STAYING WITH A PARTNER WHO CHEATS: THE INFLUENCE OF GENDER AND RELATIONSHIP DYNAMICS ON ADOLESCENTS’ TOLERANCE OF INFIDELITY

Christine M. Flanigan

A Thesis

Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of

MASTER OF ARTS

August 2007

Committee:

Wendy Manning, Advisor

Peggy Giordano

Monica Longmore

ii

ABSTRACT

Wendy Manning, Advisor

Teens and young adults in the United States have higher rates of sexually transmitted infections than do older adults, and female adolescents generally have higher rates than same-age males. Some existing literature, often based on an evolutionary psychological approach, suggests that females may be more likely to tolerate sexual infidelity, a potential explanation for gender differences in STI rates. This paper uses data from wave 3 of the Toledo Adolescent

Relationships Study (n=583) to explore the association of sexual infidelity with the breakup of adolescents’ dating relationships. Specifically, this study addresses three questions: first, are young women more likely than young men to remain in a relationship that is not sexually exclusive? Second, do the qualities of these dating relationships (e.g., commitment, conflict, etc.) influence the relationship between infidelity and break-up, and explain any gender differences if found? Third, does infidelity have the same relationship with break-up when the couple does not expect fidelity? Logistic regression is used to predict the break-up of adolescents’ most recent dating relationship based on the occurrence of infidelity, relationship qualities, and demographic controls such as gender. Results indicate that partner’s cheating is associated with higher odds of breaking up and there is no gender difference in breakup when a partner cheats. Relationship qualities predict breakup, but they do not mediate the associations between infidelity and breakup. Couples without expectations for fidelity are more likely to end their relationships. The effects of partner cheating significantly differ according to fidelity expectations. iii

ACKNOWLEDGMENTS

First, I’d like to thank my committee, Wendy Manning, Peggy Giordano, and Monica

Longmore, for giving me such helpful feedback, for providing encouragement, and for collecting such great data. Also, thanks to Al DeMaris for providing feedback on an early draft of this thesis. I’d like to thank my former colleagues at the National Campaign, particularly Sarah

Brown and Cindy Costello, and members of the Campaign’s Research Task Force, for exposing me to the research process and encouraging me to continue with my education. Finally, I’d like to thank my family, friends, and fellow sociology graduate students for their support. iv

TABLE OF CONTENTS

Page

INTRODUCTION ...... 1

CHAPTER I. BACKGROUND...... 4

Prevalence of and Attitudes Toward Infidelity...... 4

Gender Differences in Reactions to Infidelity ...... 5

Other Demographic and Individual Antecedents of Infidelity and Breakup ...... 11

Relationship Qualities, Infidelity, and Breakup...... 12

CHAPTER II. CURRENT INVESTIGATION ...... 17

CHAPTER III. DATA ...... 19

CHAPTER IV. MEASURES...... 21

Dependent Variable...... 21

Focal Independent Variables...... 22

Independent Variables Related to the Relationship...... 23

Demographic Control Variables ...... 26

CHAPTER V. ANALYTIC STRATEGY ...... 29

CHAPTER VI. RESULTS...... 30

Descriptive Statistics...... 30

Regression Results...... 33

Additional Analyses...... 41

CHAPTER VII. DISCUSSION ...... 43

SOURCES...... 47

APPENDIX A. CORRELATIONS BETWEEN RELATIONSHIP QUALITIES...... 56 v

LIST OF FIGURES/TABLES

Figure/Table Page

1 Descriptive Statistics, Respondents and Their Most Recent Dating Relationships,

Sexually Active Relationships Only, Toledo Adolescent Relationships Study (TARS),

Wave 3 ...... 32

2 Logistic Regression of Whether Most Recent Dating Relationship Has Ended (vs. is

Current), Only Relationships That Included Vaginal Sex, Wave 3 TARS...... 35

3 Logistic Regression of Whether Most Recent Dating Relationship Has Ended (vs. is

Current), Only Relationships That Included Vaginal Sex, Wave 3 TARS...... 38

4 Correlations Between Relationship Qualities ...... 56

1

INTRODUCTION

Sexually transmitted infections (STIs) pose a serious problem for young people in the

United States. STI rates in the U.S. are quite high compared to other developed nations (e.g.,

Panchaud, Singh, Feivelson, & Darroch, 2000), with a third of young adults contracting an STI by age 24 (Kaiser Family Foundation, 1998). STIs cause a variety of health problems in both the infected person and in infants of women who had an STI during pregnancy. Notably, transmission of HIV can occur through sexual activity, and being infected with other STIs increases the likelihood of acquiring HIV from an infected partner (Kaiser Family Foundation,

1998).

STI rates are generally high for females relative to same-aged males. For example, in

2005 there were 505 reported Chlamydia cases per 100,000 males aged 15-19, while the comparable statistic for females aged 15-19 was 2,797 per 100,000. Likewise, 2005 gonorrhea rates for youth aged 15-19 were 261 per 100,000 for males and 625 per 100,000 for females

(Centers for Disease Control and Prevention, 2006). There are many reasons why young women might have higher STI rates than young men. From a biological standpoint females are more susceptible to STI infection (National Institute of Allergy and Infectious Diseases, 2001), and female teens are more likely than male teens to have older sexual partners (Abma & Sonenstein,

2001), which is a known risk factor for STI infection (Ford & Lepkowski, 2004). In addition, studies generally find lower rates of condom use among young women compared to young men: for example, according to the 2002 National Survey of Family Growth, only 31% of never- married, sexually experienced females aged 15-24 used condoms every time they had sex in the past 12 months; the comparable statistic for males was 48% (Abma, Martinez, Mosher, &

Dawson, 2004). 2

However, gender differences in behavior related to sexual exclusivity may also play a part in disparities in STI rates. For example, Eyre and colleagues (1998) found that in cases where infidelity occurred, teen boys were more likely to break off the relationship, while teen girls were more likely to stay in the relationship but withdraw trust, talk about the partner to others behind his back, or withhold sex for a time as a punishment. For females, greater tolerance of infidelity may lead to an increased exposure to STIs acquired from their partners’ extrarelational sex partners, especially if consistent condom use is lower in these relationships.

Eyre et al.’s findings are consistent with a body of literature that takes a biological/evolutionary stance on gender differences in reactions to infidelity, but there are also a number of studies that find no gender differences in tolerance of partner’s sexual nonexclusivity. Much of this literature, however, deals with reactions to a hypothetical case of infidelity instead of with youths’ actual experiences, and many of the samples involved are nonrepresentative.

This paper uses data from the Toledo Area Relationships Study (TARS) to examine whether or not male and female adolescents vary in their willingness to remain in a relationship where sexual nonexclusivity has occurred. In addition to providing results from a randomly selected, more representative sample that includes in- and out-of-school youth, this study adds to the literature by including measures of various qualities of the adolescents’ relationships, which may affect both the likelihood of cheating and respondents’ reactions to it, and which have generally not been included in past research on infidelity. Furthermore, the TARS data measures respondents’ reactions to real-life experiences of cheating and being cheated upon, contrasted with the more typical approach of focusing on hypothesized responses to an imagined infidelity, which may not necessarily translate into behavior. Finally, most studies implicitly or explicitly assume the relationships are marital or marriage-like relationships with expectations of fidelity, 3

while the TARS data allow for the idea that some dating couples may not expect fidelity from their partner, so “cheating” by the partner may not be the same source of conflict that it would be

in more traditional relationships.

4

CHAPTER I. BACKGROUND

Prevalence of and Attitudes toward Infidelity

Nonexclusivity in romantic relationships is fairly common, especially among dating couples. Studies of married and cohabiting adults in the United States reported that between 8-

25% of relationships have included at least one partner who has had sex with another person during the current relationship (Atkins, Baucom, & Jacobson, 2001; Haavio-Mannila, Roos, &

Kontula, 1996; Treas & Giesen, 2000; Wiederman, 1997). Infidelity is even more likely in adolescent and young adult dating and sexual relationships. Looking across all of their dating experiences, Feldman and Cauffman (1999a, 1999b) found that between 59-66% of college students in their studies had experienced sexual infidelity (either cheating themselves or being cheated on by a partner) in a dating relationship. Grello, Welsh, and Harper (2006) found that

21% of college students who reported having had casual sex also had a steady romantic partner at the time, and in a study of early adolescents, 53% of respondents’ most recent “non-romantic” sexual relationships involved cheating on the part of one or both partners (Manning, Giordano, &

Longmore, 2006). About one-fifth (21%) of respondents in the 1988 National Survey of

Adolescent Males reported multiple simultaneous sexual relationships in the previous 12 months

(Sonenstein, Pleck, & Ku, 1991), and another survey of adolescents reported that one or both partners had sex with someone else during 33% of respondents’ most recent sexual dating relationships (Manning, Giordano, Longmore, & Flanigan, 2006).

Despite sexual nonexclusivity being relatively common, attitudes strongly favor fidelity

in romantic relationships. Treas and Giesen (2000) found that 98-99% of married and 94-95% of

cohabiting respondents were expected to be faithful and expected fidelity from their partner.

Feldman and colleagues (1999a, 2000) reported that acceptability of cheating was low among 5

their college student samples, averaging 1.42-1.59 on scale of 1=totally unacceptable to 4=totally

acceptable, although men found it more acceptable than did women (1.71 vs. 1.48 in the first

study, 1.63 vs. 1.31 in the second). On the other hand, Knox, Zusman, Kaluzny, and Studivant

(2000) reported no gender difference in the proportion of college students who said they would break up with a cheating partner, with over two-thirds (69.1%) agreeing with this statement.

Vandello and Cohen (2003) observed that respondents reading a vignette about an unfaithful wife rated both the wife and her husband (who knew about affair) lower on measures of good

character and strength.

Given the general unacceptability of infidelity, it is not surprising that many relationships

are ended for this reason. In a recent poll of young adults, 30% of women and 28% of men said

that their most recent relationship had ended because of an extracurricular affair (Fetto, 2003).

In studies of college students, about 60% of dating relationships that included infidelity ended

because of it (Feldman & Cauffman, 1999b; Harris, 2003). Likewise, Cann and Baucom (2004)

found that, on a scale of 1-9, with 1=definitely not forgive and 9=definitely forgive, results

indicated that these college-age respondents would be relatively unlikely to forgive their

partner’s sexual infidelity, with a mean response of 3.04. Infidelity is also a common cause of

divorce (Amato & Previti, 2003; Amato & Rogers, 1997).

