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. Author manuscript; available in PMC: 2024 Jul 1.
Published in final edited form as: Psychol Men Masc. 2023 Jun 1;24(3):261–268. doi: 10.1037/men0000436

Masculine Drinking Norms and Alcohol Use in a National Sample of NCAA Male Student-Athletes

Byron L Zamboanga 1, Jessica K Perrotte 2, Amie R Newins 3, Jessica L Martin 4, Kayla Ford 1, David L Wyrick 5, Jeffrey J Milroy 5
PMCID: PMC10691819  NIHMSID: NIHMS1902099  PMID: 38044977

Abstract

Objectives:

Participation in sports can increase young adults’ risk for heavy alcohol use and related consequences. Among student-athletes, more men report heavy drinking than women. These gender differences may reflect men’s expression of masculinity which can encompass excessive consumption. While a growing body of research indicates that general masculine norms are positively associated with alcohol use and consequences among men, the extent to which alcohol-specific masculine norms can increase student-athletes’ risk for elevated drinking and related outcomes is not yet known. Thus, we examined how masculine drinking norms are associated with alcohol use and related consequences while accounting for demographics and multiple dimensions of general masculine norms.

Methods:

1,825 NCAA student-athletes (White=79%, Mage=20.1/SDage=1.3; 50 colleges/universities) completed a confidential online survey which included questions regarding masculine drinking norms of excess and control and conformity to general masculine norms.

Results:

We created latent constructs and tested a path model in SEM. Results indicated that, after accounting for demographics and multiple dimensions of general masculine norms, the masculine drinking norm of excess was positively associated with alcohol use and consequences. Conversely, control was negatively related to alcohol use but unrelated to consequences. Compared to control and other dimensions of general masculine norms, excess was most strongly related to alcohol use and consequences.

Conclusions:

A move from assessing general masculine norms toward alcohol-specific masculine norms can further researchers’ and practitioners’ knowledge of masculine norms and their link to drinking behaviors, and enhance the application of masculine norms in alcohol intervention and prevention programs.

Keywords: Masculine norms, alcohol use, alcohol consequences, college athletes

Introduction

The link between sports participation and increased risk for heavy drinking among college-aged individuals is well established in the literature (e.g., Mastroleo et al., 2019; McNamara et al., 2022; Martens et al., 2006; O’Kane & Foote, 2022; Sønderlund et al., 2014, Zhou & Heim, 2014). Factors that can heighten student-athletes’ risk for heavy alcohol use include having to cope with the stressors associated with being a student and an athlete, trying to meet the drinking expectations of their teammates, and/or endorsing a “work hard play hard” attitude and the perceived social norm of heavy drinking among their teammates and other athletes (Martens et al., 2006; Moore & Abbe, 2021; O’Kane & Foote, 2022). Studies with student-athletes also indicate that more men than women report heavy alcohol consumption and negative consequences (e.g., Moore & Abbe, 2021; NCAA, 2018; Williams et al., 2020). Such gender differences may reflect men’s expression of masculinity, which can entail drinking excessively and exhibiting a robust tolerance for consuming alcohol (Lemle & Mishkind, 1989; Peralta, 2007). Given the prevalence of heavy alcohol use and related consequences (e.g., physical/sexual assault) among college students (see White & Hingson, 2013, for overview), especially those involved in athletics, research aimed at understanding alcohol risk and protective factors among college student-athletes is needed.

Gender schema theory posits that sextype behaviors are learned early in life and gender role norms are acquired and reinforced through social learning (Bem, 1981; Perrotte & Zamboanga, 2021; see Addis et al., 2010 for discussion on gendered social learning). According to Addis et al. (2010), individuals can “learn to enact gendered repertoires of behavior to achieve particular social means and ends” (p. 81). Moreover, socially-acquired gender roles are context-dependent such that the social acceptability of certain behaviors used to assert one’s masculinity may vary by context (Addis et al., 2010). It has been posited that alcohol consumption symbolizes masculinity, in such a way that those who can drink a lot and remain in control are behaving in a highly masculine manner (Lemle & Mishkind, 1989; Peralta, 2007). Thus, in the context of drinking, men can learn that consuming large quantities of alcohol (which can increase the likelihood of experiencing more negative alcohol consequences; e.g., Iwamoto et al., 2011) is one way of establishing or enacting their manliness. The most widely used masculinity measure, the Conformity to Masculine Norms Inventory (CMNI; Mahalik et al., 2003), assesses different aspects of masculine norms which include, but are not limited to winning, emotional control, risk-taking, self-reliance, being a playboy, and power over women. Several dimensions of the CMNI are associated with alcohol use among young adult men (e.g., Iwamoto et al., 2011). A content analysis reporting the correlations between dimensions of the CMNI with alcohol use and binge drinking among men across four studies indicated that the majority of the subscales were positively related to drinking behaviors (Gerdes & Levant, 2018). Meta-analytic work also indicates a positive but small association between the CMNI and substance use (including alcohol use, Wong et al., 2017). While conforming to some of these broad masculine norms is associated with heavy drinking and negative alcohol consequences among men, a limitation of the CMNI is that it does not capture alcohol-specific masculine norms and is thus conceptually distal in relation to drinking behaviors.

