Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2013 Jun 14.
Published in final edited form as: Subst Use Misuse. 2009;44(7):934–942. doi: 10.1080/10826080802490659

The Moderating Role of Gender in the Prospective Associations Between Expectancies and Alcohol–Related Negative Consequences Among College Students

Martie P Thompson 1, Hugh Spitler 1, Thomas P Mccoy 2, Laura Marra 1, Erin L Sutfin 2, Scott D Rhodes 2, Catherine Brown 1
PMCID: PMC3682922  NIHMSID: NIHMS466978  PMID: 19938937

Abstract

This study examined if alcohol expectancies (assessed with the Comprehensive Effects of Alcohol–Brief Form) were prospectively related to negative consequences (assessed with the Rutgers Alcohol Problem Index) and if these associations varied by gender. Data were collected from 558 first-year college students at a university in the south-eastern United States as part of an intervention study conducted during their initial residence hall meetings of the fall semester of 2007. Only those students who used alcohol and completed both baseline and 3-month follow-up surveys were included in the analyses (n = 347). Mixed-model multivariate analyses indicated that higher sexuality and tension reduction expectancies were prospectively related to more alcohol consumption–related negative consequences for males but not for females. Findings suggest that intervention efforts to prevent problem drinking would benefit from being gender-specific. The study's limitations are noted.

Keywords: expectancies, college students, alcohol–related negative consequences, gender, problem drinking

Introduction

Nationally representative surveys of alcohol use among U.S. college students indicate that problem drinking is highly prevalent (Wechsler et al., 2002). Heavy alcohol use among college students is associated with alcohol use disorders in later adulthood (O'Neill, Parra, and Sher, 2001), as well as an increased likelihood of alcohol–related negative consequences, such as unintentional and intentional injuries (Hingson, Heeren,Winter, and Wechsler, 2005).

Positive expectancies about the effects of alcohol have been found to be associated with subsequent drinking problems (Blume, Lostutter, Schmaling, and Marlatt, 2003; Leigh and Stacy, 2004; Park and Grant, 2005). Alcohol expectancies and internal motivation to drink among college students vary by gender, by level of “heavy drinking,” and by environmental context (Krank, Wall, Stewart, Wiers, and Goldman, 2005; Read and Curtin, 2007). Alcohol expectancies at the beginning of the freshmen year are significantly related to drinking levels and alcohol–related problems at the end of the school year (Werner, Walker, and Greene, 1995). Alcohol expectancies are more predictive of drinking problems than are demographic variables (Baer, 2002). The fact that alcohol expectancies decrease over the 4 years of college (Sher, Wood, Wood, and Raskin, 1996) suggests that the first year of college is a pivotal time period for addressing expectancies.

Males are more likely than females to engage in problem drinking (Spear, 2002), yet data suggest that the gender gap is getting smaller (Johnston, O'Malley, and Bachman, 2002). Men also tend to evaluate alcohol–related problems less negatively than women, plan to drink more than women, and rate avoidance of negative consequences as less important to them than do women (Gaher and Simons, 2007; Patrick and Maggs, 2008). Prospective data also suggest that alcohol expectancies may be more predictive of alcohol consumption patterns among males than females (Kidorf, Sherman, Johnson, and Bigelow, 1995; Read, Wood, Lejuez, and Palfai, 2004).

The purpose of the current analysis is to explore whether expectancies are prospectively related to alcohol–related negative consequences and if these associations vary for males and females.

Method

Participants and Procedures

Data were collected as part of an intervention trial to decrease heavy episodic drinking and alcohol–related consequences among first-year college students. One male and one female freshman residence hall were selected as the study population because they each contained nine floors, were equal in total population, similar in demographics, located next to each other in the same area of campus, and permitted more effective control over cross-contamination between exposure conditions by gender. One of three exposure conditions was randomly assigned by floor within each residence hall to three of the nine floors. Baseline data were collected during student orientation sessions the day before classes began in the fall semester. Students were told that the university wanted to develop more effective alcohol intervention programs and that they were being asked to complete an anonymous 30-minute baseline survey, including questions about alcohol use, alcohol expectancies, and alcohol–related consequences, and then hear information presented in a 1-hour session by a team of two peer health educators.