Gender Differences in Reactions to Infidelity

Eyre, Auerswald, Hoffman, and Millstein (1998) found a variety of gender differences

related to infidelity in their qualitative study of high school students (n=39), including teens’

perceptions of males and female peers who engage in what they call “third partying,” as well as

boys’ and girls’ ideas about what constitutes infidelity. While these researchers reported that

breaking up over infidelity was common among both genders, they found that this reaction was 6

more common among male teens, with females more likely to stay in the relationship, but to

retaliate by decreasing trust, withholding sex, or humiliating their partners in public.

Findings from this article are consistent with the evolutionary psychological approach to gender differences in jealousy, which provides implicit support for the notion that females are more likely to tolerate sexual infidelity. As described by Shropshire (2003), in the evolutionary model, the overall goal for males is reproductive success, which has two components – impregnating as many females as possible, but also having any offspring live to reproductive age. Thus, from this perspective it may make sense for a male to split time between mating and provisioning one’s offspring. However, if the female partner is not faithful, the male runs the risk of spending time nurturing a rival’s offspring, taking away resources from his own offspring.

The female does not have the same concern about fidelity because she is certain her offspring are biologically hers, but she does have concerns about losing her mate’s provisioning and having her offspring fail to thrive. Over the course of evolution, the most successful will manage within this system – females will be able to signal faithfulness through modesty and other means, and males will be successful in gauging their partners’ faithfulness and engaging in strategies to prevent her from sexual nonexclusivity. According to proponents of this theory, in modern society these concerns about reproductive success play out as gender differences in jealousy, with males being more upset about their female partners’ sexual infidelity because it could result in them unknowingly raising a rival’s child, and females being more upset about their male partners’ emotional connection with another woman because this might impel him to end their relationship in order to form a new relationship with the other woman, thereby eliminating his provision of resources. 7

The empirical findings rely on a range of measures of infidelity and there is not a strong

set of conclusions supporting a gender gap in acceptance of infidelity. Rather than relying on

actual reports of infidelity, the standard study focusing on evolutionary theory asks respondents

(usually college students) to imagine a partner has been unfaithful, either emotionally or

sexually, and then testing if there are gender differences in which type of infidelity is seen as

more upsetting. Many studies support the evolutionary psychological approach (e.g., Buss,

Larsen, Westen, & Semmelroth, 1992; Buunk, Angleitner, Oubaid, & Buss, 1996; Cramer,

Manning-Ryan, Johnson, & Barbo, 2000). Other studies, however, have found no gender

differences using this type of approach (e.g., Berman & Frazier, 2005; Cann & Baucom, 2004;

Nannini & Meyers, 2000; Sabini & Silver, 2005), and still others have reported mixed findings

(e.g., Becker, Sagarin, Guadagno, Millevoi, & Nicastle, 2004). The results appear to depend on partner type. Cann and Baucom (2004) concluded that cheating with a former partner was

hypothetically more upsetting than cheating with a new person for both men and women, although differences in distress levels by partner type were larger for females and women were

more likely to forgive infidelity with a new partner versus a former partner. They also found that both males and females were more likely to forgive emotional infidelity than sexual infidelity.

In terms of defining infidelity, Randall and Byers (2003) asked college students if each of a

range of sexual behaviors, from deep kissing to vaginal intercourse with orgasm, would be

“unfaithful” behavior by a partner, and did not observe gender differences.

To date, only two quantitative studies have studied reactions to actual, as opposed to

hypothetical, instances of infidelity in dating relationships. Feldman and Cauffman (1999b)

studied both those who cheated and those who were cheated on, and found no gender difference

in break-ups because of infidelity in the group whose partners cheated, but did find a gender 8 difference in the cheaters sample, with females significantly more likely to end the relationship.

Harris (2003) also studied college students who had experienced infidelity, and did not observe a gender difference in the level of upset or the proportion whose relationships ended because of the infidelity, although she did note that, of those whose relationships had ended, females were more likely to say that they, and not their partners, made the decision to end the relationship. Even a study like Haden and Hojjat’s (2006) which was still based on an imagined infidelity, but asked about behavioral reactions such as shouting/yelling or refusing to talk to the partner, instead of just internal emotional reactions, found no gender differences. For the research questions examined in this paper, studying reactions to actual instead of hypothetical infidelity is key because, as Harris pointed out (2003): “hypothetical situations may evoke complex inferential thinking more than immediate emotional reactions and therefore may not reflect how people actually feel when confronted with a mate’s infidelity.” In that study she found gender differences in reactions to a hypothetical case of infidelity as expected by the evolutionary approach, but quite different reactions when respondents reported on an actual past experience where their partners cheated.

It may be important to take a step back and predict infidelity, rather than study the response to infidelity. Regarding adolescent and young adult daters, most studies have not observed gender differences in cheating (Feldman and Cauffman, 1999a; Giordano, Manning, and Longmore, 2005; Grello, Welsh, and Harper, 2006; Manning, Giordano, Longmore, &

Flanigan, 2006). Associations of gender with marital infidelity appear to be mixed: some studies have found no difference by gender (Treas & Giesen, 2000), while others have concluded that husbands are more likely than wives to report being unfaithful (Atkins, Baucom, & Jacobson,

2001). It may be relatively more common for men to have favorable attitudes and intentions 9

related to infidelity. McAlister, Pachana, and Jackson (2005) found that male students were more likely than female students to report being willing to have extradyadic sex.

A number of social theories exist that could explain relationships between gender, infidelity, and relationship breakup. Traditional gender socialization regarding issues such as caring, assertiveness, and empathy could easily result in females being more likely to forgive their partners’ infidelity. Double standards regarding sexuality might also contribute to gender differences, as individuals have a tendency to react more negatively to a female engaging in a non-normative behavior such as sex outside of a relationship (Marks & Fraley, 2006), and this might lead to a greater tendency among their male partners to end the relationship. Also,

discussions of breakup due to infidelity usually assume that the non-cheating partner initiates the

breakup in reaction to the partner’s cheating, but the opposite case could be true, that the

cheating partner ends the relationship to form a new relationship with his or her extradyadic

partner. This is relevant in terms of gender differences in breakup over infidelity because there

is some evidence that young adult females are more likely than males to say that relationships

ended because they found a new partner (Knox, Gibson, Zusman, & Gallmeier, 1997). It could

be, then, that females’ infidelity is more likely to be part of the search for a new dating partner,

compared to other reasons given for infidelity, such as a desire for sexual variety or ego boosting

(Drigotas, Safstrom, & Gentilia, 1999) that would not necessarily lead to the dissolution of the

primary relationship.

There are also several social perspectives that would predict that females would be more

likely than males to end a relationship with a cheating partner. First, females generally hold

more conservative attitudes toward sexuality (Eisenman & Dantzker, 2006; Knox, Cooper, &

Zusman, 2001; Wilson & Medora, 1990), which might lead them to be less accepting of 10

infidelity. To the extent that friendship networks are predominantly same-gendered, this would

imply that females would also have friends who are more conservative regarding sexuality, and

this feedback would further encourage negative reactions to a partner’s infidelity, according to

Fishbein and Ajzen’s Theory of Reasoned Action (Fishbein & Ajzen, 1975). Second, females

tend to be more relationally oriented (Knox & Zusman, 1997; Manning, Giordano, & Longmore,

2006), and therefore may react more strongly to a breach of trust, and they may also have greater

skills in navigating relationships that enable them to end undesirable relationships, as is the case

in Knox & Zusman’s study.

It is also entirely possible that there are no gender differences in reactions to infidelity.

We know, for example, that the sexual behavior of male and female teens has become markedly more similar in the past decades (Abma, Martinez, Mosher, & Dawson, 2004; Abma &

Sonenstein, 2001). Recent research with adolescents found greater similarities than expected in male and female teens’ experiences of romantic relationships (Giordano, Longmore, & Manning,

2006). As noted above, some studies find no gender differences in attitudes toward infidelity or willingness to break up with a partner because of it; male and female college students are also equally likely to say they are unwilling to end an unsatisfactory relationship (Knox, Zusman,

McGinty, & Davis, 2002).

Finally, it is important to consider the fact that all of these theoretical approaches to gender, infidelity, and breakup assume that the nonexclusivity is actually cheating, violating an agreement to be sexually exclusive. While this is true for virtually all marriages, it seems to not be the case for a significant minority of relationships – for example, over 30% of one college

student sample said they would not end a relationship if a partner cheated on them (Knox,

Zusman, Kaluzny, & Sturdivant, 2000). At the very least, one should expect that infidelity 11

occurring in this context should result in a different partner reaction than infidelity would in a

couple where fidelity is expected.

Other Demographic and Individual Antecedents of Infidelity and Break-Up

In addition to gender, a variety of other variables have been examined in relation to the incidence of infidelity, reactions to infidelity, break-up over infidelity, and break-up in general.

These variables range from sociodemographic characteristics of respondents, respondents’

attitudes toward sex, and characteristics of couples and their relationships.

Mixed results have been found when using many of the basic demographic variables to

predict breakup and infidelity. For example, some studies have found no association between

age and breakup (e.g., Cutrona, Hessling, Bacon, & Russell, 1998) or age and infidelity (e.g.,

Giordano, Manning, & Longmore, 2005; Manning, Giordano, Longmore, & Flanigan, 2006;

Treas & Giesen, 2000), while others have reported that age is negatively associated with cheating

and breakup (e.g., Atkins, Baucom, & Jacobson, 2001; Wang, Kao, & Joyner, 2006). Likewise,

some studies have concluded that education and income levels have no significant relationship

with infidelity (e.g., Amato & Rogers, 1997; Giordano, Manning, & Longmore, 2005; Treas &

Giesen, 2000) or breakup (e.g., Cutrona, Hessling, Bacon, & Russell, 1998), while others have found these variables to be positively associated with infidelity (e.g., Atkins, Baucom, &

Jacobson, 2001; Haavio-Mannila, Roos, & Kontula, 1996) and breakup (Wang, Kao, & Joyner,

2006). Some studies have observed that parent’s education and family structure during childhood did not predict sexual exclusivity among teen and young adult daters (e.g., Giordano,

Manning, & Longmore, 2005; Manning, Giordano, Longmore, & Flanigan, 2006), although

Amato and Rogers (1997) reported that marital infidelity was more likely when the wife’s parents had divorced. Differences between partners in race/ethnicity, religion, education, and 12

age have generally not been found to have a significant association with infidelity (e.g.,

Manning, Giordano, Longmore, & Flanigan, 2006; Treas & Giesen, 2000), although studies have

reported that dating couples where the partners were of different racial/ethnic groups were more

likely to breakup (Felmlee, Sprecher, & Bassin, 1990; Wang, Kao, & Joyner, 2006). One of the

few demographic characteristics to significantly predict infidelity is race/ethnicity, with African

Americans more likely than Whites to report sexual nonexclusivity (e.g., Amato & Rogers, 1997;

Giordano, Manning, & Longmore, 2005; Manning, Giordano, Longmore, & Flanigan, 2006;

Treas & Giesen, 2000; Wiederman, 1997). Breakup of adolescent dating relationships, on the

other hand, has been found to be more likely among White youth (Wang, Kao, & Joyner, 2006).

