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GENDERED CONDOM USE:

AN EXPLORATORY SOCIOLOGICAL ANALYSIS

A Thesis

Presented to

The Graduate Faculty of The University of Akron

In Partial Fulfillment

Of the Requirements for the Degree

Master of Arts

Courtney Blue

May, 2015 GENDERED CONDOM USE:

AN EXPLORATORY SOCIOLOGICAL ANALYSIS

Courtney Blue

Thesis

Approved: Accepted:

______Advisor Dean of the College Dr. Robert L. Peralta Dr. Chand K. Midha

______Committee Member Interim Dean of the Graduate School Dr. Adrianne Frech Dr. Rex D. Ramsier

______Committee Member Date Dr. Tiffany Taylor

______Department Chair Dr. Matthew Lee

ii ACKNOWLEDGEMENTS

I would like to acknowledge and thank my advisor, Dr. Robert Peralta, for all his support and guidance throughout this process. I also would like to thank my thesis committee members, Dr. Adrianne Frech and Dr. Tiffany Taylor for their expertise, guidance, and time spent on this project.

iii TABLE OF CONTENTS

Page

LIST OF TABLES...... vi

CHAPTER

I. INTRODUCTION...... 1

Review of the Literature...... 3

Male Condoms...... 4

‘Hooking Up’ in College...... 5

Life Course Perspective...... 6

College Students and Alcohol Use...... 7

Condom Attitudes...... 8

Theoretical Framework...... 9

Gender Power Imbalance Theory...... 10

Gendered Condom Use...... 11

Hypotheses...... 12

II. METHODS...... 14

Data...... 14

Measures: Dependent Variable...... 17

Measures: Independent Variables...... 17

Measures: Control Varaiables...... 18

Drunk in Last 12 Months...... 19

iv CMNI: Sex and Committed Relationships...... 19

Condom Attitudes...... 20

Analytic Strategy...... 21

III. RESULTS...... 23

IV. CONCLUSIONS AND DISCUSSION...... 29

Study Strengths...... 33

Study Limitations...... 34

Future Research...... 35

REFERENCES...... 36

v LIST OF TABLES

Table Page

1 Descriptive Statistics for All Analysis Variables...... 16

2 Logistic Regression Results, without Interactions...... 25

3 Logistic Regression Results, with Interactions...... 28

vi CHAPTER I

INTRODUCTION

Sociological research consistently shows that compared to women, men are more likely to engage in a variety of risk behaviors (Courtenay, McCreary, and Merighi 2002;

Courtenay 2000; 1998). When examining sexual risk behaviors among heterosexuals, men begin to participate in sexual activities earlier in their lives and accumulate more sexual partners throughout their life compared to women (Mosher, Chandra, and Jones

2005). But, research shows that one particular type of sexual risk behavior, unprotected sex, is more likely to occur among women than men (Jones, Mosher, and Daniels 2012;

Reece, Herbenick, Schick, Sanders, Dodge, and Fortenberry 2010). Researchers emphasize the importance of gender socialization and its effect on condom use behaviors since this socialization affects all aspects of social life, including how sexual practices are negotiated (Amaro 1995; Ehrhardt and Wasserheit 1991). This thesis will explore the association between condom use, sex, and gender.

During any sexual activity, the most effective way for heterosexual men and women to protect oneself from contracting an STI, outside of abstinence, is consistent and correct use of male condoms (CDC 2014; Holmes, Levine, and Weaver 2004;

Warner and Stone 2007). Condoms are readily available across the United States and they do not require a prescription to purchase. However, given the accessibility of

1 condoms, research has failed to adequately address why women use condoms infrequently (Jones, Mosher, and Daniels 2012; Reece et al 2010).

Sexually transmitted infections (STIs) continue to be a public health concern, especially in younger adults. Many STIs often do not show symptoms, but when symptoms emerge they then become sexually transmitted diseases (STDs). Every year about half of new STD cases occur in young people ages 15 to 24, even though they are only a quarter of the sexually active population (Centers for Disease Control and

Prevention [CDC] 2012). Within the college setting, sexual risk behavior is prominent among young students and this is partly due to the culture of college itself. Embedded in this particular setting is the ‘hook-up’ culture (Heldman and Wade 2010), in which casual sexual exchanges between non-dating partners replace monogamous relationships (Bogle

2008; Hamilton and Armstrong 2009). The behavior to engage in these exchanges is normative for both men and women, which is supported through high participation

(Garcia, Reiber, Massey, and Merriwether 2012).

The focus of this thesis will be on examining the effects of gender socialization on condom use behaviors. By taking a sociological approach, I examine why women use condoms less frequently than men, which is not adequately explained by current literature. The theoretical framework of the thesis draws from hook-up culture, the life- course perspective, and the gender-power imbalance theory (Amaro 1995; Morokoff

2000). The focus of the study is on college students between the ages of 18 and 25 who are transitioning from adolescence into adulthood. Arnett (2000) refers to this transition as emerging adulthood, which is a distinct period of the life course both theoretically and empirically. In essence, compared to adolescence, emerging adults are in a period of

2 self-exploration (Arnett 2000). This includes sexual exploration in that they experience more independence and autonomy in their ability to make decisions.

The second theoretical framework, gender-power imbalance theory, specifies that women have lower rates of condom use compared to men because women cannot always negotiate safe sex due to socially constructed gender dynamics and this suggests that women are at greater sexual risk (Amaro 1995; Morokoff 2000). These dynamics disempower women while empowering their male counterparts. Research that has looked at gender processes as an influence on condom use behavior has mainly been male and masculinity focused. This thesis will explore the association between being female and identifying with traditional feminine characteristics and condom use.

Review of the Literature

The Center of Disease Control and Prevention estimates nearly 20 million sexually transmitted diseases (STDs) occur every year. Half of these diseases are contracted by young people ages 15-24 (CDC 2014). The threat of immediate and long- term consequences due to not practicing safe sex are pronounced and includes reproductive health problems (e.g., infertility, pregnancy complications) cancer, and risk of HIV infection. The general population is not equally at risk for all STDs or HIV. For example, gay and bisexual men have higher rates of syphilis and about half of all new

HIV infections occur in gay and bisexual men (CDC 2014). In addition, rates of STDs show disparities between white and racial and ethnic minorities with black and Hispanic men and women having higher rates of many STDs compared to their white counterparts

(CDC 2012). Infection also varies by age: specific STDs such as chlamydia and

gonorrhea have the highest rates among women under the age of 24 compared to men or individuals over the age of 24 (CDC 2012).

