe

cts

Work

-to-f

amily

confli

ctW

:–.0

01

(.032)

H:–.0

89**

(.032)

–.0

45*

(.023)

–.0

56**

(.018)

Fam

ily-t

o-w

ork

confli

ctW

:–.1

04**

(.037)

H:–.0

32

(.043)

–.0

69*

(.029)

–.1

32***

(.022)

Chi-sq

uar

e23.1

14***

24.7

49***

2.9

42

7.0

64

24.4

77***

df4

62

46

Com

par

ativ

eFi

tIn

dex

.98

.98

.98

.98

.98

Root

mea

nsq

uar

eer

ror

of

appro

xim

atio

n.0

5.0

5.0

2.0

3.0

5R

2(w

ives

).0

6.0

7.0

9.0

9.0

8R

2(h

usb

ands)

.06

.05

.07

.07

.07

Not

e.T

his

study

also

contr

ols

for

the

follo

win

gva

riab

les:

mar

ital

dura

tion,w

ork

hours

,ed

uca

tion,nat

ional

ity,

inco

me,l

ivin

gin

Eas

tor

Wes

tG

erm

any,

and

hav

ing

pre

schoolch

ildre

nliv

ing

inth

ehouse

hold

.H

igher

score

sin

dic

ate

grea

ter

rela

tionsh

ipsa

tisf

action.B

est-

fitting

model

ishig

hlig

hte

din

bold

.*p

\.0

5.**p

\.0

1.***p

\.0

01

(tw

o-t

aile

dte

sts)

.

45

Tab

le4.

Pre

dic

tive

Model

of

Men

talH

ealth

among

Mar

ried

Couple

s(N

=1,0

43

Couple

s).

Model

1Te

stin

gfo

rA

ctor

Effec

ts

Model

2Te

stin

gfo

rG

ender

Diff

eren

ces

inA

ctor

Effec

ts

Model

3Te

stin

gfo

rPar

tner

Effec

ts

Mo

del

4T

est

ing

for

Gen

der

Dif

fere

nces

inP

art

ner

Eff

ects

Model

5Te

stin

gfo

rD

iffer

ence

sin

Act

or

and

Par

tner

Effec

ts

b(S

E)

b(S

E)

b(S

E)

b(S

E)

b(S

E)

Indiv

idual

-lev

elac

tor

effe

cts

Work

-to-f

amily

confli

ctW

:.0

89***

(.016)

H:.1

56***(.015)

.125***

(.011)

.090***

(.017)

.155***

(.016)

.088***

(.016)

.154***

(.015)

.072***

(.008)

Fam

ily-t

o-w

ork

confli

ctW

:.1

20***

(.019)

H:.1

23***

(.021)

.117***

(.014)

.119***

(.019)

.121***

(.021)

.120***

(.019)

.122***

(.021)

.067***

(.010)

Indiv

idual

-lev

elpar

tner

effe

cts

Work

-to-f

amily

confli

ctW

:.0

30*

(.013)

H:.0

27

(.015)

.021*

(.010)

.072***

(.008)

Fam

ily-t

o-w

ork

confli

ctW

:.0

34*

(.016)

H:.0

27

(.021)

.019

(.014)

.067***

(.010)

Chi-sq

uar

e10.1

54*

21.7

90***

1.9

69

4.5

70

115.3

41***

df4

62

46

Com

par

ativ

eFi

tIn

dex

.98

.98

.98

.98

.98

Root

mea

nsq

uar

eer

ror

of

appro

xim

atio

n.0

4.0

5.0

3.0

3.0

5R

2(w

ives

).1

6.1

9.1

6.1

7.1

5R

2(h

usb

ands)

.21

.17

.22

.22

.15

Not

e.T

his

study

also

contr

ols

for

the

follo

win

gva

riab

les:

mar

ital

dura

tion,w

ork

hours

,ed

uca

tion,nat

ional

ity,

inco

me,l

ivin

gin

Eas

tor

Wes

tG

erm

any,

and

hav

ing

pre

schoolch

ildre

nliv

ing

inth

ehouse

hold

.H

igher

score

sin

dic

ate

wors

em

enta

lhea

lth.B

est-

fitting

model

ishig

hlig

hte

din

bold

.*p

\.0

5.**p

\.0

1.***p

\.0

01

(tw

o-t

aile

dte

sts)

.

46

associated with lower relationship satisfaction for

both wives (b = –.084, p \ .001) and husbands

(b = –.093, p \ .001). In addition, both spouses

with higher WFC (b = .156, p \ .001; b = .089,

p \ .001 for husbands and wives, respectively)

and FWC (b = .123, p \ .001; b = .120, p \.001 for husbands and wives, respectively) report

worse mental health.

