The Relationship Between Conformity to Masculine Norms and Men s Health Behaviors: Testing a Multiple Mediator Model

Transcription

1 RONALD F. LEVANT 1, ED.D., and DAVID J. WIMER 2, PH.D. The Relationship Between Conformity to Masculine Norms and Men s Health Behaviors: Testing a Multiple Mediator Model Relationships between men s scores on subscales of the Conformity to Masculine Norms Inventory-46 (CMNI-46) and the Health Behavior Inventory-20 (HBI-20) are complex. Some subscales appear to act as risk factors, as predicted by the Gender Role Strain Paradigm (GRSP), and others as protective buffers, as predicted by positive masculinity and social norms theories. We compared the relative strengths of these two theories in explaining the buffering effects by assessing the roles of two theorized positive aspects of the traditional masculine role (general self-efficacy and emotional stability) and a key construct of social norms theory (perceptions of men s normative health behaviors) in mediating the relationships between CMNI-46 and HBI-20. We evaluated a multiple mediator model of these relationships with 585 men who responded to an online survey. Emotional stability was not a mediator, but general self-efficacy and perceptions of normative health behaviors together partially mediated the relationship between CMNI-46 and HBI-20, transmitting a protective buffering effect. However, an examination of the individual mediating effects indicated that perceptions of normative health behaviors better accounted for the buffering effect. The results are discussed in terms of future research, implications for health care practitioners, and limitations. Keywords: men s health behaviors, conformity to masculine norms, positive masculinity, social norms, multiple mediator model Recent research estimates that half of all morbidity and mortality may be attributable to behaviors that put one s health at risk (Mokdad, Marks, Stroup, & Gerberding, 2004). Gender is the strongest socio-demographic predictor of health behaviors, with men engaging in 1 The University of Akron. 2 The Pennsylvania State University. Correspondence concerning this article should be addressed to Ronald F. Levant, Department of Psychology, The University of Akron, Akron, OH , USA. levant@uakron.edu INTERNATIONAL JOURNAL OF MEN S HEALTH, VOL. 13, NO. 1, SPRING 2014, by the Men s Studies Press, LLC. All rights reserved. jmh /$15.00 DOI: /jmh ISSN/ eissn/

2 CONFORMITY TO MASCULINE NORMS AND MEN S HEALTH BEHAVIORS more risky and fewer health-promoting behaviors than women (Courtenay, 2000a, 2000b). Men compare unfavorably with women on such health practices as spending time with their physicians (Kandrack, Grant & Segall, 1991), eating a nutritional diet (Garfield, Isacco, & Rogers, 2008), having proper sleep habits (Garfield et al., 2008), exercising (Garfield et al., 2008), managing weight (Galuska, Serdula, Pamuk, Siegal, & Byers, 1996), engaging in preventive health behaviors (Kandrack et al., 1991), limiting alcohol and tobacco consumption (Garfield et al., 2008), and foregoing violent behavior (Centers for Disease Control, 2004), risky behaviors such as unsafe driving and daredevil acts (Centers for Disease Control, 2004), and risky sexual practices (Levant & Brooks, eds., 1997). The poor health practices of American men as compared to American women appear to be a major contributor to their lower life expectancy of 5.2 years (Courtenay, 2000b; Minino, Heron, Murphy, & Kocharek, 2007), especially since biological factors are relatively weak predictors of gender differences in morbidity and mortality (Courtenay, 2000a). Research on the variables that influence men s health behaviors is thus of considerable importance (Addis et al., 2007; Baker, 2001; Bonhomme, 2007). The Gender Role Strain Paradigm (GRSP), the perspective used in the present study, has been described as one of the most influential theoretical paradigms for investigating aspects of men s health (Cochran, 2010; Wong, Steinfeldt, Speight, & Hickman, 2010). It is a social constructionist perspective developed within the tradition of quantitative empirical psychology (Levant, 2011; Pleck, 1995), sharing fundamental views of the origin and maintenance of gender roles with other social constructionist perspectives in psychology (Edley & Wetherell, 1995) and sociology (Connell & Messerschmidt, 2005), such as the perspective that gender roles arise from and serve to maintain the power differences between men and women. However, rather than using such methods as the analysis of discourse, the GRSP uses hypothetico-deductive reasoning and quantitative investigation. The GRSP posits that, in the U.S. and Western Europe, traditional masculinity ideology influences how parents, teachers, and peers socialize children and thus how children and adults think, feel, and behave in regard to gender-salient matters (Levant, Wimer, & Williams, 2011). Specifically, through social interactions resulting in reinforcement, punishment, and observational learning, traditional masculinity ideology informs, encourages, and constrains boys (and men) to endorse and conform to the prevailing male role norms by adopting certain socially-sanctioned behaviors and avoiding certain proscribed behaviors (Levant, 2011). The GRSP also posits that gender roles are contradictory and inconsistent, that the proportion of persons who violate gender roles is high, and that both violation of and adherence/conformity to gender roles leads to gender role strain. In the Gender Role Strain Paradigm, traditional masculinity ideology is thought to foster men s dominance over women (Levant, 2011), and thus of hegemonic masculinity (Connell & Messerschmidt, 2005). Hence, behavior that results from adherence to traditional masculine norms, such as toughness, self-reliance, and risk-taking, serves to assert male power, privilege, and status. In regard to health behaviors, male status can thus be asserted by being tough, self-reliant, and taking risks, which usually results in risky health behaviors. Accordingly, a frequent contributor to the psychological literature on men s health theorized that health behaviors are used in daily interactions in the social structuring of gender and power, and that the social practices that undermine men s health are often signifiers of masculinity and instruments that men use in negotiation of social power and status (Courtenay, 2000b, p. 1385). Hence, in the GRSP, adherence to traditional masculine norms has 23

