UNDERGRADUATE STUDENT HIGH RISK DRINKING USE: IMPLICATIONS FOR STUDENT AFFAIRS HEALTH PROMOTION PRACTICE By ELEANOR MAUREEN MILLER A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL F ULFILLMENT OF THE REQUIREMENTS FOR TH E DEGREE OF DOCTOR OF EDUCATION UNIVERSITY OF FLORIDA 2014
2 Â© 2014 Eleanor Maureen Miller
3 To my parents, Alan and Shelia, and my sister Leigh Anne. You are my light, my heart , and my world. I love you. To Dr. Luis PonjuÃ¡n a brilliant and supportive mentor, colleague, and friend. This disse rtation is dedicated to all of you.
4 ACKNOWLEDGMENTS I would not be where I am today without the unconditional love, support, and inspir ation of my family : my parents, Alan and Shelia, and my sister, Leigh Anne. I do not have the words to be able to express my gratitude for all that they have each sacrificed, beginning from my decision in spring 2010 to return to school to pursue this dre am to the point of watching and cheering me on as I walk across the stage four years later. I am truly grateful for my parents who role modeled to my sister and me many times over the accomplishment of returning to school and pursuing your passion and lif encouraging me every day to keep moving forward and to tango on. I am forever indebted to their love and unwavering confidence , and will do my very best each to make my family p roud . I would like to thank my dissertation committee, Dr. Dale Campbell, Dr. Arthur Sandeen, Dr. Ana Puig, and Dr. Virginia Dodd, for their support, feedback, and exp ertise, which has only helped to strengthen me professionally and personally. I would like to thank my support group of fellow Student Affairs professionals and doctoral students: Diane Bruxvoort, Beverly Cribbs, Cliff Haynes, JoCynda Hudson, Mary C. Jorda n, Ayola Singh Kreitz, Mike Mironack, Michael Murphy, Leslie Pendleton, Mary Anne Primack, and Jeannie Starobin. The amount of unconditional support, encouragement, and friendship is something I am forever grateful to have to help me finish this journey. I would also like to recognize my work family who never stopped cheering me on even during the times when things seemed insurmountable. I would a lso like to thank Meridith , an amazing person and beautiful friend.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 LIST OF DEFINITIONS ................................ ................................ ................................ ... 9 ABSTRACT ................................ ................................ ................................ ................... 10 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 12 Statement of the Problem ................................ ................................ ....................... 17 Purpose of the Study ................................ ................................ .............................. 18 Research Questions ................................ ................................ ............................... 18 Importance of Study ................................ ................................ ................................ 19 Organization of Remaining Chapters ................................ ................................ ...... 19 2 LITERATURE REVIEW ................................ ................................ .......................... 21 Social and Psychological Factors Related with Excessive Drinking ....................... 21 Gender ................................ ................................ ................................ ............. 22 Ethnic ity ................................ ................................ ................................ ............ 24 Academic Classification and Age ................................ ................................ ..... 25 Work Status ................................ ................................ ................................ ...... 29 Greek Affi liation ................................ ................................ ................................ 29 Residency Status ................................ ................................ ............................. 32 Event Level and Context Drinking ................................ ................................ .... 34 Theoretical Framework ................................ ................................ ........................... 36 Ecological Model of Health Behavior ................................ ................................ 37 Intrapersonal Factors and Microsystem ................................ ........................... 41 Interpersonal Factors and Mesosystem ................................ ........................... 42 Institutional Factors and Exosystem ................................ ................................ . 42 Community and Policy Factors and Macrosystem ................................ ............ 43 Time ................................ ................................ ................................ ................. 44 Chapter Summary ................................ ................................ ................................ ... 45 3 MET HODOLOGY ................................ ................................ ................................ ... 46 Survey Instrument ................................ ................................ ................................ ... 47 Data Source ................................ ................................ ................................ ............ 48 Student Sample 1 (S pring 2011) ................................ ................................ ...... 50 Student Sample 2 (Fall 2011) ................................ ................................ ........... 51
6 Measures ................................ ................................ ................................ ................ 52 Dependen t Variable ................................ ................................ .......................... 52 Independent Variables ................................ ................................ ..................... 53 Data Analysis ................................ ................................ ................................ .......... 55 4 DATA ANAL YSIS ................................ ................................ ................................ .... 58 Descriptive Univariate Results ................................ ................................ ................ 58 Descriptive Crosstabulation ................................ ................................ .................... 59 Independent Sample T Tests ................................ ................................ .................. 61 Analysis of Variance ................................ ................................ ............................... 64 Multivariate Regression Analysis ................................ ................................ ............ 65 Student Individual Characteristics ................................ ................................ .... 66 Student Residency and Engagement ................................ ............................... 66 Chapter Summary ................................ ................................ ................................ ... 67 5 DISCUSSION, IMPLICATIONS, RECOMMENDATIONS ................................ ....... 73 Summary of the Results ................................ ................................ .......................... 73 Di scussion of Findings for Hypotheses and Research Questions ........................... 74 Student Individual Characteristics ................................ ................................ ........... 74 Student Enrollment Period ................................ ................................ ................ 81 Limitations ................................ ................................ ................................ ............... 82 Implications for Health Promotion Practitioners ................................ ...................... 84 Re commendations for Health Promotion Practitioners ................................ ........... 85 Programmatic Recommendations at the Organizational (Exosystem) Level .... 86 Policy Recommendations at the Organizational (Exosystem) Level ................. 87 Programmatic Recommendations at the Interpersonal (Mesosystem) Level .... 88 Policy Recommendations at the Interpersonal (Mesosystem) Level ................ 88 Programmatic Recommendations at the Intrapersonal (Microsystem) Level .... 89 Policy Recommendations at the Intrapersonal (Microsystem) Level ................ 89 Conclusion ................................ ................................ ................................ .............. 90 APPENDIX : CORE ALCOHOL AND DRUG SURVEY LONG FORM ........................... 92 LIST OF REFERENCES ................................ ................................ ............................... 96 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 105
7 LIST OF TABLES Table page 3 1 Number of drinks consumed in a week by drinking behavior categories ............ 56 3 2 Independent variables for the high risk drin king behavior regression model ...... 57 4 1 Academic term descriptive statistics, dependent variable (n = 1,198) ................ 68 4 2 Student age by w ork status ................................ ................................ ................ 68 4 3 Student age by residency status ................................ ................................ ......... 68 4 4 Student age by living with status ................................ ................................ ........ 69 4 5 Student academic classification ................................ ................................ .......... 69 4 6 Student age by academic classification ................................ .............................. 69 4 7 Student gender by average number of drinks per week t test ............................ 69 4 8 Student age by average number of drinks per week t test ................................ . 69 4 9 Student ethnici ty by average number of drinks per week t test .......................... 69 4 10 test ........... 70 4 11 test ................... 70 4 12 test ............................ 70 4 13 Greek status by average number of drinks per week t test ................................ 70 4 14 ............ 70 4 15 hoc tests of mean differences for average number of drinks by ................................ ................................ .................. 71 4 16 sidency status ...................... 71 4 17 hoc tests of mean differences for average number of drinks by ................................ ................................ .................. 71 4 18 Standardized beta coefficients for multivariate regression analysis on average number of drinks per week ................................ ................................ ... 72
8 LIST OF FIGURES Figure page 2 1 ....... 40 4 1 Students self reported weekly drinking patterns ................................ ................. 68
9 LIST OF DEFINITIONS Binge or High Risk Drinking F our or more drinks for females or five or more drinks for males in a two hour time period at least once in a two week time frame (Wechsler et al., 1994). Blood Alcohol Concentration (BAC) n a person's bloodstream. BAC is commonly expressed in percentage terms. For instance, having a BAC of 0.08 percent means that a person has eight parts Information System, 2014). At the 0.08% leve l, decision making and impulse control are slowed, memory begins to lapse, and driving related skills are noticeably impaired (Hingson & White, 2010). Drink Standard drink equivalents are 12 ounces of beer, 12 ounces of wine cooler, five ounces of wine, o r 1.5 ounces of liquor in a shot or mixed drink (White, Kraus, & Swartzwelder, 2006). Environmental Management AOD strategies that encompass more than just the individual legal environme nt that affects AOD use, which in turn can be influenced through a combination of institutional, community, and Whitman, Colthurst, Cretella, Gilbreath, Rosati, & Zweig, 1998, p. 2). Frequent Binge Drinking B inge drink ing three or more times in a two week time period (Wechsler et al., 2002). Harvard School of Public Health College Alcohol Study (CAS): National surveys of college students at 120 four year colleges in 40 states conducted in 1993, 1997, 1999, and 2001, an d then in 2005 at previously identified schools with increased levels of alcohol rates (Harvard School of Public Health, 2005).
10 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillm ent of the Requirements for the Degree of Doctor of Education UNDERGRADUATE STUDENT HIGH RISK DRINKING USE: IMPLICATIONS FOR STUDENT AFFAIRS HEALTH PROMOTION PRACTICE By Eleanor Maureen Miller August 2014 Chair: Dale Campbell Major: Higher Education Ad ministration High risk drinking among the college student population remains a serious public health issue that campuses nationwide struggle to address on a daily basis. Annually, thousands of college students across the country experience a multitude of negative consequences associated with high risk drinking behaviors. T he present quantitative study , utilizing the Ecological Model of Health Behavior supported by Urie examined several social and psychological risk drinking behaviors. These factors were categorized into three blocks, student individual characteristics, student residency and engagement, and student enrollment period. This research utilized student alcohol data previously collected during two time frames, spring and fall 2011 , as time is a key factor of interest in this study when determining what impact, if any exists when comparing the nuances associated with two different semester s. Results from this research indicated there were significant differences in two of the three blocks, student individual characteristics and student residency and engagement. This study concludes with programmatic and policy
11 recommendations on decreasin g high risk drinking behaviors outlined through each of the levels within the theoretical framework.