Religiosity/church attendance has generally been demonstrated to be negatively associated with

reports of infidelity (e.g., Amato & Rogers, 1997; Atkins, Baucom, & Jacobson, 2001; Treas &

Giesen, 2000).

Attitudes toward sexuality and past sexual behavior have been found to be associated

with the risk of infidelity. Treas & Giesen (2000) reported that those who said they think about

sex more often were more likely to report cheating, and not surprisingly, those who reported disapproving of infidelity were less likely to say that they had engaged in this behavior. An earlier age at first sex and a greater number of past romantic relationships/sex partners has predicted infidelity (e.g., Feldman & Cauffman, 1999a; Treas & Giesen, 2000), and number of

sex partners has also been associated with the inclination to be unfaithful (e.g., McAlister,

Pachana, & Jackson, 2005).

Relationship Qualities, Infidelity, and Break-Up 13

A few studies have also examined relationship qualities as predictors of infidelity.

Relationship qualities have also been examined as predictors of relationship dissolution in

studies that do not examine infidelity.

Several studies have tested the Rusbult Investment Model (Rusbult, Martz, & Agnew,

1998), which focuses on commitment, satisfaction, investments, and perceptions of alternative

partners to predict breakup or infidelity, and others have included similar variables while based

on a more general exchange model. These studies, mostly based on college student samples, generally found that commitment levels were negatively associated with breakup (Arriaga &

Agnew, 2001; Etcheverry & Agnew, 2004; Hendrick, Hendrick, & Adler, 1988; Lund, 1985;

Rusbult & Martz, 1995; Rusbult, Martz, & Agnew, 1998; Sprecher, 2001). Positive perceptions

of alternative partners were often associated with relationship breakup (Berg & McQuinn, 1986;

Bui, Peplau, & Hill, 1996; Felmlee, Sprecher, & Bassin, 1990; Johnson & Rusbult, 1989;

Rusbult & Martz, 1995; Rusbult, Van Lagne, Wildschut, Yovetich, & Verette, 2000; Sprecher,

2001), although some studies reported that the strong relationship between commitment and

perceptions of alternative partners (Johnson & Rusbult, 1989) or other relationship qualities

often results in mediation of the relationship between alternative partners and breakup (Bui,

Peplau, & Hill, 1996; Simpson, 1987). Investments in, and satisfaction with the relationship

were sometimes protective against breakup (Bui, Peplau, & Hill, 1996; Felmlee, Sprecher, &

Bassin, 1990; Hendrick, Hendrick, & Adler, 1988; Simpson, 1987; Sprecher, 2001), but were

often nonsignificant with the addition of other relationship qualities (Bui, Peplau, & Hill, 1996;

Rusbult & Martz, 1995; Sacher & Fine, 1996; Sprecher, 2001).

Drigotas, Safstrom, and Gentilia (1999), in their research based on the Rusbult

Investment Model, reported that respondents who said they were more satisfied and commited in 14 their current relationships were less likely to cheat; previous analysis of TARS data also found a negative relationship between commitment and infidelity (Manning, Giordano, Longmore, &

Flanigan, 2006). McAlister, Pachana, and Jackson (2005) observed that relationship satisfaction was negatively associated with willingness to cheat (although commitment was not significantly related to an inclination toward cheating), and that the perceived availability of alternate partners was positively associated. A study of emotional vs. sexual infidelity (Cann & Baucom, 2004), reported that several relationship qualities predicted responses. For example, men were more likely to say they would forgive a partner when they were more satisfied with their current relationship. For women, investment in their current relationships mattered, particularly when their partner’s infidelity occurred with a former girlfriend. Many studies have also concluded that marital satisfaction predicts fidelity (Atkins, Baucom, & Jacobson, 2001; Treas & Giesen,

2000).

Enmeshment also seems to predict relationship continuance and sexual exclusivity.

Greater time spent with partner was associated with lower odds of breakup (Berg & McQuinn,

1986; Drigotas & Rusbult, 1992; Felmlee, Sprecher, & Bassin, 1990), as was talking to one’s mother about the dates, friends knowing about the relationship, and as the couple makes a greater public show of commitment (Wang, Kao, & Joyner, 2006), although the number of shared friends had no significant relationship with couple breakup (Etcheverry & Agnew, 2004).

Greater approval of the relationship from the partners’ social networks, particularly the female partners’, has been associated with decreased likelihood of breakup (Etcheverry & Agnew, 2004;

Sprecher & Felmlee, 1992), as was the female partner’s approval of the male partner’s friends and family (Sprecher & Felmlee, 1992). Treas and Giesen (2000) noted that couples who were 15 more integrated into each other’s friend and family networks were less likely to experience infidelity.

Higher levels of love were protective against breakup (Berg & McQuinn, 1986; Drigotas

& Rusbult, 1992), but “closeness” had no significant relationship with breakup (Simpson, 1987).

Kasian and Painter (1992) found that support from partner reduced the likelihood of breakup, but other researchers reported no such relationship (Felmlee, Sprecher, & Bassin, 1990). Self disclosure was protective against breakup (Berg & McQuinn, 1986; Sprecher & Felmlee, 1992).

Having a controlling partner was a risk factor for breakup (Kasian & Painter, 1992), but conflict itself was not predictive of breakup (Berg & McQuinn, 1986). Berman and Frazier (2005) found that including measures of relationship power in their models partially explained the gender difference in choice between hypothetical emotional and sexual infidelity as more upsetting.

Zak, et al. (2002) found that increased levels of social support, romantic love, and trust were each associated with decreased likelihood of respondent having cheated, for both men and women. Manning, Giordano, Longmore, & Flanigan (2006) found that lower levels of self disclosure and higher scores on a measure of dysfunctional conflict resolution style predicted sexual infidelity.

Duration has usually been found to be negatively associated with breakup (Felmlee,

Sprecher, & Bassin, 1990; Simpson, 1987) but sometimes had no significant relationship with breakup (Sacher & Fine, 1996). Having had sex in the relationship has sometimes been observed to be protective against breakup (Simpson, 1987; Wang, Kao, & Joyner, 2006), but was also sometimes nonsignificant in predicting breakup (Felmlee, Sprecher, & Bassin, 1990).

Some studies that survey both partners in a couple have found that one respondent’s reports of relationship qualities are stronger predictors of relationship dissolution. Female’s 16 responses have been found to better predict breakup, using measures such as perceptions of alternative partners (Sacher & Fine, 1996) and under/overbenefiting (Sprecher, 2001). Other studies reported that the male partner’s responses to be more predictive of breakup on measures such as satisfaction (Berg & McQuinn, 1986) and rewards (Berg & McQuinn, 1986). Attridge,

Berscheid, & Simpson (1995) observed that having both partners’ reports of relationship qualities resulted in a better fitting model to predict breakup than either partner’s reports alone, but found few gender interactions.

17

CHAPTER II. CURRENT INVESTIGATION

This paper addresses three key research questions. First, are females less likely to break with up with their most recent dating partner, given infidelity in the relationship? This finding would be consistent with evolutionary psychological approaches to gender differences in reactions to infidelity and would support Eyre et al.’s finding that males were more likely to end a dating relationship when their partner cheated. However, this literature seems far from conclusive and has faced considerable criticism (e.g., Harris, 2003; Harris & Christenfeld, 1996;

DeSteno & Salovey, 1996). The few behavioral studies report no gender differences. Such findings would be more in line with literature that finds traditional ideas about gender roles in romantic relationships seem less relevant for more recent cohorts of young people (Giordano,

Longmore, & Manning, 2006). We may even observe a higher rate of breakup in cheating relationships among female respondents, which might reflect theories that girls are more relationally oriented (Manning, Giordano, & Longmore, 2006) and may therefore see a partner’s infidelity as a greater breach of trust.

Second, is some of the difference in the likelihood of breakup between sexually exclusive and nonexclusive couples due to poorer relationship quality among the latter group? This is partly a question of selection: perhaps those in poor-quality relationships are more likely to be unfaithful, and are also more likely to end their poor-quality relationships, but the actual contribution of unfaithfulness itself to the increased odds of breakup is small. Previti and

Amato’s (2004) longitudinal study of married couples found reciprocal effects – marital problems predicted infidelity, but infidelity also predicted marital problems – but this issue has not been examined within adolescent dating couples. It could also be that gender differences in the perception of one’s relationship quality would mediate gender differences in breakup, 18 although prior research has found few gender differences in romantic relationship qualities

(Giordano, Longmore, & Manning, 2006). This question will be tested using both positive and negative measures of relationship quality. For example, higher commitment, self-disclosure, and heightened emotionality should be associated with lower odds of breakup, while higher levels of conflict and asymmetry will be associated with higher odds of breakup.

Third, is having an “open relationship” related to the odds of break-up, in general and specifically for nonexclusive couples? One might hypothesize that those couples who had agreed to that it is “OK to see others” may be less serious or may have already been troubled before this agreement was made, resulting in a positive main effect for this variable. On the other hand, having agreed as a couple that it is “OK to see others” should reduce the likelihood that couples will break up given that sexual nonexclusivity has occurred, as individuals would be less justified in becoming upset if a prior agreement on this issue had been reached.