Model 2, Tables 2 through 4, shows the results

for gender differences in AEs. According to the

chi-square difference test, comparing Models 1

and 2, the effects are not significantly different

for job satisfaction and relationship satisfaction

(Dx2 = 4.51, df = 2, p . .10; Dx2 = 3.30, df = 2,

p . .10, respectively). This indicates that there

are no gender differences in AEs. Specifically,

the negative effects of WFC on job satisfaction

(b = –.080, p \ .001) and FWC on relationship

satisfaction (b = –.086, p \ .001) are similar

between spouses. On the other hand, for models

that predict mental health, the models are signifi-

cantly different between Models 1 and 2 (Dx2 =

11.64, df = 2, p \ .01). This indicates that there

are indeed gender differences in AEs for mental

health. Specifically, the AE of WFC on mental

health is significantly stronger for husbands (b =

.156, p \ .001) than wives (b = .089, p \ .001).

There are no gender differences, however, in the

AEs of FWC on mental health.

Model 3 in Tables 2 through 4 tests whether

PEs significantly improve the path models of job

satisfaction, relationship satisfaction, and mental

health. According to the chi-square difference

test, comparing Models 2 and 3 across Tables 2

through 4, adding PEs does improve our under-

standing of the correlates of job satisfaction, rela-

tionship satisfaction, and mental health among

married couples (Dx2 = 9.04, df = 4, p \ .10;

Dx2 = 8.84, df = 4, p \ .10; Dx2 = 19.82, df = 4,

p \ .001, respectively). Model 3 is preferred

over Model 2. Specifically, wives of husbands

who report higher WFC have lower job satisfac-

tion (b = –.033, p \ .01), and husbands of wives

who report higher FWC have lower relationship

satisfaction (b = –.029, p\ .05). Finally, husbands

of wives who report higher WFC and FWC have

worse mental health (b = .030, p \ .05; b =

.034, p \ .05, respectively).

Model 4 in Tables 2 through 4 tests whether

there are gender differences in PEs. Comparing

Model 3 and Model 4, the results indicate that

there are gender differences in PEs for job satis-

faction (Dx2 = 6.84, df = 2, p \ .05). Specifically,

wives of husbands with higher WFC report lower

job satisfaction (b = –.033, p \ .01). Thus, Model

3 is preferred over Model 4. For relationship satis-

faction and mental health, PEs work similarly

between husbands and wives (Dx2 = .35, df = 2,

p . .10; Dx2 = 2.60, df = 2, p . .10, respectively).

Thus, Model 4, the restricted model, is preferred

over Model 3. Specifically, individuals who are

married to spouses with higher FWC also report

lower relationship satisfaction (b = –.025, p \.05). Finally, individuals who are married to

spouses with higher WFC conflict report lower

mental health (b = .021, p \ .05). These findings

are independent of the significant AEs in the

model.

Model 5 in Tables 2 through 4 tests whether

AEs and PEs are statistically equal. For example,

the analysis examines whether a person’s job sat-

isfaction is equally associated with one’s own

reports and one’s spouse’s reports of WFC and

FWC. The chi-square difference tests comparing

Models 4 and 5 are significant, so Model 4 is pre-

ferred for job satisfaction, relationship satisfac-

tion, and mental health (Dx2 = 43.52, df = 4,

p \ .001; Dx2 = 25.49, df = 2, p \ .001; Dx2 =

110.77, df = 2, p \ .001, respectively). AEs and

PEs are significantly different from each other.

Specifically, the AE of WFC on job satisfaction

(b = –.080, p \ .001) is significantly stronger

than the husbands’ PE on their wives’ job satisfac-

tion (b = –.033, p \ .01), whereas wives’ PE on

their husbands’ job satisfaction is not significant

(b = .008, p . .10). Moreover, the results suggest

that AE of FWC on relationship satisfaction (b =

–.089, p \ .001) is significantly stronger than

the PE of FWC (b = –.025, p \ .05). Moreover,

the AE of WFC on mental health (b = .088, p \.001; b = .154, p \ .001 for wives and husbands,

respectively) is significantly stronger than the PE

(b = .021, p \ .05). Finally, the AE of FWC on

mental health for both wives and husbands is sig-

nificant (b = .120, p \ .001; b = .122, p \ .001,

respectively), whereas the PE of FWC is not.

Overall, the best-fitting model for job satisfac-

tion is Model 3 (see the bold text in Table 2),

where there are no gender differences in AEs but

gender differences in PEs and these effects remain

distinct. The best-fitting model for relationship

satisfaction is Model 4 (see the bold text in Table

3), where there are no gender differences in AEs

and PEs but these effects remain distinct. The

best-fitting model for mental health is Model 4

(see the bold text in Table 4), where there are

Yucel and Latshaw 47

gender differences in AEs but no gender differen-

ces in PEs and these effects remain distinct. For

the job satisfaction model (see Model 3 in Table

2), the significant coefficients are the AEs (for

both genders) and husbands’ PE of WFC (b =

–.080, p \ .001; b = –.033, p \ .01, respectively).