12 CHAPTER 1 INTRODUCTION The impact of high risk drinking behaviors upon the health and safety of college students, as well as the effect on the campus and surround ing local community, can be far reaching and is a long standing and complex issue administrators struggle to address on a continuous basis. The National Institute on Alcohol Abuse and Alcoholism essive drinking in 1976 and since that seminal work, advances in research have resulted in a more comprehensive and in depth understanding of alcohol abuse and the associated negative consequences among college students. Almost 40 years since that report there are still many unanswered questions and ongoing challenges. Multiple national surveys denote that approximately 80% of traditional college students, defined as 18 to 24 year olds attending four year institutions, consume alcohol (e.g. beer, wine, e tc.) annually (Hingson & White, 2012). Also, previous research indicates evidence of some first year students entering college with established drinking patterns and behaviors. These behaviors were formalized while in high school and for some, middle sch ool (Ross & DeJong, 2008). This study and earlier reports, suggest that pre college alcohol consumption behaviors are powerful predictors of college drinking behaviors and point to the need for new and continued research studies. The Harvard School of P ublic Health College Alcohol Study (CAS), a groundbreaking initiative launched by Dr. Henry Wechsler in 1993 to collect data on college drinking, utilized a nationally representative sample of more than fourteen thousand undergraduates at 140 four year ins titutions. The CAS data indicated that more than 44% of the respondents met the criteria for binge drinkers (four or more
13 drinks for females or five or more drinks for males in a two hour time period at least once in a two week time frame) and one fifth o f the participants met the criteria for frequent binge drinkers (three or more binge drinking episodes in the past two weeks) (Wechsler, Davenport, Dowdall, Moeykens, & Castillo, 1994). In the 2001 CAS study, similar to the 1993, 1997, and 1999 results, f indings confirmed the national binge drinking rate remained steady at 44% (Wechsler, Lee, Kuo, Seibring, Nelson, & Lee, 2002). In addition, binge drinking was more prevalent among males, members of fraternities and sororities, and student athletes. The CA S, similar to the NIAAA report, highlighted the ongoing challenges, but also shed light on the affects of alcohol consumption on students across all racial and ethnic groups. Specifically, data indicated 50% of White students were binge drinkers, compared to 34% of Hispanic students and 22% of African American students (Wechsler et al., 2002). National studies highlighting the negative consequences of binge drinking are irrefutable and thus, reinforce the need to address this issue. Binge drinking cause s students to face many detrimental individual health outcomes. Hingson and colleagues (2009) analyzed data on 18 to 24 year olds, college and non college students, from each of the following data sources: the National Highway Traffic Safety Administratio n Fatality Analysis Reporting System, Centers for Disease Control and Prevention Injury Mortality Data, National Coroner Studies, census and college enrollment data, the National Household Survey on Drug Use and Health, and the College Alcohol Study. For comparison purposes, separate analyses were conducted for the time frames of 1998 2001 and 1998 2005. Among 18 to 24 year old college students, deaths as a result of all alcohol related unintentional injuries, including traffic and other unintentional
14 inj uries (i.e., poisoning, drowning, fall, gunshot), increased from 1,442 in 1998 to 1,647 in 2001 to 1,825 in 2005. Between 1998 and 2005, the percentages of college students ages 18 to 24 who reported having five or more drinks on at least one time in the past month increased from 41.7% to 44.7% (Hingson, Zha, & Weitzman, 2009). In addition, approximately 700,000 college students are assaulted or experience violence from an intoxicated peer, and 97,000 college students experienced an alcohol related sexual assault or date rape (Hingson, et al., 2009). College students who participate in high risk drinking behaviors engage in unsafe sexual behaviors. Research indicates that 400,000 college students between the ages of 18 and 24 report having unprotected sex and 100,000 students report being too drunk to know if they consented to having sex (Hingson, Heeren, Winter, & Wechsler, 2003). Regarding driving while intoxicated, from 1999 to 2002, the percentage of college students ages 18 24 who reported driving whi le under the influence of alcohol during the past year increased from 26.9% to 31.4%. However, by 2005 these rates had decreased to 28.9% (Hingson et al., 2009). Even with the slight decrease, driving while intoxicated remains a serious public health iss ue requiring ongoing educational and legislative initiatives. During the college tenure, more than 150,000 students develop an alcohol related health issue (Hingson, Heeren, Zakocs, Kopster, & Wechsler, 2002). Previous research reports between 1.2% to 1. 5% of college students reported an alcohol or substance use related suicide attempt in the past year (Presley, Leichliter, & Meilman, 1998). Further, in questionnaire based self reports about their alcohol consumption in the past 12 months, 31% of college students met criteria for a diagnosis of alcohol abuse and 6% met the criteria for alcohol dependence (Knight, Wechsler,
15 Kuo, Seibring, Weitzman, & Schuckit, 2002). Academic performance, including missing class, performing poorly on exams or papers, falli ng behind in class, and getting lower grades in general is another negative consequence students experience as a result of their heavy drinking (Engs, Diebold, & Hanson, 1996; Presley, Meilman, & Cashin, 1996a; Presley, Meilman, Cashin, & Lyerla, 1996b; We chsler et al., 2002). In the 1999 College Alcohol Study, based on a nationally representative sample, 62.5% of students who identified as binge drinkers reported missing a class and 46.3% reported getting behind in their schoolwork as a consequence of the ir alcohol consumption (Wechsler, Lee, Kuo, & Lee, 2000). In a national survey of college students, those who engaged in high risk drinking and consumed alcohol at least three times per week reported the following consequences as compared to their peers who drank but not heavily: 5.9 times more likely to do badly on a test or project, 40.2% compared to 6.8% respectively; 5.4 times more likely to have missed a class, 64.4% compared to 11.9% respectively; and 4.2 times more likely to have experienced a memo ry loss due to drinking, 64.2% compared to 15.3% respectively (Presley & Pimentel, 2006). A national survey revealed that average students consumed 9.8 drinks (Presley et al., 1996a). In addition to high risk alcohol consumption damaging cognitive skills necessary for performing well academically, the very act of drinking and the recovery from, detracts time away from other activities related to making positive progress in school. Excessive alcohol consumption can indirectly affect academic performance by decreasing the time
1 6 available for studying, going to class, and other academically r elated tasks (Porter & Prior, 2007). National surveys specify that from 1999 to 2007 (Substance Abuse and Mental Health Services Administration, 2000, 2002, 2006, 2008) the percent of 18 to 24 year old college students who consumed five or more drinks on an occasion in the past 30 days rose from 41.7% to 43.8%, a substantial 5% proportional increase within an eight year span. Students categorized as binge drinkers are significantly more likely than non binge drinkers to experience a variety of the pre viously described alcohol related consequences, and frequent binge drinkers are more likely than infrequent binge drinkers to experience these negative consequences (Wechsler et al., 1994; Wechsler & Isaac, 1992; Wechsler et al., 2000). Students categoriz ed as binge drinkers are more likely to experience additional health and behavioral problems such as smoking cigarettes and engaging in illicit drug use (Wechsler, Dowdall, Davenport, & Castillo, 1995), and are more likely to report blood alcohol concentra tion (BAC) levels greater than the .08 legal limit for intoxication (McMillen, Hillis, & Brown, 2009). These serious findings contribute to the importance of research examining the many complexities associated with students engaging in high risk drinking behaviors . Students who identify as either abstainers or social drinkers also report being adversely impacted by their peers who engage in frequent binge drinking. Specifically, 75% of these abstainers or social drinkers report experiencing the followin g secondhand negative consequences as a result of their interactions with heavy binge drinkers: property damage; unwanted sexual advances; physical aggression; sleep and study time disruptions; and personal insults (Nelson & Winters, 2012).
17 As demonstrat ed through a brief review of the research, these studies highlight the seriousness and urgency to address binge drinking among the college student population, as challenges remain for higher education leaders to focus on this complicated issue. These chal lenges include the stagnant rates of decreasing this type of behavior, the dangerous consequences of binge drinking, and the societal norms and campus climate regarding alcohol consumption. This brief snapshot of the negative consequences associated with excessive alcohol consumption and the risky drinking behaviors of the college student population provide the framework and rationale for this study. S tatement of the Problem Binge drinking and the associated negative consequences have continued to increase over the past few decades and are now identified as a significant health risk for the college student population, a challenge for higher education leaders, and a primary research focus for many student affairs health promotion practitioners. College s tud ents spend $5.5 billion annually on alcohol, which is more than their expenses for books and nonalcoholic beverages combined (Eigan, 1991). Societal costs for underage drinking are estimated at $61.9 billion annually. This cost includes traffic crashes, medical treatment, alcohol poisoning, violence, and crime (Miller, Levy, Spicer, & Taylor, 2006). Addressing binge drinking and the associated negative consequences requires a comprehensive approach for both immediate and sustained impactful positive beha vior changes which incorporate both individual and environmental management strategies. This study sought to examine and understand this ongoing student health behaviors crisis in help inform higher education health promotion professionals .
18 Purpose of the Study Despite the abundance of research studies, awareness of high risk drinking and the negative outcomes for many college students, student affairs health promotion practitioners will benefit from research that provides new insights on how to address th is ongoing public health and student wellness issue. Therefore, the purpose of this study was risk drinking patterns; and 2) to provide new insights and strategies (via programmatic and policy recommendations) for student affairs health promotion practitioners to utilize for reducing high risk drinking behaviors among the college student population. R esearch Questions In order to address the purpose of this dissertation, th e following research questions we re posed: 1. To what extent do individual demographics and student residency and reported high risk drink ing behaviors? 2. To what extent does student enrollment in the spring and fall semesters reported high risk drinking behaviors? These two complementary research questions rely on the current research literature. The first rese arch question examines specific student factors identified in the student drinking behavior literature. For example, gender differences in drinking are greater than m behavior as a function of the time period of the academic term. This nuanced
19 investigation of these po tential time period effects may alter how student affairs health promotion practitioners plan future outreach initiatives. Finally, for both of these research questions, the ecology theoretical framework is utilized to better understand the influence of t I mportance of Study This study will contribute to the alcohol and other drug abuse literature by helping behaviors are ca ptured, as well as exploring the potential environmental factors impacting alcohol consumption specific to the spring and fall semesters, respectively. Additionally, this study will assist student affairs health promotion practitioners in determining whic h strategies to utilize to address high risk drinking at various levels of ecological influence through a systems theory model. Lastly, this study will identify specific individual demographic, student residency and engagement factors that are more likel y to contribute to high risk drinking, thus allowing campuses to focus more of their resources on developing and implementing tailored interventions designed to create long lasting and positive behavior changes in alcohol consumption behaviors among the co llege student population. O rganization of Remaining Chapters Chapter 1 provides background information relevant to this study, the overall purpose and significance, and the specific research questi ons to be answered. Chapter 2 reviews the literature on th e overall scope of college student drinking, as related to specific demographics of interest in this study: gender, ethnicity, classification and age, work status, Greek affiliation, and residency status. An explanation of the theoretical framework, the e cological model, utilized fo r this study will be included. Chapter 3
20 includes the details pertaining to the methods and procedures utilized to answer the research questions, as well as outlining the data conditioning and data analyses techniques . Chapter 4 provides the data analyses results and chapter 5 includes the discussion of findings, implications and recommendations for health promotion practitioners, and study limitations.
21 CHAPTER 2 LITERATURE REVIEW Chapter 2 will present findings from a comprehensive rev iew of the literature risk drinking behaviors and the primary factors associated with those behaviors. Towards that goal, this review of the research will explore literature from the following academic are as: student affairs, health promotion, and public health. Upon examining the literature, the second half of the chapter will conclude with a discussion of the theoretical framework that guides the direction of this research. The next section of C hapter 2 highlights and summarizes the predictors of high risk drinking among the college student population as identified in the literature, specifically focusing on the factors of interest for this particular study. The primary themes explored in the literatur e are the social and psychological factors associated with excessive drinking in college students. Within these themes, factors prevalent in the literature include: gender; ethnicity; classification and age; work status; Greek affiliation; student residen cy; and event level and context drinking, all related to college student high risk drinking behaviors. Examining this critical public health issue through the lens of these themes and other associated factors provides a deeper understanding of the complex ity and challenges of addressing college student high risk drinking behaviors, confirming the need for this study. Social and Psychological Factors Related with Excessive Drinking As highlighted and examined in greater detail in Chapter 1 , the national st atistics regarding college student drinking and the adverse health consequences including alcohol related deaths, injuries, violence, alcohol impaired driving, and blackouts,
22 provide a strong rationale for this study, and reinforce the seriousness of this issue. While it is important for campuses to recognize and are aware of these statistics that provide the backdrop to the ongoing national discussion around college student high risk drinking behaviors, it is even more critical that campuses identify and grasp the complexities associated with the factors related with excessive alcohol consumption. Scholars and practitioners argue that when these social and psychological factors are recognized, campuses can begin to focus on the nuances and create and impl ement specific theory and evidence based strategies targeting different student populations through a comprehensive, multi pronged approach. Thus, the subsequent sections in C hapter 2 provide a comprehensive discussion of the extant research literature, s pecifically highlighting factors associated with high risk drinking behaviors. Gender Scholars have examined various individual demographic characteristics associated with high risk drinking behavior. Given the notable gender differences in high risk drin king behaviors, researchers have extensively examined gender as an essential individual characteristic because of the consistent findings that reveal college aged males compared to females exhibit high risk drinking behaviors and the associated negative co nsequences. Specifically, males consume alcohol more frequently and in greater amounts than female students (Engs et al., 1996; Wechsler et al., 1994; Presley & Meilman, 1992; Wechsler et al., 1995; Presley et al., 1996a). Despite these long standing tre nds, there is growing concern regarding female However, these rates of high ri sk drinking among college women have been increasing
23 over time with almost 40% of college women reporting binge drinking, and another 20% reporting binge drinking three or more times in the past two weeks (Wechsler et al., 2002). In another national study , 50% of male students and 34% of female students Johnston, 2002). Given the enrollment trends that suggest women now represent a majority of incoming undergraduates on col lege campuses, these troubling increases experiencing negative consequences are steadily becoming more similar to those of McCabe (2002) examined male and femal e drinking behaviors and found that sophomore, junior, and senior females were less likely to engage in high risk drinking as compared to freshman women. Conversely, males who were sophomores, juniors, and seniors were more likely to engage in high risk d rinking behaviors when compared with freshmen men. These findings point to the need for designing health promotion These l atter factors will be discussed in greater det ail later in C hapter 2 . Gender differences in risk factors for high risk drinking deserve closer attention in the context of the surrounding environment. Earlier work by McCabe (2002) compared males living in a fraternity house to males living in one of t hree conditions namely: substance free residence hall room, living and learning residence hall room, and off campus. Study findings revealed that residing in a fraternity house was a significant risk factor for excessive alcohol consumption. In contrast, McCabe found that these various places of student residencies, substance free residence hall room, living and learning
24 residence hall room, and off campus, were all associated with greater high risk drinking rates among undergraduate females. Findings su ch as these highlight the need to risk drinking behaviors. Another area scholars and practitioners have explored relates to the relationship between gender roles and associated negative beh avioral consequences. For example, aggression, deviance, and public risk taking behaviors are culturally embedded qualities of male gender roles and are often related to high risk drinking behaviors . However, private personal health consequences, the gender gap is greatly decreased. For example, males are more likely than females to damage property, get into a fight, and have altercations with the police due to their high risk drinking behaviors. However, bot h genders experience the personal and private consequences such as memory loss, unintended sexual activity, vomiting, and hangovers (Lo, 1996; Perkins, 2002; Wechsler & Isaac, 1992). In addition, as gender norms continue to evolve, their influence on the rising prevalence and frequency of risk drinking behavior (Ham & Hope, 2003). Gender, as demonstrated in the literature, is a critical factor for institutions to examine when identifying and cr eating programs that focus on the varying attitudes, beliefs and behaviors surrounding high risk drinking of undergraduate students. Ethnicity The research literature indicates that overall, White college students report higher rates of high risk drinking behaviors and higher alcohol related negative consequences as compared to Non White college students (Engs, Diebold, & Hanson,
25 1996; Presley et al., 1996a; Wechsler et al., 1995). In examining five national data sets of college student drinking behaviors White students were highest in high risk drinking. In addition, the researchers found that since 1980 there were steady trends indicating African American students had the lowest heavy drinking rates, with Hi spanic American students drinking rates in between. Further, Asian American students and African American students reported having the lowest rates of alcohol related negative consequences, with Hispanic American students having an in between rate of nega tive consequences, and White college students reporting the highest proportions of consequences (Presley et al., 1996a; Wechsler et al., 2000). In another study, based on self reported student responses of the Harvard College Alcohol Study, White student s were more likely than Non White students (e.g. Asian and African American students) to begin engaging in high risk drinking behaviors upon arriving on campus (Weitzman, Nelson, & Wechsler, 2003). These studies within the last 20 years suggest that there are significant racial differences in high risk drinking behaviors. However, as the makeup of the college student population is rapidly changing the landscape of higher education, in terms of who is attending college based on demographics including race and ethnicity, it is important to determine if these differences still exist and to develop targeted high risk drinking prevention initiatives for a more racial/ethnic diverse student population. Academic Classification and Age Researchers have closely exa the health promotion research literature, in particular the drinking behaviors of the freshmen population and students under the age of 21 or over the age of 21. For
26 example, researchers have found that f irst year students entering college are at a higher risk for consuming greater quantities of alcohol, thus increasing their risk of experiencing negative alcohol related consequences (Ross & DeJong, 2008). Engaging in binge drinking frequently (three or m ore times in a two week time period) results in an increased risk of negative consequences than binge drinking infrequently (one or two times per two week time period) or socially drinking (Wechsler et al., 2002). Researchers have found the first year of college, especially the first few weeks within the first semester of arriving on campus, to be a particularly high risk period for first year students (Bishop, Weisgram, Holleque, Lund, & Wheeler Anderson, 2005; Borsari, Murphy, & Barnett, 2007; Capone, W ood, Borsari, & Laird, 2007; Grekin & Sher, 2006; Hartzler & Fromme, 2003; Leibsohn, 1994; McCabe, Schulenberg, 2003; White et al., 2006). This transition time between hi gh school and the first year of college can be particularly challenging as students are developing their identity, establishing new social networks, and lea rning how to navigate their new found sense of freedom away from home and parental influence for perh aps the first time in their life (Ross & DeJong, 2008). However, as students begin heavy drinking during the first few weeks of college, the possibility exists for high risk drinking to hinder their successful adjustment to campus life. As the transition to college is frequently challenging to navigate, approximately one third of first year students do not enroll for their second year (Upcraft, 2000). In examining the factor of classification in more detail, it is important that campuses recognize that first year students bring their own perceptions and beliefs
27 a bout drinking with them to college, which includes viewing alcohol as essential for fitting in and making new friends. Some researchers have argued that f irst year students may enter college, e do not participate then they will potentially miss out on an important college ritual and further risk b eing labeled boring or immature (Ross & DeJong, 2008). They also suggest that these students are attempting to discover their place of belonging and to be included in a community, which may contribute to the belief that alcohol will strengthen their confi dence as they form a new peer group in the college setting. Being aware of the misperceptions and preconceived notions of drinking norms held by first year students, will allow for effective tailoring of health promotion initiatives focused on correcting these beliefs. First year students may also have concerns regarding how to act in new social settings and rather than examine positive and healthy ways to form new friendships and relationships, they engage in heavy alcohol use as a way to ensure they will experience perceived social success (Chapman & Zaballero, 2006). This study also found that some first year students may regard alcohol and drinking in the following ways: as a requirement for having a good time and a guarantee of fun in college; the goa l of drinking is to get drunk; it is necessary for socializing; all college students drink heavily and often; it is expected as part of the college experience; drinking produces funny and memorable stories; and is viewed as a sign of independence and a sta tement of individual freedom (Chapman & Zaballero, 2006).