3 LEVANT & WIMER been viewed as a risk factor for men s health behaviors because it is thought to motivate risky health practices (Levant et al., 2011). As detailed below, research on men s health using the Gender Role Strain Paradigm has studied the links between health-related behaviors and four conceptually related masculinity constructs : (1) the endorsement of traditional masculinity ideology, which refers to beliefs about how men should or should not think, feel and behave, and which is measured by the Male Role Norms Inventory-Revised (MRNI-R; Levant, Rankin, Williams, Hasan, & Smalley, 2010); (2) conformity to masculine norms, which is a man s self-assessment of the degree to which he personally conforms to traditional norms of masculinity, and which is measured by the Conformity to Masculine Norms Inventory (CMNI; Mahalik et al., 2003); and (3) masculine gender role stress and (4) gender role conflict, which refer to the stress or conflict that a man experiences while personally conforming to the traditional norms of masculinity, and which are measured by the Masculine Gender Role Stress Scale (MGRSS; Eisler, 1995) and the Gender Role Conflict Scale (GRCS; O Neil, Helms, Gable, David, & Wrightsman, 1986), respectively. While some studies have supported the GRSP hypothesis that masculinity is a risk factor for men s health, other, more recent, research has indicated that the relationships between the various masculinity constructs and men s health behaviors appear to be more complex than had been assumed. In these latter studies, some aspects of masculinity were associated with health risk behaviors whereas others were associated with health-promoting behaviors and could be considered protective health buffers. A brief review of this research on men s health behaviors follows. Affirming the Gender Role Strain Paradigm prediction, gender role conflict was associated with risky health behaviors such as substance abuse (Blazina & Watkins, 1996), and masculine gender role stress was associated with behaviors linked to cardiac disease risk (Eisler, 1995). Conformity to masculine norms was linked with health risk behaviors for both U.S. and Kenyan college men, (Mahalik, Lagan & Morrison, 2006) and for gay men (Hamilton & Mahalik, 2009). However, a study of U.S. college men found that while higher levels of gender role conflict predicted more risky health behaviors, greater endorsement of traditional masculinity ideology was associated with less risky health-related behaviors (Levant, Wimer, Williams, Smalley, & Noronha, 2009). These results suggest that while experiencing psychological conflict as a result of one s own conformity to traditional masculine norms is positively associated with health risk behaviors, endorsing the view that men should conform to traditional norms may be a protective buffer, in that it is negatively associated with health risk behaviors. Similarly, focus groups of men in Scotland found that while there was widespread endorsement of the idea that men should avoid seeking medical care, there were instances in which the men resisted this view (O Brien, Hunt, & Hart, 2005, p. 503). That is, these men would allow themselves to seek health care in order to be able perform a masculine role, either as worker in a risky profession or as sexual agent. In the same vein, an investigation of the link between the endorsement of traditional masculinity ideology and health beliefs and behaviors for African American men found that while endorsement of the traditional masculine norm of restrictive emotionality was associated with the belief that one does not have control over one s health status, endorsement of the traditional norms of self-reliance and aggression were associated with positive health behaviors (Wade, 2009). This study suggests that while endorsing a particular traditional masculine norm (e.g., men should restrict the expression of emotions) is associated with 24