For the relationship satisfaction model (see Model

4 in Table 3), the significant coefficients are the

AEs and PEs (for both genders) of FWC (b =

–.089, p \ .001; b = –.025, p \ .05, respectively).

For the mental health model (see Model 4 in Table

4), the AE of WFC for wives and husbands is b =

.088 (p \ .001) and b = .154 (p \ .001), respec-

tively. The AE of FWC for wives and husbands

on mental health is b = .120 (p \ .001) and b =

.122 (p \ .001), respectively. On the other hand,

the PE of WFC on mental health is b = .021

(p \ .05). The best-fitting models for all three

outcomes for married couples are also shown in

Figure 1.

Cohabiting Couples

Table 5 shows the same five steps as described

previously for cohabiting couples. The results are

different from married couples, indicating that

the best-fitting model is Model 2, where there

are no gender differences in AEs and PEs do not

significantly add to the model. This is the best

model for predicting job satisfaction, relationship

satisfaction, and mental health. This model also

shows that for cohabitors, individuals with higher

WFC report lower job satisfaction (b = –.114, p \.001). In addition, those with higher FWC report

lower relationship satisfaction (b = –.049, p \.01). Lastly, those with higher WFC and FWC

report worse mental health (b = .151, p \ .001;

b = .116, p \ .001, respectively). On the other

hand, among cohabitors, partners’ reports do not

significantly add to the models predicting job sat-

isfaction, relationship satisfaction, and mental

health. Only the best-fitting model for all three

dependent variables is displayed in Table 5. The

full tables showing all five models for all three

dependent variables can be provided on request.

Multigroup Analyses

As the last step, this paper tests whether the AEs of

WFC and FWC on job satisfaction, relationship

satisfaction, and mental health vary between mar-

ried and cohabiting couples.12 Following the same

analytical approach from prior research (Yucel

2017a; Yucel and Gassanov 2010), multigroup

analyses are used to examine group differences

by running a series of nested models where all

Table 5. Final Model for Job Satisfaction, Relationship Satisfaction, and Mental Health among CohabitingCouples (N = 323 couples)

Job satisfaction Relationship Satisfaction Mental Healthb (SE) b (SE) b (SE)

Individual-level actor effectsWork-to-family conflict –.239*** (.038) –.012 (.036) .151*** (.019)Family-to-work conflict –.082 (.052) –.143** (.048) .116*** (.026)

Individual-level partner effectsWork-to-family conflictFamily-to-work conflict

Chi-square 4.949 13.670* 7.246df 6 6 6Comparative Fit Index .98 .98 .98Root mean square error of approximation .02 .05 .03R2 (female partners) .18 .08 .21R2 (male partners) .11 .11 .22

Note. This study also controls for the following variables: relationship duration, work hours, education, nationality,income, living in East or West Germany, plans to marry their current partner in the future, and having preschoolchildren living in the household. Higher scores indicate greater job and relationship satisfaction but worse mentalhealth.*p \ .05. **p \ .01. ***p \ .001 (two-tailed tests).

48 Society and Mental Health 10(1)

AEs of WFC and FWC are constrained to be equal

across groups in consecutive steps (Byrne 2013).13

Then, using chi-square difference tests, the model

fit between each of these constrained models is

compared to the model fit of the baseline uncon-

strained model (Model 1).14 Most chi-square tests

suggest that adding equality constraints at each

step improves the fit of the baseline model (Model

1). Thus, these findings suggest that most AEs do

not differ between married and cohabiting couples.

On the other hand, two models indicate that

constraining some parameters to be equal across

Figure 1. Unstandardized coefficients for the best-fitting models in structural equation model (for jobsatisfaction, relationship satisfaction, and mental health) for married couples.Note. WFC = work-to-family conflict; FWC = family-to-work conflict; JS = job satisfaction; RS = relationship satisfac-

tion; MH = mental health; e1–e6 = error terms associated with each indicated variable.

*p \ .05. **p \ .01. ***p \ .001.

Yucel and Latshaw 49

groups worsens the baseline model’s fit signifi-

cantly. Specifically, Step 4 in Table 6 constrains

the AE of females’ WFC on mental health to

equality across married and cohabiting couples.

Based on the difference in the chi-square test,

this result suggests that the AE of females’ WFC

on mental health differs significantly for married

and cohabiting couples (Dx2 = 5.891, df = 1,

p \ .05) such that it is stronger among cohabiting

couples. In addition, Steps 2 and 4 in Table 6 con-

strain the AEs of men and women’s WFC on job

satisfaction to equality across married and cohab-

iting couples, respectively. Based on the differ-

ence in the chi-square test, the AE of males’ and

females’ WFC on job satisfaction differs signifi-

cantly for married couples versus cohabiting cou-

ples (Dx2 = 3.31, df = 1, p\ .10) such that the neg-

ative AE of females’ WFC on mental health and

the AEs of females’ and males’ WFC on job satis-

faction are stronger among cohabiting couples.