28 In addition to individual beliefs and misperceptions, a major contributing factor t o consider when addressing high risk alcohol consumption among first year college students is the campus and commu nity environment. Environmental cues include social networks endorsing high risk drinking, alcohol outlet density in areas close to college campuses, aggressive marketing by the alcohol industry, unenforced policies and laws, and cheap drink specials. In one study, students were significantly more likely to begin engaging in high risk alcohol consumption when paying one dollar or less for a drink, than were students who reported paying more than a dollar per drink, reinforcing the influence of egregious d rink specials upon high risk alcohol behaviors (Weitzman et al., 2003). Including the variables of classification and age in this study will help in identifying gaps of need and developing potential future initiatives targeting unique populations . These specific populations can include upper level students who are still under the age of 21, as well as students of legal drinking age who have different drinking behaviors and who have not received focused alcohol prevention interventions similar to those tar geting the first year college student population. With many campuses recognizing the need to focus their time and efforts in targeting first year students, especially within the first six weeks of arriving to campus, older students are not receiving the s ame level of educational programming and intervention efforts as the rationale for including age and classification in this study is to help address the gap of research f ocused on upper class students.
29 Work Status There is limited r esearch as to whether a student s work status while in college is a potential influence upon their high risk drinking behaviors. Butler and colleagues (2010) explored the relationship between c ollege student employment and drinking behaviors and determined that daily work status (e.g. working or not) was negatively related to alcohol consumption, in addition to finding that college students in their sample drank more alcohol on the days when the y worked more hours. It is important to note that the participants in this study were employed for five or more hours per week and the results may not be generalizable for students who work substantially more hours per week while in college (Butler, Dodge , & Faurote, 2010). There is research graduation indicating that drinking rates decrease as students assume more life responsibilities such as gaining employment and family obligations (Gotham, Sher, & Wood, 199 7; Ham & Hope, 2003). Research has also risk drinking behaviors, indicating that the greater amount of unstructured free time college students possess, the greater the potential for students t o consume large amounts of alcohol Borsari et al., 2007 ; Wechsler et al., 1995 ). Other areas of research have examined the positive impact of volunteering and community service involvement and decreased high risk drinking behaviors ( Borsari et a l., 2007; Weitzman & Kawachi, 2000 ), but there remains a dearth in the literature specifically regarding the role of while enrolled at college . Greek Affiliation Several researchers have examined the influe nce of Greek affiliation on alcohol related behaviors (Alva, 1998; Engs et al., 1996; Lo & Globetti, 1995; Wechsler et al.,
30 2002). College students who are either planning to join a Greek organization, or are already part of the Greek system, consume grea ter amounts of alcohol and more frequently, as compared to their peers. In addition, they are at greater risk for Engs et al., 1996; Presley, Meilman, & Leichliter, 2002; Weit zman et al., 2003). One of the strongest predictors for high risk drinking is students living in a fraternity or sorority house, as 75% of fraternity members who engaged in heavy alcohol use in high school became high risk drinkers upon arriving at colle ge (Borsari & Carey, 1999; McCabe, 2002; Presley et al., 2002; Sher, Bartholow, & Nanda, 2001; Wechsler et al., 1995). Further, in a national sample of 179 colleges, 86% of fraternity house residents engaged in high risk drinking behaviors , compared with 71% of nonresident fraternity members, and 45% of males not affiliated with a fraternity. Forty five percent of fraternity house residents experienced five or more alcohol related consequences (getting hurt or injured, missing class, engaged in unplanned or unprotected sexual activity, falling behind in school work) as compared to 31% of nonresident fraternity members and 17% of males not affiliated with a fraternity. In addition, similar to male students living in fraternity houses, 43% of college women living in sorority houses engaged in high risk drinking. Specifically, one study found that since the beginning of the school year, 19% of sorority house residents reported experiencing five or more alcohol related consequences as compared to 20% of nonr esident sorority members, and 11% of females not affiliated with a sorority (Wechsler, Kuh, & Davenport, 1996). The literature provides several themes that have emerged over the years relating to the reasons why the Greek population engages in higher rat es of alcohol
31 consumption than their non Greek affiliated peers. Borsari and Carey (1999) identified five themes relating to heavy alcohol use in fraternities consistently appearing in the literature from 1980 through 1998. The themes are as follows: (a) continuity of heavy alcohol use from high school to college; (b) self selection into heavy drinking environments; (c) the central role that alcohol plays in fraternity socialization; (d) misperceptions of drinking norms; and (e) the enabling physical envi ronment of the fraternity house. These themes have continued to be supported by subsequent studies as important for recognizing the differing intervention needs of this population (Barry 2007; Borsari et al., 2007; Sher et al., 2001). While the study did not focus on the sorority population, as males engage in high risk drinking more frequently than females and consume greater amounts of alcohol, it is still important to consider these themes when designing targeted strategies for sorority members. Sher and colleagues (2001) examined the short and long term effects of fraternity and sorority involvement on drinking behaviors and found that while Greeks consistently consumed greater quantities of alcohol than non Greeks, the Greek affiliation did not pred ict heavy drinking behaviors beyond their college years. This phenomenon supports the research that Greek involvement during college is a risk factor for engaging in high risk drinking, as well as stressing the importance of campuses examining the role of the environment as potentially supporting and encouraging norms around excessive drinking. The living and social environment of fraternity and sorority houses are two facets of concern as these are situations in which heavy drinking is viewed as the norm and, as a result, students may consume more alcohol than they might otherwise. In addition, some researchers have found that students upon
32 graduating from college and moving away from the living and social environment in which heavy drinking is viewed as normative and encouraged, experience a decrease from heavy drinking to moderate drinking levels, indicating just how powerful the campus drinking norms and residency within a Greek living environment is when identifying targeted interventions (Sher et al. , 2001). In spite of the years of data and literature indicating the relationship between Greek affiliation and excessive alcohol consumption, this study will aim to isolate Greek affiliation and its proposed influence at different times of the year, speci fically the fall versus spring semester, on student drinking behaviors. Residency S tatus Researchers have found that a college student living residenc y status is also a factor to include when determining the profile of students who engage in high risk dri nking behaviors. Previous research has examined the role of the living environment Johnston, & Schulenberg, 1997; Martin & Hoffman, 1993; Presley, et al., 1996a; Presley, et al., 1996b; Wechsler, Lee, Nelson, & Lee, 2001). Students living in on campus residences, including fraternities, sororities, or residence halls, report consuming greater amounts of alcohol, engaging in heavy drinking behaviors more frequently, and experi encing more alcohol related negative consequences as compared to students who live with their parents (Martin & Hoffman, 1993; Valliant & Scanlan,1996; Weitzman et al., 2003). In a national study, students living in substance free residence halls or off campus with their parents reported the lowest rates of high risk drinking and negative secondhand effects of alcohol consumption compared with students living in residence
33 halls permitting drinking, fraternities or sororities, and students living off campu s without parents who reported higher rates of high risk drinking (Wechsler, Lee, Nelson, & Kuo, 2002). These findings illustrate the influence of the campus environment, characterized as an uncontrolled setting where alcohol is readily available, peer ap proval of heavy drinking norms exists, and concern for getting into trouble is limited, compared to a more controlled setting such as living at home with parents. When examining the role of residency, researchers highlight the importance of examining gende r and age differences as additional variables of influence upon drinking behaviors . Valliant and Scanlan (1996) report ed that first year male students living off campus in apartments or single houses consume more alcohol than male students living on campu s or off campus with their parents, with no pattern for female students. Another environment al living factor to consider is coed residence halls where students report greater alcohol related negative consequences than students living in single gender resi dence halls ; but these students living on campus also report much lower rates of drinking and driving as compared to students living off campus (Harford, Wechsler, & Muthen, 2002). Students living off campus are a different population and deserve interve ntions tailored to their drinking behaviors and negative consequences. The majority of first ear students live in residence halls during their first year of college. Their new freedom and social opportunities which include parties and drinking games make them a Johnson, 2002). Place of residency and living environment, as demonstrated through the research, is a critical factor for institutions to examine when assessing campus
34 norms around alcohol behaviors, as well as when identifying populations for targeted and tailored intervention strategies. Event Level and Context Drinking T he research literature identifies the need for high risk drinking prevention initiatives targetin g college students to consider both the event level and contextual perspectives. The event level perspective includes 21 st birthdays, spring break, Halloween, th social events. The contextual perspective includes weekends, acade mic breaks, sporting events especially college football games, tailgating, pre gaming (drinking before going out), parties, and drinking games. A major difference between the two perspectives lies with the timing of the occasion. For example, planned eve nts occur on pre specified dates that students look forward to, whereas, contextual events occur but are not necessarily assigned a specific date or time. However, this separation between events and contexts can cause confusion. For instance, sporting ev ents are often linked to students engaged in high risk drinking behaviors , but a particular sporting event, such as the NCAA Basketball Tournament evaluated from the event level perspective. In addition, parties are also considered from the contextual perspective but when occurring to certain events such as Halloween, 21 st level perspective. Further, researchers have argued that these high risk drinking contexts (Neighbors, Foster, Fossos, & Lewi s, 2012, p. 54).