There are also different health consequences for men and women. In addition to women being more susceptible biologically to contract an STI, women also suffer more long-term health consequences (CDC 2011). Two of the most common STDs reported by women, chlamydia and gonorrhea, are generally asymptomatic for women (CDC

2012). When left untreated women can develop pelvic inflammatory disease (PID), which can result in infertility or if they were to become pregnant, then it can result in an ectopic pregnancy. Other STIs are not as observable for women as they are for men. For example, genital ulcers or sores, which could be caused from herpes or syphilis, can develop inside the vagina making it difficult for women to notice and thus, treat (CDC

2011). Also, the most common STI among women, the human papillomavirus (HPV), is the main cause of cervical cancer. HPV is also common among men, however men typically do not develop any serious health problems associated with it (CDC 2011).

Male Condoms

Among heterosexual men and women, the male condom is one of the original methods of contraception (Reece, Hebernick, Schick et al. 2010). When used correctly and consistently, condoms also help reduce the risk of contracting a sexually transmitted infection (STI) or HIV (CDC 2014). Condoms do this by acting as a barrier for the major exit and entry points of STI pathogens (Warner and Stone 2007). Since condoms act as both a contraceptive and an STI preventive measure, there are several advantages compared to other forms of birth controls. For example, the birth control pill, which is the

most popular oral contraception, helps prevent pregnancy but has no efficacy with preventing STDs (East, Jackson, O’Brien, and Peters 2007).

Condoms also offer consumers practical advantages such as accessibility and can be purchased without a prescription. Condoms can be found in drug stores, grocery stores and gas stations. If condoms are not obtainable to purchase in person, then they can be purchased online. They are a big business and generate high revenues for specific companies. For example, the three major brands of male condoms–Durex, Lifestyle, and

Trojan—reportedly bring in 90 million dollars annually in the United States (D’Ambrosio

2014), while it is estimated that 5 billion condoms are sold annually worldwide

(Neporent 2011). Given the sales and profits of condoms as well as the many preventive programs promoting safe sex and STD awareness, STIs are still highly prevalent among younger adults. Hook-up culture among emerging adults may explain part of this prevalence.

‘Hooking-Up’ in College

Of the total students enrolled in degree granting colleges and universities, over half of them are under the age of 24 (Hussar and Bailey 2014). In addition to making up the majority of those in college, younger students are also at a higher risk of acquiring

STDs (CDC 2012). This risk stems partly from the culture of college, which includes the

‘hook-up’ culture (Heldman and Wade 2010). Researchers have only recently begun to differentiate “a sexual culture that includes hooking up [from] a ‘hook-up culture’”

(Heldman and Wade 2010:323). Within the hook-up culture, an expectation of starting and maintaining a relationship is replaced by casual sexual exchanges between non- dating partners (Bogle 2008; Hamilton and Armstrong 2009). Casual sexual exchanges,

which include any sexual activity, have thus become the primary path into a relationship

(England, Shafer, and Fogarty 2008). Research indicates that a substantial portion of college students participate in hook-up culture with about two-thirds to three-quarters of students reporting hooking up at least once during their collegiate careers (Armstrong,

England, and Fogarty 2009; England, Shafer, and Fogarty 2008). These figures lend support to the notion that a new script has emerged for college students and this script has virtually replaced the “going steady” script of previous generations (Wade and Heldman

2012). Hooking up has thus been seen by college men and women as normative and acceptable (Garcia, Reiber, Massey, and Merriwether 2012).

Life Course Perspective

Situating individuals within the life course perspective reflects their personal biography with the intersections of social and historical factors (Elder 1985). Thus, life course patterns vary across populations and across time and space. Crucial to the life course perspective is also locating individuals trajectories, transitions, and cumulative advantages/disadvantages. It is not unreasonable to situate individuals sexuality within a life course framework (Carpenter and DeLamater 2012). I argue that college students are in a particular phase of a life course transition, in which they have to navigate their sexuality in distinct and new ways.

Using Arnett’s (2000) concept of emerging adulthood, which is the transition from adolescence to adulthood, college students enter a unique period of the life course.

It is theoretically and empirically distinct from other periods. It is the age of identity exploration, instability, and self-focus (Arnett 2005). Arnett (2005) posits that during emerging adulthood, individuals experience identity exploration, instability, and self-

focus, which may explain why this period of the life course sees a rise in the exploration of risk taking behavior, including risky sexual behavior (Halpern and Kaestle Chapter

2014). Instead of settling into committed adult relationships, emerging adults may feel the need to engage in sexual exploration, which may include the accrual of sexual partners (Halpern and Kaestle 2014). They typically have less attachment to adult roles and have more autonomy in making decisions (Arnett 2000). This independence allows emerging adults to explore new cultural and sexual territories without the fear of parental sanctions.

Arnett’s emerging adulthood perspective is not without critique . Some researchers justly point out that Arnett and the emerging adulthood paradigm does not give credence to existing opportunity structures (Silva 2012). This makes Arnett’s emerging adulthood more of a middle and upper class transition, since not everyone is in an advantageous position to explore alternative identities or focus exclusively on themselves. However, for the purpose of this thesis, emerging adulthood is used to understand and emphasize that there is a distinction between adolescence and adulthood

(Arnett 2000). This distinction also includes specific markers that are not typically present in adulthood, even though not everyone will experience emerging adulthood through these markers.

College Students and Alcohol Use

In addition to engaging in risky sexual behavior, college students have an opportunity to engage in other risky behaviors, including a variety of drinking behaviors.