Seven hundred eighty students from the two dormitories were eligible to participate in the study. Approximately 72% of eligible students completed baseline surveys (Time 1, n = 558). Of these students, 75% (n = 416) were resurveyed 3 months later (Time 2) on each residence hall floor during a residence hall meeting. We used mixed-effects logistic regression to examine differences in attrition rates by gender, race, age, Greek status, alcohol expectancy scores, and Rutgers Alcohol Problem Index (RAPI) scores. Bivariate and multivariable attrition analyses revealed no significant differences (p > .05) on any of these variables except for gender, with females being more likely to complete the 3-month follow-up survey. Students who reported that they had never consumed alcohol were excluded from the analyses, reducing the analytic sample to 347.

Measures

Alcohol-Related Negative Consequences (Dependent Variable)

The Rutgers Alcohol Problem Index (RAPI) was used to assess alcohol–related negative consequences. The 23 items were answered on a 5-point Likert scale (0–4), and responses were summed across items. The RAPI has demonstrated good convergent and discriminant validity, as well as reliability (White and Labouvie, 1989; α = .89 in current sample).

Alcohol Expectancies (Predictor)

The 15-item Comprehensive Effects of Alcohol–Brief Form (B-CEOA; Ham, Stewart, Norton, and Hope, 2005) was used to measure the perception that a particular effect would occur from drinking. Items were answered on a 4-point Likert scale. The B-CEOA has four subscales: sociability and risk, cognitive and behavioral impairment, sexuality, and tension reduction. The scale has good psychometric properties (Ham et al., 2005), and the subscales were internally consistent in our sample: sociability and risk = .80, cognitive and behavioral impairment = .73, sexuality = .70, and tension reduction = .70.

Gender (Hypothesized Moderator)

Males were assigned a score of 0 and females were assigned a score of 1.

Covariates

We controlled for race (white = 0, other = 1), age (coded continuously), if the respondent was in a Greek organization (0 = no, 1 = yes), and RAPI scores at Time 1.

Interaction Terms

We computed four interaction terms to represent the cross products of gender and each expectancy subscale. The components of the interaction terms were centered before computing the cross-products in order to reduce multicollinearity (Aiken and West, 1991).

Results

Sample Descriptives

Descriptive information on the study variables for males and females are shown in Table 1. The table also depicts gender differences on each variable using simple linear regression with adjustments for dorm floor clustering. Males were more likely than females to have higher levels of tension reduction expectancies, and females were more likely than males to be a member in a Greek organization. We performed an outlier analysis by assessing for Normality and by examining graphs using boxplots and histograms. We also performed an analysis of residuals for the regression modeling and examined influence statistics.

Table 1. Selected descriptive statistics for males and females on study variables.

Study variable Male (n = 114) Female (n = 233) t-value
Age −1.40
M 17.99 17.92
 SD 0.41 0.44
Greek status (yes) 11% 52% 5.42***
RAPI Time 1 −0.91
M 4.61 4.01
 SD 6.25 5.51
RAPI Time 2 −0.32
M 4.27 4.06
 SD 6.16 4.90
Sociability expectancies −1.73
M 16.82 16.14
 SD 3.14 3.53
Cognitive expectancies 0.19
M 10.16 10.20
 SD 1.73 2.20
Sexual expectancies −0.46
M 3.95 3.84
 SD 1.31 1.45
Tension reduction expectancie s −3.38**
M 5.14 4.53
 SD 1.19 1.28
**

p < .01;

***

p < .001.

Bivariate Correlations Between Main Study Variables

Table 2 presents the correlation matrix between the primary study variables. Most of the expectancy subscales were correlated significantly with each other, such that positive expectancies in one domain were associated with positive expectancies in other domains. Of particular note, sociability and risk, sexuality, and tension reduction expectancies were related to higher scores on the RAPI at Time 2.

Table 2. Bivariate correlations between primary study variables.