The findings from this study will contribute to our understanding of adolescent romantic relationships in a number of ways. The data provide a unique opportunity to simultaneously study both partners’ infidelity, agreements about exclusivity, and relationship qualities, reducing the omitted variable bias existing in the fairly separate bodies of literature on infidelity and relationship breakup. With the focus on gender interactions, the study may help answer some of the questions about the extent to which adolescent romantic relationships follow traditional male- dominated or more egalitarian power structures. Finally, knowing more about predictors of remaining in a nonexclusive relationship, with its potential increased risk of STI transmission, should help program planners design and target interventions.

19

CHAPTER III. DATA

Data for this thesis come from the Toledo Adolescent Relationships Study (TARS), a longitudinal study conducted by researchers at Bowling Green State University with the purpose of learning about adolescents’ experiences in different types of relationships—parents, peers, and romantic partners—and how the qualities of these relationships affect sexual risk-taking and other problem behaviors. While the TARS data set is not nationally representative, the demographic characteristics of Lucas County closely match those of the United States on a number of key aspects, including race/ethnicity, education levels, and family income.

Unfortunately, nationally representative data sets such as the National Longitudinal Study of

Adolescent Health and the National Survey of Family Growth cannot be used to explore these research questions because they do not include information on respondent and partner cheating behavior, and include few questions on relationship qualities beyond partner demographics.

The TARS sample was randomly selected from student enrollment records for the 2000-

2001 school year in Lucas County, OH, a largely urban county that includes the city of Toledo.

The 1,321 respondents in wave 1 were selected from male and female youth who were enrolled in grades 7, 9, and 11, even if they were not attending school by the time of selection. TARS interviews usually occurred in respondents’ homes, and were collected via a combination of computer-assisted personal interviewing and computer-assisted self interviewing, with the latter used for the more sensitive items, such as the romantic partner section. The first wave included interviews with both the teens and a custodial parent, while waves 2 and 3 interviewed the teen only. Waves 1 and 3 also included qualitative interviews with a small subsample of the TARS youth, but those data are not analyzed here. This thesis primarily uses data from wave 3 of

TARS, collected in 2004, which included 1,114 respondents (84% of wave 1 respondents). The 20

sampling strategy included oversamples of African Americans and Hispanics, so descriptive

statistics will be calculated using weighted data.

The final analytic sample includes those who, at wave 3, reported having dated

(defined below) someone of the opposite sex in the previous 2 years (only 120 did not date at all

during this time period). In addition, the sample is limited to those who had vaginal intercourse

within their most recent dating relationship, both because this is the subset of youth most at risk

of exposure to STIs from a partner’s infidelity, and also because this analysis is attempting to

replicate the findings from Eyre et al., which was limited to those in sexually active relationships1. Thus, 395 respondents who had not had vaginal intercourse in their most recent

relationship were dropped. Finally, I remove from analyses the few respondents who are missing

data on the dependent or independent variables, including one respondent who refused to answer the majority of questions in the romantic partner section, two cases that were missing data on partner’s age, and a final five cases were dropped for being missing on respondent’s cheating,

the Intimate Self-Disclosure Scale, the relational asymmetries question, and respondent’s or

partner’s race/ethnicity, respectively. The resulting analytic sample consists of 583 respondents,

267 males and 316 females.

1 Of course, infidelity can also occur in relationships where the partners have not had sex with each other. In the full Wave 3 TARS sample, cheating occurred in 23% of relationships that did not involve vaginal sex between partners, compared to 32% of those where the couple did have vaginal sex (χ²=8.24, p<.0041). Results based on alternative formulations of the analytic sample are discussed below. 21

CHAPTER IV. MEASURES

Dependent Variable

The dependent variable for these analyses is whether the respondent’s most recent dating relationship has ended, or is still an ongoing, current relationship. Dating in TARS is defined for male respondents as “when you like a girl and she likes you back; it doesn’t have to mean going on a ‘formal’ date,” with female respondents seeing “guy” inserted where “girl” is used in this phrase (gender-specific language regarding dating partners is used throughout the questionnaire).

Respondents are asked at the beginning of the romantic partner section how many people of the opposite sex they have dated in the previous two years. By wave 3, nearly all respondents (92% of the full wave 3 sample) have dated someone of the opposite sex, and nearly all of those who have ever dated someone have dated in the past 2 years (89% overall, or 96% of those who have ever dated). It is worth noting that respondents in wave 3 of TARS were also asked about “non- relationship” sexual partners (that they were not dating) as well as a few questions about same- gender sex partners, but analysis of these data are beyond the scope of this thesis.

Those who said they had dated someone in the past 2 years (e.g., had given a number greater than 0 to the question about number of dating partners in the past 2 years) were then asked, “Is there someone you are currently dating – that is, a guy [girl] you like and who likes you back?” Logically, those who answered this question negatively had ended their most recent dating relationship—they had dated someone in the past 2 years but were not currently dating— while those who answered this question affirmatively are coded as currently being in their most recent relationship. Note that, for those who answered that question negatively, the wording for all questions related to the relationship was changed to the past tense – for example, those currently in relationships might be asked, “Is [PARTNER] in school” while those whose most 22

recent relationship had ended would be asked, “Was [PARTNER] in school,” where

[PARTNER] would be the name or initials of the most recent dating partner as provided by the respondent. The six respondents who refused to say whether they were still dating their most recent partner appear to be given the question wording for relationships that had ended, so they have been coded as ended for the purposes of this analysis.

Focal Independent Variables

Cheating, on the part of the respondent and the partner, is measured by the following two questions for male respondents (genders flipped in the wording for female respondents): “How often have you gotten physically involved (‘had sex’) with other girls?” and “How often do you think [PARTNER] has gotten physically involved with other guys?” Response options to these

questionnaire items are never, hardly ever, sometimes, often, and very often. These variables

have highly skewed distributions: for example, only four respondents in the entire sample say

they had sex with others very often. Some preliminary analyses used a three-category version of

these variables—never, hardly ever, and sometimes/often/very often—in regressions. However, differences between the coefficients for the two dummy variables indicating different levels of cheating, hardly ever vs. more often, were not statistically significant (results not shown), indicating that there would be no loss of information in representing infidelity with two dummy variables to indicate whether or not respondent and partner had ever cheated. Further preliminary analyses indicated a significant interaction between respondent’s and partner’s cheating status, so the final measure used in this study is a set of dummy variables that represent infidelity status at the couple-level (only partner cheated, only respondent cheated, and both cheated, with neither cheated as the reference category). 23

Gender was originally captured at wave 1 and was confirmed at wave 2. Females are

coded 1, males are coded 0.

Independent Variables Related to the Relationship

The study contains three indicators to love and intimacy. To measure respondent’s

emotionality within the relationship, I use 3 items from Hatfield and Sprecher’s Passionate Love

Scale (1986): “I would rather be with [PARTNER] than anyone else,” “[PARTNER] is always

on my mind,” and “I feel like [PARTNER] is my soulmate.” There are 5 valid responses for each

of these statements: strongly disagree, disagree, neither agree nor disagree, agree, and strongly

agree. The responses of the three items are summed, with the resulting scale ranges from 3-15,

with higher scores indicating greater love. Chronbach’s alpha for this scale in the analytic

sample is .86. As all information on the romantic relationship is reported by the respondent,

partner’s emotionality within the relationship is measured using the words and actions by which

the partner expresses his/her emotionality. This scale, called the Emotional Rewards Scale, is

based on the following 4 items: “[PARTNER] makes me feel attractive,” “[PARTNER] makes

me feel good about myself,” “Sometimes [PARTNER] doesn’t pay enough attention to me”

(reversed) and “How often does [PARTNER] tell you how much your relationship means.” The

first 3 items have a 5-item Likert-style response option set of strongly disagree, disagree, neither agree nor disagree, agree, and strongly agree, and the final item includes 5 responses: never, hardly ever, sometimes, often, and very often. The items are summed, with the resulting scale ranging from 4-20, and higher levels here represent that the respondent perceives greater levels of caring from his/her partner. Chronbach’s alpha for this scale for the analytic sample is .71.

The Intimate Self-Disclosure Scale includes four items, asking how often the respondent talks to his/her partner about four different topics: “something really bad that happened,” “your home life 24

and family,” “your private thoughts and feelings,” and “your future,” based on a scale by West

and Zingle (1969). Each of these questions has five response options: never, hardly ever,

sometimes, often, and very often. These questions are summed to form the scale, which ranges

from 4-20, with higher scores indicating more self-disclosure. Chronbach’s alpha for this scale

for the analytic sample is .89.

The Commitment Scale includes 6 items from Stanley and Markman’s (1992)

Commitment Scale: “I like to think of [PARTNER] and me in terms of us and we instead of me

and him/her,” “I want this relationship to stay strong no matter what rough times we may encounter,” “I believe we can handle whatever conflicts will arise in the future,” “I feel uncertain about our prospects to make this relationship work for a lifetime” (reversed), “I am very confident when I think of our future together,” and “we have the skills a couple needs to make a relationship work.” The response to each item was based on a 5-point Likert scale: strongly disagree, disagree, neither agree nor disagree, agree, and strongly agree. Summing the items results in a scale ranging from 6-30, with higher scores indicating greater commitment.

Chronbach’s alpha for this scale for the analytic sample is .86. As an additional measure of commitment, length of relationship is measured in the wave 3 questionnaire via the question,

“How long have you been together” for those currently in relationships, and “How long were you together” for those whose relationships have ended. This question has eight response options: less than a week, a week, 2 to 3 weeks, about a month, 2 to 5 months, 6 to 8 months, about nine months to a year, and a year or more. As response options vary quite a bit in the length of time they represent, this item has been recoded to a value in number of weeks that represents the response (or the midpoint of the response, for those options that are range over a period of time).

Those recoded values are, respectively, 0.5, 1, 2.5, 4.3, 15, 30, 45, and 78, with the final value 25 being chosen for the open-ended top category based on responses in a previous wave of TARS, when those whose relationships had lasted more than a year were asked how many years the relationship had lasted.