The National Institute of Alcohol Abuse and Alcoholism ([NIAAA], 2013) estimates about 80 percent of college students drink, which indicates that 4 out of 5 college

7 students drink. In the most recent National College Health Assessment (NCHA) survey,

20 percent of students reported that they never use alcohol, while approximately 67 percent of students used alcohol at least once within 30 days (American College Health

Association 2014). Alcohol use is related to a variety of risky behaviors, including having unprotected sex. Among casual or non-steady partners, drinking alcohol can reduce condom use by both men and women (Brown and Vanable 2007; LaBrie,

Earleywine, Schiffman, Pederson and Marriot 2005). According to the NCHA, approximately 20 percent of students who drank alcohol reported that they had an experience in which they had unprotected sexual intercourse within the last 12 months

(American College Health Association 2014).

Often, students regret drinking and their decision to engage in sexual activity as a result (Oswalt, Cameron, and Koob 2002). This regret may not be only a result of drinking but also a result of how much one decided to drink. Research shows that the amount someone drinks affects the rates of condom use. For example, Certain, Harahan,

Saewyc, and Fleming (2009), found that female students who either binge drink or consumed large amounts of alcohol were less likely to report using a condom consistently.

Condom Attitudes

In addition to alcohol use, research has shown that condom-related beliefs and attitudes affect condom usage among college students (Shearer, Hosterman, Gillen, and

Lefkowitz 2005). Compared with women, men of all ages have negative attitudes towards using condoms during sexual activity (Dehne and Riedner 2005; Flood 2003;

Shearer et al. 2005). Literature shows that men report condoms interfere with both sexual

pleasure and intimacy (Crosby, Yarber, Sanders, and Graham 2005; Flood 2003;

Skidmore and Hayter 2000). In addition, both men and women report perceived and actual condom discomfort as a ‘turn-off’ for readiness to use condoms (Crosby,

Milhausen, Yarber, Sanders, and Graham 2008).

Research has also shown an indirect relationship between masculine ideology and condom attitudes. For example, Noar and Morokoff (2002) used the Male Role Norms

Scale (MRNS) to measure masculine ideology, an ideology that supports the traditional male gender role. They found that negative condoms attitudes were related to strong support of masculine ideology (Noar and Morokoff 2002). In addition, negative condom attitudes were related to decreased willingness to use condoms. Although Noar and

Morokoff (2002) focused on young adults, they only focused on men and masculinity.

Compared to men, women report more favorable attitudes towards condom use

(Dehne and Riedner 2005; Flood 2003; Shearer et al. 2005). However, women also have less control over using them.

Theoretical Framework

Entrenched in our society are social and cultural norms that support male dominance and female passivity even in sexual encounters (Amaro 1995; Morokoff

2000). These gender norms are socially constructed, not biologically determined.

Initially, biological criteria determines one’s sex categorization—man and woman, which reflects a binary system (Fenstermaker and West 2002). Categorization is then maintained “by socially necessary displays of identification as a member of one category or another” (2002: 29). These displays of identification are situationally accomplished in any given interaction, in which individuals are held accountable to the normative

conceptions of their gender. The emphasis is on gender as an accomplishment that is created and re-created repeatedly within social interaction. There are consequences when men and women fail to live up to the normative expectations of masculinity and femininity. For example, men who consume larger quantities of alcohol are expected to handle their alcohol in way that meets hegemonic masculinity expectations or risk being labeled a “‘two-beer queer’” (Peralta 2007: 751). The label is applied as a result of failing to accomplish hegemonic masculinity within the interaction.

This example sheds light on how characteristics of men and women are essentialized and appear natural. This naturalness legitimizes what being a man is versus what being a woman is. This effects the social organization of society, including the decision to use a condom or not (Fenstermaker and West 2002).

Gender Power Imbalance Theory

Gender socialization affects all aspects of social life, including how sexual practices are negotiated (Ehrhardt and Wasserheit 1991). Amaro (1995) asserts the power inequality that socializes women to be passive, also makes women sexually passive. Our patriarchal society structures men to have more privilege compared to women (Schwalbe 2005). This privilege results from the control of an uneven distribution of social benefits and these benefits are reflected across various social structures.

These benefits also apply to college campuses. While hooking up has replaced dating among college students and women have been increasingly engaging in the practice of hooking up, research shows that casual sexual exchanges favor men over women due to a gender power imbalance (Armstrong, Hamilton, and England 2010;

Bogle 2008). This power balance includes interpersonal relationships and sexual encounters. Connell (1987:113) notes that “the members of a heterosexual couple are not just different, they are specifically unequal.” This unevenness is also evident not only in men and women’s interaction during sexual encounters, but also after the encounter in which a double standard exists for men and women (Bogle 2008; England, Shafer, and

Fogarty 2008). Women’s sexual agency is policed during encounters while they are also subjected to a harsher judgment after the encounter compared with men. Women are more exposed to being labeled a “slut” while a man has more of an opportunity to be labeled a “player” (Bogle 2008). In this sense, men are ‘doing gender’ since they are adhering to masculinity ideals, while women fail to live up to the normative conceptions of femininity.

In a study on grinding, which refers to a certain sexualized style of dancing,

Ronen (2010) notes that in interactions hetero college men’s pleasure was privileged, while women’s agency was prohibited. Women had to present themselves as sexually desirable for grinding, but risked being seen as ‘whores’ and ‘sluts’ if they were to take part in grinding. The results are indicative of how women and men are constantly being held accountable for ‘doing gender’, which mirror patterns of inequality across an array of institutions and interactions (Peralta 2010).

Gendered Condom Use

As noted above, gender inequality presents itself in a series of interactions including sexual negotiations. Overall, men tend to engage in more risky behaviors compared to women. However, women and men are not engaging in the same type of risk behavior, especially risk behavior pertaining to sex (Amaro 1995). For example, condom

use calls for two different behaviors between men and women. For men the behavior is deciding to wear a condom, while for women the behavior is persuading men to wear a condom. This relies on men’s cooperation, which by default “place women at a disadvantage of determining their exposure to risky sexual behavior” (1995: 437). In order for a man to be a man in the context of traditional masculine hegemony, he must exert control over another and avoid being controlled (Schwalbe 2005). A man must express his manhood which is performed and achieved in a given interaction. The manhood acts performed often reflect conventional norms such as qualities of strength, courage, and sexual potency. It is in these interactions that inequality is reproduced, since men attempt to achieve dominance over the subordinate gender group (Schrock and

Schwalbe 2009). Following this, a man would enforce condom use only when he desired it, while refusing to wear one if he perceived it as a controlling force by a woman. In addition, men’s negative attitudes towards using condoms place the burden on women to insist on their usage (Ehrhardt, Exner, Hoffman, Silberman, Yingling, Adams-Skinner, and Smart-Smith 2002).