4 CONFORMITY TO MASCULINE NORMS AND MEN S HEALTH BEHAVIORS health risk beliefs, endorsing other traditional masculine norms (e.g., men should be selfreliant and aggressive) may be a protective buffer, in that such endorsement is negatively associated with health risk behaviors. This latter finding is reinforced by a recent study which found that African American men who more strongly endorsed the traditional masculinity norm of self-reliance were significantly less likely to delay blood pressure screening (Hammond, Matthews, Mohottige, Agyemang, & Corbie-Smith, 2010). The most comprehensive investigation to date of links between masculinity constructs and men s health behaviors (Levant, Wimer, & Williams, 2011) examined the relationships between three of the most commonly used multidimensional masculinity measures mentioned above (MRNI-R, CMNI, GRCS) and five dimensions of health-related behaviors. The latter were measured by the Health Behavior Inventory-20 (HBI-20; Levant et al., 2011), and included diet, preventive self-care, proper use of health care resources (including medications), avoidance of anger and stress, and avoidance of substance use. The investigators found that when looking at the total scores for the masculinity and health behavior measures, only the Conformity to Masculine Norms Inventory was a significant predictor of health behaviors. It was negatively associated with health-promoting behaviors, and thus was viewed as a risk factor, a finding which replicated two prior results (Hamilton & Mahalik, 2009; Mahalik et al., 2006). When looking at the subscale scores for the masculinity and health behavior measures, Levant et al. (2011) found that the relationship between health behavior and masculinity depended on which dimension of health behavior was used as a criterion and which facets of masculinity were used as predictors. Although similar results were found for the Male Role Norms Inventory-Revised and the Gender Role Conflict Scale, both for the sake of simplicity and because it is the focus of the present study, we have limited this discussion to the results for the CMNI subscales. Scores on Winning, Primacy of Work, and Emotional Control scales were positively related to one or more scores on Health Behavior Inventory-20 subscales, and thus may be health protective factors. On the other hand, scores on Pursuit of Status, Playboy, Risk Taking and Self-Reliance scales were negatively related to one or more scores on HBI-20 subscales, and thus may be health risk factors. Finally, scores on Dominance were negatively related to two HBI-20 subscales and positively related to a third. Thus, while the CMNI Total Scale scores and some subscale scores were associated with health risk, other CMNI subscale scores were associated with positive health behaviors. It should also be noted positive and negative associations of masculinity scales with health-promoting behaviors have also been observed in other studies (Levant et al., 2009; Levant & Wimer, 2014). There is no obvious pattern from which an explanation might be provided for this complex set of relationships between masculinity constructs and health behaviors, in which some masculinity scales appear to be risk factors and others protective buffers. Therefore, further investigation is warranted. Since in any given study there are typically a host of unmeasured variables that might play a role in the observed relationships, one possible direction is to assess whether there are mediating or moderating variables that affect the relationships between masculinity constructs and health behaviors. Mediating variables are intervening variables between a predictor and a criterion that can transmit some or all of the effect of the predictor on the criterion, whereas moderator variables change the strength or direction of the relationship between a predictor and a criterion (Frazier, Tix, & Barron, 2004). Identifying such mediators or moderators might help understand how some facets of 25

5 LEVANT & WIMER masculinity are associated with risky health behaviors and others are associated with healthpromoting behaviors. THE PRESENT STUDY The present study undertook the investigation of mediating or moderating variables in the relationship between the CMNI and the HBI-20, using the CMNI-46 (Parent & Moradi, 2009), which is a new short version of the CMNI. As noted above, the GRSP accounts for the relationships found between CMNI scales and health risk behaviors in prior research. The theoretical framework must now be extended to account for the prior findings that conformity to some traditional masculine norms is associated with positive health behaviors. We intend to extend theory in two different ways to allow comparisons for the strength of each extension. First, scholars investigating positive masculinity (Hammer & Good, 2010; Kiselica & Englar-Carlson, 2010; Levant, 1995) have theorized that the traditional masculine gender role has, in addition to negative attributes such as restrictive emotionality, a number of positive attributes as well, including courage, autonomy, self-efficacy, endurance, resilience, stoicism, and emotional stability. We have selected two of these constructs of positive masculinity theory for the present study, self-efficacy and emotional stability, based on their use in prior research on men s health. Self-efficacy refers to confidence in one s ability to handle whatever challenges arise, and emotional stability refers to the ability to stay on an even emotional keel no matter how challenging the circumstances. None of the aforementioned masculinity measures used in men s health research have subscales titled selfefficacy or emotional stability, although several have scales titled self-reliance, restrictive emotionality, or emotional control. Hence we theorized that self-efficacy and emotional stability are variables that may be associated with the masculinity scales and health behaviors. In addition, self-efficacy and emotional stability may function as mediators or moderators of the relationship between the masculinity scales and health behaviors. According to social cognitive theory general self-efficacy is a broad and stable sense of personal competence to deal effectively with a variety of stressful situations (Bandura, 1977). It is measured by the General Self Efficacy Scale (GSES; Schwarzer & Jerusalem, 1995). Australian men s GSES scores were found to moderate the relationship between their CMNI scores and their scores on one subscale of the Barriers to Help Seeking Scale (Boman & Walker, 2010), a measure of attitudes toward seeking help for health problems, indicating its plausibility as a mediator or moderator in the present study. Emotional Stability is the reverse of Neuroticism on the Big-Five public domain personality scales from the International Personality Item Pool (Goldberg, 1999). The Emotional Stability Scale (ESS) was predictive of scores on a measure of positive health behaviors (Health Activities Questionnaire, Goldberg, 1999), suggesting that it might play a role as a mediator or moderator in the present study. The second way we intend to extend theory is by using social norms theory (Cialdini & Trost, 1998). Cialdini and Trost (1998) theorized that descriptive norms (i.e., norms that simply describe what the expected behavior is in a given situation, without stating that one should or must engage in the behavior) function to guide behavior through such social influence processes as conformity and compliance. Research has shown that normative restructuring programs, aimed at correcting inflated estimates of how much peers drink can combat alcohol use problems among U.S college students (Rimal & Real, 2005). Mahalik, 26