The highlighted numbers in Table 6 also show

a significant worsening of the model fit for job sat-

isfaction and mental health. A table displaying

nonsignificant chi-square test results when com-

paring models for relationship satisfaction can be

provided on request.

DISCUSSION

Prior research has studied the effects of WFC and

FWC on a variety of outcomes (Allen et al. 2000;

Amstad et al. 2011; Bakker et al. 2008; Cooklin

et al. 2014; Kinnunen, Geurts, and Mauno 2004;

Minnotte 2016; Pedersen and Minnotte 2012), but

most studies that have examined spillover and cross-

over effects using couple-level data have had small

sample sizes (Abeysekera and Gahan forthcoming;

Amstad and Semmer 2011; Hammer et al. 1997;

Matthews et al. 2006), with few exceptions (Shi-

mazu et al. 2013). Even fewer studies have com-

pared married couples to other union types

(Symoens and Bracke 2015). Additionally, whereas

most prior research on work-family conflict focuses

on workers from specific occupations or regions, this

study uses a large, representative sample of dual-

earning married and cohabiting couples in Germany,

allowing for stronger generalizability. With this in

mind, our study contributes by using couple-level

data to test the spillover and crossover effects of

work-family conflict (in both directions) on three

outcomes across multiple domains and assessing

whether they vary by gender or union type.

Our findings confirm the application of several

key theoretical frameworks in assessing the

dynamics of WFC and FWC on job satisfaction,

relationship satisfaction, and mental health. First,

when considering the usefulness of applying the

cross-domain (Frone et al. 1992a) versus matching

hypotheses (Amstad et al. 2011) to interpret the

findings, our research lends strong support to the

latter. As predicted by the matching hypothesis,

and in support of the meta-analyses by Amstad

et al. (2011) and Nohe et al. (2015), we find that

for domain-specific outcomes, only the domain

where the root of the conflict lies is significantly

correlated with declines in well-being in that

same domain. This is evident in several of our

key findings. Among both married and cohabiting

couples, only WFC negatively impacts work-

related domain outcomes (e.g., job satisfaction),

and only FWC negatively impacts family-related

domain outcomes (e.g., relationship satisfaction).

Thus, our findings align with two key theoretical

underpinnings of the matching hypothesis—

appraisal theories (Lazarus 1991) and source attri-

bution (Shockley and Singla 2011). For example,

as predicted by the matching hypothesis, when

a salient role (spouse) is strained due to the

increasing demands of another role (worker), an

individual will begin to negatively appraise (via

lower job satisfaction) the original source of the

strain on their relationship (working too many

hours). Despite this finding, the matching and

cross-domain perspectives are not without limita-

tions. Because of the inherent overlap and interac-

tion that takes place between roles in the

workplace and home, to examine outcomes of

work-family conflict rooted in the work versus

the family domains, as though they are separate,

mutually exclusive entities, might oversimplify

a more complex, fluid reality (Clark 2000).

Further, in support of prior literature, results

suggest that married individuals who experience

higher levels of work-family conflict have lower

job satisfaction, lower relationship satisfaction,

and worse mental health. These findings illustrate

the continued usefulness of several theoretical

concepts. As the role scarcity hypothesis (Edwards

and Rothbard 2000) proposes, individuals have

limited resources and can feel strain when their

roles as employees and spouses compete for their

time. As conservation of resources theory explains

(Hobfoll 1989), this strain can also be exacerbated

when stressful events (e.g., an unexpected dead-

line at work) cause an individual to be unable to

50 Society and Mental Health 10(1)

balance both employee and spousal roles (because

of their inability to conserve the amount of time

they need to both meet the deadline and be

home to help their family). As a result of these

conflicts, our findings suggest that individuals

can suffer a decline in job satisfaction, relationship

satisfaction, and mental health. Likewise, our find-

ings match the predictions of Pearlin’s (1999)

stress process model, which proposes that primary

stressors (e.g., unexpected work deadlines) might

lead to secondary stressors (e.g., arguments

between partners over how long a spouse should

stay at work that evening). Thus, work-family con-

flict can potentially heighten existing conflicts

and/or proliferate additional conflicts, negatively

impacting individuals’ mental health.