The study contains several measures of asymmetry in the relationship. The first is a set of dummy variables based on the item: “In many relationships one person is more ‘into’ the relationship than the other. Would you say:” and the response options for this question are “you are more into it,” “[PARTNER] is more into it,” and “you are about the same.” For this analysis, responses were dummied to compare those respondents who said they or their partner were

“more into” the relationship with those who said both were equally “into” the relationship as the reference group. Respondent’s perceptions about the availability of alternate dating partners was measured via two items developed by Udry (1981, 1983), “I could find another girl/guy as good as PARTNER is” and “it’s likely there are other girls/guys I could be happy with.” With 5- point Likert responses to the items, this scale ranges from 2-10, with higher scores indicating the respondent perceives a greater likelihood of forming a satisfying relationship with an alternate partner. Cronbach’s alpha for this scale in the analytic sample is .79. Male partner is older by more than 2 years is measured by first subtracting female partner’s age from male partner’s age, which are both measured in whole years. If the difference is greater than 2, then the final binary variable is coded 1, otherwise it is coded 0. Age difference is dichotomized partly to build on past research on age differences and power differentials between partners, and partly because laws often dichotomize sexual relationships into lawful and unlawful based on an age difference between partners (Donovan, 1997). Whether or not respondent and partner are of different races or ethnicities is a yes/no variable based on reports of the individuals’ racial/ethnic make- up. Respondent’s race/ethnicity is discussed below. Partner’s race/ethnicity is measured with a 26

single item, “What is [PARTNER]’s racial/ethnic background,” with response options White,

African-American/Black, American Indian/Alaska Native, Native Hawaiian or Other Pacific

Islander, Asian, Hispanic/Latino(a), or Other, with a write-in space to provide more information.

This response is collapsed in a similar fashion to the recode for respondent’s race/ethnicity, and

is then compared to the respondent’s race/ethnicity, using the 4-category recode for those who

are Hispanic, Non-Hispanic White, or Non-Hispanic Black, and then the questionnaire item for

those who are Non-Hispanic Other, in order to see if, say, an Asian respondent is dating an Asian

partner, specifically, and not just someone who falls into the “other” category.

Dysfunctional conflict resolution style is measured with a 4-item scale based on questions

used to measure negative couple interaction (Stanley, Markham, and Whitton, 2002), focusing on

how often the following has occurred in the relationship: “little arguments that become bigger

fights;” “fights with accusations, criticisms, and name calling;” “fights where you bring up past

problems,” and “when we argue, one of us usually doesn't want to talk about it anymore and

leaves.” Each item has five response choices: never, hardly ever, sometimes, often, and very

often. The resulting scale, which has a Cronbach’s alpha in the analytic sample of .85, ranges

from 4-20, with higher scores indicating greater problems with conflict resolution.

Couple agreed it is OK to see others is measured directly in the survey via the item: “Did you and [PARTNER] agree it was OK to see other people,” with response options no, yes, and did not discuss it. For this analysis, a new dichotomous variable was created that contrasts those who said yes with the other two groups.

Demographic Control Variables

Age is measured in years at the time of the wave 3 interview. It is calculated from the respondent’s date of birth, with the result confirmed by all respondents. 27

Respondent’s race/ethnicity is measured at wave 3 using two questions: the first asks if

the respondent is Hispanic or Latino (yes/no), and the second asks the respondent’s race. For this second question, response options are White, African-American/Black, American

Indian/Alaska Native, Native Hawaiian or Other Pacific Islander, Asian, or Other, with write-in

space provided for the interviewer to enter the actual race of those who select Other. Responses

to the race and Hispanic ethnicity questions are collapsed into a 4-category variable (which is then used to create a series of dummy variables) as follows. First, individuals are coded as

Hispanic if they said they were Hispanic/Latino(a), either via the Hispanic ethnicity question or by writing in Hispanic or Latino(a) under Other in the race question. Otherwise, those who chose White or who wrote in Middle Eastern under Other (following Census Bureau classification) are coded as Non-Hispanic White, and those who chose African-American/Black are coded as Non-Hispanic Black in this new 4-category variable. The final category includes

American Indian/Alaska Native, Native Hawaiian or Other Pacific Islander, and Asian, as well as the remaining responses to the Other category not already included in one of the previous categories (who are all multi-race individuals). As discussed above, two cases are missing race/ethnicity, and are not included in the final analytic sample.

Family structure during childhood is family structure measured at wave 1. Specifically, youth were asked at wave 1 who they had lived with most of the time in the past 12 months.

Response options were: mother only and no other adults, father only and no other adults, both parents, mother and stepfather, father and step mother, mother and her boy/girlfriend, father and his boy/girlfriend, other relatives, foster parents, and someone else, with write-in space attached to the other option. As with race/ethnicity, these responses were collapsed to a 4-category variable that was in turn used to create a series of dummy variables. Two Parents, the reference 28

category, includes those who said they lived with both parents or with adoptive parents (a write-

in under “other”). The Single Parent category includes those who said they lived with mother

only and no other adults, or father only and no other adults. Stepfamily includes those who said

they lived with mother and stepfather, or father and stepmother. All other response options are

coded as Other Living Situation. Twelve respondents are missing data on this item, and are

dropped from the final analytic sample.

Parent Education was also measured at wave 1, and is the only variable from the parent

questionnaire used in this analysis. The questionnaire item asked how far the parent respondent

(usually the teen respondent’s mother) had gone in school, and had seven valid responses: 1st-8th

grade; Less than 12 years; 12 years (or obtained GED); Went to business, trade, or vocational

school after high school; 1-3 years of college; Graduated from a college or university; and

Obtained professional training beyond a 4-year college or university. These responses were

collapsed into a 4-category variable that was then used to create dummy variables. The first two

options were combined into a Less than High School option, the third option was coded as High

School, the next two were coded as Greater than High School but No 4-Year Degree, and the

final two were coded as College Degree or More. For this variable, the 22 cases where the

original variable was coded missing/don’t know/refused were assigned to the modal category,

High School Degree, for the 4-category recode. High school degree will be the reference

category in the regression analyses.

29

CHAPTER V. ANALYTIC STRATEGY

I first present descriptive statistics for the analytic sample, as well as bivariate comparisons of intact and broken-up relationships (with differences tested via Chi Square or t- test as appropriate). I then use logistic regression to identify the effect of the independent variables on the odds of whether or not respondent’s most recent relationship has ended. The initial two models concentrate on the focal independent variables of cheating and gender, testing main effects and interactions. The next model tests if having a high-quality relationship mediates the relationship between infidelity and break-up. A fourth model adds the dummy variable for relationships where the couple had agreed that it would be OK to see other people, as well as interactions between this variable and couple exclusivity status, and a fifth shows interactions between the “agree to see others” and cheating status. A sixth model adds demographic controls. The seventh and final model shows gender interactions with the relationship qualities and demographic controls.

30

CHAPTER VI. RESULTS

Descriptive Statistics

Table 1 presents univariate and bivariate statistics for the analytic sample. The dependent variable is whether the respondent’s most recent dating relationship has ended or is still current.

In this sample, about a quarter of relationships have ended (24.3%).

A key independent variable is the couple-level measure of infidelity. Overall, no cheating occurred in about two-thirds of relationships (67.6%). Of the remaining one-third of relationships, 6.9% are relationships in which the partner cheated, but the respondent did not;

10.4% are relationships in which the respondent cheated, but not the partner; and both partners cheated in 15.1% of relationships. Intact relationships are more likely to be sexually exclusive

(72.0% vs. 54.1%, p<.001).

Respondents tended to rate their relationships highly in terms of love and intimacy.

Mean scores on the Passionate Love (11.2 on a scale of 3-15) and Emotional Rewards Scales

(15.6 on a scale of 4-20) are both above the midpoints of those scales. Likewise, the mean score on the Intimate Self-Disclosure Scale is 16.0, on a scale of 4-20. Respondents in intact relationships report higher scores on these measures than those in relationships that have ended

(p<.001 for all three scales), with mean scores about 2 points higher on the Passionate Love

Scale (11.7 vs. 9.7), the Emotional Rewards Scale (16.0 vs. 14.3), and the Intimate Self-

Disclosure Scale (16.5 vs. 14.2).

The mean Commitment Scale score, on a range of 10-30, is 22.2. Again, those in intact relationships report higher scores, on average (23.1), than those whose relationships have ended

(19.1), p<.001. The estimated average length of relationships is close to a year (49 weeks). 31

Intact relationships have lasted longer than those that have ended (52.9 weeks vs. 36.6 weeks,

p<.001).

The majority (61.3%) of respondents reported that they and their partners are equally

“into” the relationship, while 15.0% said that they were more into the relationship and 23.8%

said their partners were more into the relationship. Respondents whose relationships had ended

were less likely to report being equally “into it” than those whose relationships were ongoing

(50.6% vs. 64.7%, p<.001). The mean score on the Alternative Partners Scale was 6.1, on a

range of 2-10, with those in relationships that have ended reporting higher scores than those

whose relationships are intact (7.1 vs. 5.8, p<.001). Regarding the demographic asymmetries,

just under a quarter of relationships consists of an older male dating a younger female (22.3%) or contains partners of different races or ethnicities (22.7%). At the bivariate level, there is no 32

Table 1: Descriptive Statistics, Respondents and Their Most Recent Dating Relationships, Sexually Active Relationships Only, Toledo Adolescent Relationships Study (TARS), Wave 3 % or Mean Total Intact Broken Up Relationship Has Ended 24.3% ------

Couple-Level Cheating Measure: - Neither Cheated 67.6% 72.0% 54.1% - Only Partner Cheated 6.9% 4.3% 14.8% - Only Respondent Cheated 10.4% 9.7% 12.6% - Both Cheated 15.1% 14.0% 18.4% ***

Relationship Qualities: Love and Intimacy: Passionate Love (3-15) 11.2 11.7 9.7 *** Emotional Rewards (4-20) 15.6 16.0 14.3 *** Intimate Self-Disclosure (4-20) 16.0 16.5 14.2 *** Commitment Commitment (10-30) 22.2 23.1 19.1 *** Length of Relationship (Est. Weeks, 0.5-78) 49.0 52.9 36.6 *** Asymmetries: Who's More "Into" the Relationship: Respondent 15.0% 11.7% 25.0% Partner 23.8% 23.6% 24.4% Equally "Into It" 61.3% 64.7% 50.6% *** Alternative Partners (2-10) 6.1 5.8 7.1 *** Male Partner Older >2 Years 22.3% 22.6% 21.6% Partners are of Different Race/Ethnicity 22.7% 23.5% 20.2% ** Conflict: Dysfunctional Conflict Resolution Style (4-20) 8.8 8.7 9.1 Agreement About Nonexclusivity: OK to See Others 19.9% 8.8% 54.3% ***

Respondent Demographics: Gender: - Male 48.3% 43.8% 62.4% - Female 51.7% 56.2% 37.6% *** Age (15-22) 18.7 18.7 18.7 Race/Ethnicity: - Hispanic 9.1% 9.0% 9.4% - Non-Hispanic White 60.8% 61.3% 59.3% - Non-Hispanic Black 27.3% 26.8% 28.9% - Non-Hispanic Other 2.8% 2.9% 2.5% Living Situation at Wave 1: - Single Parent 24.8% 25.4% 23.0% - 2 Parents (Bio/Adopted) 48.4% 47.2% 51.9% - Stepfamily 15.3% 15.0% 16.4% - Other 11.5% 12.5% 8.7% *** Parent's Education: - Less than High School 14.2% 14.4% 13.6% - High School 33.6% 34.6% 30.7% - More Than High School, no Degree 36.0% 35.9% 36.4% - 4-Year College Degree or Higher 16.2% 15.2% 19.3% ***

N 583 445 138 + p < .10, * p < .05, ** p < .01, *** p < .001 33

significant difference between the proportion of intact and broken-up relationships that involve

older male partners (22.6% vs. 21.6%), while relationships involving individuals of different

races or ethnicities are more likely to be current (23.5% vs. 20.2%, p<.01).