6 Burns, and Syzdek (2007) found that conformity to masculine norms and the perception of men s health behaviors as normative (that is, the extent to which men view the engagement in health-promoting behaviors and the avoidance of health risk behaviors as a normative expectation for men) significantly predicted the self-reported health behaviors of participants. In other words, men tended to follow the health-promoting behaviors of other men when they perceived those behaviors as normative. Although Mahalik et al. (2007) viewed perception of men s health behaviors as normative as a predictor of men s health behavior it could also be viewed as a mediator or moderator of the relationships between masculinity constructs and men s health behaviors. How does a researcher determine whether a variable should be considered to be either a mediator or a moderator? The recently developed MacArthur Foundation Network approach specifies eligibility criteria for differentiating mediation and moderation (Kraemer, Kiernan, Essex & Kupfer, 2008). For moderation, the moderator must temporally precede the predictor. It is the reverse for mediation: the predictor must temporally precede the mediator. In the present study, the predictor (conformity to masculine norms) can logically be specified as having occurred before the hypothesized mediators (general self-efficacy, emotional stability, and the perception of men s health behaviors as normative) since such conformity is theorized to have resulted from socialization processes that originated in childhood. Hence general self-efficacy, emotional stability, and the perception of men s health behaviors as normative are hypothesized mediators of the relationships between the CMNI-46 and men s health behaviors. Hypothesized Model CONFORMITY TO MASCULINE NORMS AND MEN S HEALTH BEHAVIORS We hypothesized a multiple mediator model, which allows the comparison of the relative strengths of the mediators (Preacher & Hayes, 2008), in which general self-efficacy, emotional stability, and perception of men s health behaviors as normative would mediate the relationship between the CMNI-46 and men s health behaviors (as measured by the HBI- 20). We assessed men s general self-efficacy using the General Self Efficacy Scale (GSES), emotional stability using the Emotional Stability Scale (ESS), and perception of men s health behaviors as normative using an adaptation of the Perceptions of Normative Health Behaviors Scale (PNHBS; Mahalik et al., 2007). Power Analysis METHOD For tests of mediation using path analysis in structural equation modeling, we consulted Table 4 in MacCallum, Brown and Sugawara (1996), which provides the minimum sample size to achieve power of 0.80 for selected levels of degrees of freedom. This table indicated that to achieve a power of 0.80 with 10 degrees of freedom with a test for close fit (RMSEA between.05 and.08), the minimum N would be 782. Participants As can be seen in Table 1, the participants tended to be young, White/European American, unattached, heterosexual, high school or GED graduates, middle class, and Christian. 27

7 LEVANT & WIMER Table 1 Demographic Characteristics of the Participants (N = 591) Mean SD Range Age Other Demographic Variables N % Race/Ethnicity White Black Latino Asian-American Bi/Multi racial Other or no response Relationship Married/partnered/engaged Exclusive Dating Casual Dating Single, not dating anyone Divorced/separated/widowed No response Sex Orientation Heterosexual Bi-sexual Gay No response Education HS/GED BA/BS Masters Doctorate No response Socioeconomic Status Lower class Lower middle class Middle class Upper middle class Upper class No response Religion Christian Atheist Agnostic Jewish Other or no response

8 CONFORMITY TO MASCULINE NORMS AND MEN S HEALTH BEHAVIORS Procedure The present study was part of a larger data collection effort that also resulted in the publication of Levant and Wimer (2014), which replicated Levant, Wimer, and Williams (2011), which reported complex relationships between masculinity and health behaviors, and of Wimer and Levant (2013), which analyzed the relationships between the consumption of energy drinks, three masculinity constructs, jock identity, and fraternity membership. The study was approved by the University of Akron and The Pennsylvania State University IRBs. Participants were recruited through several methods. For the University of Akron, undergraduate student participants were solicited from Psychology courses and offered an incentive of 2 extra credit points for their participation in the study. Students who wished to participate provided their address to the research assistant who had visited their classroom, and were subsequently ed the link to the online survey site, which is supported by a commercial survey utility licensed to the University of Akron. For The Pennsylvania State University, students from Introduction to Psychology courses chose to participate in the study in order to partially fulfill the research participation aspect of the course, and they entered the survey via university s subject pool web site. The first page of the survey site provided the informed consent information, and participants who consented clicked yes and were taken to the survey. Upon completion of the survey participants were provided with an educational briefing on the study, including the rationale and hypotheses in addition to and references with more information on the topic. Once participants clicked done they were directed to the incentive fulfillment page, which first asked how they had been recruited for the study, either from one of the two universities or from an internet website. If they responded that they had been recruited from a university, they were directed to the extra credit or research participation credit pages (which asked for their name, , course for which they wanted credit, and the instructor of that course). Community participants were solicited by contacting a number of listservs of potential interest to men (e.g., sports, motorcycles, hunting, and fishing). We posted a description of the study, request for participants, and link to the online survey site. At the online survey site, the procedures were the same as those used with the students, except that they were offered the opportunity to enter a raffle to win a $200 gift card to the retailer of their choice for their participation in the study. In addition, when they got to the incentive fulfillment page they were directed to the raffle page (which asked for their name, , and address). About 20% of the participants were recruited from the community via the internet. The incentive fulfillment, extra credit, and raffle pages were not linked to participants answers on the survey, thus keeping their answers to the survey completely anonymous. The survey consisted of 116 questions and took approximately minutes to complete. It was presented in the following order: Demographic Form, Conformity to Masculine Norms Inventory-46, Health Behavior Inventory-20, Emotional Stability Scale, General Self-efficacy Scale, and Perceptions of Normative Health Behaviors Scale. The survey was part of a larger study that included two additional scales that were used to replicate Levant et al. (2011; Levant & Wimer, 2104), and one other scale that was used to assess energy drink consumption (Wimer & Levant, 2013). 29