While these findings on spillover are consistent

with well-established existing literature, our main

contribution lies in our use of couple-level data to

compare the crossover effects of work-family con-

flict by gender and union type. Among married

couples, our findings of significant negative PEs

of WFC and FWC on job satisfaction and relation-

ship satisfaction, respectively, support Amstad et

al.’s (2011) matching hypothesis, while the nega-

tive PE of FWC on mental health supports West-

man’s (2001, 2006) assertion that stress and strain

associated with work-family conflict are transmit-

ted across spouses. This finding that when hus-

bands and wives experience WFC and FWC, the

job satisfaction, relationship satisfaction, and men-

tal health of their spouses are negatively affected

can be interpreted through the theoretical lenses

of crossover stress and empathy among significant

others (Bakker and Demerouti 2009; Westman

2001, 2006). Essentially, when partners share

closely connected lives and frequently communi-

cate their work and family stressors, the “cost of

caring” for one another (Kessler and McLeod

1984) likely translates into a decline in well-being

for both individuals and their spouses across mul-

tiple domains. These findings related to the trans-

mission of stress due to empathy among partners

are underscored by existing literature (see e.g.,

Bakker et al. 2008; Matthews et al. 2006), partic-

ularly in terms of negative mental health outcomes

(Young et al. 2014). Still, as expected, while add-

ing in PEs improves our models, AEs are generally

stronger and more significant than PEs because

they have a more direct and consequential impact

on individuals’ behavioral outcomes.

When testing gender differences in AEs and

PEs of WFC and FWC for married couples, how-

ever, we find mixed support for the usefulness of

Table 6. Fit Indices for Nested Models in Multigroup Analyses for Mental Health and Job Satisfaction.

Mental Health Job Satisfaction

Models df Chi-square CFI RMSEA df Chi-square CFI RMSEA

Step 1: The baseline model 10 17.407+ .98 .03 12 19.400+ .98 .02Step 2: Actor effect of husbands’

work-to-family conflict is equalacross groups

11 17.447+ .98 .03 13 22.522* .99 .02

Step 3: Actor effect of husbands’family-to-work conflict is equalacross groups

11 17.456+ .98 .03 13 19.626 .98 .02

Step 4: Actor effect of wives’work-to-family conflict is equalacross groups

11 23.298* .98 .03 13 22.522* .99 .02

Step 5: Actor effect of wives’family-to-work conflict is equalacross groups

11 17.427+ .98 .03 13 19.626 .98 .02

Note. Multigroup analyses are only performed for variables that are the same for both married and cohabiting couples.The control variable “plans to marry in the future” cohabiting couples were therefore not used for multigroup analysis.No partner effects emerged for cohabiting couples, therefore only actor effects were compared between married andcohabiting couples. Higher scores indicate worse mental health and greater job satisfaction. CFI = Comparative FitIndex; RMSEA = root mean square error of approximation.+p \ .10. *p \ .05 (two-tailed tests).

Yucel and Latshaw 51

applying theoretical frameworks on the persis-

tence of traditional gender expectations (Ridge-

way 2011). In contrast to our hypotheses, the neg-

ative AEs of both WFC and FWC on job

satisfaction and relationship satisfaction, respec-

tively, are similar between husbands and wives,

and there are no gender differences in the PEs of

either FWC and WFC on relationship satisfaction

and mental health, respectively. This lack of gen-

der differences in some of our analyses could be

due to growing egalitarianism and equality in the

work and family experiences of men and women

(Frone et al. 1992b; Young et al. 2014). Alterna-

tively, some gender differences do emerge. As

predicted, the PE of WFC on job satisfaction is

stronger for women than men. In addition, the

AE of WFC on mental health is significantly

stronger for husbands than wives. In other words,

in accordance with existing literature (see e.g.,

Frone et al. 1996), it does appear that husbands’

WFC crosses over to their wives, perhaps due to

the continued emphasis on empathy throughout

women’s gender socialization. Likewise, men’s

continued adherence to the work domain, even

as societal expectations of involved fatherhood

become more dominant (Winslow 2005), is asso-

ciated with stronger negative effects of WFC on

husbands’ mental health. Thus, our findings point

to the need for more effective government and

workplace policies designed to help married cou-

ples balance work and family. In light of recent lit-

erature documenting a rise in reports of work-

family conflict among married, dual-earning

fathers in particular (Aumann et al. 2011; Galink-

sky et al. 2011; Nomaguchi and Johnson 2009),

this finding on mental health is critical.