Applying the Social Ecology Model to college athletes’ alcohol use (Williams et al., 2006, 2008) suggests that student-athletes’ perceptions of their teammates’ and other athletes’ drinking attitudes and behaviors can influence their alcohol beliefs and consumption behaviors. Certain aspects of sports can encompass (O’Brien et al., 2018) and reinforce (Ramaeker & Petrie, 2019) masculine ideals such as competition, emotional control, violence, and risk-taking, all of which align with dimensions captured in the CMNI. Moreover, sports team membership, where team norms around masculinity are enacted through heavy drinking, can influence individual athletes’ drinking behaviors (Sønderlund et al., 2014).

Although the limited research precludes definitive conclusions about the link between masculinity and alcohol-related outcomes among athletes, evidence suggests there is a positive association between these variables. O’Brien et al. (2018) found a small but positive (bivariate) correlation between masculine traits and alcohol use (r=.12) among men across 10 U.K. universities; multivariate analysis controlling for alcohol use indicated that masculine traits were associated with an increased likelihood of driving while drinking. In another study, Ramaeker and Petrie (2019) found that, while violence and risk-taking on the CMNI were positively associated with hazardous alcohol use among NCAA male student-athletes, the amount of variance in severity of hazardous alcohol use accounted for by masculine norms was modest. Together, these studies on masculinity and alcohol use among sports participants indicate a positive (albeit modest) association between broad masculine norms and drinking behaviors. Perhaps the modest effect sizes indicate that alcohol-specific masculine norms have the potential to explain more fully the association between masculinity and drinking behaviors among male student-athletes.

To advance researchers’ and practitioners’ understanding of masculine norms and their associations with alcohol use, Perrotte, Zamboanga, and Kearns (2020) created the Masculine Drinking Norms Measure (MDNM). The MDNM was adapted from the Traditional Machismo and Caballerismo Scale (TMCS; Arciniega et al., 2008). The TMCS measured traditional machismo, which is characterized by maladaptive traits including hypermasculinity, dominance, and aggression that align with traits measured in other measures of masculinity like the CMNI. However, unlike the CMNI, the TMCS also measures caballerismo, which is considered to be a more adaptive dimension of masculinity and is characterized by traits such as respect, nurturance, and polite etiquette. Perrotte and colleagues (2020) relied on the concept underlying the TMCS to measure how norms around drinking for men can be maladaptive (i.e., through excessive drinking) or adaptive (i.e., through exerting behavioral control while drinking). These gender role scripts align with Klein’s (1992) early work with college students which indicated that compared to women, men reported higher levels of agreement with the statement that “a real man should be able to hold his liquor” than women. Moreover, students who agreed with this statement also reported more alcohol problems than those who did not (Klein, 1992). The ability to drink heavily while holding one’s liquor was echoed by participants in Peralta’s (2007) qualitative work. More recently, Perrotte et al.’s (2020) prospective study of Hispanic college men indicated that higher endorsement of the masculine drinking norm of excess during the summer before their first semester of college was associated with more frequent alcohol use and binge drinking, heavier consumption, and more alcohol consequences during their second semester of college. Conversely, the masculine drinking norm of control was prospectively associated with fewer alcohol consequences. Importantly, only the MDNM and not the TMCS was related to drinking in the study, suggesting that alcohol-specific masculine norms are more conceptually proximal to alcohol behaviors than more general masculine norms.