9 LEVANT & WIMER Measures Demographic Questionnaire. The demographic questionnaire had questions about gender, age, race/ethnicity, relationship status, sexual orientation, highest degree completed, family/household income, socioeconomic status, and religion. Conformity to Masculine Norms Inventory-46 (CMNI-46). The CMNI-46 (Parent & Moradi, 2009) is a short version of the Conformity to Masculine Norms Inventory (CMNI; Mahalik et al., 2003). The CMNI assesses the extent to which an individual male conforms or does not conform to the actions, thoughts and feelings that reflect masculinity norms in the dominant culture in U.S. society (Mahalik et al., 2003, p. 5). Confirmatory factor analysis of the 46-item version of the CMNI found a nine-factor scale (Parent & Moradi, 2009). Responses to items (e.g., In general, I will do anything to win ) are made on a four-point scale (0 = Strongly disagree, 3 = Strongly agree). Eighteen items were reverse-scored. A total scale score was obtained through the averaging of scores on all items (α =.88; Parent & Moradi, 2009). Construct validity of the CMNI-46 was supported by finding that CMNI-46 subscales had large positive correlations with their parent CMNI subscale (r s ranged.89 to.98; Parent & Moradi, 2009). For the present study α =.90. Health Behavior Inventory-20 (HBI-20). To assess health behaviors we used the Health Behavior Inventory-20 (HBI-20; Levant et al., 2011), which resulted from modifications to the Health Risks Inventory (Courtenay, 1998). Exploratory factor analysis found a 20-item, five-factor instrument (Levant et al., 2011). Participants were asked to rate the extent to which each item (e.g., I fill my medicine prescriptions immediately ) was self-descriptive, using a scale from 1 = always to 7 = never. Since the HBI-20 is an index where higher scores reflect health promoting behavior, the 6 items that assessed risk behaviors (e.g., I use tobacco products ) were reverse scored. A total scale score was obtained through the averaging of scores on all items (α =.72). Levant et al. (2011) reported evidence for concurrent validity of the HBI-20 through a significant positive correlation between the HBI-20 and the Attitudes Toward Seeking Professional Psychological Help, and significant negative correlations between the HBI-20 and two masculinity measures (CMNI, GRCS). For the present study α =.78. Emotional Stability Scale (ESS). The ESS is one of Big-Five public domain personality scales from the International Personality Item Pool, designed to tap the personality domain of Emotional Stability (Goldberg, 1999). For the present study we used the 10-item format, which consists of 2 positively keyed items reflecting emotional stability (e.g., I am relaxed most of the time ) and 8 negatively keyed items (e.g., I get stressed out easily ) reflecting neuroticism. Participants rate their level of agreement or disagreement with each item using a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree). Since in the present study we were interested in Emotional Stability rather than its reverse, Neuroticism, we reverse-scored the negatively-keyed items so that high scores indicate a greater degree of Emotional Stability. A score is obtained through the averaging of scores on all items. Goldberg (1999) reported an α of.86 and evidence for construct validity through a correlation of.72 with a set of Markers for the Big Five construct of Emotional Stability. For the present study α =

10 General Self-efficacy Scale (GSES). The GSES is a 10-item measure designed to assess a broad and stable sense of personal competence to deal effectively with a variety of stressful situations (Schwarzer & Jerusalem, 1995). Responses are made using a four-point Likert-type scale (1 = Not at all true, 4 = Exactly True) to statements such as I can usually handle whatever comes my way. None of the items were reverse-scored. Responses to all 10 items are summed up to yield the final composite score, with a range from 10 to 40, in which higher scores indicate greater general self-efficacy (α =.89). Schwarzer and Jerusalem (1995) reported that in samples from 23 nations α s ranged from.76 to.90, a series of confirmatory factor analyses found the scale to be unidimensional, and criterion-related validity was documented in numerous correlation studies, where positive relationships were found with favorable emotions, dispositional optimism, and work satisfaction, and negative coefficients were found with depression, anxiety, stress, burnout, and health complaints. For the present study α =.89. Perceptions of Normative Health Behaviors Scale (PNHBS). We adapted the PNHBS developed by Mahalik, Burns, and Syzdek (2007) for this study. Participants perception of the 20 health behaviors described in the HBI-20 as normative for men were assessed through statements that used men whom you look up to as the reference group. A sample item is Most men whom I look up to limit the amount of red meat they eat. Each statement was rated on a 7-point Likert-type scale (1= strongly disagree, 7 = strongly agree). To obtain an index where higher scores reflected perceptions of health promoting behavior, the 6 items that assessed perceptions of health-risk behaviors (e.g., Most men whom I look up to use tobacco products ) were reverse scored. A total scale score was obtained through the averaging of scores on all items (α =.82; Mahalik, et al., 2007). Concurrent validity of the PNHBS was demonstrated by its association with men s health behaviors (Mahalik, et al., 2007). For the present study α =.83. Analytic Approach CONFORMITY TO MASCULINE NORMS AND MEN S HEALTH BEHAVIORS We used path analysis in structural equation modeling (SEM), assisted by Mplus version 7.11 (Muthén & Muthén, ) to test the multiple mediator model. The overall fit of the SEM model was assessed with the chi-square goodness-of-fit statistic. However, this statistic is often overly sensitive to minor and theoretically uninteresting sources of model misfit, especially when sample sizes are large as in the current study. Thus we also used a set of alternative fit indices which are typically also consulted to determine whether a model demonstrates adequate fit (Kahn, 2006). These indices and the criteria used to assess their values (based on Kline, 2011) were the: (a) Comparative Fit Index (CFI), values of >.90 indicate reasonable fit; (b) Root Mean Square Error of Approximation (RMSEA), for which good model fit is suggested by values of.05 or lower and values between.05 and.08 suggest reasonable fit; and (c) Standardized Root Mean Square Residual (SRMR), for which values of less than.10 are considered good. These criteria are rules of thumb and the indices should be regarded as providing descriptive information about model fit. According to Kline (2011, p. 205): The value of this [descriptive] information increases when you report values of indices that as a set assess model fit from different perspectives. Baron s and Kenney s (1986) classic causal steps criteria for mediation had four steps: (1) Show that a predictor is significantly associated with a criterion variable, which is re- 31