The mean score on Dysfunctional Conflict Resolution Style, a scale that ranges from 4-

20, is 8.8. At the bivariate level, differences between mean scores on this scale for those in intact

(8.7) and broken-up relationships (9.1) are not statistically significant. About one in five couples

(19.9%) had agreed that it was OK to see others, and there are large differences between

relationships that are current and those that have ended on whether or not the couple had such an

agreement (8.8% of intact vs. 54.3% of broken-up, p<.001).

In terms of demographics for the sample, slightly more than half of the respondents are

female (51.7%), and females are over-represented in intact vs. broken up relationships (56.2%

vs. 37.5%, p<.001). The average age of respondents in both relationship categories is 18.7 years.

The majority of the sample is non-Hispanic White (60.8%) or non-Hispanic Black (27.3%), with

relatively few in the Hispanic (9.1%) and non-Hispanic Other categories (2.8%); the racial/ethnic breakdown of the intact and broken-up relationship groups are similar. About a quarter of the entire sample grew up in a single parent home (24.8%), close to half lived with both parents

(48.4%), and the remaining quarter grew up in a stepfamily (15.3%) or in some other living situation (11.5%). Childhood living situation was significantly different for the two groups at the

p<.001 level – for example, the intact relationship group had a smaller percentage of those from

2-parent families (47.2% vs. 51.9%) and a higher proportion of those who were raised in some

“other” type of family structure (12.5% vs. 8.7%). Regarding education of the custodial parent,

14.2% of respondent’s parents have less than 12 years of education, 33.6% of parents have a high school degree, 36.0% have some training beyond high school but no 4-year college degree, 34 and 16.2% have at least a 4-year college degree. There are statistically significant differences between respondents whose most recent relationship is current and those whose most recent relationship has ended (p<.001), with respondents in intact relationships more likely to have parents with a high school education (34.6% vs. 30.7%) and less likely to have parents with a 4- year degree or more (15.2% vs. 19.3%).

Regression Results

Table 2 shows the results of logistic regression models predicting whether or not respondents’ most recent relationships have ended. Model 1 includes only the couple-level cheating status and gender. The model shows that the odds of a couple having broken up are significantly higher in relationships where the partner has cheated (OR=5.83, p<.001), but couples where only the respondent cheated and those where both partners cheated are not significantly different from couples where neither partner cheated, in terms of the odds of breakup. Female respondents are less likely than males to have ended their most recent relationships (OR=0.44, p<.001), controlling for couple-level cheating status. Note that the model chi-square tests for this model, as well as all later models, are significant, indicating that at least one coefficient is nonzero.

Model 2 examines whether girls are more likely than boys to stay with a cheating partner by adding an interaction term for partner cheats and female gender. The coefficient of the interaction term is not significant, indicating that the impact of partners’ cheating on the odds of breakup does not depend on gender. In other words, there is no evidence at this point to conclude that females react differently than males to infidelity. Also, not surprisingly, the nested chi-square test comparing this model to model 1, the model without the interaction term, did not significantly add to the fit of the model, (χ2=0.5, df=1). The interaction term was included in the 35

additional models to see if it strengthened with the addition of other independent variables, but it did not. There is also no significant interaction between gender and the other two cheating categories.

Table 2: Logistic Regression of Whether Most Recent Dating Relationship Has Ended (vs. is Current), Only Relationships That Included Vaginal Sex, Wave 3 TARS Model 1 Model 2 BExp(B) BExp(B) Intercept -1.04 0.35 *** -1.06 0.35 ***

Couple-Level Cheating Measure: - Neither (ref.) 1.00 1.00 - Only Partner 1.77 5.85 *** 2.15 8.62 ** - Only Respondent 0.34 1.40 0.35 1.41 - Both 0.43 1.53 0.43 1.54

Respondent Demographics: Gender (Female) -0.81 0.44 *** -0.77 0.46 ***

Interactions: Only Partner Cheats x Female -0.54 0.59

Test Statistics: df df -2 Log L 598.7 598.3 Model χ² 39.37 4 *** 39.8 5 *** Δ χ² (Compared to Previous Model) 0.5 1 + p < .10, * p < .05, ** p < .01, *** p < .001

Table 3 shows additional models that address the second research question, whether or

not relationship qualities mediate the relationship between cheating and breakup. Model 1 adds

variables measuring relationship quality and demographic characteristics of the relationship

(with all scales centered). The addition of relationship qualities significantly improves the fit of

the model compared to Model 1 in Table 2 (Δχ2=122.8, df=11, p<.001). It does appear that

infidelity has a unique relationship with breakup, separate from measures of relationship quality.

With the addition of relationship qualities, the odds of breakup among couples where only the

partner cheated have decreased, but they are still elevated compared to couples where neither 36

partner cheated (OR=2.92, p<.05). Please refer to Appendix 1 for correlations between these

relationship measures.

In Model 1, relationship qualities related to love and intimacy are only weakly associated

with breakup status due to mediation by other types of relationship qualities. For example, in

Model 1 neither the Passionate Love Scale (OR=0.92), or the Emotional Rewards Scale

(OR=0.97) are significantly associated with breakup, even though both of these variables were

significantly protective (p<.001) in zero-order models (not shown)2. Odds of breakup were marginally reduced as scores on the Intimate Self-Disclosure Scale increased (OR=.93, p<.10).

Commitment is protective against breakup, with the odds of breakup decreasing as scores on the

Commitment Scale increasing (OR=.87, p<.001), and as the length of the relationship increasing

(OR=.99, p<.01).

Relational and demographic asymmetries are associated with the odds of breakup but not always in the expected ways. In both a zero-order model and in Model 1, the respondent being

more “into” the relationship is associated with increased odds of breakup (OR=1.98 in Model 1,

p<.05). Believing that one’s partner is more “into” the relationship, on the other hand, is not

significant in the zero-order model and is associated with decreased odds of breakup in Model 1

(OR=0.32, p<.001)3. Higher scores on the Alternative Partners Scale are marginally associated

with increased odds of breakup in Model 1 (OR=1.13, p<.10), a much weaker relationship than is

found at the zero-order level (p<.001)4. Note that the Alternative Partners Scale and the “more

into it” measure are independent, and one does not mediate the effect of the other.

2 Additional analyses show that the effect of the Passionate Love Scale is mediated by the Commitment Scale alone, while the effect of the Emotional Rewards Scale is mediated by a combination of commitment, relational asymmetry, and self-disclosure. 3 This change occurred with the addition of the Passionate Love and Commitment Scales. 4 A combination of commitment, relationship length, and the cheating measure seems to result in the weakening of the relationship between the Alternative Partners Scale and breakup. 37

Regarding the demographics of the relationship, odds of breakup were lower for couples

where partners were of different racial or ethnic groups. Relationships where the male partner is more than 2 years older than the female are not significantly more likely than other couples to have broken up (OR=1.47), while odds of breakup were lower when partners were of different races or ethnicities (OR=0.53, p<.05)5. Finally, scores on the Dysfunctional Conflict Resolution

Style Scale are not associated with breakup (OR=1.05).

Models 2 and 3 add a variable related to sexual nonexclusivity: whether or not the couple

agreed that it is/was OK for them to see other people. Model 2 adds this variable alone to Model

1, and shows that having agreed that it is OK to see others is associated with a much higher odds

of breakup (OR=16.00, p<.001). The addition of this single variable is a significant

improvement in model fit (Δχ²=95.6, p<.001). There are also several changes in the significance

of variables first introduced in previous models. Couples where only the partner cheats still have

elevated odds of breakup compared to those where neither partner cheats, but now the odds of

breakup for couples where both partners cheat are marginally significantly lower than those for

sexually exclusive couples (OR=0.54, p<.10). The magnitude of the coefficients for the Intimate

Self-Disclosure and Dysfunctional Conflict Resolution Style Scales increase, with the former

changing from being marginally significant to significant at the p<.05 level (OR=0.98) and the

latter changing from nonsignificant to significant at the p<.05 level (OR=1.11). The Alternative

5 The latter is a change from the zero-order model, where there is no significant difference between same- race/ethnicity and different-race/ethnicity couples, and seems to be the result of the addition of relationship length and cheating status. 38

Partners Scale, on the other hand, weakened from being marginally significant to nonsignificant

(OR=1.13).