Other known risk factors for heavy alcohol use among student-athletes include sports type and membership in a fraternity/sorority (NCAA, 2018; O’Kane & Foote, 2022; Zhou & Heim, 2014). For example, student-athletes who participate in interacting (e.g., football) versus co-acting (e.g., gymnastics) sports teams are at increased risk for alcohol misuse (Brenner & Swanik, 2007; Sønderlund et al., 2014; Zhou & Heim, 2014). Students who are both a member of a fraternity/sorority and participate in college athletics report heavier alcohol use than their non-fraternity/sorority/non-student-athlete counterparts (Meilman et al., 1999). Among NCAA student-athletes, a higher proportion of fraternity/sorority members report alcohol use compared to their non-fraternity/sorority counterparts (NCAA, 2018). Given the role of fraternity/sorority membership and sports type on alcohol use, we included these variables as covariates in our analysis.

Study Aims

The extent to which endorsement of masculine drinking norms regarding excess and control are associated with drinking behaviors and related outcomes over and above general masculine norms among NCAA male student-athlete drinkers has yet to be examined. Thus, our primary study aim is to investigate the extent to which endorsement of these beliefs is associated with alcohol use and consequences while accounting for (a) known demographic (age, fraternity/sorority membership status; Merrill & Carey, 2016) and sports-related (co-acting/interacting sports team) risk factors, and (b) certain dimensions of the CMNI that have been linked to alcohol use or misuse (e.g., Gerdes & Levant, 2018; Iwamoto et al., 2011, 2014; Radimer & Rowan-Kenyon, 2019). Based in part on prior research (Perrotte et al., 2020) and gender role scripts around drinking (Lemle & Mishkind, 1989; Peralta, 2007), we hypothesized that the excess norm would be positively associated with alcohol use and consequences while the control norm would be negatively associated with these drinking outcome variables.

Method

Participants and Procedure

Our study sample consisted of a subsample of varsity student-athletes from MyPlaybook (an athlete-specific online alcohol/substance use education/prevention program; Wyrick et al., 2014) who self-identified as male (ages 18–25) and were invited to participate in the College Athlete Risky Drinking Study (e.g., Zamboanga et al., 2022). Data were collected from over 200 Division I, II, and III NCAA member institutions during the 2017–2018 academic year (fall/spring semesters). Respondents received no compensation for participating in the study. The Institutional Review Board at the project investigator’s university approved all study protocols.

Given the aim of investigating alcohol outcomes and considering the theoretical proximity of the masculine drinking norms of excess and control to alcohol use, we restricted our sample to current drinkers (i.e., consumed one drink or more in the past 30 days). Participants who failed to pass an attention check embedded within the variables or were missing responses on all of the MDNM items were excluded from the present study, yielding a final analytic sample of 1,825 (50 colleges/universities; White=79%, Black/African American=9.7%, Hispanic=5.9%, Asian/Asian American=2.8%, American Indian=0.2%, Not listed=2.5%; Mage=20.1, SDage=1.3). Of these, 208 (7.6%) reported being a member of a fraternity/sorority. See Table 1 for descriptives and zero-order correlations among the primary study variables.

Table 1.

Zero-Order Correlations and Descriptive Statistics of Observed Variables

Variables 1 2 3 4 5 6 7 8 Mean SD Range Cronbach’s alpha
Alcohol Outcomes
 1. Alcohol Usea -- 12.33 10.40 1–55 --
 2. Alcohol Consequencesb .43*** -- 4.93 4.35 0–23 .86
Masculine Drinking Norms c
 3. Excess .26*** .23*** -- 2.00 0.62 1–4 .78
 4. Control −.05* −.05 .08** -- 3.09 0.60 1–4 .65
General Masculine Norms d
 5. Playboy .12*** .20*** .31*** −.06** -- 1.73 0.67 1–4 .82
 6. Self-Reliance .08** .14*** .20*** .08** .18*** -- 2.30 0.66 1–4 .80
 7. Winning .06** .05* .08*** .01 .01 −.01 -- 3.07 0.63 1–4 .83
 8. Risk-Taking .14*** .26*** .25*** −.00 .34*** .25*** −.06* -- 2.36 0.56 1–4 .75
 9. Power over Women .06* .09*** .36*** −.04 .38*** .19*** .02 .27*** 1.59 0.59 1–4 .83
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Notes. ns range from 1,781 to 1,799. Discrepancies across ns due to patterns of missing data.

a

Daily Drinking Questionnaire,

b

Brief Young Adult Alcohol Consequences Questionnaire,

c

Masculine Drinking Norms Measure,

d

Conformity to Masculine Norms Inventory.