Hypotheses

Three main hypotheses will be tested in my analyses. First (H1a), I hypothesize that a majority of men and women will not have used a condom during their most recent sexual intercourse, however, men will be more likely to have used a condom compared to women (H1b). Prior research shows that condom use is inconsistent and low among college men and women, but women have lower condom use rates since condom usage appear to be ultimately handled by men. Next (H2), I hypothesize that female students

12 with a feminine orientation will be less likely to have used a condom during their most recent sexual encounter compared to women without a feminine orientation Due to gender socialization and in line with the ‘doing gender’ framework, I expect women who prescribe to traditional ideals of femininity to experience a power imbalance in sexual negotiations. Lastly (H3), I hypothesize that women with masculine orientations will either increase or decrease the likelihood of condom use compared to women with feminine orientations. This hypothesis is open-ended because researchers have not explored this question. Moreover, women are expected to be less likely to use a condom, but given the masculinity measure, it is possible that women who score higher on the masculinity scale will be more assertive in negotiating condom use with their sexual partner.

13 CHAPTER II

METHODS

Data

The data I use in my analyses are from the “Health Behavior Survey”. It is important to mention that the data used is part of a larger study whose purpose was to collect epidemiological data on health risk behavior and to assess if normative gender roles were associated with health risk. Also, full IRB approval was granted for this study.

Recruitment for the present study was conducted through advertising to

Introduction to Sociology students at a mid-sized Midwestern public university during the fall semester of 2013 and spring semester of 2014. All Introduction to Sociology courses were used to advertise the study except for those courses that were distance learning courses. These particular courses were excluded because a large number of high school students were enrolled in these courses. Students were offered extra credit for taking part in the survey. Eligibility to take part in the survey was described in the informed consent notice at the beginning of the survey – those under 18 years of age were not eligible to participate in the study. Only college students attending the university in which the study was taking place were eligible to take part.

An online survey was used to get an electronic copy of the consent form where they also completed the survey. The name of the service provider was Survey Gizmo.

To maintain confidentiality, students were directed to a secure access portal (https://) and

14 only the primary investigator and members of the research team had any access to the data. No personal identifying information was collected (e.g., home/email address; computer Internet Protocol addresses) except for standard demographic information. The survey included questions to assess health behavior (HIV risk), mental health status (i.e.,

CES-D), violence experience (CTS), gender identity (BEM) as well as sociodemographic characteristics. The online survey took approximately 50 minutes to complete.

A total of 1,026 students completed the survey yielding a rough response rate of

53 percent, however after preliminary examination of the data, several adjustments had to be made. Students under the age of 18 took the survey and had to be removed from analysis to stay in accordance with the IRB guidelines. In addition, students that were over the age of 25 were constrained from the analysis since the study is concerned with traditional college students whom are also emerging adults. It is important to note that the age markers of emerging adulthood are not fixed and that they are culturally situated

(Arnett 2000; 2005). However, I followed the typical age markers for emerging adults which are 18 to 25 year olds. Dropping those participants that did not meet that criterion resulted in a sample size of 859. Further participants were dropped that answered a fictional drug question on the survey to help ensure that analyses included those who took the survey seriously. In addition, three respondents did not identify whether they were male or female and were dropped from analyses. Since the focus of this thesis is on sexually active heterosexual men and women, respondents were dropped if they did not explicitly identify as heterosexual or if they answered that they did not engage in sexual activity within the last twelve months. Thus, the trimmed sample is comprised of 623

15 respondents. Table 1 contains a detailed list of the descriptive statistics for the variables used for this analysis.

Table 1: Descriptive Statistics for All Analysis Variables

Variable All Males Females Mean(SD) Mean(SD) Mean(SD) Range Dependent Variable Condom Used (1=Yes) .50 (.50) .54(.50) .46(.50) 0-1 Independent Variables

Masculinity 15.99(4.32) 16.56 (4.60) 15.62(4.03) 0-28 (Scale: least to most)

Femininity 17.45(4.72) 15.87(4.64) 18.56(4.45) 0-27

Control Variables Sex (1=Female) .58(.49) ------0-1 Age 20(1.78) 20(1.95) 20(1.64) 18-25 Education Father’s Education (0 = Completed college or more, 1 = Some College or less) .88(.33) .88(.32) .88(.33) 0-1

Mother’s Education .87(.34) .88(.33) .86(.35) 0-1 Live on Campus (1=Yes) .39(.49) .39(.49) .40(.49) 0-1 Drunk within last 12 months (0=0 occations, 1=1-2, 2=3- 2.28 (1.57) 2.52(1.58) 2.13(1.54) 0-4 5, 3=6-9, 4=10+) CMNI: I would only have sex if I were in a committed .48(.50) .30(.46) .61(.49) 0-1 relationship (0=D/SD 1=A/SA,) Condom Attitude: I don’t use condoms because .32(.47) .38(.49) .29(45) 0-1 sex is better without them (0=D/SD, 1=A/SA)

16 Measures: Dependent Variable

Condom use is measured by whether a condom was used during the respondent’s most recent sexual intercourse. The survey had two sections that asked questions pertaining to HIV risk, but one section was for males respondents only and the other was for females only. For men, the question was the following: Did you use a condom the last time you had vaginal intercourse with a female? For women, the question was the following: Was a condom used the last time you had vaginal intercourse with a male?

Respondents could only respond yes or no. Since respondents were excluded if they did not identify as heterosexual and if they were not sexually active within the last twelve months, I combined both questions and recoded them into one variable.

About 50 percent of respondents reported that they did not use a condom during their most recent vaginal intercourse. Women were more likely to not have reported using a condom compared to men.