11 LEVANT & WIMER ferred to as path c. However, Shrout and Bolger (2002) suggested that this step can be omitted under circumstances where power might be low. (2) Show that the predictor significantly predicts the mediating variable, which is referred to as path a. (3) Show that the mediator variable significantly predicts the criterion, controlling for the predictor, which is referred to as path b. (4) Show that the strength of the relationship between the predictor and criterion is significantly reduced when the mediators are added to the model, path c ; that is c < c. If the path between predictor and criterion is reduced by a non-trivial amount but not to zero, partial mediation has occurred. If the path is reduced to zero, perfect or complete mediation has occurred. This step is referred to as the differences in coefficients test. Frazier, Tix, and Barron (2004) noted that the differences in coefficients test (c - c), is no longer considered a sufficient test of whether mediation has occurred, but rather the mediating effect must be assessed directly through what is termed the product of the coefficients approach. The mediating effect is thus expressed in SEM as an indirect effect, the product of two path coefficients, a and b (a*b). MacKinnon, Lockwood, Hoffman, West, and Sheets (2002) compared the various ways to test the statistical significance of the mediating effect in a Monte Carlo study, and recommended testing the joint significance of the two path coefficients comprising the mediating effect. We followed the Shrout and Bolger (2002) recommendations for doing this with a bootstrapping approach, which has the advantage of not imposing the assumption of normality on the sampling distribution. The criterion for significance was whether the 95% confidence interval for the mediating effect, based on generating 1,000 bootstrap samples, contained zero. RESULTS Data Cleaning and Descriptive Statistics The data were screened before conducting statistical analyses to eliminate random responding and data entry errors. A total of 743 participants began the survey. After eliminating those who did not complete it and those who identified as female and transgender, the sample included 594 men, with a completion rate of 79.9 %. The data were next examined for multivariate outliers, using as the criterion Mahalanobis distance at p <.001 (Tabachnick & Fidell, 2007), resulting in the deletion of 3 cases, for a final N = 591. The data set (not including demographics) consisted of 106 items which had been responded to by 591 participants, of which 160 data points were missing (0.17%), with the number of missing responses per item ranging from 0 to 6. Following recent recommendations on best practices for handling missing data, missing data analyzed using SPSS were handled using pairwise deletion (Parent, 2013), and missing data analyzed using Mplus were handled using full information maximum likelihood (FIML) estimation procedures (Schlomer, Bauman, & Card, 2010). In both analyses, no cases were deleted and no missing values were imputed; rather, all available responses for each item were used in the analyses. Descriptive statistics and bivariate correlations of study variables are presented in Table 2. Testing a Multiple Mediator Model Before testing the model, we examined the data for multicollinearity, or high levels of common variance using the variance inflation factor (VIF). The study variables had VIF val- 32