*

p<.05,

**

p<.01,

***

p<.001.

Measures

Demographics.

Participants reported their age, race/ethnicity, fraternity/sorority member status, and sports team. We categorized each sports team as an interacting (e.g., basketball) or co-acting (e.g., gymnastics) sport1 (Rockafellow & Saules, 2006).

Masculine Drinking Norms and General Masculine Norms.

We used the MDNM2 (Perrotte et al., 2020) to assess two dimensions of masculine drinking norms using a 4-point scale (1=strongly disagree to 4=strongly agree): excess (i.e., the ability to drink large quantities of alcohol; α=.87) and control (i.e., the ability to drink in a controlled manner and maintain controlled behavior while drinking; α=.65). Given their known associations with drinking behaviors, we also measured five dimensions of conformity to general masculine norms with the CMNI-29 (Hsu & Iwamoto, 2014) using a 4-point scale (1=strongly disagree to 4=strongly agree): Playboy, Self-reliance, Winning, Risk-taking, and Power over Women. Due to space limitations in the questionnaire, we were unable to include other CMNI-29 subscales.

Alcohol Use and Negative Drinking Consequences.

Participants completed the Daily Drinking Questionnaire (Collins et al., 1985). Student-athletes reported the typical number of drinks they consumed on each day of the week over the past 30-days and total number of drinks reported were summed to compute alcohol use. We used the Brief Young Adult Alcohol Consequences scale (24-items; Kahler et al., 2005) to measure negative alcohol consequences. Participants endorsed (0=no/1=yes) whether they experienced each consequence (e.g., memory lapses) during the past 30 days; items were summed to compute a total score for alcohol consequences (α=.87). We chose this timeframe (as opposed to a longer timeframe, e.g., past year) to help increase the accuracy of student-athletes’ retrospective self-reported drinking behaviors and related consequences.

Analytic Approach

Analyses were conducted using Mplus version 8. A sandwich estimation method to compute standard errors accounted for clustering within universities (Muthén & Muthén, 2017) and standard errors were estimated using robust full information maximum likelihood. We employed a two-step structural equation modeling (SEM) approach in which the fit of the measurement model was assessed before examining the nature of the structural model (Weston & Gore, 2006). First, we verified the MDNM factor structure identified by Perrotte et al. (2020) using confirmatory factor analysis (CFA). Next, we constructed latent factors for each of the MDNM and CMNI dimensions using all within-dimension items as indicators (Matsunaga, 2008). We adjusted for the following covariates during SEM analysis: age, race/ethnicity (0=non-White, 1=White), fraternity/sorority member status (1=member of fraternity/sorority organization; 2=non-member), and sports type (0=co-acting sports [e.g., cross-country, gymnastics], 1=interacting [e.g., basketball, baseball]).

Results

We verified the two-factor structure of the MDNM using CFA, χ2(8)=38.97, p<.001, CFI=.98, RMSEA=.05, SRMR=.03. Each dimension’s respective indicators loaded strongly onto hypothesized factors (all βs>.50 with ps<.001). For the measurement model, we specified all latent factors in the model (i.e., MDNM and CMNI dimensions) and allowed for correlations across all latent variables, which yielded the following acceptable fit indices, χ2(188)=614.68, p<.001, CFI=.96, RMSEA=.04, SRMR=.04.

Next, to examine our primary study aim, we specified a structural model that regressed observed alcohol use and consequences onto each of the MDNM and CMNI latent factors, while adjusting for age, race/ethnicity, fraternity/sorority member status, and sports type, and while correlating alcohol use with alcohol consequences (see Table 2/Figure 1). Excess was most strongly related to both alcohol variables and was associated positively with alcohol use (β=.28) and consequences (β=.20). Conversely, control was negatively related to both alcohol variables (both use and consequences βs=−.09) Risk-taking was positively related to both alcohol use (β=.09) and consequences (β=.19) while power over women was negatively related to both alcohol use (β=−.12) and consequences (β=−.11). Playboy (β=.11) and self-reliance (β=.06) were related to more alcohol consequences but unrelated to alcohol use. Winning was unrelated to both alcohol variables.

Table 2.