Measures: Independent Variables

The Personal Attributes Questionnaire (PAQ) is a 24 item self-reporting instrument developed by Spence, Helmreich, and Stapp (1974), which asked respondents to indicate the extent to which they could be characterized in terms of various adjectives.

It has two scales, instrumentality and expressivity, that measure the degree to which a person can be classified according to masculinity or femininity. There are eight items that make up each the instrumentality and expressivity scale. There are also eight items that comprise an additional scale, which is the androgyny scale. It is more important to consider the scale items in terms of a whole cluster, rather than a single item.

The descriptives show that on average more respondents scored higher on the expressive or feminine scale than on the instrumental or masculine scale. However, as expected, women scored slightly higher on the expressive scale compared to men. The instrumental scale scores show an even smaller difference between men and women, with men (16.56) reporting a slightly higher score on the scale than women (15.62).

Measures: Control Variables

The control variables used in analyses include three demographic variables. Sex was coded so that males = 0 and females = 1. Three respondents did not indicate whether they were female or male and they were excluded from analysis.

Respondents that were under the age of 18 and over the age of 25 were excluded from analyses. The majority of the sample were either 18 (30 percent) or 19 (28 percent) years old, which reflects the introduction classes used in the sample.

The survey asked respondents about their mother’s and father’s educational attainment that ranged from grade school or less to graduate or professional degree. I recoded each variable into a dichotomous variable where the reference category educational attainment categories, which are the following: some high school or grade school or less, completed high school, some college, completed college, and graduate or professional school. Both father’s education and mother’s education, on average, was between completed high school and some college, but the average educational attainment of respondents’ mothers was slightly higher for both males and females.

The only question on the survey that asked about where students resided was whether they lived on campus or not. Although not specified in the questionnaire, on- campus housing refers to those that actually live on the college campus space. This

18 includes residence halls as well as sorority and/or fraternity houses located on college property. On average, students were more likely to not have lived on campus.

Drunk in last 12 months

An alcohol variable was included in the analysis since alcohol use is shown to affect condom use rates among college students (American College Health Association

2014; Brown and Vanable 2007; Certain et al. 2009; LaBrie et al.2005). The NIAAA

(2013) estimates college student drinking at about 80 percent. The variable asked respondents how many times students were drunk within the last twelve months. The specific time frame of the variable was used to capture drinking occurrences when students had extended periods of break from school, such as Christmas break. On average, students reported that they had been drunk on nearly three to five occasions in the last twelve months.

CMNI: Sex and Committed Relationships

The Conformity to Masculine Norms Inventory (CMNI) assesses the degree to which men’s affective, behavioral, and cognitive functioning adheres to hegemonic masculinity (Mahalik, Locke, Ludlow, Deimer, Scott, Gottfried, and Freitas 2003).

While the survey collected a 46 item short-form CMNI (Parent and Moradi 2009), only one item is used in the analysis. The item asked to which degree respondents agreed with the following statement using a 4-point Likert-type scale: I would only have sex in a committed relationship. Responses were dichotomously coded from 0 (disagree/ strongly disagree) to 1 (agree/strongly agree) to access the level of respondents conformity to the question.

19 This variable is included in the analysis for two reasons. One, there is not a sound variable that measures relationship status in the study. Although this variable does not control for relationship status, it does suggest the importance of a relationship preceding sexual intercourse. This in turn leads to the second reason behind its inclusion, which involves the entire notion behind the hook up culture. Monogamous relationships are replaced by casual sex partners and this exchange is acceptable within the context of college (Bogle 2008; Hamilton and Armstrong 2009). Thus, it is reasonable to assume that those who do not adhere to the statement are more likely to find themselves engaging in activity outside of the relational confines of monogamy.

Condom Attitudes

Condom attitudes can be predictive of condom use among college students

(Shearer et al 2005), while literature shows that men report condoms interfere with both sexual pleasure and intimacy (Crosby et al. 2005; Flood 2003; Skidmore and Hayter

2000). Also, when asked about condom ‘turn-offs’, both men and women report condom discomfort as a ‘turn-off’ for readiness to use condoms (Crosby et al. 2008). A condom attitude variable was included that asked respondents if they strongly disagreed (=0), disagreed (=1), agreed (=2), or strongly agreed (=3) with the following statement: I don’t use condoms because sex is better without them. This was recoded into a dichotomous variable in which those that disagreed or strongly disagreed was one category, while those that agreed or strongly agreed was used as the reference category. I believe that this statement represents both issues of sexual pleasure and discomfort, however, there is not a condom attitude variable in the survey that addresses the issue of intimacy and condom use. For the whole sample, respondents were more likely to disagree or strongly

disagree with that statement (x = .32), but males were more likely to agree or strongly agree with that statement compared to women.

Analytic Strategy

The outcome variable of interest, condom use, is a dichotomous variable, thus the method of analysis for the current study used a series of logistic regression models to examine the relationship between the outcome variable and its predictors. Logistic regression is preferred over ordinary least squares regression (OLS) since binary outcomes produce a heteroscedastic distribution of residuals terms, which also violates normality (Kline 2005).

I first computed a series of preliminary regression models for the variables of interest separately for males and females. The results showed changing patterns of significance for the outcome and predictor variables across both groups. In order to make sure my models were correctly specified, interaction terms for both predictor variables were created. Since both the PAQ femininity and masculinity scales are continuous variables, their means were centered for interpretative purposes. I then took the centered means of both of the scales and created an interaction with the dichotomous sex variable, in which females represent the reference category.

Table 2 represents the models without the interaction for the whole sample, but still controlling for sex. The purpose of these models was to see what the patterns were for each of the predictor variables, as well as a model testing both predictors, without the interaction terms. Table 3 represents the models with the interactions terms included. As with table 2, the first two models test for the interactions with each predictor variable

(Female X PAQ masculinity; Female X PAQ femininity) with all of the control variables.

The third model represents both of the interaction terms in addition to all of the control variables.

The odd ratios (OR) are reported for each variable, which represents the odds of observations being in a given category of a variable (Treiman 2009). In other words, odds ratios refer to the likelihood of being in one category or another. The models show the standard errors and confidence intervals for each variable. The ORs that have an asterisk next to the value represents the significance level of that variable, which include p-values <05, .01, and .001. The ORs that have ┼ next to it represents a p-value < .10.