35 The research on spring break and high risk drinking from the event perspective dates back to the late 1990s, and emerged from the advertising and media attention of entities such as MTV, which promoted destination spring break packages t o college students (Josiam, Hobson, Dietrich, & Smeaton, 1998). The literature had primarily focused on identifying the large proportions of high risk drinking prevalence data and Sher, & Krull, 2007; Lee, Maggs, & Rankin, 2006; Lee, Lewis, & Neighbors, 2009; Patrick, Morgan, Maggs, & Lefkowitz, 2010; Sonmez, Apostolopoulos, Yu, Yang, Mattila, & Yu, 2006). While not the primary focus of this study, a gap exists in the research ide ntifying and evaluating prevention interventions targeting spring break drinking and sexual behavior among college students (Cronin, 1996; Neighbors, Walters, Lee, Vader, Vehige, Szigethy, & DeJong, 2007; Snyder & Misera, 2008). The focus of this particu lar study wa s to examine a spring and fall semester s in order to include a broader lens for assessing the contextual impact of a full semester on drinking behaviors, as compared to focusing on a specific event or shorter time period. Incorporating the per iod effects lens will allow for deeper exploration and comparison of differences present within each semester about high risk drinking phenomena among the college student population, and will hopefully shed light on the type of impact the time of year/seme reported negative consequences. As a practitioner fo cused study, the ultimate goal wa s to identify potential areas and practical recommendations campuses can implement through the ecological model of health behavior framework to continue to address this entrenched problem in a comprehensive manner that is also related to the time of the
36 academic year. Thus, this research will contribute to the field by identifying the influence an academic semester c an have on student drinking behaviors and implications for campuses to consider when implementing environmental management strategies through use of the ecological model when targeting specific student populations. Theoretical Framework The Ecological Mode Ecological Systems Theory (1977), was utilized for this study, as this allows for the integration of both the public health and student development perspective in a complementary approach. Framing t he study through this lens capture s the significance of addressing high risk drinking behaviors through an environmental context. Examining human development through the ecological lens allows for the ability to understand how interactions between people a nd their surrounding environments foster growth and development. Additionally, the ecological framework helps to explain how people impact their environments and the ways in which some environments support individual development as compared to others. Ec ological models can be beneficial for student affairs professionals to utilize in recognizing ways in which campus environments can be created to foster ideal student growth and development (Evans, Forney, Guido, Patton, & Renn, 2010). The influence of Uri overlooked as his work provides the foundational underpinnings for the Ecologic al Model of Health Behavior. His model is comprised of four primary elements: process, person, context, and time (PPCT). The process element is at the center of the model
37 developmentally appropriate interactions for an individual. The person element in combination with process, offers an in depth insight into how the PPCT model describes what occurs in the how and what of the person environment interaction. Within the context element, the individual is the primary focus with the immediate context considered an important setting for interact ions (the process) to occur between the individual and the environment. The time element plays an important role as it works together with process, person, and context to impact the developmental influence of proximal processes. Ecological Model of Hea lth Behavior The Ecological Model of Health Behavior highlights the environmental and policy perspectives of behavior, while integrating social and psychological factors. Over the past two decades, there has been a remarkable interest in, and application of, ecological models in research and practice, due to their potential for shaping comprehensive population wide strategies to changing behaviors that will decrease severe and prevalent health issues (e.g. high risk drinking behaviors) (Sallis, Owen, & Fis her, 2008). The primary purpose of the Ecological Model of Health Behavior is to guide the creation and implementation of comprehensive intervention strategies that can systematically address mechanisms of change at multiple levels of influence. Behavio r change is anticipated to be enhanced when environments and policies support healthful decisions, when social norms and social support for healthful decisions are strong, and when individuals are encouraged and educated to make those decisions. For
38 ecolo gical models to result in significant changes in health behaviors, both individual level and environmental and policy level initiatives are needed (Sallis et al., 2008). core pri nciples have been identified to help form the Ecological Model of Health Behavior. These are: multiple influences on specific health behaviors exist, such as factors at the intrapersonal, interpersonal, organizational, community, and public policy levels; influences on behaviors act together across these different levels, ensuring that multiple variables work in sync; the focus of ecological models are tailored to specific health behaviors; and multi level initiatives are most effective in shifting behavio r. Ecological models of health behavior are important when entire populations are the focus of change, as this allows for multiple levels of influence to be examined concurrently and expanding the selection of interventions identified in sustaining behavi or changes. Changing environments and impacting policies are often times a lengthy and tedious process. However, creating and sustaining environments and policies that remove barriers and enhance the convenience, attractiveness, and economic benefits of healthy decision making, and then encouraging and educating the greater population about their choices, will contribute to improved health for individuals and the greater good (Sallis et al., 2008). Creating and sustaining behavior change requires a com prehensive approach and social ecology is a prominent strategy for explaining behavior. Ecology proposes that behavior is impacted by multiple levels of influence. As alcohol use, specifically high risk drinking among the college student population, is a multi faceted behavior in which influence is comprised from multiple sources including social and environmental
39 issues, using an ecological approach as the lens to view the problem is a sound method for enacting significant, long lasting behavioral change (Williams, Perko, Belcher, Leaver Dunn, Usdan, & Leeper, 2006). As outlined above , the intrapersonal, interpersonal, institutional, community, and public policy factors comprise the Ecological Model of Health Behavior and will be e xplored in greater dep th specifically as it relates to high risk drinking among the college student population. The Ecological Model of Health Behavior highlights the intrapersonal factors at the very center of the model (e.g. microsystem) , then surrounded by the interpersonal factors (e.g. mesosystems), followed by the institutional factors layer (e.g. exosystem), the community factors, and ultimately working out to the public policy factors (e.g. macrosystem). Within each level, the influence of specific factors is included as is their relation to that factor. Each factor is connected and and intrapersonal factors are at the center of the model and all other environmental influences are woven together to comprise the rest of the model.
40 Chronosystem capture the force of the flow of historical time Figure 2 1 . Revised . When examining the overlap and complem entary nature of the Ecological Model of Health Behavior, the various contextual factors play a very important role. Bronfenbrenner identified microsystems, mesosytems, exosystems, and macrosystems nested, interdependent, dynamic structures ranging from the proximal, consisting of immediate face to face Community (macrosystem) community mobilization , such as a campus community coalition to address high risk drinking Organizational ( exosystem ) strategies the campus can implement to change the environment Interpersonal ( mesosystem ) peer norms, normative beliefs, and perception of drinking norms Intrapersonal (microsystem) individual attitudes and beliefs about alcohol
41 settings, to the most distal, comprising broader social contexts such as classes and center of the model surrounded by these four levels of context interacting in complex ways on an the Ecological Model of Health Behavior and the various context elem ents from risk drinking and college students to demonstrate the corresponding role both theories play when addressing this issue. Intrapersonal Factors and Microsystem Intrapersonal factors and the microsystem c ontext place individual attributes such as personal attitudes, knowledge, and beliefs regarding specific behaviors at the core of the Ecological Model of Health Behavior. Bronfenbrenner (1993) defined a microsystem As nterpersonal relations experienced by the developing persons in a given face to face setting with particular physical, social, and symbolic features that invite, permit, or inhibit engagement in sustained, progressively more complex interaction with, and activity in, the immediate For example, a microsystem for college students includes roommates, friendships, student organizations, living settings, a campus job, employment, and an athletic team. Intrapersonal factors that mold stu individual level include: personal alcohol consumption patterns and substance abuse history; a family history of alcohol, high risk drinking, and addiction issues; awareness of the consequences associated with high risk al cohol consumption; views regarding what comprises normative drinking behavior; tendency toward high risk drinking and other dangerous behaviors; an inclination toward refusing peer and other social pressures;
42 and access and availability to alcohol (includi ng price of alcohol, nearness of alcohol outlets, and modes of transportation) (Nelson & Winters, 2012). Interpersonal Factors and Mesosystem Interpersonal factors and the mesosystem context include the influence of social networks upon the individual, such as peers, family, and normative beliefs in the next level of the Ecological Model of Health Behavior . The mesosystem, as defined by more settings co ntaining the devel oping person. Special attention is focused on the synergistic effects created by the interaction of developmentally instigative or inhibitory to form a network of dev elopmental opportunities which contribute to the formation of the mesosystem. Family and peer influence, including family attitudes and perceptions; high school and college friends; co curricular involvement including Greek affiliation and student organiz ations; and athletic involvement including both a college sports team and intramural sports participation, all make up potential interpersonal factors at the mesosystem context as influencers upon student drinking behaviors (Nelson & Winters, 2012). Ins titutional Factors and Exosystem Institutional factors and the exosystem context shifts from primarily on the individual to the broader environment in the next level of the Ecological Model of Health Behavior. The exosystem, as described by Bronfenbrenner , exists in a setting where the individual is not included, but still applies influence on the environment and developmental potential as a result of interactions with the microsystems. Including the impact of the exosystem on student development provides student affairs practitioners
43 with a means to identify factors often thought of as outside their control, as well as offering a mechanism for concentrating on the diversity of student experiences (Renn & Arnold, 2003). Campus influence, including the con sistent enforcement of campus alcohol policies; consistent consequences when campus alcohol policies are violated; the campus climate regarding drinking including traditions, stories, and norms; campus prevention and intervention initiatives; where the cam pus is physically located in relation Party School Ranking, are all examples of institutional factors occurring within the exosystem context that influence student d rinking behaviors (Nelson & Winters, 2012). Community and Policy Factors and Macrosystem Community and policy factors and the macrosystem context extends to encompass an even broader focus incorporating policy development as an influence in the outer mos t level of the Ecological Model of Health Behavior. A macrosystem, as defined by Bronfenbrenner (1993), meso and exosystems characteris tic of a given culture, subculture, or other extended social structure, with particular reference to the developmentally instigative belief systems, resources, hazards, lifestyles, opportunity structures, life course options and (p. 25). The four levels of systems within the context element operate dependently of each other in a complex manner, as whatever occurs in one level impacts all other levels. Within this level of influence, several factors contribute to high risk drinking among the colleg e student population. When identifying and developing strategies to address high risk drinking, it is important to include the macrosystem context and the
44 community and policy factors, as many college students obtain their alcohol off campus property and within the broader community environment. Further, it is imperative to development of responsible drinking behaviors. While college students and even practitioners may not be direct ly aware of how campus and community policies shape their behaviors and decisions, without these mechanisms in place the campus culture learning. Time The final compone nt of this model focuses on the concept of time and is captured developmental life course is seen as embedded in and powerfully shaped by conditions and events occurring during 641). Time plays an important role as it works together with the process, person, and context to impact the developmental influence of proximal processes. Time influences include national and glob al events that define the era in which students are at college, addition of life experiences over time is a long lasting effect of the chronosystem on the individual, a nd students attend college with distinctive characteristics molded by common social norms and influences and individual experiences (Renn & Arnold, 2003). Within the context of this study, time is a key factor of interest when determining what impact, if any, exists when comparing spring and fall semesters as it relates to students self reported high risk drinking behaviors.
45 C hapter Summary As highlighted in C hapter 2 , multiple social and psychological factors influence risk drinking behavio rs. Recognizing the role these factors play in campuses seek to develop and implement interventions targeting specific student populations. Utilizing the Ecological Model of Health Behavior supported by Urie levels of the environment, such as policy, curriculum, and peer and family influence, and strategies campuses can focus their tailored effor ts and intervention points through multiple initiatives (Evans et al., 2010). As outlined through the different factors of the theoretical framework, a comprehensive approach to addressing high risk drinking and the negative consequences includes both foc using on the individual student and on the environmental state that guides the behaviors of the br oader population. Chapter 3 provides an overview of the methods utilized to implement the current study.
46 CHAPTER 3 METHODOLOGY Chapter 3 provides an overview of the methods utilized for this proposed study. This chapter includes a description of the research design, survey instrument, proposed study sample, and data analysis methods. As outlined in Chapters 1 and 2 , high risk drinking behaviors among the college st udent population is a serious and challenging issue that many institutions and surrounding communities struggle to continuously address. The purpose of this study was twofold: 1) to examine in greater depth the risk alc ohol consumption and specific factors and strategies for student affairs health promotion practitioners to utilize in order to reduce high risk drinking behaviors among t he college student population. The proposed research questions are as follows: 1. To what extent do individual demographics and s tudent residency and engagement reported high risk drinking behaviors? 2. To what extent does stude nt enrollment in the spring and fall semesters relate reported high risk drinking behaviors? Based upon the research questions guiding this study, as well as the literature relevant to the drinking behaviors of the college student popula tion, the foll owing hypotheses we re proposed: H O1 : There will be no difference between the spring 2011 and fall 2011 samples in H O2 : There will be no difference between the drin king behaviors of male and female stud ents. H O3 : There will be no difference between the drinking behaviors of Greek and non Greek affiliated students.