Table 3: Logistic Regression of Whether Most Recent Dating Relationship Has Ended (vs. is Current), Only Relationships That Included Vaginal Sex, Wave 3 TARS Model 1 Model 2 Model 3 Model 4 Model 5 B Exp(B) B Exp(B) B Exp(B) B Exp(B) B Exp(B) Intercept -0.29 0.75 -1.52 0.22 *** -1.63 0.20 *** -1.18 0.31 -0.74 0.48

Couple-Level Cheating Measure: - Neither (ref.) 1.00 1.00 1.00 1.00 1.00 - Only Partner 1.07 2.92 * 1.04 2.82 * 1.65 5.22 ** 1.57 4.82 ** 1.90 6.70 ** - Only Respondent -0.17 0.84 -0.32 0.72 0.13 1.14 0.07 1.07 0.26 1.30 - Both -0.38 0.68 -0.62 0.54 + -0.41 0.67 -0.49 0.62 -0.53 0.59

Relationship Qualities: Love and Intimacy: Passionate Love -0.09 0.92 -0.03 0.97 -0.03 0.97 -0.03 0.97 -0.04 0.96 Emotional Rewards -0.03 0.97 -0.02 0.98 0.00 1.00 -0.01 0.99 0.01 1.01 Intimate Self-Disclosure -0.07 0.93 + -0.09 0.92 * -0.09 0.92 * -0.09 0.92 * -0.08 0.93 + Commitment: Commitment -0.14 0.87 *** -0.16 0.85 *** -0.17 0.85 *** -0.18 0.83 *** -0.12 0.89 * Length of Relationship (Est. Weeks) -0.01 0.99 ** -0.02 0.98 *** -0.02 0.98 *** -0.02 0.98 *** -0.02 0.98 *** Asymmetries: Who's More "Into" the Relationship: Respondent 0.68 1.98 * 0.73 2.07 * 0.78 2.19 * 0.75 2.12 * 0.81 2.24 * Partner -1.13 0.32 *** -1.49 0.23 *** -1.44 0.24 *** -1.55 0.21 *** -1.57 0.21 *** Equally "Into It" (Ref.) 1.00 1.00 1.00 1.00 1.00 Alternative Partners (2-10) 0.12 1.13 + 0.12 1.13 0.12 1.12 0.12 1.12 0.11 1.11 Male Partner Older >2 Years 0.39 1.47 0.33 1.39 0.33 1.38 0.34 1.41 0.42 1.52 Partners are Different Race/Ethnicity -0.63 0.53 * -0.80 0.45 * -0.89 0.41 ** -0.92 0.40 * -0.95 0.39 * Conflict: Dysfunctional Conflict Res. Style 0.05 1.05 0.10 1.11 * 0.10 1.11 * 0.10 1.11 * 0.09 1.10 * Agreement About Nonexclusivity: OK to See Others 2.77 16.00 *** 3.33 27.89 *** 3.42 30.46 *** 3.78 43.62 ***

Respondent Demographics: Gender (Female) -0.87 0.42 ** -0.81 0.44 ** -0.88 0.42 ** -0.86 0.42 ** -1.51 0.22 * Age -0.04 0.96 -0.05 0.95 Race/Ethnicity: - Hispanic 0.36 1.44 -0.75 0.47 - Non-Hispanic White (Ref.) 1.00 1.00 - Non-Hispanic Black 0.42 1.52 -0.75 0.47 - Non-Hispanic Other 0.58 1.78 -0.10 0.91 Living Situation at Wave 1: - Single Parent -0.17 0.85 0.02 1.02 - 2 Parents (Bio/Adopted) (Ref.) 1.00 1.00 - Stepfamily 0.34 1.40 0.52 1.69 - Other -0.49 0.61 -0.39 0.67 Parent's Education: - Less than High School -0.01 0.99 0.95 2.58 - High School (Ref.) 1.00 1.00 - More Than High School, no Degree 0.36 1.44 0.77 2.15 + - 4-Year College Degree or Higher 0.14 1.16 0.39 1.47

Interactions: Only Partner Cheats x OK See Others -2.51 0.08 * -2.42 0.09 * -2.92 0.05 ** Only Respondent Cheats x OK See Others -1.46 0.23 -1.42 0.24 -1.87 0.15 + Both Partners Cheat x OK See Others -0.76 0.47 -0.82 0.44 -1.01 0.37 Commitment x Female -0.16 0.85 * Hispanic x Female 2.32 10.20 * Non-Hispanic Black x Female 2.49 12.03 *** Non-Hispanic Other x Female 1.61 5.02 Parent Ed. < High School x Female -1.85 0.16 + Parent Ed. Some Post-HS x Female -0.93 0.39 Parent Ed. 4-Year Degree+ x Female -0.98 0.38

Test Statistics: df df df df df -2 Log L 475.9 380.3 373 366.9 345.5 Model χ² 162.2 15 *** 257.8 16 *** 265.1 17 *** 271.2 27 *** 292.6 30 *** Δ χ² (Compared to Previous Model) 122.8 11 *** 95.6 1 *** 7.4 1 ** 13.4 10 27.4 3 *** + p < .10, * p < .05, ** p < .01, *** p < .001 39

Model 3 shows a statistically significant interaction between agreeing that it is OK to see others and the situation where the only partner cheats. When the couple does not have an

agreement that nonexclusivity is OK, odds of breakup are elevated when the partner cheats but

the respondent does not (OR=5.22, p<.01). However, when the couple has agreed that it is OK

to see others, the coefficient for couples where only the partner cheated is not statistically

significant, perhaps because of the small proportion of the sample that falls into this category

(OR=0.425). Coefficients for the interactions between agreements about nonexclusivity and the other two cheating statuses are not significant. However, the actual relationships between these variables is that when there is no agreement, odds of breakup are not significantly different from exclusive couples without an agreement that it is OK to see others. With an agreement, odds of breakup are marginally significantly lower for couples where only the respondent cheated

(OR=0.26, p<.08) and couples where both partners cheated (OR=0.313, p<.06). The relationships between all other variables and the odds of breakup remain roughly the same as in

Model 2. As with the previous model, the addition of the interaction term significantly improves the fit of the model (Δχ²=7.4, df=1, p<.01).

Model 4 adds the remaining demographic control variables for the respondent, none of

which was significant. Coefficients remain virtually unchanged from the previous model, except

that the odds ratio for couples with an agreement not to be exclusive, where both partners cheat,

is now significant (OR=0.272, p<.05). Not surprisingly given the lack of significant coefficients

for the demographic control variables, this model is not a significant improvement over model 3

in terms of fit (Δχ2=13.4, df=10, p<.21). 40

Model 5, the final model, shows the statistically significant gender interactions with

relationship qualities and demographic characteristics of the respondent (nonsignificant

interactions were removed from the model for ease of interpretation). There is a significant

gender interaction between the Commitment Scale and gender, such that higher commitment

scores are protective for males (OR=0.89, p<.05) and even more protective for females

(OR=0.75, p<.001). There are also gender differences for Hispanics and non-Hispanic Blacks in

odds of breakup, with males not significantly different from non-Hispanic White males to have

ended their most recent relationships, but females in these two groups have increased odds of

breakup compared to non-Hispanic White females (OR=4.83 for Hispanics, p<.05, and OR=5.68

for non-Hispanic Blacks, p<.001). Parent’s education has a marginally significant interaction

with gender. It indicates that odds of breakup are significantly different for males (OR=2.58)

and females (OR=0.41) are significantly different from each other, even though they are both not

significantly different from those whose parents have a high school degree. Parent’s education

does become marginally significant for one group, with males whose parents have some training

beyond high school but no 4-year college degree having increased odds of breakup (OR=2.15, p<.10). Note that the interaction of gender and agreeing that it is OK to see others is nonsignificant, as is the 3-way interaction between nonexclusivity agreements, gender, and partner cheating. The only change in the other covariates from the previous model is that the

only respondent cheats by “OK to see others” interaction strengthens slightly, so that the lowered

odds of breakup for couples where the respondent cheats and the couple has agreed that

nonexclusivity is OK (OR=0.20) is now significant at the p<.05 level, instead of p<.10. Adding

the gender interactions does significantly improve the fit of the model compared to model 4 41

(Δχ2=22.5, df=3, p<.001). Variance inflation factors for the variables in the final model were all less than 5, indicating that multicolinearity is not an issue.

Additional Analyses

While the sample is limited to couples who have had vaginal sex, on the basis that these are the couples truly at risk of transmitting an STI acquired through extradyadic sex, one could argue that looking at these research questions with a broader sample of couples is reasonable.

Couples that have not had vaginal sex by interview may go on to have sex later, and may be engaging in other behaviors, such as oral or anal sex, that also carry a risk of STI transmission.

Re-analyzing the data while including couples that have not had sex, but where the respondent is not a virgin (n=699), results in few differences from the models presented above.

In Model 5 with this new analytic sample, controlling for whether or not the couple has had sex, self-disclosure is no longer a significant predictor of breakup (OR=0.94, p<.16) whereas before it was marginally significant. The interaction of both partners cheat and OK to see others is still not significant, but the odds of breakup for those who both cheat and do not have such an agreement strengthen from being nonsignificant to marginally significant (OR=0.49, p<.10).

The commitment X gender interaction is only marginally significant (p<.07), whereas before it was significant at the p<.05 level. The interaction of parent’s education at less than high school

X gender is no longer significant (p<.18), while with the more restricted sample it was marginally significant. All other variables that were significant at p<.05 are still significant, and those that were not (including the interaction of gender and partner only cheats) still are not with this new sample.

Including respondents who are virgins increases the sample size to 962. Controlling for whether or not the respondent has had sex, differences in Model 5, compared to the original 42 analysis, is that the partner being more “into” the relationship is no longer significantly associated with breakup, and several of the interactions are no longer significant: Only

Respondent Cheats X OK to See Others, Commitment X Female, Hispanic X Female, and

Parent’s Education is Less than High School X Female. All other variables that were significant at p<.01, including gender, cheating status, agreeing that it is OK to see others, and the interaction of “OK to see others” and partner only cheats, are also statistically significant in this new analysis, and variables that were not significant in the original Model 5 are still nonsignificant, including gender by cheating interactions.

43

CHAPTER VII. DISCUSSION

This study shows that dating relationships among sexually active adolescents and young

adults often includes some kind of cheating. About a third had cheating by one or both members

of the couple. The most common type of cheating is when both partners were cheating. At the

same time there is not a universal expectation for fidelity in these adolescent and young adult

relationships, as about one-fifth of couples had agreed to accept nonexclusivity in the relationship. Clearly, the same fidelity expectations that are implied in marriages do not exist in all dating relationships.

Cheating in relationships is associated with breaking up, and young men and women who

experience infidelity in their relationships share similar odds of dissolving relationships. Thus, these findings do not support the evolutionary psychology or social roles arguments. Instead, this is more consistent with the argument that there has been a convergence in male and female

attitudes toward, and behavior in, romantic and sexual relationships. Cheating has a particularly

strong influence on breaking up among couples who are in relationships in which fidelity is

expected.

This investigation also examines the qualities of relationships. None of the qualities explains the effect of cheating on breaking up. However, many relationship qualities are associated with breakup. For example, relationships where respondents report lower levels of

commitment and more problems with conflict resolution were more likely to be broken up, as

were those where the respondent reported being more “into” the relationship.