22 CHAPTER III

RESULTS

Table 1 displays the descriptive statistics of the current study sample.

Approximately 58 percent of the sample is female, while approximately 57 percent of the sample was 18 or 19 years old. About 50 percent of the sample used a condom during their most recent sexual intercourse, with 54 percent of men using a condom compared with 46 percent of women. Educational attainment for both respondents’ mothers and fathers were relatively low with only 13 percent of respondents’ mothers completing at least college and 12 percent of fathers completing at least college. About 40 percent of women live on campus compared to 39 percent of men. About 20 percent of the sample said that they were never drunk in the last 12 months, but approximately 36 percent said they were drunk at least 10 times in the same period. More women agreed that they would only have sex in a committed relationship, while 70 percent of men disagreed that they would only have sex in a committed relationship. The condom attitude variable included in analyses asked to which degree respondents agreed or disagreed with whether sex was better without condoms. About 38 percent of men who agreed that sex better without a condom compared with 29 percent of women.

Table 2 shows the three logistic regression models without interaction terms. The first model show logistic regressions results of condom use with control variables and femininity (or expressivity) included in the model. Model 2 contains the masculinity (or

instrumentality) variable only in addition to my control variables. The third model includes both predictor scales and control variables.

Consistently across all of the models in Table 2 is that females were statistically less likely to use a condom during their most recent sexual encounter compared to men.

When both predictor scales are included in model three, females have an odds ratio of .45

(p <.05). A significant odds ratio that has value below 1 indicates that being female reduces the odds of having used a condom. To get the percent change in the odds ratio, you subtract 1 from the odds ratio and multiply that number by 100. For example the females odds ratio is .45 and when you subtract 1 and multiple that number by 100 you get a negative .55 (.45-1*100). In other words, being female has an associated 55 percent decrease in the odds of having used a condom.

In addition to sex remaining statistically significant across Table 2, respondents’ fathers level of education, living on campus, and having a negative attitude towards condoms significantly affected whether a condom was used during respondents most recent sexual encounter.

Parent’s education was used as a proxy for social class, but the data show that only father’s education significantly predicts condom use. Furthermore, in all of the models in Table 2 respondents whose father completed at least some college had greater odds of a condom being used then fathers with at least a college degree. For example, in

Model 3 father’s educational attainment has an odds ratio of 2.31 (p<.05). Taking the percent change of that odds ratio (2.31-1*100) tells us that having a father whose educational attainment is some college or less has an associated 131 percent increase in

C.I.

.11

2.99

4.83

.75

1.08

1.05

2.37

1.23

1.50

1.14

.04

.27

.97

.95

.84

.90

.41

.85

95%

1.04

1.10

.03

.02

.37

.08

.48

.26

.87

.07

.12

Model3

.99

.79

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.241

1.30

1.03

1.42

1.05

.45**

.06***

1.76**

2.31**

.11

3.08

5.21

.73

1.08

2.15

1.20

1.57

1.15

.04

.28

.97

.80

.89

.44

.86

95% C.I. 95%

1.08

1.21

.03

.02

.33

.08

.49

.27

.93

.07

.11

Model2

.83

.99

.238

1.19

1.03

1.31

1.03

.07***

1.83**

2.51**

.45***

4.6

.13

1.5

.76

2.21

1.22

2.57

1.05

1.13

.04

.43

.29

.83

.91

.93

.95

1.10

.85

95% C.I. 95%

.02

.34

.08

.40

.26

.82

.07

.12

.02

Model1

.80

.98

.99

.219

1.28

1.35

1.05

2.25*

.47**

1.54

.07***

y have sex if sex were have I y

Variables

condomsbecause sex

without them (1=A/SA) them without

Female)

tter

committed relationship committed

Table 2: Logistic Regression of Condom Use on Sexual Intercourse: Without of Interactions Sexual on Regression Condom Use Intercourse: TableLogistic 2:

Femininity Femininity

Masculinity Masculinity

p<.10, *p < .05, .05, < ***p<.001 *p p<.10, **p<.01,

Father’s Education (1=Some Father’s

Mother's Education Mother's

College>)

is be is

I don't use don't I

(1=A/SA)

ina

I would onl would I

Pseudo

Intercept

Questionnaire:

Personal Attribute

CondomAttitude:

CMNI:

Drunk in monthsthe Drunk last 12

Live on Campus on (1=Yes) Live

Education:

Age

Sex ( Sex

25 odds of having used a condom. In other words, the less educational attainment the respondents’ father had, the more likely they were to use a condom.

In Table 3 the interaction terms (female X femininity, female X masculinity) are introduced. Model 1 shows us that when the femininity interaction term is introduced it gains slight significance. The odds ratio is 1.10 (p<.10) and indicates that for every one- unit increase for females on the feminine (or expressive) scale, condom use increases by

1.10 for the average woman. The percent change for that interaction is 10 percent, which indicates that for females scoring higher on the femininity scale there is an associated 10 percent increase in the odds of having used a condom during the average woman’s most recent sexual intercourse.

Model 2 in Table 3 includes the masculinity scale interaction term. It has an odds ratio of 1.11 which is statistically significant (p<.05). The percent change in the interaction term is 11 percent, which signifies that for females who score higher on the masculinity scale there is an associated 11 percent increase in the odds of having used a condom for the average female.

When controlling for both interaction terms in Model 3, the masculinity interaction term loses its statistical significance while the femininity interaction term remains marginally significant. The odds ratio of the femininity interaction term is 1.10

(p<.10). Again, this suggests that for every one-unit increase for females on the feminine scale, condom use increases by 1.10 for the average woman or for females who score higher on the femininity scale there is an associated 10 percent increase in the odds of having used a condom.

26 As in Table 2, having a father whose educational attainment is some college or less and living on campus increases the odds of having used a condom compared to having a father with college degree or more and not living on campus. Also in Table 3, being female and having a negative attitude towards condoms decreases the odds of a condom being used compared to being male and having a more positive attitude towards condom usage. Important to note is even with the interaction term included in the models in Table 3, the odds of females not using a condom during their most recent sexual encounter has similar odds when the interaction terms are not included.