47 A n alpha level of .05 wa s used to accept or reject the test. Rej ecting the null hypotheses indicate s a statistically significant difference between the spring and fall semesters and the dependent variable suggests there is a period effect, as well as a statistically significant difference between high risk drinking behaviors and key ation). Survey Instrument This study utilize d a survey methodological approach to analyze survey data from a secondary source to answer the proposed research questions and hypotheses. Specifically, the survey data for this study was collected using the Co re Alcohol and Drug Long Form Survey instrument. This instrument was developed in 1989 and is used by many college campuses to examine the alcohol and drug prevalence rates i mplemented for several consecutive years to capture trend analysis data about alcohol and drug prevalence rates of their specific college student population was utilized. Specifically, the Long Form Survey is comprised of questions on demographics, percep tions of campus policies and enforcement issues, similarities in alcohol and drug drinking, campus violence, campus climate, and participation in extracurricular activitie s. Several advantages of utilizing this instrument include the following: large samples are obtained, allowing for subgroups to be examined in greater detail; institution level variables and policies can be analyzed as the information collected about the v arious institutions and participants are grouped by institution; and there are a variety of questions about alcohol and other drug usage rates and additional alcohol
48 stu dies have determined that the survey instrument is statistically reliable and valid, appropriate for a college student population, inexpensive and easy to implement, and comparable across campuses (Presley et al., 1996a). The Core Institute continues to st udy the psychometric properties of the survey to determine if the most accurate data possible is being collected, as well as ensuring campuses are being provided with the optimal data gathering instrument (Presley et al., 1996a). The Core Survey has been tested and demonstrates high content and construct validity, as well as test retest reliability. Content validity has been established through examining the existing literature and related instruments to determine the relevant consequences, viewpoints, an d types of alcohol and other drug use to be included as items on the instrument. Findings from the survey are continuously aggregated and housed by the Core Institute, a federally funded initiative, as part of the Center for Alcohol and Drug Studies at So uthern Illinois University Carbondale Student Health Center in what is currently a substantial national database on alcohol and other drug use in the higher education realm. Through this format, campuses have the ability to benchmark their specific data a gainst the national data set. Data Source The institution , a public, research extensive, highly selective four year institution, on average has approximately 50,000 students enrolled each year. Out of the 50,000 students, almost 34,000 are undergraduate , over 50% of the overall student population identify as female, and more than 50% of the overall student population identify as White. This institution is a member of the Association of American Universities and is comprised of approximately 5,000 facult y members, responsible for teaching, service,
49 and research across many different disciplines. This institution is situated in a city of approximately 125,000 citizens. There are over 900 registered student organizations at this institution. There is also an active Greek community with over 6,000 members and a pproximately 20% of the unde rgraduate student population involved . This institution also has very prominent and successful athletic programs. The revenue generating sports attract fans to the campus every year. Each of these events brings additional concerns such as hospital transports and negative consequences including fighting, sexual assaults, and driving while intoxicated. Because of these chronic cases of high risk drinking behaviors this stu dy specifically focused on examining whether these types of campus events significantly increase these types of incidents during a specific time period (i.e. time period effect). During 2011, the following events made national and international headlines: the U.S. unemployment rates remained high; the U.S. economy was in the process of slowly recovering ; the Occupy Wall Street movement gained traction throughout the country ; Osama Bin Laden was assassinated ; preparations for campaigns for the 2012 U.S. pres idential election were underway; Japan experienced one of their worse natural disasters with an earthquake and tsunami; the U.S. national debt crisis; and the Penn State child sex abuse scandal involving several senior administrators and football coaches. The institution of focus for this study experienced the following during 2011: the adoption of a Medical Amnesty Policy for alcohol and drug related emergency situations in spring 2011 and the implementation of a comprehensive educational marketing campai gn in fall 2011; a football season with winning half of their games and
50 losing the remaining games; the Elite Eight of the NCAA tournament; and a student dying of alcohol poi soning while out of tow n on spring break. These events, internationally, nationally, and locally all potentially shaped the students at this specific institution and the context in which they existed and developed while at college. Student Sample 1 (Spring 2011) The population sampled for both the spring and fall 2011 semesters, included two separate groups of 4,000 randomly selected students between the ages of 18 and 24 currently enrolled in the institution. For the spring 2011 semester, the Core Alcohol and Drug Long Form Su rvey was opened and coordinated through the Core Institute at Southern Illinois University, at the beginning of April 2011 with the pre notification email informing students to expect an email with the survey link in a few days sent out at the end of March 2011. Reminder emails were subsequently sent three times throughout the month of April with the survey closing at the end of April . The final student sample to the survey being im plemented in spring 2011. Out of the 535 participants (academic year 2010 2011), 251 males and 280 females, 47.3% and 52.7% respectively, completed the survey. Additionally, 19.8% were freshmen, 15.5% were sophomores, 24.3% were juniors, 21.9% were senior s, 18.1% were graduates, and 0.4% were other; 71.8% reported living off campus, 23.7% reported living in a residence hall, and 3.8% reported living in a fraternity or sorority house. A majority of the student respondents reported consuming alcohol in the past year (82%) , providing the annual prevalence drinking data. Seventy one percent of the students reported consuming alcohol in the past 30 days, providing the 30 day
51 prevalence rate. Sixty percent of underage students (younger than 21) reported consum ing alcohol in the past 30 days. Forty four percent of students reported engaging in binge drinking in the past two weeks, defined as having five or more drinks in one sitting. Data was stored on a campus password protected computer with no identifying i nformation from participants. Student Sample 2 (Fall 2011) For the fall 2011 semester, the Core Alcohol and Drug Long Form Survey was again opened and coordinated through the Core Institute at Southern Illinois University, at the very end of October 2011 , with the pre notification email informing students to expect an email with the survey link in a few days sent out towards the end of October 2011. Reminder emails were subsequently sent three times throughout the month of November with the survey closin g at the end of November. The final student sample size was 678 participants. Similar to the spring 2011 survey, reminder emails were sent to students who had not yet completed the survey with brief instructions on survey access and instrument completion . The last reminder email informed students of the survey closing date. During the fall semester the survey was open during the middle of the football season. Out of the 678 participants (academic year 2011 2012), 316 males and 358 female s, 46.9% and 53.1% respectively, completed the survey. Additionally, 23.0% were freshmen, 17.0% were sophomores, 20.1% were juniors, 27.7% were seniors, 12.0% were graduates, and 0.1% were other. Seventy one percent reported living off campus, 25.4% repo rted living in a residence hall, and 3.0% reported living in a fraternity or sorority house. A majority of the students respondents reported consuming alcohol in the past year (80%) , providing the annual prevalence drinking data. Sixty
52 nine percent of th e students reported consuming alcohol in the past 30 days, providing the 30 day prevalence rate. Fifty six percent of underage students (younger than 21) reported consuming alcohol the past 30 days. Forty one percent of students reported engaging in bing e drinking in the past two weeks, defined as having five or more drinks in one sitting. Data was stored on a campus password protected computer with no identifying information from participants. In addition as part of the data conditioning, the two studen t data files spring 2011 (n = 535) and fall 2011 (n = 678) , were merged into one master student file to conduct the analysis (n =1,213). Institutional Review Board approval was obtained for each survey. Both random samples including gender, names, and ema il addresses were obtained through the Office of the Registrar and sent to the Core Institute in an excel spreadsheet for uploading into their system. Risk to individual participants was minimal due to the anonymous nature of the survey, as there were no personal identifiers collected, maintained, or associated with the student responses. Students accessing the survey in both the spring and fall semester were informed they could skip any or all questions they did not wish to answer and still remain eligi ble for the incentive of a gift card to the Measures Dependent Variable The dependen t variable used for this study wa s the average number of drinks students consume in a seven day week period. The response option for this question is continuous . Table 3 1 highlights the data collapsed into the high risk drinking behaviors categorized as abstainers, social drinkers, binge drinkers, and frequent binge drinkers for both the spring and fall 2011 student population.
53 This particular que stion on the Core Alcohol and Drug Survey has not received the level of national scrutiny and revision as compared to the question included right before on the instrument which measured the number of times students report having five or more drinks at a se tting. This item provides campuses with their high risk drinking rate. There are limitations to this question including the vagueness surrounding alcohol absorpt ion, and uncertainty as to what comprises a single drink. However, the items on the Core Alcohol and Drug Survey remain the same as before and question 14 had five or mo 3 to 5 times, 6 to 9 times, and 10 or more times. For this study, Question 15 was utilized as the dependent variable, and the question asking students the following, Independent Variables The independent variab les for this study as identified from the Core Alcohol and Drug Long Form Survey include d several key blocks of variables that we re arranged into three main categories: 1) student individual characteristics; 2) student residency and engagement; and 3) stud ent academic term enrollment (i.e. period effect). These three m ain blocks of variables provide valuable information about the relationship between high risk drinking behaviors and key student characteristics. The f irst block of variables examined studen characteristics. For example, as highlight ed in Chapter 2 , previous extensive research
54 has examined and determined these social and psychological factors of gender, ethnicity, classification and age, Greek participation, and pla ce of residency, all in greater amounts than female students (Engs et al., 1996; Presley & Meilman, 1992; Presley et al., 1996a; Wechsler et al., 1994; Wechsler e t al. , 1995). This study e xamine d if there were similar gender related patterns in high risk drinking at this particular institution. students report higher rates of heavy alcohol co nsumption and higher alcohol related negative consequences as compared to Non White college students (Engs et al., 1996; Presley et al., 1996a; Wechsler et al., 1995). The factors of classification and age also have an impact, as first year students enter ing college are at a higher risk for consuming greater quantities of alcohol, thus increasing the risk of experiencing negative alcohol related consequences (Wechsler et al., 2002). The next block of variables examined characteristics. For example, researchers have found that the factor of residency is important to examine as students living in on campus residences, including fraternities, sororities, or residence halls, report consuming greater amounts of alcohol, enga ging in heavy drinking behaviors more frequently, and experience more alcohol related negative consequences as compared to students who live with their parents (Martin & Hoffman, 1993; Valliant & Scanlan, 1996; Weitzman et al., 2003). Similarly, there ar e many studies that have examined the influence of student Greek affiliation and the increasing probability of high risk drinking, as college students
55 who are either planning on joining a Greek organization or are already part of the Greek system and invol ved with Greek activities, consume greater amounts of alcohol and more frequently, as compared to their peers, as well as being at greater risk for experiencing the negative consequences (Cashin et al., 1998; Engs et al., 1996; Presley et al., 2002; Weitzm an et al., 2003). Finally, while in depth research has been conducted on these aforementioned factors as it relates to college student drinking behaviors and the negative consequences, including these as the indepe ndent variables for this study wa s criti cal when examining the potential impact of the period effect between a spring and fall semester academic enrollment at a four year research extensive institution. Therefore, the last block of variables examined was the primary focus of this study. That i s, the risk drinking behaviors was examined . There is less known about this particul ar issue and this study attempted to provide some empirical evidence to understand this relationshi p. Table 3 2 highlights the manner in which the independent variables were code d for data analysis . Data Analysis Data analysis procedures begins with descriptive statistics to describe the population and the variables of interest including drinking quant ity, classification and age, gender, ethnicity, academic performance (cumulative grade point average), and living arrangements including on campus, off campus, and fraternity or sorority. Descriptive analyses will include frequencies and cross table analy ses. Incorporating multiple types of data analysis will provide a comprehensive analysis to thoroughly answer the research questions. Next, the advanced data analysis procedures will
56 include t tests, ANOVA, and a multivariate regression analysis. The mu ltivariate regression analysis will allow for the inclusion of multiple independent variables to determine which have a greater impact upon the dependent variable of the number of drinks students report consuming. The dependent variable is the drinking qu antity, specifically, the average number of drinks students reported consuming in a week. Table 3 1. Number of drinks consumed in a week by drinking behavior categories Number of Drinks Consumed A Week Spring 2011 Fall 2011 Abstainers (0 Drinks) 38%.3 41.9% Social Drinkers (1 4 Drinks) 37.7% 33.8% Binge Drinkers (5 9 Drinks) 11.2% 12.6% Frequent Binge Drinkers (10+ Drinks) 12.8% 11.2%
57 Table 3 2. Independent variables for the high risk drinking behavior regression model Variable Name Variable Ty pe Variable Coding Student Individual Demographics Student Gender Categorical (Male) Female Student Age Categorical (Above 21) 21 and Below Student Classification Categorical (Upperclassman) Freshman Student Ethnicity Categorical (White) Non White Student Residency and Engagement Categorical (On Campus) Off Campus Greek Participation Categorical (Greek) Non Greek Continuous 1 13 Student Enrollment Term (period effect) Academic Term Categorical (Fall 2011) S pring 2011 Note: all of the variables in parentheses are the reference group for this analysis.
58 CHAPTER 4 DATA ANALYSIS Chapter 4 reports the results from the data analysis based on the two related research questions as described in chapter three. Chapter 4 begi ns with a brief discussion of the descriptive statistics for the student data set. This analysis include d a closer examination of the dependent variable for the student population. In addition, a broader discussion of independent variables in order to pr ovide additional context of the research time period will be presented, followed by the results of the t test analyses. This section of C hapter 4 risk drinking behavior by different student group characte ristics (e.g. gender differences, race/ethnicity differences). In the next section, the ANOVA results for the group mean risk drinking behaviors are addressed , concluding with the results of the multivariate regression analysis. This regression model includes the key independent variables related to the ou tcome variable. T he implications of the results will be discussed in Chapter 5 . Descriptive Univariate Results This section of C hapter 4 b egins with a brief description of students drinking quantity and frequency patterns during two academic terms. First, a compariso n between academic terms revealed that students from spring 2011 had on average 3.43 drinks per week compared to the students f rom fall 2011 who had on avera ge of 3.19 drinks per week (Table 4 1). Upon closer review different drinking patterns between the students from the spring and fall terms were found . For example, fewer students from spring 2011 compared to the fall 2011 student group reported consu ming zero drinks in a week (Figure 4 1 ) (202 students versus 281
59 students) . In addition, more students in the fall 2011 term compared to students from the spring 2011 term reported drinking on average five nine drinks per week (85 and 59 students, respectively) and drinking on average 10 or more drinks per week (78 and 67 respectively). Descriptive Crosstabulation In order to provide context to the research study, several cross table analyses between ke y independent variables were conducted . These results provide d a richer description of the research data and help ed shape the narrative for the s ubsequent chapter five. T living with status will be addressed , followed by a discussion of academic classification. Prior to discussing the results, several key variables were recoded in order to conduct meaningful group comparisons. For example, in order to compare s tudents by age, the student age variable was recoded into two groups: 1) a student group below the age of 21 and 2) a student group aged 21 years and above. There were approximately 52% of the students below the age of 21. Next, the working categorical v ariable was recoded into two groups: 1) not working and 2) working. The majority of students reported not working at 62.5% compared to 37.5% of students reporting working. In the first cross table analysis, the relationship between stu status was examined (Table 4 2). Students above and below the age of 21 both reported higher rates of not working, at 51.2% and 72.8%. These results indicate d that overall a greater percentage of students are not working in a full or part time position regardless of their age. However, there was more of an equal breakdown of students
60 above the age of 21 reporting working versus not working, as compared to an unequal breakdown of students below the age of 21 with 27.2% reporting working. In addition to t he status and residency living with status was also recoded residency categorical variable was recoded into two groups: 1) on campus (e.g. residence hall, fratern ity or sorority) 2) off campus (e.g. house, apartment). Next, the categorical variable of whom students report ed living with was recoded into three groups: 1) roommate, 2) alone, and 3) other (includes parents, spouse, chi ldren, other). T he differences b etween these two independent variables will be examined . The next section examines how student s age is related to their living status and arrangements. For instance, students above and below the age of 21 both reported higher rates of living off campus, a t 90 .1% and 53.5% respectively (Table 4 3). These results indicate d that overall a greater percentage of students are living off campus regardless of their age. Compared to the cross table analysis examining student age by work status, there was more of an equal distribution of students below the age of 21 reporting living on campus at 46.5%, versus 9.9% of students above the age of 21 living on campus. In a r elated fashion, the patterns of who students live with by their age were examined . For example, students above and below the age of 21 both reported higher rates of living with a roommate, at 79. 1% and 92.8%, respectively (Table 4 4). More students above the age of 21 reported higher rates of either living alone or with someone else (parents, spouse , children, other) as compared to students below the age of 21.