1 2 3 4 5 6
1. Time 1 RAPI 1.00
2. Time 2 RAPI .49*** 1.00
3. Sociability expectancies .36*** .30*** 1.00
4. Cognitive expectancies .02 .04 .39*** 1.00
5. Sexuality expectancies .27*** .27*** .42*** .06 1.00
6. Tension expectancies .10 .14** .2*** .09 .19*** 1.00
*

p < .05;

**

p < .01;

***

p < .001.

Multivariate Regression Analyses

Linear mixed-model regression analyses were conducted to examine prospective associations between expectancies at Time 1 and alcohol–related consequences at Time 2, adjusting for dorm floor (random effect) and controlling for age, Greek membership, race, and Time 1 RAPI scores (fixed effects). As shown in Table 2, there were significant main effects for sexual and tension reduction expectancies, with higher expectancies being associated with higher RAPI scores 3 months later. There was also a significant main effect for RAPI at Time 1. Two of the four interaction terms (Gender × Sexual Expectancies, Gender × Tension Reduction Expectancies) were significantly related to RAPI scores at Time 2.

To interpret the nature of the interaction terms, we conducted post hoc probing of significant moderation effects (see Holmbeck, 2002). Results indicated that sexuality (z = 2.86, p < .01) and tension-reduction expectancies (z = 2.24, p < .05) were significantly related to higher levels on Time 2 RAPI for males but not for females.

Discussion

Findings indicated that higher levels of sexuality and tension reduction expectancies were predictive of more alcohol–related negative consequences for males but were unrelated to females' alcohol–related consequences. Although this study was strengthened by a prospective design, psychometrically sound measures, and multivariate statistical techniques that controlled for many potential confounding variables, several limitations should be noted. First, we do not know how those who completed follow-up surveys may have differed from participants who did not complete surveys at the follow-up period. There were no significant differences on demographics or key study variables at baseline between those who completed the 3-month follow-up and those who did not except for gender. Second, although the assignment of students to residence hall by the university's housing department was random, the extent of the findings' generalizability to students in other residence halls is not certain. Third, we did not control for other variables that may influence alcohol–related negative consequences, such as personality and social functioning measures.

Limited research has examined if alcohol expectancies operate similarly for males and females in predicting drinking outcomes. Our results are consistent with two prior studies that suggest that expectancies are more predictive of alcohol consumption patterns among males than females (Kidorf et al., 1995; Read et al., 2004). Thus, this study adds to the small body of literature showing that expectancies may be significantly associated with problem drinking for males but not for females.

These findings add further support for interventions to prevent problem drinking to be gender-specific. For example, males with positive sexuality and tension-reduction expectancies may need to be cautioned that these perceptions can result in an increased likelihood of experiencing alcohol–related negative consequences. As strategies are developed to address problem drinking among college students, consideration of contextual factors must be a priority. It is well documented that health promotion and disease prevention efforts must be tailored for the population, community, or individuals targeted. Similarly, programs to reduce problem drinking among college students must incorporate strategies that acknowledge how males and females approach alcohol differently in order to increase their effectiveness.

Table 3. Mixed-model linear regression analyses predicting RAPI Time 2 scores.

Estimate1 Standard error t-value
Gender 0.32 0.60 0.53
Age 0.12 0.59 0.20
Race 0.13 0.95 0.14
Greek 0.69 0.58 1.19
Time 1 RAPI 0.37 0.05 7.78***
Expectancies
Sociability and risk 0.18 0.09 1.92
Cognitive/behavioral 0.24 0.27 0.90
Sexuality 1.05 0.35 3.02**
Tension reduction 0.92 0.38 2.41**
Interaction terms
Gender × Sociability 0.18 0.19 0.92
Gender × Cognitive −0.37 0.31 −1.19
Gender × Sexuality −0.98 0.42 −2.32*
Gender × Tension −0.90 0.45 −1.99*
1

Estimates are unstandardized regression coefficients.

*

p < .05;

**

p < .01;

***

p < .001.