In both tables the most robust predictor of a condom not being used during respondents’ most recent sexual intercourse is having a negative attitude towards condoms. In Model 3 of Table 2, the odds ratio of the condom attitude variable is .06 and is highly statistically significant (p<.001). The percent change indicates that the odds of having a negative attitude towards condoms decrease the odds of a condom being used by

94 percent. In other words, agreeing with the statement ‘I don’t use condoms because sex is better without them’ accurately reflects respondents’ likelihood of having last used a condom.

Although the results are not shown in Table 3, both of the PAQ scales’ main effects were not statistically significant and were not included in the model. In addition, the scales did not significantly affect men’s odds of having used a condom, which are also not shown in the table. Furthermore, the drinking variable, which measured how many occasions respondents were drunk within the last year, had positive but non- significant odd ratios on condom use.

C.I.

.10

3.22

5.19

.74

1.22

2.44

1.25

1.44

1.15

.03

.26

.97

.98

.86

.91

.38

.85

95% 95%

1.10

1.16

.06

.02

.39

.09

.52

.25

.94

.08

.12

Model 3 Model

.74

.99

.253

1.21

1.09

1.45

1.09

1.10+

.44**

.06***

1.88**

2.45**

1.24

.11

3.17

5.58

.73

2.25

1.21

1.57

1.15

.04

.27

.83

.89

.44

.86

95% C.I. 95%

1.00

1.11

1.27

.06

.02

.35

.08

.50

.27

1.0

.07

.11

Model 2 2 Model

.83

.99

.245

1.16

1.37

1.03

1.11**

.06***

1.88**

2.67**

.45***

.12

1.22

4.62

.75

2.22

1.24

2.69

1.44

1.14

.04

.28

.83

.91

.96

.40

.86

95% C.I. 95%

1.00

1.09

.05

.02

.34

.08

.42

.25

.83

.07

.11

Model 1 Model

.77

.99

.226

1.36

1.06

1.23

Condom Use on Sexual Intercourse: With Interactions Sexual on CondomUse Intercourse:

.46**

1.10

1.61+

.07***

2.25**

of of

sex

A/SA)

Variables

without them (1= them without

*p < .05, .05, < ***p<.001 *p **p<.01,

Female)

able 3: Regression able3: Logistic

ld only have sex if ldsex were only have in I

A/SA)

better

committed relationship committed

p<.10, p<.10,

Female X Masculinity X Female

Female X Femininity X Femininity Female

Father’s Education (1=Some Father’s

Mother's Education Mother's

College>)

s s

Pseudo

Intercept

PersonalQuestionnaire: Attribute

Interaction Effects InteractionEffects

I don't use don't condoms because I

(1=

a a

I wou I

+ +

CondomAttitude:

CMNI:

Drunk in monthsthe Drunk last 12

Live on Campus on (1=Yes) Live

Education:

Age Age Sex ( Sex

28 CHAPTER IV

CONCLUSIONS AND DISCUSSION

I find mixed support for my hypotheses. Hypothesis 1a states that a majority of men and women will not have used a condom, while Hypothesis 1b states that women will be less likely to use condoms compared to men. Hypothesis 1a was not supported in the data since half of respondents used a condom, while Hypothesis 1b is supported in all models. Hypothesis 2 states that women with a more feminine orientation, or those women that score higher on the feminine scale, will be less likely to use condoms than those who score lower on the scale. I only found support for Hypothesis 2 at a significance level of p<.05 when the interaction term, female X femininity, was regressed on condom use without controlling for the other interaction term. Hypothesis 3 was an open ended hypothesis. It states that women with a more masculine orientation, or those who score higher on the masculine scale, will have either an increase or decrease in likelihood of a condom being used. When regressing only the female X masculinity interaction term on condom use, there is some statistical significance. Furthermore, results suggest that those who score higher on the masculinity scale have greater odds of having used a condom.

The descriptive statistics show that about half of all respondents used a condom during their most recent sexual encounter, while the other half did not use a condom.

This fails to support the first part of my first hypothesis since results were split in the

29 middle, however the fact that only half of respondents used a condom does cause concern from a public health perspective.

In regards to the second part of my first hypothesis, women were less likely to use a condom compared to men. About 46 percent of women did not use a condom compared to 54 percent of men. Across all logistic regression models in Tables 2 and 3, women were statistically less likely to use a condom compared to men. In fact, the percent change in the odds from all of the models range from a 53 percent to a 56 percent decrease in the odds of having used a condom for women. This supports prior research showing women having lower rates of condom usage (Jones, Mosher, and Daniels 2012;

Reece, Herbenick, Schick et al 2010). But, prior research has failed to identify why heterosexual women have lower condom use rates.

In order to address why women use condoms less often than men, I used Spence,

Helmreich, & Stapp’s (1974) 24 item self-reporting Personal Attributes Questionnaire

(PAQ) to explore how traditional masculine and feminine gender traits might affect women’s condom use rates. As to my knowledge, I am the first to use the PAQ in testing for the relationship between women, normative gender traits, and condom use. Noar and

Morokoff (2002) used the Male Role Norms Scale (MRNS) to measure masculine ideology and tested how that ideology affected condom attitudes; however, they specifically focused on young adult men.

Results from my data analysis were contradictory to what I expected in my second hypothesis. First, in the models in which interaction terms were included women that scored higher on the femininity scale had slightly greater odds of using a condom. These odds were also significant, but there was not any statistical significance in models that

30 did not include the interaction terms. But, when interaction term for masculinity (female

X masculinity) was controlled for in the third model in Table 3, the statistical significance was only marginal (p<.10).

While the data did not support my second hypothesis, I am hesitant to claim that the hypothesis and the theory behind the hypothesis should be fully rejected. I am tentative to dismiss my hypothesis and theory because of the significance of women having lower odds of not using a condom across all of the models. Women are still at a disadvantage in negotiating condom use, since at Amaro (1995) notes, there are two different processes happening: men have to wear the condom, while women have to convince men to wear a condom. In addition to men having control over wearing a condom or not, it is likely that they are expected to carry them. Traditional expectations of femininity and womanhood may lead women to be stigmatized if and when women purchase and/or carry condoms.