61 Finally, the distribution of student classification and age for this study was examined . First, there was an even distribution across the student sample with Seniors comprising the highest pe rcentage at 25.2% followed closely by Junior and Freshman students at 21.9% and 21.6%, Sophomores at 16.4%, and students in other areas: Graduate/Professional students, a nd other non degree at 15% (Table 4 5). Unlike some studies, a student sample was uti lized that represents the diverse student population in a typical large research institution. related to their academic classification, there is a risk of multicollinearity in a regression analysis. That is, students who are below the age of 21 but are classified in upper division classifications would make it classification. In some instances, age is counter to academic classification , as there are students above the age of 21 who are classified at Juniors, Seniors, and Graduate level. e and academic classification, it was found that 4.2% of the seniors and gradua te and professional students were under the age of 21 and 0.5% of the freshmen and sopho mores were 21 or above (Table 4 6). Because of this overlap of students by various ages across different academic classifications it is difficult to draw conclusions about high risk drin king behaviors based on this student characteristic. Therefore, this variable of academic classification was not included in the final analysis. Independent Sample T Tests In the next step of the data analysis plan, preliminary inferential statistical tes ts were conducted, particularly multiple independent sample t tests to examine mean differences on specific group attributes. The first t tests examined student
62 er, age, ethnicity) and student s drinking behaviors (i.e. av erage number of drinks per week). Next, student s work status , and weekly drinking patterns were examined were examined . Assumptions of inde pendence, normal distribution, and equal variances were made for each t test assumes that the student groups have equal variances at the p < .05. In the first t test analysis, it was determined that there were gender differences in high risk drinking behaviors. For this sample, t test results revealed a significant difference between males and females, with males reporting drinking more than females in a week, M = 4 . 52, M = 2.22 respectively (Table 4 7). Based on these results, the null hypothesis is rejected indicating that males and females differ in their drinking behaviors (i.e. average number of drinks per week), suggesting that drinking behaviors are directly r elated to gender. Next, drinking behaviors based on students age were compared . The t test results revealed a significant difference between students under and over the age of 21, with students over the age of 21 reporting drinking more than students u nder the age of 21 in a week, M = 4 .46, M = 2.24 respectively (Table 4 8). Not controlling for any other independent variables, this suggests that drinking behaviors are directly related to Simila r to age and gender, drin king behaviors bas ed on student s race/ethnicity were examined . The t test results revealed a significant difference between White and Minority students, with White students reporting drinking more than Minority students in
63 a week, M = 3 .98, M = 2.10, respectively (Table 4 9). Not controlling for any other variables, The next set of independent s amples t tests examined student s residency status and work status and weekly d rinking patterns. I ndependent samples t test were conducted to determine if high risk drinking beha viors were related to a student s place of residency status (e.g. living on or off campus). The t test results revealed a significant difference between students living on a nd off campus, with students living off campus reporting drinking more in a week than students living on campus, M = 3.73, M = 2.24, r espectively (Table 4 10). These results indicate d a significant difference in drinking behaviors (i.e. average number of drin ks per week) based on a student s place of residency. The next analysis examined if high risk drinking behaviors were related to Based on these results, there wa s no significant difference in drinking behaviors (i.e. average number of drinks per week) between students who reported their working status (i.e. part time or fulltime) and students who did not work (Table 4 11). Not controlling for any other variables, this suggests that drinking behavior is not directly related to work status of these students. Next, an independent samples t test was conducted academic grade performance differed by work status. Base d on the t test results, there wa s no significant difference in academic performance betw een students who reported their working status (i.e. part time or fulltime) and students who did not work (Table 4 12). This suggests that academic grade performance is not directly related to work status of these students . Finally , an independent sample s t test was conducted to
64 determine if high risk drinking behaviors varied social fraternity or sorority organization. The results revealed a significant difference between students involved and not involved in a social fraternity or sorority, with students involved in a social fraternity or sorority reporting drinking more in a week than students not involved, M = 5.8 6, M = 2.59, respectively (Table 4 13). Based on thes e results, the null hypothesis wa s rejected indic fraternity and sorority impacts their drinking behaviors. Overall, the basic inferential statistical analysis revealed several significant terns. Not controlling for any other variables, the variables of gender (male), age (above the age of 21), ethnicity (White), residency status (living off campus), and Greek participation drinking behaviors, as Analysis of Variance A one way analysis of variance (ANOVA) was conducted to determine if between group differences existed between with wh om a student reported living (i.e. roommate, alone, and other which includes parents, spouse, children, other) and their drinking behaviors. Based on these results, with who m a student reported living had no significant difference on drinking behaviors (i.e. average number of drinks per week) (Table 4 hoc tests were conducted to determine if differences existed i n as influenced b y their living with status (Table 4 15). These results also indicated that regard less with a roommate, alone, or with someone else such as a parent, spou se, or children, does not influence how much student will drink in a week.
65 Coupled with students living arrangements, a one way analysis of variance (ANOVA) w as conducted to determine if between group differences existed between living residency status (i.e. on campus or off campus) and their drinking behavi ors. Based on these results, difference on drinki ng behaviors (i.e. average number of drinks per week) (Table 4 16). hoc tests were conducted to det ermine if differences existed in drinking behaviors as inf luenced by where they live (Table 4 17). Based on these results, where s tudent li ved, whether off campus (i.e. house, apartment) or on campus (i.e. in a residence hall, fraternity or sorority), all had a significant difference on drinking behaviors (i.e. average number of drinks per week). Further, students reporting living in either a fraternity or sorority were more than seven times likely to engage in high risk drinking behaviors than students living in a residence hall or off campus. Students report ing living in a residence hall we re the least likely to engage in high r isk drinking behaviors. Multivariate Regression Analysis A hierarchical blocked multivariate regression analysis was conducted to determine the relationship between the following blocks: student individual characteristics, student residency status and eng agement, and student academic enrollment term and the primary outcome variable: st 4 18). The final model explained 19% of the total variance in the model F (9, 1176)= 31.57 , p< 0.001, and each block, except the last bloc k, produced a significant change in the model (p<0.001 ; Table 4 18 ). Finally, the results of the full regression model by the three regression blocks will be presented.
66 Student Individual Characteristics Based on the results, female students compared to their male college peers drank significantly fewer drinks on average per week (p<0.001) (Table 4 18). Likewise, comparing students by racial/ethnic classification, minority college students compared to their White college peers, drank significantly fewer drinks on average per week (p<0.001). Most importantly, there were significant differences between students based on their age. In particular, students under the age of 21 drank significantly fewer drinks on average per week (p<0.001) compared to student s who were 21 or older. Finally, there were no differences in drinking patterns for students based on their work status (i.e. not working versus working full or part time). Student Residency and Engagement D ifferences were found based on student s reside ncy status, type of campus engagement, and their academic performance. For example, students who lived on campus compared to students who lived off campus drank significantly fewer drinks on average per week (p<0.05) (Table 4 18). However, students who l ived in fraternity or sorority housing compared to students who lived off campus drank significantly more drinks on average per week (p<0.001). Next, there was a significant difference in student drinking patterns based on specific campus engagement activ ities. Specifically, students not involved in student Greek activities compared to students who participate in fraternity or sorority activities drank significantly fewer drinks on average per week (p<0.001). Finally, students who earned higher academic grades drank significantly fewer drinks on average per week compared to students who earned lower academic grades (p<0.001).
67 Student Enrollment Period Finally, there was no difference between academic term and student drinking patterns. That is, student s from the spring 2011 term compared to students from the fall 2011 term did not have significantly different number of drinks on average per week (p<0.001). Chapter Summary The purpose of C hapter 5 was to report the analysis of data from the Spring 2011 and Fall 2011 from t he Core Alcohol and Drug Survey. The results provided important insights about drinking behaviors at this institution. Specifically, the t tests and ANOVA individual characteristics, residency status, and campus engagement. Finally, based on a full multivariate regression analysis, significant results were found . Net all variables, sidency status and curricular and co curricular variables were found, but not with the student s academic term. Next, chapter five will include a discussion of the results and implications for programming and policy.
68 Table 4 1. Academic term d escr ipti ve statistics, dependent v ariable (n = 1,198) Academic Term N Mean Std. Deviation Spring 2011 Fall 2011 527 671 3.43 3.19 5.767 5.199 Figure 4 1 . Students self reported weekly drinking patterns Table 4 2 . Student age by work status Student Age Grou p Not Working Working Student 21 years or above Students below 21 years 51.2% 72.8% 48.8% 27.2% Table 4 3 . Student age by residency status Student Age Group On Campus Off Campus Student 21 years or above Students below 21 years 9.9% 46.5% 90.1% 53.5% 202 281 199 227 59 85 67 78 0 50 100 150 200 250 300 Spring 2011 Fall 2011 Abstainers (0 drinks) Social drinkers (1-4 drinks) High risk drinkers (5-9 drinks) Heavy drinkers (10+ drinks)
69 Table 4 4 . Student age by living with status Student Age Group Roommate Alone Other Student 21 years or above Students below 21 years 79.1% 92.8% 11.8% 5.1% 9.0% 2.1% Table 4 5 . Student academic classification Frequency Percentage Fresh man Sophomore Junior Senior Graduate/Professional/Other Total 260 197 263 303 180 1203 21.6 16.4 21.9 25.2 15.0 100.0 Table 4 6 . Student age by academic classification Student Age Group Freshman Sophomore Junior Senior Graduate Students 21 years or ab ove Students below 21 years 0.2% 41.3% 0.3% 31.1% 20.2% 23.4% 48.9% 3.7% 30.4% 0.5% Table 4 7 . Student gender by average number of drinks per week t test Gender N Mean Std. Deviation Male Female 563 634 4.52*** 2.22 6.575 3.922 * p < .05, ** p < .01, *** p < .001 Table 4 8 . Student age by average number of drinks per week t test Student Age Group N Mean Std. Deviation Students 21 or above Students less than 21 571 626 4.46 *** 2.24 6.434 4.109 * p < .05, ** p < .01, *** p < .001 Table 4 9 . Student ethnicity by average number of drinks per week t test N Mean Std. Deviation Std. Error Mean White Students Minority Students 744 449 3.98 *** 2.10 6.074 3.911 0.223 0.185 * p < .05, ** p < .01, *** p < .001
70 Table 4 10 . Students test Residency Status N Mean Std. Deviation Std. Error Mean On Campus Off Campus 347 849 2.24 3.73 *** 4.036 5.890 0.217 0.202 * p < .05, ** p < .01, *** p < .001 Table 4 11 . us by average number of drinks per week t test N Mean Std. Deviation Std. Error Mean Working Not Working 450 747 3.63 3.10 5.594 5.366 0.264 0.196 * p < .05, ** p < .01, *** p < .001 Table 4 12 . grade performance t test N Mean Std. Deviation Std. Error Mean Working Not Working 452 750 10.42 10.58 1.776 1.676 0.084 0.061 * p < .05, ** p < .01, *** p < .001 Table 4 13 . Greek status by average number of drinks per week t test Greek Status N Mean Std. Deviation Std. Error Mean Greek Non Greek 258 924 5.86 *** 2.59 7.259 4.621 0.452 0.152 * p < .05, ** p < .01, *** p < .001 Table 4 Sum of Squares d f Mean Square F p Between Groups Within Groups Total 132.145 35454.980 35587.125 2 1192 1194 66.072 29.744 2.221 0.109 * p < .05, ** p < .01, *** p < .001
71 Table 4 15 . hoc tests of mean differences for average number of drinks by st (I) Living With Status (J) Living With Status Mean Difference (I J) Std. Error Roommate Roommate Living Alone Living Alone Other Other Alone Other Roommate Other Roommate Alone 0.253 1.467 0.253 1.214 1.467 1.214 0.574 0 .703 0.574 0.875 0.703 0.875 * p < .05, ** p < .01, *** p < .001 Table 4 16 . Sum of Squares df Mean Square F p Between Groups Within Groups Total 2239.054 33358.891 35597.945 2 1192 1194 1119.527 27.986 40.004 0.000 * p < .05, ** p < .01, *** p < .001 Table 4 17 . hoc tests of mean differences for average number of drinks (II) Living Arrangement (J) Living Arrangement Mean Difference (I J) S td. Error Off Campus Off Campus Residence Hall Residence Hall Fraternity or Sorority Fraternity or Sorority Residence Hall Fraternity or Sorority Off Campus Fraternity or Sorority Off Campus Residence Hall 1.937* ** 5.556* ** 1.937* ** 7.492* ** 5 .556* ** 7.492* ** 0.357 0.856 0.357 0.891 0.856 0.891 * p < .05, ** p < .01, *** p < .001
72 Table 4 18 . Standardized beta coefficients for multivariate regression analysis on average number of drinks per week Variable name Block 1 Block 2 Block 3 In dividual characteristics Female student (Male student) 0.192*** 0.186*** 0.186*** Minority students (White students) 0.162*** 0.154*** 0.154*** Students under the age 21 (Students 21 or above) 0.178*** 0.148*** 0.148*** Working full or par t time (Not working) 0.000 0.007 0.007 Student residency and engagement On campus housing (Off campus housing) 0.073* 0.073* Fraternity or Sorority housing (Off campus housing) 0.109*** 0.109*** No Greek activities (Greek activities par ticipation) 0.198*** 0.198*** Academic grades 0.136*** 0.136*** Student enrollment period Fall 2011 academic term (Spring 2011 term) .000 R 2 0.104 0.196 0.196 Change in R 2 0.104 0.092 0.000 F 33.854*** 33.481*** 0.000 ( + p < .10, *p < .05, **p < .01, ***p < .001)
73 CHAPTER 5 DISCUSSION, IMPLICATIONS, RECOMMENDATIONS The purpose of this study was to examine in greater depth the relationship risk alcohol consumption and specific factors hypothesized to drinking patterns and to provide new insights and strategies (via programmatic and policy recommendations) for student affairs health promotion practitioners to utilize for decreasing high risk drinking behaviors among the college student population. This study utilized quantitative research methods to examine risk d rinking behaviors. Chapter 4 provided a detailed description of the results from the variou s quantitative analyses. Chapter 5 includes a brief summary of the key results, a dis cussion of the results, implications for student affairs health promotion practitioners, and recommendations for future research. Summary of the Results As highlighted in Chapter 2 , a vast amount of literature currently exists examining the complex issue o f college student high risk drinking and associated negative consequences. However, a dearth of information exists regarding the influence an entire academic semester (time period effect) can have on college student drinking behaviors, compared to existin g research focused on specific event and context level drinking (Neighbors, Foster, Fosso s, & Lewis, 2012). S everal important results were reported in Chapter 4 . The independent variables of gender, ethnicity, age, place of residency, participation in Gr eek activities, and academic performance all significantly influenced student drinking behaviors. As indicated in the multivariate regression time) and with whom a student lives (i.e. roommate, alone, or with someone else such as a