12 CONFORMITY TO MASCULINE NORMS AND MEN S HEALTH BEHAVIORS Table 2 Means, Standard Deviations, Bivariate Correlations, and Cronbach Alpha Coefficients of Study Variables Variable M SD α Range 1. HBI **.11 **.22 **.46 ** CMNI ** -.16 ** ESS.26 **.10 * GSES.16 ** PNHBS Note. N = 591. HBI-20, Health Behavior Inventory-20; CMNI-46, Conformity to Masculine Norms Inventory-46; ESS, Emotional Stability Scale; GSES, General Self-Efficacy Scale; PNHBS, Perception of Normative Health Behaviors Scale. * p <.05, two-tailed; ** p <.01, two-tailed. ues ranging from 1.08 to 1.41; hence none reached 2.50, the most conservative threshold (Miles & Shevlin, 2001). Similarly, the bivariate correlations, which can indicate multicollinearity if values are above.70, ranged from.06 to.46 (see Table 2). The hypothesized initial model (M1), in which general self-efficacy (GSES), emotional stability (ESS), and perceived normative health behaviors (PHNBS) mediated the relationships between conformity to masculine norms (CMNI-46) and health-promoting behaviors (HBI-20) demonstrated poor fit. As can be seen in Table 3, the chi-square goodness-of-fit statistic was significant indicating that the null hypothesis of no difference in fit between the implied model and the data covariance matrices should be rejected. Further, none the three remaining fit indices were within the guidelines described earlier. We attempted an additional analysis with the Emotional Stability Scale. Since eight of the ten items of the ESS tapped the avoidance of neuroticism (that is, they were reverse-scored neuroticism items) we created a second variable, consisting of the two items that directly tapped emotional stability. As can be seen in Table 3 (Model M1A), the chi-square goodness-of-fit statistic and the three other fit indices were all much worse than the original model M1. Since in the analysis of Model M1, the only non-significant path was path b (unstandardized path coefficient =.012, p =.747) between ESS and HBI-20, and the estimate of the indirect effect through ESS was also non-significant (.001, p =.756), we trimmed the initial model by eliminating ESS but retaining GSES and PNHBS as mediators. As can be seen in Table 3, the chi-square goodness-of-fit statistic for model M2 was significant indicating that the null hypothesis of no difference in fit between the implied model and the data covariance matrices should be rejected. However, two of the three remaining fit indices (CFI and SRMR) were within the guidelines described earlier. The question of whether model M2 shows reasonable fit is thus somewhat equivocal, depending on which fit statistics one considers. However model M2 has resulted in significantly improved model fit as compared to model M1. Since M2 is nested within M1, we compared the two models with the chi square difference test, which allows an assessment of whether the improvement in fit associated with the trimmed model M2 is statistically significant. However, the chi- 33

13 LEVANT & WIMER Table 3 Model Fit Statistics and Comparisons of Nested Models Model χ 2 CFI RMSEA estimate SRMR BIC (df) & 90% CI M (10).152,.231 M1A (10).315,.371 M (6).114,.250 Model Comparison: Δχ 2 p ΔCFI ΔBIC Conclusion (df) M1 vs. M < Prefer M2 (4) Note. CFI = Comparative Fit Index; RMSEA = Root Mean Square Error of Approximation; SRMR = Standardized Root Mean Square Residual; BIC = Bayesian Information Criterion. The conclusion is based on a joint consideration of Δχ 2, ΔCFI, and a comparison of BIC values. square difference test may be too sensitive to misfit when sample sizes are large. Thus, two alternative indices were also consulted, the change in CFI and a comparison of the BIC values for the two models (Cheung & Rensvold, 2001). Support for the trimmed model M2 would consist of a change in CFI of greater than.01 and a smaller BIC value. As shown in Table 3, M2 resulted in improved fit over M1 by all three criteria. Even though the fit of model M2 may be somewhat equivocal (with regard to the RMSEA values), the path analysis for this model met the criteria for mediation as described above, as shown in Figure 1. For step 1, the unstandardized coefficient for path c between the CMNI-46 and the HBI-20 (without any mediators in the model) was -.758, p <.001. The next two steps resulted in significant coefficients for paths a and b for both mediators. In step 4, using the bootstrapping approach to directly assess the significance of the mediating or indirect effects, the overall indirect effect of both mediators was significant (unstandardized path coefficient = -.103, p <.01). Hence, General Self Efficacy and Perceived Normativeness of Health Behaviors mediated the relationship between Conformity to Masculine Norms and Health Promotion Behaviors. Using the differences in coefficients test, the path between the exogenous and the endogenous variables was reduced by a non-trivial amount but not to zero (from c = to c = -.653). Thus partial mediation has occurred. Both mediators together act as a buffer, which can be seen when one compares the total effect of the CMNI-46 on the HBI-20 without the two mediators in the model, path c = -.758, with the direct effect with the two mediators in the model, path c = That is, with the two mediators in the model, the negative effect (meaning that higher conformity to masculine norms is associated with worse health behaviors) is reduced. 34

14 CONFORMITY TO MASCULINE NORMS AND MEN S HEALTH BEHAVIORS Figure 1. Final multiple mediation model (M2), in which General Self-Efficacy and Perceptions of Normative Health Behaviors mediate the relationship between Conformity to Masculine Norms and Health Behaviors. All values are unstandardized. The path from Conformity to Health Behaviors is shown with two values, the first without mediators, and the second with both mediators in the model. ** p <.01, *** p <.001 As noted in the Introduction, the multiple mediator approach allows the comparison of the strengths of the two mediators, and thus of the relative usefulness of the two extensions of theory: positive masculinity (as represented by the GSES) and social norms theories (as represented by the PNHBS). Using the SEM approach outlined by Preacher and Hayes (2008), both indirect effects were significant and their 95% confidence intervals did not contain zero. These values were.068, p =.012, 95% CI =.015,.113 for GSES and -.171, p =.001, 95% CI = -.268, for PNHBS. Since the total effect, c (-.758) equals the direct effect, c (-.658) plus the indirect effect a*b (-.103), the indirect effect for PNHBS (-.171) accounts for all of the buffering effect, since it is both negative and larger than that for GSES (.068). Thus, these results indicate that social norms theory provides a better account for the protective buffering effect on the relationship between conformity to masculine norms and men s health behaviors than does positive masculinity. 35