While some of our results on the relationship

between work-family conflict and mental health

replicate those found in existing literature (Young

et al. 2014), we extend prior work by using

couple-level data to examine whether outcomes

across multiple domains of social life vary by

union status, assessing whether crossover stress

(in particular) operates differently among spouses

versus cohabiting partners. Among cohabitors,

findings suggest there are some significant AEs

between WFC, FWC, and our outcomes but no

significant PEs. Further, we find that the negative

AEs of men’s and women’s WFC on job satisfac-

tion and the negative AE of women’s WFC on

mental health are stronger among cohabiting cou-

ples than married couples. On one hand, similar to

the results on married couples, some of these

findings lend strong support to Amstad et al.’s

(2011) matching hypothesis. This suggests that

Amstad et al.’s theoretical framework can be use-

fully applied to better understand the spillover and

crossover dynamics of work-family conflict

among individuals in both married and cohabiting

partnerships. Our findings on cohabitors also align

with differential vulnerability theories and their

prediction that cohabitors are often more vulnera-

ble (emotionally and economically) and thus

might feel less commitment, connection, and sta-

bility in their relationship, making the negative

spillover effects of WFC seem more pronounced

in the absence of a strong support system from

a partner (Pearlin and Johnson 1977; Simon 1998).

The lack of significant PEs for cohabiting

couples also confirms our prediction that higher

levels of commitment, relationship closeness,

and intimacy among married people coupled

with the increased emphasis on freedom and self-

fulfillment among cohabitors (Brown 2003, 2004;

Brown et al. 2015) might result in PEs being stron-

ger for married couples. This also matches the the-

oretical mechanisms of crossover that Westman

(2001, 2006) outlines, suggesting that negative

crossover effects are typically transmitted because

of the empathy and shared connection couples

share when they are in long-term, committed rela-

tionships (something cohabitors often lack). Thus,

it is possible that the cost of caring (Kessler and

McLeod 1984; Wethington 2000) and the emo-

tional burden of crossover stress, particularly its

negative relationship to mental health (Young

et al. 2014), is not as pronounced among cohabi-

tors as it is among spouses. These variations by

union status lend support to the use of couple-level

data to study crossover stress among couples as it

reduces the possibility of assumed-similarity bias

and the possibility that cohabitors in particular

might lack sufficient information about one

another.

Life course perspective can also be applied to

better make sense of the absence of significant

PEs among cohabiting couples. This theoretical

perspective “emphasizes the importance of time,

context, process, and meaning on human develop-

ment and family life” (Bengston and Allen

1993:471). When using life course perspective to

examine partnering and relationship processes,

one might infer that younger cohabitors interpret

their unions as being shorter-term, less committed,

or more about convenience than longevity and

thus are less likely to transition to marriage. In

52 Society and Mental Health 10(1)

other words, due to their being in a different

life stage with varying relationship dynamics

(see e.g., Sassler 2010), cohabitors in our study

could be in qualitatively different than married

respondents.

It is also possible that these variations we find

among married and cohabiting partners are driven

by other factors that are not easily captured in sur-

vey data. For example, prior research suggests that

factors such as differing norms (Brown and Booth

1996; Cherlin 2004), gender ideologies (Davis and

Greenstein 2009; Sassler and Miller 2011), atti-

tudes (Brown 2000; Stanley, Whitton, and Mark-

man 2004), and/or levels of social acceptance

and support from families (Brown 2003; Brown

and Booth 1996) might either select people into

cohabitation or emerge as a result of cohabiting.

While we cannot measure or control for these fac-

tors in the present study, our findings underscore

the growing importance of examining family con-

text (e.g., union status) and how it shapes work-

family conflict itself as well as various outcomes

associated with it (see e.g., Kossek and Lee

2017; Young 2015). As the role cohabition and

marriage play in family formations and life course

experiences continues to shift (Brown et al. 2015),

the import of social context should not be over-

looked. We suggest scholars continue to test

the mediating and/or moderating effects of union

status on outcomes (particularly mental health)

using a larger, more diverse sample of cohabiting

couples. In addition, future research should con-

sider more nuanced and integrated theoretical

approaches for explaining variations in the effects

of work-family conflict among cohabiting and

married couples (Kossek and Lee 2017).

Limitations and Suggestions for FutureResearch

There are several limitations of this research. First,

the cross-sectional design of the data limits our

ability to make causal arguments. In addition,

some of the relationships between our key varia-

bles are likely bidirectional. For example, those

with poor mental health and problems at work

and/or in their relationships might experience

higher WFC and FWC. Likewise, being dissatis-

fied at work might lead to discord at home

(WFC), and experiencing marital strain might

cause problems at work (FWC). Without the use

of longitudinal data, we cannot conclude that

causality is occurring or assume causal, directional

positioning between our key variables (for a com-

prehensive review of antecedents of WFC and

FWC, see Michel et al. 2011). While we can

only be certain of correlation between the varia-

bles in our study, the wealth of prior research the-

oretically and empirically demonstrating that

WFC and FWC likely precede changes in job sat-

isfaction, relationship satisfaction, and mental

health lends confidence to our findings (see e.g.,

Allen et al. 2000; Amstad et al. 2011; Bellavia

and Frone 2005; Nohe et al. 2015). This is also

supported by longitudinal research (Yucel and

Fan 2018), where changes in work-family conflict

over time are associated with changes in well-

being outcomes among married couples. Second,

although this research makes a contribution by

exploring the spillover and crossover effects of

WFC and FWC on various outcomes, one of our

key variables (relationship satisfaction) is mea-

sured using only one item. This could create reli-

ability issues and/or introduce measurement error.