74 parent, spouse, or children) does not significantly influence the average number of drinks a student consumes in a week. Lastly, no difference exists between academic term (i.e. term period effect) an d student drinking behaviors , which may suggest that other period effect factors beyond the academic term period affect may influence student drinking behaviors . These findings, as they relate to individual hypotheses will be discussed in greater depth in the next section. Discussion of Findings for Hypotheses and Research Questions The first research question of to what extent do individual demographics and reported high risk drinking behav iors, will be discussed in further detail as organized by the first two regression blocks, student individual characteristics and student residency and engagement, from the multivariate regression analysis. Student Individual Characteristics The null hypot hesis that there will be no difference between the drinking behaviors of male and female students was rejected as the independent samples t test results revealed a significant difference with males drinking twice as much as females in a week. As indicated in the multivariate regression analysis, the variable of gender is drinks per week on average compared to females. This finding was anticipated and is consistent with previ ous literature in which males drink greater quantities and at higher Wechsler et al., 1994; Wechsler et al., 1995). Results of the independent samples t test reveal that White st udents drink twice as much as Minority students. Results of the multivariate regression analysis also
75 revealed that the variable of ethnicity is a significant individual characteristic, as White students on average drink more per week compared to Minority students. These findings are consistent with the literature on racial/ethnic drinking patterns of college Previous research determined that campuses with greater racia l and ethnic diversity such as larger enrollments of minority students, resulted in lower high risk drinking rates among the White majority students (Wechsler & Kuo, 2003). These findings may have future implications for how White students are placed in o n campus living arrangements as well as in social student organizations. Other analyses examining the variable of with status, and place of residency. Regarding wo rk status, both White and Minority students reported high rates of not working at 61.3% and 64.5% respectively. Regarding with whom students report living , for both White and Minority students, the overwhelming response was living with a roommate at 86.1% and 86.5% respectively. Both White and Minority students reported a high percentage of living off campus at 69.4% and 73.3% respectively. These cross table analyses served to paint a more complete portrait of the student population for this study and whi le they are not statistically significant, they remain key nuances for consideration when health promotion practitioners are making the determination as to how to prioritize resources and interventions targeting high risk drinking. Results of the independe nt samples t test reveal that students above the age of 21 consume alcohol at rates twice as high as their peers under the age of 21. Multivariate regression analysis results also revealed that the variable of age is a
76 significant individual characteristi c, as students above the age of 21 on average drink more per week compared to students below the age of 21. Other analyses examining with status, and place of res idency. Regarding work status, both students above and below the age of 21 reported high rates of n ot working at 51.2% and 72.8% res pectively. Regarding with whom students report living with, for both students above and below the age of 21, the overwhelm ing response was living with a roommate at 79.1% and 92.8% respectively. Regarding place of residency, a greater percentage of students above the age of 21 reported living off campus compared to students below the age of 21, 90.1% and 53.5% respectively. These results indicate that students under the age of 21 largely do not work, report living with a roommate, and are almost evenly split as to whether they report living on or off campus. Compared to students above the age of 21 who are almost evenly spl it as to whether they report working, who are slightly more likely to report living alone compared to students under 21, and who primarily live off campus. These are two different groups of students who deserve unique health promotions programming and po licy interventions. For example, if the majority of students below the age of 21 report no t working, the issue becomes how they are spending their free time. Additionally, for students below the age of 21 almost evenly split as to where they report livin g, does this imply that the 47% of students who live on campus are engaging in their drinking behaviors within their place of residence on campus. Compared with students above 21, with 90.1% reporting living off campus, an
77 issue of concern is whether thei r peers are responsible for influencing their drinking behaviors. While the literature demonstrates the need for campuses to develop targeted initiatives for students under the age of 21 including a heavy focus on first year students, these results indica te the need for health promotion practitioners to develop and implement strategies addressing the above 21 student population and their specific drinking behaviors as well (Montauti & Bulmer, 2014; Weitzman et al., 2003). This may include conducting futur e research exploring the motivation for students above the age of 21 to consume alcohol at higher rates in an effort to create targeted initiatives, similar to a booster shot this group of students can receive as they progress through their college career. As there is substantial research (Borsari et al., 2007; Hartzler & Fromme, 2003; Ross & DeJong, 2008; White et al., 2006) on first year college students and their current or newly established drinking behaviors upon arriving to campus, an area of future research to expand upon is the upperclassmen group of students and their drinking behaviors. While students aged 21 and up do not have the same challenges that first year students face upon arriving to campus, a recommendation for future research is exami ning the nuances and challenges specific to students 21 and above as it relates to their drinking patterns. Results of the independent sam ples t test reveal that there was no significant difference in drinking behaviors between students who reported thei r working status (i.e. part time or fulltime) and students who did not work. An additional t test involving work status revealed no significant difference in academic performance (i.e. academic grade point average). Results of the multivariate regression analysis confirm ed that work
78 status does not influence drinking behaviors. These results indicate d the variable of be considered as the main priority for health prom otion practitioners to focus on when creating specific initiatives addressing high risk drinking behaviors. Student Residency and Engagement Characteristics Within the student residency and engagement block, the variables of residency (e.g. on campus, off campus, Fraternity or Sorority housing), participation in Greek activities, and academic grades were examined in relation to the dependent variable of the average number of drinks students report consuming in a week. Results of the independent samples t t est reveal ed that students living off campus report ed consuming more drinks on average per week compared to students who report ed living on campus. Further, the results of the ANOVA conducted to determine if between group differences existed between stude significant difference regardless of where students reported living. Lastly, results of the multivariate regression analysis indicate d that students living off campus drink more on average per week compared to students living on campus. The place of residency resulting in the lowest drinking behaviors among students is a residence hall, followed by students living off campus who are twice as likely to drink on average more drinks in a week tha n students living in a residence hall. These findings are corroborated by the research (Wechsler & Nelson, 2008; Wechsler et al., 2002). Students reporting living in a Fraternity or Sorority house consume d the highest quantities of alcohol. Specificall y, these students are almost six times more likely to drink on average more drinks in a week compared to students who live in a residence
79 hall, and almost three times more likely compared to students living off campus. These findings support the current l iterature (Cashin, et al., 1998; Collins & Liu, 2014; Wechsler & Nelson, 2008) and reinforce the urgent need for health promotion practitioners to develop specific initiatives as well as examine the high risk environment of the fraternity and sorority hous es in efforts to decrease the excessive drinking behaviors of these students. The null hypothesis that there will be no difference between the drinking behaviors of Greek and non Greek students was rejected as the independent samples t test results reveale d a significant difference with students participating in Greek Specifically, students involved in Greek activities report ed consuming almost six drinks per week comp ared to less than three drinks per week reported being consumed by students not involved in Greek activities. Results of the multivariate regression analysis confirm ed be haviors. This finding was anticipated and affirms the research on college students involved with Greek activities typically consume more alcohol than students not involved with Greek activities (Borsari, Hustad, & Capone, 2009; Cashin et al., 1998; Collin s & Liu, 2014; Danielson, Taylor, & Hartford, 2001; Ham & Hope, 2003; Lo & Globetti, 1995; Wechsler et al., 1996). While there are many benefits for students to be involved in Greek activities including social, academic, and philanthropic, these findings also highlight ed the need for this population to be targeted with specific interventions, at different levels within the ecological model of health behavior to ensure a comprehensive approach is
80 implemented encompassing the individual student, the broader group norms, and the environmental context in which these drinking behaviors occur. Health promotion practitioners are encouraged to develop and implement multiple initiatives targeting these specific populations of males and students participating in Gr eek activities as it relates to their high risk drinking behaviors. Results of the multivariate regression analysis reveal ed 0.434; p < 0.001). That is, stu finding also confirmed in previous research (Presley et al., 1996a; Wechsler et al., 2000; Wolaver 2002). Unlike student s work status, there are negative repercussions between high risk d rinking behaviors and poor academic performance. Thus , there is the need for interventions to be implemented to create and sustain an academic environment that supports health promoting norms such as adjusting the academic schedule to have Friday classes, assigning projects and tests on Friday classes, and engaging faculty to be mindful of inadvertently normalizing the behavior of high risk drinking and further promoting harmful and inaccurate misperceptions around alcohol use (e.g. everyone drinks at coll ege). Additional suggested initiatives can include developing messages highlighting one of the negative and salient consequences of students engaging i n high risk drinking behaviors: the short and long term impact upon their academic performance. Short term consequences include missing a class or doing poorly on an exam or project the day after an evening of drinking, with long term consequences including falling behind in class and a low GPA (Hingson & White, 2012). These messages can frame the positiv e
81 exchange (e.g. academic success) students will receive as a result of either decreasing the amount of alcohol consumed or choosing to abstain altogether from drinking. The second research question of to what extent does student enrollment in the s pring a nd fall semesters relate reported high risk drinking behaviors, will be discussed in further detail as organized by the third regression block, student enrollment period, from the multivariate regression analysis. Student Enrollment Perio d Within the student enrollment period block, the variable of the academic term was examined in relation to the dependent variable of the average number of drinks students report consuming in a week. The null hypothesis that there will be no difference be tween the spring and fall 2011 samples in regards to s behaviors failed to reject as the multivariate regression analysis revealed that students from the spring 2011 academic term compared to students from the fall 2011 academic term did n ot have significantly different number of drinks on average per week. Results of descriptive statistics revealed that different drinking patterns exist ed between the students from the fall and spring terms with more students in the fall 2011 group report ing consuming zero drinks in a week as compared to the students in the spring 2011 group. Research indicates that traditionally the fall semester is considered to be the time frame in which students consume greater quantities of alcohol at higher frequenc ies and report experiencing more of the associated negative consequences (Del Boca, Darkes, Greenbaum, & Goldman, 2004; Neighbors et al., 2007). The fall semester is traditionally a time when campuses implement a vast amount of programming , particularly t he first few weeks of the fall semester aimed at the new and returning group of students, with not as much emphasis on the spring semester. The
82 unanticipated drinking patterns revealed through the data analysis of more students reporting abstaining from c onsuming alcohol in the fall semester than the spring semester warrant the need for campuses to pay closer attention to this issue and perhaps reconsider the type of programming implemented in the fall and spring semesters. However, as indicated by the da ta, the drinking patterns of more students reporting drinking on average five to nine drinks per week in the fall 2011 semester compared to the spring 2011 semester reinforce the need for campuses to continue their comprehensive programming targeting stude nts throughout the fall academic period. Limitations T his study has several limitations. First, self report data, utilized as the basis for this study, can include students not accurately remembering their past drinking behaviors, as well as not able to p recisely remember the number of drinks they consumed. Second, due to the somewhat delicate nature of the study, some students especially those under the age of 21 may have been reluctant to reveal any sensitive information specifically around their drinkin g behaviors for fear of legal outcomes, potentially resulting in under reported underage drinking statistics. Third, the issue of multicollinearity occurred when conducting a cross table analysis of student age and academic classification, as these two fa ctors are so closely related. This resulted in that factor not being included in the multivariate regression model. Fourth, the timing of the Core Alcohol and Drug Survey distribution is a limitation to be considered. As the multivariate regression mod el indicated, there is not a are enrolled (i.e. spring versus fall term). For this study, the survey implemented in the
83 spring 2011 semester occurred a few weeks after spring break had taken place in an future recommendation is to address the timing of when the survey is administered for data collection efforts as a potential strate gy for garnering different student responses. However, it is important to remember that when attempting to explain the differences in drinking rates between a spring and fall semester, it is challenging to control for all variables, especially environment al influences, as it relates to high risk drinking among the college student population and this needs to be take n into account moving forward. Fifth, the sample was heterogeneous as both undergraduate and graduate students between the ages of 18 and 24 we re included. This makes it more difficult to be able to generalize the findings of this study. Sixth, there was difficulty in the secondary data analyses as a few of the questions on the Core Alcohol and Drug Survey did not separate out alcohol and drug use, resulting in those questions not being ideal for helping to craft the comprehensive portrait of the student sample. Seventh, because the survey instrument was not created to test this theoretical model, it was beyond the scope of this study to test w hether macrosystem level programmatic and risk drinking behaviors. Eighth, the and background upon their drinking behaviors, wh ich can be a powerful factor upon decisions students make regarding the role alcohol plays in their life. Lastly, as this study is conducted at a large institution, the findings cannot be generalized to dissimilar institutions, such as two year or private institutions.