Unstandardized Path Coefficients from the Structural Equation Model

Variable Alcohol Usef Alcohol Consequencesg
B SE p 95% LLCI 95% ULCI B SE p 95% LLCI 95% ULCI
Demographics
 Age 0.05 0.16 .776 −0.26 0.35 0.24 0.08 .002 0.09 0.40
 Race/Ethnicitya 3.77 0.51 <.001 2.78 4.77 0.68 0.22 .002 0.26 1.11
 Fraternity/Sorority Member Statusb −3.30 0.63 <.001 −4.53 −2.06 −0.95 0.22 <.001 -1.38 −0.52
 Sports Typec 3.14 0.76 <.001 −0.10 0.61 0.26 0.18 .155 −0.10 0.61
Masculine Drinking Norms d
 Excess 4.71 0.70 <.001 3.35 6.08 1.42 0.24 <.001 0.96 1.88
 Control −1.90 0.44 <.001 −2.76 −1.05 −0.79 0.30 .008 −1.37 −0.20
General Masculine Norms e
 Playboy 0.69 0.48 .153 −0.26 1.63 0.69 0.19 <.001 0.32 1.07
 Self-reliance 0.19 0.48 .698 −0.76 1.13 0.41 0.17 .013 0.09 0.74
 Winning 0.09 0.62 .888 −1.13 1.30 0.26 0.22 .233 −0.17 0.69
 Risk-taking 1.61 0.46 <.001 0.71 2.51 1.39 0.20 <.001 0.99 1.79
 Power Over Women −2.73 0.54 <.001 −3.78 −1.67 −0.97 0.28 <.001 −1.50 −0.43
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Note. Model fit: χ2(306)=987.89; RMSEA=.04; CFI=.95; SRMR=.04. Significant effects highlighted in bold. LLCI=lower limit confidence interval; ULCI=upper limit confidence interval.

a

Race/ethnicity (0=non-White, 1=White),

b

Fraternity/sorority member status (1=member of fraternity/sorority organization; 2=non-member),

c

sports type (0=co-interacting; 1=interacting),

d

Masculine Drinking Norms Measure,

e

Conformity to Masculine Norms Inventory,

f

Daily Drinking Questionnaire,

g

Brief Young Adult Alcohol Consequences Questionnaire.

Figure 1.

Figure 1.

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N=1,800. For ease of presentation, only significant standardized path coefficients (all p’s<.05) are presented, and covariances are not illustrated (significant covariances: alcohol use with alcohol consequences [β=.35]; excess with risk-taking [β=.27], playboy [β=.37], self-reliance [β=.25], winning [β=.08], and power over women [β=.44]; control with playboy [β=−.09] and self-reliance [β=.09]; playboy with self-reliance [β=.22], risk-taking [β=.38], and power over women [β=.42]; self-reliance with risk-taking [β=.28] and power over women [β=.25]; power over women with risk-taking [β=.28]. aSports type (0=co-acting, 1=interacting), bRace/ethnicity (0=non-White, 1=White), and cFraternity/sorority member status (1=member of fraternity/sorority organization; 2=non-member). MDNM=Masculine Drinking Norms Measure, CMNI=Conformity to Masculine Norms Inventory, DDQ=Daily Drinking Questionnaire, B-YAACQ=Brief Young Adult Alcohol Consequences Questionnaire.

Discussion

We examined how masculine drinking norms of excess and control were associated with alcohol use and consequences among NCAA male student-athletes. There are three key findings to highlight. First, consistent with Perrotte et al. (2020), the two-factor structural model of the MDNM fit the data well, indicating the importance of these masculine drinking norms beyond Hispanic college students. Indeed, among NCAA student-athletes, drinking in a masculine way involves the ability to drink heavy amounts of alcohol (i.e., excess), but also being able to control drinking and related behaviors (i.e., control).

Second, the masculine drinking norm of excess was positively associated with alcohol use and consequences after accounting for demographics and certain dimensions of the CMNI. This finding is consistent with our hypothesis and prior work (Perrotte et al., 2020). Our hypothesis regarding the masculine drinking norm of control was also supported, as it was related negatively to alcohol use and consequences. This is partially consistent with Perrotte et al.’s (2020) findings, which indicated a negative association between control and alcohol consequences but not alcohol use among first-year Hispanic male college students. In light of the differences in the samples across this study and other work (Perrotte et al., 2020), further research should examine whether the pathways linking the MDNM dimensions to alcohol outcomes are invariant across men from different demographic groups.