I do not find much support for the theoretical perspectives applied to research on

infidelity. I find no gender difference in acceptance of a cheating partner, as would be predicted

by the evolutionary psychological approach to gender differences in reactions to infidelity. 44

Neither do I find strong evidence for exchange and equity theories, given that the Alternative

Partners Scale is not a significant predictor of breakup after controlling for other relationship

qualities and cheating, and imbalances in who’s more “into” the relationship do not have

symmetrical effects for both partners. Acceptance of infidelity in the relationship does not

operate in the way one might think, as the odds of breakup given cheating were not always

significantly different based on whether or not the couple had come to such an agreement. It

does appear that infidelity, relationship qualities, agreements about nonexclusivity, and gender

all play a role in the breakup of adolescent romantic relationships, even if these roles are not well

understood in the context of traditional theories. It may be that such theories, developed with a

focus on marital relationships, need to be adapted somewhat given the differences between

marriage and dating in terms of seriousness, structural barriers to breakup, and developmental

stage of the romantic partners.

A few caveats should be kept in mind when considering this research. First, while I have

described respondents as “tolerating” or “not tolerating” infidelity based on whether or not their

relationships have broken up, the reality is probably much less black-and-white. Those whose relationships have ended may have tolerated their partner’s cheating for some time before

deciding to end the relationship – for example, in one of the Wave 3 TARS qualitative interviews, a respondent described how his girlfriend finally broke up with him the ninth time

she caught him cheating. Couples might also forgive each other for infidelity, but then break up because of other problems in the relationship, but the TARS survey does not contain questions about reasons for breakup, so we cannot know how often this is the case. For that matter, both partners may not even know about the nonexclusivity in their relationship at the time of breakup

– in one study that interviewed young adults who had cheated on a partner, 44% said their 45 partners never found out about it, and 5% of those who did learn about it did so only after the relationship had ended (Feldman & Cauffman, 1999b). Nonexclusive relationships might also potentially end not because of hurt feelings by the faithful partner, but because the unfaithful partner decides to form a new relationship with the “other woman” or “other man.”

Second, it is important to note that there are really two ways that respondents increased their likelihood of an ongoing relationship being captured at the time of interview. The more obvious way is to have a more serious, longer-lasting relationship, but having very short time intervals between relationships would also increase the likelihood of being interviewed while in an ongoing relationship. I think the latter situation probably explains the finding that interracial relationships are more likely to be current relationships, which runs counter to most research on this topic. I attempted to duplicate findings from a recent article on interracial dating (Wang,

Kao, & Joyner, 2006) that compared lengths of relationships that had ended, and did find shorter average durations for interracial relationships when I drew my sample in that way. This implies that my finding in this paper is probably not due to longer relationship lengths for interracial couples, but that respondents who begin new relationships quickly after ending a relationship are more likely to date interracially. This may be the explanation for significant findings related to other independent variables included in this study, although most would seem to be consistent with an explanation of longer, more serious relationships being more likely to be ongoing.

Like most research on dating relationships, the data on the actual relationship is cross- sectional. This means that those respondents who had ended their most recent relationships were describing how they felt about the relationship after the breakup, so it is possible they may have revised their feelings about, say, commitment or heightened emotionality downward based on the fact that the relationship has ended. Thus, it might be that, for instance, couples that experience 46

a dysfunctional conflict resolution style are more likely to break up, or it may be that respondents

who have ended their relationships are more likely to think back on the relationship as having

poorly-managed conflict. This may not truly be a problem for this study, though, if revisions in

relationship qualities among those who have ended their relationships do not differ by couple

cheating status. I hope to avoid this potential bias in future research by studying relationships

longitudinally over waves 3 and 4 of TARS.

Future research should attempt to determine the contexts in which infidelity is more or

less likely to result in relationship breakup. While this study adds to the literature by measuring

the infidelity of both partners, as well as including a measure of agreements about seeing other

people, many other circumstances surrounding the infidelity might affect whether or not it leads

to breakup. For example, measuring whether the cheating occurred in a casual or more

emotionally charged relationship would allow for a better test of the evolutionary psychological

theory behind much of the existing literature on this topic. It might also be interesting to

measure the how long the relationship had lasted before infidelity first occurred/was discovered, the number of different partners with which the cheating occurred, motivations for cheating, and whether any agreements that it is OK to see others were in place at the beginning of the

relationship, or if such an agreement was made after an initial infidelity was discovered.

Knowing more about the circumstances under which relationships continue despite cheating by

one or both partners would help with the development and targeting of future STI prevention

interventions.

47

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APPENDIX A

Table 4: Correlations Between Relationship Qualities Couple-Level Cheating Category Partner Only Respon- Both Passionate Emotional Self- Commit- dent Only Love Rewards Disclosure ment

Partner Cheats 1 -0.09 -0.11 -0.04 -0.12 -0.09 -0.08 0.03 0.01 0.33 0.00 0.03 0.05

Respondent -0.091 -0.14 -0.11 -0.04 -0.08 -0.17 Cheats 0.03 0.00 0.01 0.38 0.05 <.0001

Both Cheat -0.11 -0.141 -0.17 -0.20 -0.15 -0.21 0.01 0.00 <.0001 <.0001 0.00 <.0001

Passionate -0.04 -0.11 -0.171 0.43 0.36 0.71 Love 0.33 0.01 <.0001 <.0001 <.0001 <.0001

Emotional -0.12 -0.04 -0.20 0.431 0.40 0.48 Rewards 0.00 0.38 <.0001 <.0001 <.0001 <.0001

Self-Disclosure -0.09 -0.08 -0.15 0.36 0.401 0.44 0.03 0.05 0.00 <.0001 <.0001 <.0001

Commitment -0.08 -0.17 -0.21 0.71 0.48 0.44 1 0.05 <.0001 <.0001 <.0001 <.0001 <.0001

Relationship -0.03 -0.03 -0.13 0.29 0.08 0.21 0.33 Length 0.41 0.41 0.00 <.0001 0.04 <.0001 <.0001

Respondent 0.17 0.00 0.00 0.06 -0.30 0.00 -0.09 More "Into It" <.0001 0.91 0.92 0.16 <.0001 0.95 0.03

Partner More -0.06 0.14 0.13 -0.37 -0.04 -0.19 -0.33 "Into It" 0.17 0.00 0.00 <.0001 0.34 <.0001 <.0001

Alternative 0.14 0.08 0.14 -0.47 -0.38 -0.23 -0.47 Partners 0.00 0.05 0.00 <.0001 <.0001 <.0001 <.0001

Male Partner 0.07 -0.05 0.03 0.11 0.03 0.04 0.12 Older >2 Yrs. 0.09 0.22 0.42 0.01 0.45 0.31 0.00

Different 0.02 0.07 0.01 0.02 -0.03 0.05 0.03 Race/Ethnicity 0.61 0.07 0.85 0.66 0.54 0.26 0.43

Dysfunctional 0.15 0.07 0.07 0.04 -0.15 0.11 -0.04 Conflict Resol. 0.00 0.08 0.11 0.36 0.00 0.01 0.31

OK to See 0.04 0.05 0.08 -0.25 -0.17 -0.15 -0.23 Others 0.37 0.19 0.05 <.0001 <.0001 0.00 <.0001 57

Table 4: Correlations Between Relationship Qualities, Continued Who's More Into It Relation- Respondent Partner Alternative Male Partner Different Dysfunction- OK to See ship Length Partners Older >2 Yrs. Race/ al Conflict Others Ethnicity Resol. Partner Cheats -0.03 0.17 -0.06 0.14 0.07 0.02 0.15 0.04 0.41 <.0001 0.17 0.00 0.09 0.61 0.00 0.37

Respondent -0.03 0.00 0.14 0.08 -0.05 0.07 0.07 0.05 Cheats 0.41 0.91 0.00 0.05 0.22 0.07 0.08 0.19

Both Cheat -0.13 0.00 0.13 0.14 0.03 0.01 0.07 0.08 0.00 0.92 0.00 0.00 0.42 0.85 0.11 0.05

Passionate 0.29 0.06 -0.37 -0.47 0.11 0.02 0.04 -0.25 Love <.0001 0.16 <.0001 <.0001 0.01 0.66 0.36 <.0001

Emotional 0.08 -0.30 -0.04 -0.38 0.03 -0.03 -0.15 -0.17 Rewards 0.04 <.0001 0.34 <.0001 0.45 0.54 0.00 <.0001

Self-Disclosure 0.21 0.00 -0.19 -0.23 0.04 0.05 0.11 -0.15 <.0001 0.95 <.0001 <.0001 0.31 0.26 0.01 0.00

Commitment 0.33 -0.09 -0.33 -0.47 0.12 0.03 -0.04 -0.23 <.0001 0.03 <.0001 <.0001 0.00 0.43 0.31 <.0001

Relationship 1 -0.04 -0.15 -0.21 -0.01 -0.07 0.26 -0.06 Length 0.39 0.00 <.0001 0.82 0.09 <.0001 0.12

Respondent -0.041 -0.23 0.12 0.15 0.05 0.17 0.02 More "Into It" 0.39 <.0001 0.00 0.00 0.21 <.0001 0.63

Partner More -0.15 -0.231 0.23 -0.12 -0.04 0.05 0.10 "Into It" 0.00 <.0001 <.0001 0.00 0.35 0.21 0.01

Alternative -0.21 0.12 0.231 0.02 0.03 0.16 0.17 Partners <.0001 0.00 <.0001 0.70 0.41 <.0001 <.0001

Male Partner -0.01 0.15 -0.12 0.021 0.05 0.01 -0.01 Older >2 Yrs. 0.82 0.00 0.00 0.70 0.20 0.87 0.82

Different -0.07 0.05 -0.04 0.03 0.051 0.07 0.00 Race/Ethnicity 0.09 0.21 0.35 0.41 0.20 0.08 0.95

Dysfunctional 0.26 0.17 0.05 0.16 0.01 0.071 -0.02 Conflict Resol. <.0001 <.0001 0.21 <.0001 0.87 0.08 0.55

OK to See -0.06 0.02 0.10 0.17 -0.01 0.00 -0.02 1 Others 0.12 0.63 0.01 <.0001 0.82 0.95 0.55