84 Implications for Health Promotion Practitioners This study provides relevant information for health promotion practitioners regarding the additional areas of future research as it relates to factors associated with high risk drinking behavi ors among the college student population. This study also provides evidence suggesting that the academic term (i.e. time period effect) in which behaviors. As a result, h ealth promotion practitioners need to take into consideration implementing continuous, comprehensive programming efforts regardless of the semester. Specifically, when examining the results of the multivariate regression analysis, health promotion practit ioners need to focus future alcohol intervention strategies targeting White male college students who live off campus or in a Fraternity house, are above the age of 21, participate in Greek activities and have low academic performance (i.e. a GPA of 3.0 or below), regardless of the fall or spring semester academic period. Strategies and campaigns should be developed with this particular audience in mind. Health promotion practitioners can target White male student leaders including those within the Greek population. These strategies can include educating this population on the signs and symptoms of alcohol poisoning, as well as creating and implementing social marketing campaigns addressing misperceptions students possess regarding how much alcohol their peers are consuming. Additional strategies include targeting students above the age of 21 as this group is consuming greater amounts of alcohol below the age of 21. While many campuses target students living in residence halls, an implication for futu re practice is to expand or even shift these efforts to students living in a Fraternity or
85 Sorority residence as well as to those students living off campus. Capone and colleagues (2007) recommend possible policy focused initiatives to establish targeting the Greek student population including implementing alcohol free rushes, delaying rush until the spring semester of the freshmen year as opposed to holding fraternity and sorority recruitment at the beginning of the fall semester which is a naturally high risk time period for new students, or eliminating alcohol use at fraternities or sororities. Additional research on students participating in Greek activities also recommends campus administrators actively implementing dry recruitment activities and defer ring recruitment to the second semester of the first year or to the sophomore year in an effort to address the risks and consequences associated with high risk drinking especially among the first year student population (Nelson & Engstrom, 2013). Dependin g upon the results of this study, potential recommendations for this specific institution may include similar environmental changes as identified in the literature as promising to address the high risk drinking behaviors in the student population at this p articular institution. Recommendations for Health Promotion Practitioners This research contributes to the current body of evidence highlighting the need to address specific factors as it relates to high risk drinking behaviors among the college student p opulation. This research explored more in depth the complex relationships between multiple social and psychological factors and college student drinking patterns, as well as examining the contextual impact of a full semester on drinking behaviors, in an e ffort to shed more light on the public health issue of high risk drinking. Future implementation of the Core Alcohol and Drug Survey can include administration every
86 th en conduct a follow up survey with the same cohort of students with a different instrument to capture longitudinal data. Currently, trend analysis data is being captured as the same instrument is being administered to a different group of students each ye ar. Implementing a longitudinal data plan would result in studying the same group of students more than once with the opportunity to ask the same set of questions at different time points to measure any change s in their drinking behaviors. s Systems Theory Model Revised (incorporating the Ecological Model of Health Behavior, Figure 2 1.) holds that the individual does not live in a discreet vacuum, but rather that all human behavior is nested within enduring, concrete context of cultural for ce; from the intimacy of a one to one encounter, up to and addition, all of these forces are active within the ongoing stream of real time; again, as the individual perceives the passage of moment to moment, day to day time as well as the passage of broad sweeps of cultural history. Therefore, pursuant to the present individual must be addressed. Thus, t he next section will provide programmatic and policy recommendations for student affairs health promotion practitioners within the context of the various Theory Model and Ecological Model of Health Behavior. Programmatic Recommendations at the Organizational (Exosystem) Level C o llaborate with the off campus life office to create educational campaigns targeting students living off campus, as the majority of the student popul ation at this institution lives off campus. Examples of potential campaigns include correcting norms and misperceptions held by students regarding alcohol and responsible social host laws, specifically when alcohol is served to minors at house parties. A dditional strategies include engaging and educating students on their overall responsibilities as part of living in a community and neighborhood
87 associations and the role that alcohol plays in this environment. Specifically door to door community campaign s to connect students living off campus with their neighbors, as this strategy communicates the standards expected of students living off campus as well as strengthening campus community relations between the neighborhood associations and the university (N elson & Winters, 2012). Create, market, implement, sustain, and expand appealing options for alcohol free late night programming on a regular basis throughout the academic year for students both below and above the age of 21 (DeJong & Langford, 2002). Research indicates developing late night alcohol free programming provides students with opportunities to socialize without the pressure and expectation to drink as a way to meet new people (Borsari et al., 2007). Additionally, when creating and implement ing this type of programming, tailor activities to recognize gender differences as male students report lower overall satisfaction from alcohol free activities than female students (Murphy, Barnett, Goldstein, & Colby, 2007). A third programmatic recommen dation includes faculty engagement such as increasing faculty student contact and educating faculty on their ability to correct student misperceptions of drinking norms. Faculty are often the first campus professionals to come into contact with students a nd they have the opportunity to engage and build relationships with students, as well as taking notice when students are not attending class on a regular basis or are performing poorly academically. Faculty can reach out to these students and provide info rmation on campus resources in the first step to ensuring help is obtained, especially as it relates to alcohol issues. Faculty can also schedule exams, quizzes, and project due dates during Friday morning classes as well as not canceling Friday morning c lasses , to establish the expectation that attendance is required for the completion of specific class deliverables, as a way to combat campus norms of students beginning their weekend and engaging in high risk drinking on Thu rsday evenings (Fairlie, Ericks on, & Wood, 2012). Policy Recommendations at the Organizational (Exosystem) Level Publicize student support of alcohol control policies, in conjunction with a comprehensive media campaign promoting university alcohol policies, alcohol related local and s tate laws, and on and off campus alcohol enforcement efforts. When promoting the university alcohol policies, include an emphasis on immediate, firm, and significant consequences for alcohol policy violations both on and off campus (Fairlie et al., 2012). Modify the academic schedule to include an increase in the offering of Friday morning classes before 10:00 a.m., particularly with an emphasis on required classes, in an effort to minimize high risk drinking on Thursday nights (Fairlie et al., 2012; Wo od, Sher, & Rutledge, 2007). Research indicates some majors may
88 be more favorable to students forming regular drinking patterns and behaviors, such as business or social science, and this may be a factor requiring further consideration and focus when impl ementing changes to the academic schedule (Wolaver, 2002). Require all Greek organizations adopt and implement a comprehensive risk management policy to decrease alcohol problems among members and at events taking place a fraternity or sorority owned build ings. Set policies controlling alcohol use and service at university sanctioned or university owned housing events. Examples of control policies include requiring the registration of events, requiring and enforcing guest lists, requiring a supervising professional bartender or server, limit the amount of alcohol served, requiring security, and limiting other entry ways so that all guests can be observed (Nelson & Winters, 2012). Programmatic Recommendations at the Interpersonal (Mesosystem) Level Creat e, implement, and sustain a campus wide social marketing campaign highlighting the social consequences of high risk drinking, specifically the immediate negative consequences from the night before such as drunk texting, regrettable sexual encounters, drivi ng while intoxicated, and getting into fights. In conjunction to the campaign focusing on these relevant consequences, the call to action encourages students to limit their alcohol consumption in exchange for the potential of experiencing fewer negative c onsequences. This campaign can also (Fairlie et al., 2012). Engage parents and family member s through educational campaigns encouraging discussions with their student about parenta l attitudes and expectations as it relates to alcohol consumption before, during, and after their transition to college (Nelson & Winters, 2012). Parental influence and especially a s students are entering college and continuing through their first year of college (Turrisi & Ray, 2010). Policy Recommendations at the Interpersonal (Mesosystem) Level Eliminate alcohol at Greek social organization events, prohibit Greek soc ial residence s, and implement alcohol free recruitment within the Greek system, in an effort to positively change the Greek environment and culture (Collins & Liu, 2014). If Greek social residences are to be maintained as a living option for students, then the recomme ndation is to implement permanent policy changes regarding the social climate characteristics and expectations within the various chapter houses. Examples include goal setting, continuous officer and executive board member education and training, clean an d well lit study spaces,
89 designated quiet hours, and other environmental changes all designed to behaviors and perceptions (Nelson & Engstrom, 2013). Establish policies to inform parents and family m embers of the scope of high risk drinking at the uni versity, as well as recommend strategies they can utilize to positively Programmatic Recommendations at the Intrapersonal (Microsystem) Level Implement a screening and intervention system to identify and assist students who experience issues as a result of their high risk drinking behaviors. Staff who work in the campus health care service, residence halls, the counseling center, athletic department, law enforcement, faculty, and others are all in a position to implement alcohol screenings, as they are likely to come into contact with alcohol impaired students (Nelson & Winters, 2012). Examine in greater high risk drinking behaviors such as aggression, alcohol expectancies, sensation and enjoyment seeking, and drinking motives to then be able to create targeted and personalized campus wide campa igns highlighting and challenging the se beliefs (Ham & Hope, 2003). These additional contributing factors can be segmented and explored more in depth with various student populations for a richer understanding of the problem. For example, students partic ipating in be addressed, as well as asking about the specific pressures to drink at fraternity and sorority functions. Students can also be segmented by gender and ethnicity when health promotion practitioners are exploring their responses to the various contributing factors around high risk drinking behaviors (Nelson & Engstrom, 2013). Through this strategy, customized campaigns can be developed focusing on various student p opulations and their individual specific drinking behaviors. Policy Recommendations at the Intrapersonal (Microsystem) Level Require all students, regardless of their age and classification, to complete brief motivational interventions at different instan ces during their time at the university. feedback and uses motivational enhancement strategies to promote alcohol risk Mandate all st udents who experience some type of alcohol related event complete some type of intervention to receive alcohol skills training and BASICS (Brief Alcohol Screening and Intervention for College Students). Over the course of two sessions, BASICS incorporates a harm reduction approach and use motivational interviewing strategies to encourage students to decrease alcohol use in an effort to reduce the negative consequences of high risk drinking.
90 Students receive customized feedback about their drinking behavio rs, information on how their personal alcohol use compares with their peers, explanations around perceived risks and benefits of drinking, and options to help in making changes to reduce or abstain from drinking (Nelson & Winters, 2012). Conclusion While when comparing the spring and fall semesters, this research demonstrates the importance of health promotion practitioners examining and taking into consideration the nuances associated with a fall and spring semester as it relates to high risk drinking. This research validates the past and current literature regarding the different factors impacting student high risk drinking behaviors. However, additional research is needed in severa l areas to continue to explore and expand upon this issue that campuses and communities address on a daily basis. These areas include the following: differences in drinking behaviors between students above and below the age of 21; the influence of student s living off campus and their drinking behaviors; the impact of students participating in Greek activities and their high risk drinking behaviors; and differences in drinking behaviors within the male student population. For example, future campus initiat reported negative consequence data by gender to capture rates and identify specific areas needing interventions for both males and females . past h igh school drinking behaviors as it impacts their current drinking behaviors in college, conducting research specific to the graduate student population and their reported drinking behaviors, conducting qualitative studies to capture individual student s to ries regarding their drinking behaviors and perceptions, and examining the student athlete population and their drinking behaviors.
91 As institutions are now encountering an increase in high risk drinking negative consequences with no indication of there bei ng a decrease of the level of severity, it is imperative health promotion practitioners and higher education administrators examine their current programs and policies to identify gaps and then outline a comprehensive strategy to ensure all students are su ccessful by persisting through graduation. Senior administrative support is essential when designing and implementing comprehensive campus initiatives to address the multitude of negative consequences. For all of these reasons, it is imperative campuses address high risk drinking through the lens of the ecological framework to maximize student success, development, and safety. These findings reinforce the need for this institution as well as campuses throughout the nation to continue to address this issu e of high risk drinking among the college student population. In conclusion, this study aimed to contribute to the wealth of literature on high risk drinking and the college student population by examining in greater detail the many factors influencing th ese behaviors as well as the potential impact of the time period effect.
92 APPENDIX C ORE ALCOHOL AND DRUG SURVEY LONG FORM
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105 BIOGRAPHICAL SKETCH Maureen received her Bachelor of Science degree in health science education from the University of Florida in 2000. In 2002, she received her Master of Public Health also from the University of Florida. She is a Certified Health Education Specialist. She began working at the University of Florida in September 2002 as a health educator specializing in the area of alcohol and other drug prevention among the college student population. She was selected as the Director of Gat orWell Health Promotion Services in the Division of Student Affairs at the University of Florida in May 2012 where she currently works. Maureen completed her doctorate in higher education administration in August of 2014.