Third, the masculine drinking norm of excess was more strongly related to alcohol use and consequences than the drinking norm of control and multiple dimensions of general masculine norms. In short, alcohol-specific masculine norms (excess) appear to be more robustly related to drinking behaviors than more general masculine norms. This was also supported in Perrotte et al.’s (2020) study, which indicated that alcohol-specific masculine norms but not general masculine norms (traditional machismo/caballerismo; see Arciniega et al., 2008) were related to drinking behaviors.

Despite the novelty of the study, strong analytic approach, and a large national sample of NCAA student-athletes, there are some limitations. One limitation of the current study is that we did not include certain CMNI subscales due to survey space constraints. We recommend that researchers account for all CMNI dimensions in future research with student-athletes given prior work showing differences in heterosexual presentation between student-athletes and non-student-athletes (Ramaeker & Petrie, 2019). We also did not account for the athletic in-season/off-season, which can affect student-athletes’ drinking behaviors (e.g., Mastroleo et al., 2019). The extent to which the athletic season can impact student-athletes’ endorsement of masculine drinking norms is not yet known and warrants further inquiry. Finally, the alpha for the three items on the MDNM control subscale was .65. As discussed by Perrotte et al. (2020), excess is a more common stereotype for masculine behavior than control. Therefore, connecting control-oriented behaviors to masculinity may be less obvious for male student-athletes. Given the relatively recent development of the MDNM, further psychometric studies on this measure are needed.

There are a few implications and future research directions that stem from our findings. First, alcohol-specific masculine drinking norms could be addressed in prevention and intervention alcohol programs provided to male student-athletes. Specifically, one program goal could be to increase male athletes’ awareness of how hypermasculine drinking norms such as excess might influence their alcohol use, and how endorsing such norms and engaging in elevated alcohol use can adversely affect individual athletic performance and overall team success. Since masculine drinking norms related to control were negatively associated with alcohol use and negative drinking consequences, program developers could aim to strengthen these beliefs and help student-athletes identify and use alcohol protective behavioral strategies (PBS) designed to limit their consumption and mitigate negative alcohol-related consequences (e.g., counting drinks). Given that student-athletes may be attracted to competitive social drinking activities (Martens, 2012), developers of alcohol programs for student-athletes could consider introducing the protective strategy of limiting involvement in competitive drinking, such as playing drinking games (Grossbard et al., 2007) and incorporate drink refusal skills in situations where competitive drinking behaviors are likely to occur. Future research could examine whether alcohol PBS can moderate the impact of masculine drinking norms on alcohol outcomes when delivered through alcohol prevention or intervention programs.

In conclusion, a move from general masculine norms toward alcohol-specific masculine norms can improve researchers’ and practitioners’ understanding of the link between masculine norms and problematic drinking, and potentially enhance the impact of discussing masculine norms in alcohol intervention and prevention programming efforts, particularly among student-athletes who are at high risk for heavy alcohol use and related consequences. During the last decade, researchers have begun to study masculine norms and drinking behavior among student-athletes in the U.S. (Ramaeker & Petrie, 2019) and abroad (O’Brien et al., 2018). We encourage researchers across the globe to build on our study and continue their scholastic efforts toward advancing our understanding of masculine norms and alcohol use among male student-athletes.

Public Health Significance Statement:

Male student-athletes represent a segment of the college population who are at risk for heavy alcohol use and negative drinking consequences; however, research linking masculine norms to problematic drinking behaviors among student-athletes remains understudied. Results from the present study indicated that among male NCAA student-athletes, endorsement of masculine norms related to drinking to excess was more strongly associated with increased alcohol use and negative drinking consequences than other masculine norms. Thus, interventions for alcohol-related harm reduction among male student-athletes could address perceptions of masculinity regarding heavy drinking.

Acknowledgments

Jessica Perrotte’s effort was supported by the National Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health (NIH) under award numbers #F31AA026477 and #K01AA029473. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Footnotes

Portions of the findings reported in this paper were presented at the 2019 annual meeting of the American Psychological Association (Chicago, IL).

1

With respect to co-acting teams (e.g., swimming), athletes perform the same task as their opponent without the need for coordinating their actions with others on their team. Conversely, regarding interacting teams, athletes must coordinate their actions with their teammates (e.g., baseball). Thus, the terms co-acting vs. interacting refers to the nature of “on-field” play and allows for individuals who play co-acting sports to still be a part of a team.

2

Given the face validity of the MDNM items and their theoretical proximity to masculine beliefs regarding excessive or controlled drinking, it stands to reason that the MDNM should apply to male drinkers more broadly, including male NCAA athletes.

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