Acknowledgments

This research was funded by a cooperative agreement (5U18AA015684-02) from the National Institute on Alcohol Abuse and Alcoholism to Dr. Hugh Spitler. We wish to thank Dr. Michael Hilton and Mr. Roger Hartman at the NIAAA for their helpful feedback on this manuscript.

Biographies

graphic file with name nihms466978b1.gif

Martie P. Thompson, PhD, is a Research Professor in the Department of Public Health Sciences and the Director of the Center for Research and Collaborative Activities at Clemson University. Her research focuses on risk factors and consequences of victimization and suicidal behavior, as well as high-risk behaviors among first-year college students.

Hugh D. Spitler, Ph.D., is an Associate Professor in the Department of Public Health Sciences. His research focuses on reducing the incidence of heavy, high-risk drinking among college students, and controlling the risks and consequences resulting from “heavy drinking” through the development of more effective intervention programs among first-year college students.

Thomas P. McCoy, M.S., is a Biostatistician in the Department of Biostatistical Sciences at Wake Forest University School of Medicine. His research focuses on design and analysis of early phase cancer trials and also intervention studies for high-risk drinking and alcohol consumption–related consequences among college students.

graphic file with name nihms466978b2.gif

Laura Marra graduated from Clemson University with a B.S. in Psychology, and worked as a Research Assistant for the Department of Public Health Sciences. Her research focuses on high-risk drinking, body image, and disordered eating among young adults.

Erin L. Sutfin, Ph.D., is a Research Assistant Professor in the Department of Social Sciences and Health Policy within the Division of Public Health Sciences at Wake Forest University School of Medicine. Her research focuses on health risk behaviors among young adults, with an emphasis on tobacco and alcohol use among college students.

graphic file with name nihms466978b3.gif

Scott D. Rhodes, Ph.D., MPH, is an Associate Professor in the Departments of Social Sciences and Health Policy and Internal Medicine at Wake Forest University School of Medicine. His research focuses on the development, implementation, and evaluation of interventions designed to improve the health and well-being of vulnerable communities.

graphic file with name nihms466978b4.gif

Catherine A. Brown, B.S., is a graduate of Clemson University's Public Health Science department with a concentration in Health Education and Promotion. She is currently involved in research at the Medical University of South Carolina's Psychiatry and Behavioral Sciences department, where her research focuses on pharmaceuticals and weight management.