Women who purchase and/or carry condoms may be signifying to men that they have more control or more agency over their sexuality. This can result in negative consequences since research shows that women’s sexual agency is policed more compared to men’s and that a double standard does exist, especially in hooking up (Ronin

2010; Bogle 2008; England, Shafer, & Fogarty 2008).

Another possible contributing factor to women’s low odds of using a condom is because of other forms of birth control that young women may be practicing. In particular, the birth control pill is the most popular oral contraceptive and is specifically controlled by women. There was no variable in the dataset in which I could control for other forms of birth control, but the pill aides in preventing pregnancy—not in preventing

31 STDs. Perhaps, then, part of the low rates of condom use is due to women (and men) focusing on preventing pregnancy, and not practicing safe and responsible sex.

In addition to the finding that women have lower odds of having used a condom compared to men, condom attitudes was another important finding. I found that having a negative attitude towards condoms greatly reduces the odds of having used a condom.

This finding supports past research of condom-related beliefs affecting condom usage among college students (Crosby et al 2005; Shearer, Hosterman, Gillen, and Lefkowitz

2005; Flood 2003; Skidmore and Hayter 2000). Some men report that condoms interfere with sexual pleasure while both men and women report perceived and actual discomfort as a ‘turn off’ for readiness to use condoms (Crosby et al. 2008). Because the statement asked whether respondents agreed or disagreed with the statement ‘I don’t use condoms because sex is better without them’, this supports research that found attitudes about sexual pleasure and discomfort affect condom use. About 38 percent of men agreed with this statement compared to 29 percent of women. This supports past research that finds women compared to men have more favorable to attitudes towards condoms (Dehne and

Riedner 2005; Flood 2003; Shearer et al. 2005)

Although alcohol use is shown to affect condom use rates among college students

(American College Health Association 2014; Brown and Vanable 2007; Certain et al.

2009; LaBrie et al.2005), but there were no statistically significant findings with the particular alcohol use variable I used. Perhaps this is due to the nature of the variable itself since it asks students to recall the number of occasions they were drunk within the last 12 months. Issues of respondents’ estimation, both under or over, and recall could have affected how students answered the question.

32 The results of the present thesis indicates that females were less likely to use condoms compared to their male counterparts. The PAQ femininity scale had the opposite effect that I hypothesized, while the PAQ masculinity effect was an open ended hypothesis and only statistically significant when not controlling for the femininity scale. Scoring higher on both scales increased the likelihood of having last used a condom. Instead of dismissing the hypotheses, it may just be that there are other more important contributing factors to predicting condom use. For example, condom attitudes and ideologies may be the most important predictor for men and women. If men are more likely to have negative condom attitudes, which decreases the likelihood of condom use, then that surely places more of the burden of women to insist on their usage.

Study Strengths

Much of the literature on condom use among heterosexual men and women is considered with only answering how often condoms are used, who are the one’s using condoms, and how does that vary by certain demographic factors (Jones, Mosher, and

Daniels 2012; Reece et al 2010). Research that has tried to address why women report lower rates of condom use compared to men only speculate as to why this is. This study offers a sociological perspective on condom use with an emphasis on how gender processes are associated with condom use. As to my knowledge, this is the first time that the PAQ has been used in studying how normative femininity and masculinity ideals affect condom use. Although results were contradictory to the second hypothesis, results suggest that there is some level of moderation between gender via PAQ and sex.

Study Limitations

As with all research, this research is not without limitations. First, the sample itself is a small convenience sample, which means that these results cannot be generalizable to larger populations without caution. Second, the personal attribute questionnaire is essentially measuring sex-type personality traits and may not represent the complexity of whether one has more of masculine or feminine orientation. Moreover, most respondents fall in the middle of the masculinity and femininity scales. Perhaps other quantitative measures of gender may be better suited for examining how gender affects health outcomes. Third, there was not a variable in the dataset that explicitly looked at relationship status. A variable asked whether students were single, divorced, separated, widowed, or engaged, but considering respondents’ average age this variable likely did not accurately capture their relationship status. Fourth, as noted previously a birth control variable would have been useful to control for, but since the study mainly focused on factors associated with condom use, the variable is not the main interest of study. Fifth, the main outcome of variable is asking about one specific condom use behavior. In other words, results do not tell us about trends of condom use, only if a condom was used during respondents’ most recent sexual intercourse. Finally, this study is interested in male condom usage among heterosexual men and women. This study acknowledges the heteronormative imagery that Ingram (1994) describes in social science research, but given the sample’s composition I found it best to specifically focus on men and women that identified as heterosexual given the small numbers of those that did not identify as heterosexual. Despite these limitations, this study was exploratory and has certainly raised more questions than it has answered.

Future Research

Future studies should continue to explore the relationship between sex, gender, and condom use among those between the ages of 18 and 25. It is important for future studies to situate this relationship within a life course perspective. As students make the transition from high school to college, they have to navigate their sexuality in new and distinct ways. For example, emerging adults entering college today are exposed to a new script that has virtually replaced the “going steady” script of previous generations and this exposure is compounded with an increase in autonomy and self-exploration (Wade and Heldman 2012; Arnett 2000; 2005). This is also indicates the importance of measuring various relational behaviors and attitudes, since casual sexual exchanges are the primary pathways into a relationship (England, Shafer and Fogarty 2008).

Research shows that condom use varies by social class and race and ethnicity.

Thus, future studies should include more variables that encapsulates respondents’ social class entirely and racial and ethnic variables beyond the black and white binary. This would allow more of an opportunity to see how condom use varies by women.

Furthermore, it is ideal for future studies to have an equal number of respondents in each age category or at least used weighted samples.

Subsequent studies should continue to include various condom attitude measures, since attitudes was a significant predictor of condom use in this study. Also, researchers may want to look at rates of condom use within a specified time period instead of one fixed instance of condom use. This will allow researchers to identify and predict who is more likely to use condoms, which may result in certain policy implications.

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