DOI
https://doi.org/10.25772/MTRQ-1H83
Defense Date
2013
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Education
First Advisor
James McMillan
Abstract
Previous literature provides an overview of the multiple relationships between alcohol use, protective behavioral strategies (PBS), alcohol-related negative consequences, depression, and sleep problems among college students, as well as differences by individual level characteristics, such as age, gender, and race/ethnicity. Several studies have found that specific demographic groups of students are more likely to reach a higher blood alcohol content (BAC) when “partying” or socializing (Turner, Bauerle, & Shu, 2004; Crotty, 2011). A variety of studies have also confirmed the positive relationship between high blood alcohol content and experiencing alcohol-related negative consequences (Turner, et al., 2004; Martens, Taylor, Damann, Page, Mowry, & Cimini, 2004; Borden, Martens, McBride, Sheline, Bloch, & Dude, 2011; Crotty, 2011). Additional studies have explored the role that protective behaviors play in the alcohol consumption-negative consequences relationship (Martens et al., 2004; Borden et al., 2011; Haines, Barker, & Rice, 2006; Martens, Martin, Littlefield, Murphy, & Cimini, 2011). These studies conclude that the frequency of protective behavior use and the number of these behaviors that are used when consuming alcohol are associated with the likelihood of a student experiencing negative consequences. Specifically, the negative relationship between protective behavior use and likelihood of experiencing negative consequences as a result of binge drinking is stronger for students who rarely use protective behaviors (Martens et al., 2004). Recent studies have also explored the role that depressive symptoms play in a model with alcohol use and alcohol-related negative consequences. The prevalence of college students who were diagnosed with depression in the last school year presents a great need to study its relationship with these constructs. Students with poor mental health or depression are also more likely to experience alcohol-related negative consequences (Weitzman, 2004), and there is a direct association between depressive symptoms and negative consequences, but not necessarily between alcohol use and depressive symptoms (Vickers, Patten, Bronars, Lane, Stevens, Croghan, Schroeder, & Clark, 2004). One study also suggests that protective behaviors partially mediate the relationship between depressive symptoms and negative consequences (Martens, Martin, Hatchett, Fowler, Fleming, Karakashian, & Cimini, 2008). Further, students with depressive symptoms who use protective behaviors drink less and experience fewer negative consequences, as compared to students without depressive symptoms who use protective behaviors (LaBrie, Kenney, Lac, Garcia, & Ferraiolo, 2009). Sleeping problems play an important role in the relationship between alcohol consumption and alcohol-related negative consequences. Poorer global sleep quality is associated with alcohol-related negative consequences after controlling for alcohol use. Further, among heavier drinkers, those with poorer sleep quality experienced greater levels of negative consequences than those who had better sleep quality (Kenney, LaBrie, Hummer, & Pham, 2012). The purpose of this study was to examine the relationships between alcohol use measured by estimated Blood Alcohol Content (eBAC), PBS, depression, and sleep problems, as they explain the variance of alcohol-related negative consequences using the spring 2009 national aggregate data set of the American College Health Association National College Health Assessment (ACHA-NCHA). This dataset was comprised of a random sample of undergraduate and graduate students from 117 U.S. colleges and universities (n=53,850). Reliability analyses, confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used for model specification and evaluation. Model fit indices for the current study indicate that the model and the data in this study are a good fit, demonstrated by RMSEA= .044, 90% CI (.044, .044) and SRMR= .066. Findings suggest that an additive effect of eBAC, PBS, depression, sleep problems, and certain demographics explain 39% of the variance in alcohol-related negative consequences and greatly impact the amount of harm that college students may experience as a result of their alcohol use. Results from the current study may assist clinicians and health educators who want to improve the probability that they will be able help reduce negative consequences among college students when they drink alcohol. These staff may engage students in a conversation about risk reduction (e.g. one on one consults, campus-wide media campaign) and also provide support for conducting brief screenings about alcohol so that clinicians may be more effective in helping students to reduce alcohol-related negative consequences. The results from this study may also assist researchers in finding more relationships that account for some of the unexplained variance in this study. Interpreting these predictive relationships are important to the way that students are screened for alcohol problems on college campuses, as well as decisions that college students make about alcohol in the greater context of healthy lifestyle decisions. Future research could include repeating the analysis with each race/ethnicity separated out instead of as a dichotomous variable (white/non-white), conducting a similar analysis with each negative consequence instead of as a scale, developing a more complete sleep problems scale within the ACHA-NCHA with improved reliability, and a further investigation into the positive correlation between sleep problems and depression in order to explore other variables that mediate the relationship between depression and sleep problems among college students.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
August 2013