References

  1. Aiken LS, West SG. Multiple regression: testing and interpreting interactions. Newbury Park, CA: Sage; 1991. [Google Scholar]
  2. Baer JS. Student factors: understanding individual variation in college drinking. Journal of Studies on Alcohol. 2002;14(Suppl.):40–53. doi: 10.15288/jsas.2002.s14.40. [DOI] [PubMed] [Google Scholar]
  3. Blume AW, Lostutter BS, Schmaling KB, Marlatt AG. Beliefs about drinking behavior predict drinking consequences. Journal of Psychoactive Drugs. 2003;35(3):395–399. doi: 10.1080/02791072.2003.10400025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Gaher RM, Simons JS. Evaluations and expectancies of alcohol and marijuana problems among college students. Psychology of Addictive Behavior. 2007;21:545–554. doi: 10.1037/0893-164X.21.4.545. [DOI] [PubMed] [Google Scholar]
  5. Ham LS, Stewart SH, Norton PJ, Hope DA. Psychometric assessment of the comprehensive effects of alcohol questionnaire: comparing a brief version to the original full scale. Journal of Psychopathology and Behavioral Assessment. 2005;27:141–158. [Google Scholar]
  6. Hingson R, Heeren T, Winter M, Wechsler H. Magnitude of alcohol-related mortality and morbidity among U.S. college students ages 18–24: changes from 1998 to 2001. Annual Review of Public Health. 2005;26:259–279. doi: 10.1146/annurev.publhealth.26.021304.144652. [DOI] [PubMed] [Google Scholar]
  7. Holmbeck GN. Post-hoc probing of significant moderational and mediational effects in studies of pediatric populations. Journal of Pediatric Psychology. 2002;27:87–96. doi: 10.1093/jpepsy/27.1.87. [DOI] [PubMed] [Google Scholar]
  8. Johnston LD, O'Malley PM, Bachman JG. Monitoring the Future: National Survey Results on Drug Use, 1975–2001: Volume I Secondary School Students. Bethesda, MD: National Institute on Drug Abuse; 2002. NIH Pub.No.02–5106. [Google Scholar]
  9. Kidorf M, Sherman MF, Johnson JG, Bigelow GE. Alcohol expectancies and change in beer consumption of first-year college students. Addictive Behaviors. 1995;20:225–231. doi: 10.1016/0306-4603(94)00067-0. [DOI] [PubMed] [Google Scholar]
  10. Krank M, Wall AM, Stewart SH, Wiers RW, Goldman MS. Context effects on alcohol congnitions. Alcohol in Clinical and Experimental Research. 2005;29:196–206. doi: 10.1097/01.alc.0000153545.36787.c8. [DOI] [PubMed] [Google Scholar]
  11. Leigh BC, Stacy AW. Alcohol expectancies and drinking in different age groups. Addiction. 2004;99:215–227. doi: 10.1111/j.1360-0443.2003.00641.x. [DOI] [PubMed] [Google Scholar]
  12. O'Neill SE, Parra GR, Sher KJ. Clinical relevance of heavy drinking during college years: cross-sectional and prospective perspectives. Psychology of Addictive Behaviors. 2001;15:350–359. doi: 10.1037//0893-164x.15.4.350. [DOI] [PubMed] [Google Scholar]
  13. Park CL, Grant C. Determinants of positive and negative consequences of alcohol consumption in college students: alcohol use, gender, and physiological characteristics. Addictive Behaviors. 2005;30:755–765. doi: 10.1016/j.addbeh.2004.08.021. [DOI] [PubMed] [Google Scholar]
  14. Patrick ME, Maggs JL. Short-term changes in plans to drink and importance of positive and negative alcohol consequences. Journal of Adolescence. 2007;31:307–321. doi: 10.10.16/j.adolescence.2008.06.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Read JP, Curtin W. Contextual influences on alcohol expectancy processes. Journal of Studies on Alcohol and Drugs. 2007;68:739–770. doi: 10.15288/jsad.2007.68.759. [DOI] [PubMed] [Google Scholar]
  16. Read JP, Wood MD, Lejuez CW, Palfai TP. Gender, alcohol consumption, and differing alcohol expectancy dimensions in college drinkers. Experimental and Clinical Psy-chopharmacology. 2004;12:298–308. doi: 10.1037/1064-1297.12.4.298. [DOI] [PubMed] [Google Scholar]
  17. Sher KJ, Wood MD, Wood PK, Raskin G. Alcohol outcome expectancies and alcohol use: a latent variable cross-lagged panel study. Journal of Abnormal Psychology. 1996;105:561–574. doi: 10.1037/0021-843X.105.4.561. [DOI] [PubMed] [Google Scholar]
  18. Spear L. Alcohol's effects on adolescents. Women and Alcohol: An Update. 2002;24:287–291. [PMC free article] [PubMed] [Google Scholar]
  19. Wechsler H, Lee JE, Kuo M, Seibring M, Nelson TF, Lee H. Trends in college binge drinking during a period of increased prevention efforts: findings from 4 Harvard School of Public Health College Alcohol Study surveys: 1993–2001. Journal of American College Health. 2002;50:203–217. doi: 10.1080/07448480209595713. [DOI] [PubMed] [Google Scholar]
  20. Werner MJ, Walker LS, Greene JW. Relationship of alcohol expectancies to problem drinking among college women. Journal of Adolescent Health. 1995;16:191–199. doi: 10.1016/1054-139X(94)00065-M. [DOI] [PubMed] [Google Scholar]
  21. White HR, Labouvie EW. Toward the assessmentof adolescent problem drinking. Journal of Studies on Alcohol. 1989;50:30–37. doi: 10.15288/jsa.1989.50.30. [DOI] [PubMed] [Google Scholar]

RESOURCES