15 LEVANT & WIMER DISCUSSION Summary and Implications for Research We tested a multiple mediator model in which general self-efficacy (GSES), emotional stability (ESS), and perceived normative health behaviors (PNHBS) mediated the relationships between conformity to masculine norms (CMNI-46) and health-promoting behaviors (HBI-20). Although ESS was not a mediator, we found that GSES and PNHBS mediated (acting together as a protective buffer) the relationship between conformity to masculine norms and health-promoting behaviors. The results also indicated that PNHBS better accounted for the protective buffering effect. These findings allow the refinement of the extension of the GRSP theoretical framework that was developed to account for the findings that conformity to some traditional masculine norms is associated with some positive health behaviors. The present findings indicate that these positive effects are mediated by the combined effects of one variable derived from positive masculinity theory (general self-efficacy), and by one variable derived from social norms theory (the perception that positive health behaviors are normative for men). They also indicate that the variable derived from social norms theory better accounts for the protective buffering effect than does the variable derived from positive masculinity theory. The strength of social norms theory in the present study is supported by findings in other areas, such as the role of descriptive norms in reducing excessive drinking (Rimal & Real, 2005) and littering behavior (Cialdini, Reno, & Kallgren, 1990). That emotional stability, a variable associated with positive masculinity theory, was not found to be a mediator in the present study further suggests the relative weakness of positive masculinity theory in explaining the protective buffering effect. This finding must be held tentatively due to the limitations of the present study delineated below. Future research should continue to assess the strength of positive masculinity theory in explaining the protective buffering effect, perhaps by using measures of other positive attributes of the traditional masculine gender role that were mentioned in the Introduction, such as courage, autonomy, endurance, resilience, and stoicism (Hammer & Good, 2010; Kiselica & Englar-Carlson, 2010; Levant, 1995). Future research should also continue to assess the strength of social norms theory in explaining the protective buffering effect, by utilizing other measures of both health behavior and of the perception of men s health behavior as normative. Future research might investigate if the mediating variables found in this study also account for the protective buffering effects observed with other measures of masculinity constructs such as the Male Role Norms Inventory-Revised and the Gender Role Conflict Scale. Finally, future research might also search for moderators of these mediated relationships, such as race/ethnicity, socio-economic status, and age. Some of these variables have been shown to moderate the relationships between some masculinity constructs and alexithymia (Levant & Wong, 2013). The next step might be to use moderated path analysis to assess whether these variables moderate the mediated relationships in a process of moderated mediation, similar to what has been found for the relationship between some masculinity constructs and attitudes toward seeking professional psychological help (Levant et al., 2013). 36

16 Implications for Health Care Providers These results have implications for assessing and counseling men on health-related matters. Health care providers working in college and university settings might consider developing normative restructuring programs, aimed at challenging low estimates of how much peers engage in positive health behaviors, in order to promote positive health behaviors and the avoidance of health risks, particularly alcohol abuse. In addition, those aspects of traditional masculinity that may be related to health behaviors, particularly general selfefficacy, could perhaps be strengthened through counseling interventions such as assertiveness training. Limitations CONFORMITY TO MASCULINE NORMS AND MEN S HEALTH BEHAVIORS In considering the mediation effects of general self-efficacy and the perception of men s health promoting behaviors as normative, we are mindful that while we speak of relationships between variables, and of variance in their relationship being mediated through other variables, we have not established the direction of causality between masculinity constructs and men s health behaviors. It may be that masculinity constructs cause men s health-related behavior, or that men s health behaviors determine masculine norms (as conceptualized by, for example, the CMNI), or that both are caused by other variables (such as social and historical context). This should be addressed in future experimental studies that allow the teasing apart of cause from effect, for example in studies that manipulate the variable of perception of men s health promoting behaviors as normative, using techniques such as those that have been used in studies of littering behavior (Cialdini et al., 1990). The current study is limited by the socio-economic and cultural characteristics of our participants (predominantly young, White/European American, middle class, unattached, and heterosexual men). Additional diverse samples should be studied to explore these relationships in other groups. Also, the self-report nature of the surveys introduces the possibility of bias due to socially-desirable responding. A future study might control for such bias by using the Marlowe-Crowne Social Desirability Scale. In addition, employing a mixedmethod design (including qualitative interviews) would allow investigators to probe the relationships found in the present study to gain a deeper understanding of these relationships and to identify other variables of potential interest. Further the present study may have been underpowered. As noted above, the minimum N to achieve power of 0.80 would be 782, yet our final sample was 585. Another limitation was that we did not have a demographic question about recent acute or chronic health concerns of participants, which would have allowed us to assess the moderating effect of health concerns. Finally, given that we drew participants from two populations it would have been prudent to compare these two populations on the study variables. Unfortunately, we were unable to conduct this analysis because participants were asked to indicate how they were recruited on the incentive fulfillment page, which could not be connected to participants responses to the questionnaires. CONCLUSION In conclusion, we evaluated a multiple mediator model to assess the relative roles of two positive aspects of the traditional masculine role (general self-efficacy and emotional sta- 37