Despite this, some prior research has shown strong

reliability and validity for single-item measures of

relationship satisfaction (Huston, McHale, and

Crouter 1986; Huston and Vangelisti 1991). Third,

the single item we have used to measure job satis-

faction fails to measure it in the conventional way.

Prior research shows mixed findings on the rela-

tionship between the level of education and job

satisfaction (for a review, see Fabra and Camison

2009) and that job and career satisfaction are

related but separate constructs (Kuchinke, Kang,

and Oh 2008; Lounsbury et al. 2007). Given this

evidence, we infer that one might be satisfied

with their job but not necessarily be satisfied

with their education or that one’s job satisfaction

does not necessarily indicate a satisfaction with

the career they may (or may not) have. Fourth,

although this study mainly focused on WFC and

FWC, various working conditions (i.e., job

demands and job resources) could likely influence

the outcomes in this study, as shown in some prior

meta-analyses (Schaufeli 2017; Schaufeli and

Taris 2014). In addition to their main effects, job

demands and job resources can act as moderators.

For example, job demands worsen the negative

effects of WFC and FWC on well-being and health

outcomes (Van Yperen and Hagedoorn 2003),

whereas job resources are expected to alleviate

the negative effects of WFC and FWC (Hughes

and Parkes 2007). Thus, future research could

expand on this study by testing the AEs and PEs

Yucel and Latshaw 53

of job demands and job resources on similar out-

comes. Moreover, though not our focus, the spill-

over and crossover effects of WFC and FWC

might be more negatively related to our outcomes

when couples have a more unequal division of

household labor (Stevens, Kiger, and Riley

2001) and possess a more egalitarian gender ideol-

ogy (Minnotte et al. 2010), when families have

greater child care responsibilities or parenting

duties (Lin and Burgard 2018), and/or when there

is a lack of available child care (Frye and Breaugh

2004). Future research might explore the AEs/PEs

of such family-related variables and attitudes on

similar outcomes.

CONCLUSIONS

In conclusion, this study makes a significant con-

tribution by empirically evaluating the relation-

ship between WFC, FWC, and three outcomes

(relationship satisfaction, job satisfaction, and

mental health) across multiple domains of social

life, testing both spillover and crossover effects.

Further, we use couple-level data and dyadic

data analysis to test gender differences in AEs

and PEs and assess whether these effects differ

by union type. Moreover, we employ a large rep-

resentative sample of dual-earning married and

cohabiting couples in Germany, allowing for

stronger generalizability than existing studies

focused only on married couples, workers from

specific occupations or regions, or outcomes in

one domain. Our findings point to a need for con-

tinued research on how WFC and FWC affect not

just individuals but couples, particularly through

a closer examination of crossover effects transmit-

ted across spouses. Future research might also

build on our findings by continuing to explore dif-

ferences in the correlates of WFC and FWC

among couples in different types of unions. As

cohabitation becomes an increasingly common

family form across the United States and Europe,

more couple level-data and research are needed,

particularly using larger data sets with greater

numbers of cohabitors.

NOTES

1. We did not use both waves in this study for several

reasons. First, the main scope of the paper was not

exploring the changes in work-to-family conflict

(WFC) and family-to-work conflict (FWC) on job

satisfaction, relationship satisfaction, and mental

health over time. This study aims to contribute to

prior research by acknowledging both the actor

effects (AEs) and partner effects (PEs) of WFC and

FWC on outcomes using couple-level data and

dyadic data analysis. Second, there is high attrition

among cohabiting couples, and thus, using both

waves would reduce the sample significantly, and

that would prevent us from doing any statistical tests

for cohabiting couples and making meaningful com-

parisons between married and cohabiting couples.

Lastly, the time change between Waves 6 (2013–

2014) and 8 (2015–2016) is only two years. Consis-

tent with some prior research that also examines

changes in work-family conflict over a relatively

short period of time (e.g., one year in research by

Kinnunen, Geurts, and Mauno 2004), in this study,

the two years between Waves 6 and 8 might not be

a long enough time to experience any meaningful

change in WFC and FWC.

2. Upper education is equivalent to a postsecondary

education that either leads or does not lead to a uni-

versity degree or equivalent according to U.S. educa-

tional standards (i.e., an associate’s, bachelor’s, mas-

ter’s or PhD).

3. Using a single item to measure job satisfaction (i.e.,

“How satisfied are you with your job overall?”) has

been common in prior research (Artz and Kaya

2014; Cotti, Haley, and Miller 2014; Hill 2005).

However, the single-item measure we use in this

study (the only one offered in our data source) does

not measure job satisfaction in the conventional

way. Please see the Discussion section for further

explanation.

4. While using multiple items to measure relationship

satisfaction is preferred, using a single item has

also been common in prior research (Hill 2005; Min-

notte, Minnotte, and Bonstrom 2015; Schoen, Rog-

ers, and Amato 2006; Yucel 2017b). Prior research

has shown strong correlations between a single-item

measure for relationship satisfaction and other rela-

tionship satisfaction scales, establishing reliability

(Huston, McHale, and Crouter 1986; Huston and

Vangelist 1991).

5. Skewness and kurtosis tests as well as Shapiro Wilk

tests all revealed deviations from normality for both

the job satisfaction and relationship satisfaction

scales. As recommended by Field (2009), the skewed

scales were transformed using a log transformation,

which has also been used in prior research for skewed

satisfaction measures (see e.g., Waismel-Manor,

Levanon, and Tolbert 2016).

6. The Center for Epidemiologic Studies Depression

Scale (CES-D) scale has been widely used in prior

research to measure mental health (Baumann et al.

2008; Gutierrez and Michaud 2017). As cited in

Thonnissen et al. (2016), the items used in this study

to measure mental health were adapted from the

State-Trait Depression Scale, which was also used

54 Society and Mental Health 10(1)

in prior research (Spaderna, Schmukle, and Krohne

2002). In another research study, it was shown that

both the CES-D and State-Trait Depression scales

are suitable to assess depressive symptoms (Lehr

et al. 2008). Further research established high reli-

ability as well as construct and external validity

of this scale to measure mental health (Krohne et

al. 2002). Since then, this scale has been used in

some additional studies (see e.g., Weigl et al. 2016).

7. The scales we use for WFC and FWC in pairfam

data are adapted from other national surveys such

as the National Study of the Changing Workforce

(NSCW; Huinink et al. 2011), where WFC and

FWC are measured by items that contain words

such as “family or other important people in your

life” and “family/personal life.” Despite the fact

that these measures of WFC and FWC are common

in prior research, the items containing such phrases

do indicate a domain that is broader than family

alone. Prior research has thus used work-family bal-

ance interchangeably with work-life balance (see

reviews by Chang, McDonald, and Burton 2010;

Rogelberg 2007).

8. To test the nonlinear effect of work hours, as sup-

ported in prior research (Pencavel 2015), we mea-

sured this variable in three categories: part-time,

full-time, and overtime work hours (reference cate-

gory). The results did not show any unfavorable

effects for those who work overtime for relationship

satisfaction and mental health, but it had a negative

AE on job satisfaction for men and women (only

among cohabiting couples). Additionally, both

effects were only moderate (p \ .10), and they

did not change the main effects of WFC and

FWC on our outcome measures.

9. We tested for interactions between WFC, FWC, and

the duration of cohabitation. We used continuous

measures for duration of cohabitation as well as cat-

egorical measures (been together for less than 5

years [\5], N = 233; and for at least 5 years [�5

years], N = 90). We could not divide the duration

of cohabitation into more than two categories due

to the small sample size. Nonetheless, these interac-

tions were not significant.

10. Consistent with prior research on differences among

cohabitors within Germany (see e.g., Perelli-Harris

et al. 2014), this study controlled for whether an

individual lives in East or West Germany. We also

tested for interactions between this dummy variable

and WFC and FWC, but none of them were signif-

icant. This indicated that there was no need to divide

the sample into East or West Germany. In addition,

the number of previous marriages (for married cou-

ples) and partners with whom the anchor cohabited

(for cohabiting couples) were only constructed for

the anchor but not the partner. Therefore, these var-

iables were not included in the analysis.

11. Between 97 and 99 percent of partners in the sample

agreed on their responses for the following control

variables: the presence of preschool-aged children

in the household, plans to get married in the future

(for cohabiting couples), marital (relationship) dura-

tion, and whether respondents lived in East or West

Germany. Thus, consistent with prior research

(Yucel 2017a; Yucel and Gassanov 2010), only

the female partner’s report was used.

12. The question of whether the PEs of WFC and FWC

on job satisfaction, relationship satisfaction, and

mental health vary between married and cohabiting

couples cannot be tested using multigroup analyses

since PEs only emerge for married couples and do

not exist among cohabiting couples. Therefore,

only AEs of WFC and FWC are compared between

married and cohabiting couples.

13. Multigroup analyses are only performed for varia-

bles that are the same for both married and cohabit-

ing couples. Therefore, the control variable “plans

to marry the current partner in the future” for cohab-

itors was not used.

14. The baseline model (Model 1) is where all AEs are

allowed to vary between married and cohabiting

couples.

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