Whitney Colbert Research Methods for the Social Sciences Trinity College Spring 2012

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1 ALCOHOL IN COLLEGE ATHLETICS: THE FIGHT TO RAISE AWARENESS OF BINGE DRINKING ON COLLEGE ATHLETIC TEAMS Whitney Colbert Research Methods for the Social Sciences Trinity College Spring 2012 While there is a great amount of information on college students and binge drinking today I wanted to focus more on the athletes perspective. This study will focus on today s generation as to why college athletes are binge drinking more now than ever before. I will be analyzing the data chosen from the Harvard School of Public Health Alcohol Study conducted in 1999, which shows the importance of alcohol in athletic teams and comparing those results to college students who are not on an athletic team. While using this secondary data I hope to draw further conclusions and develop a possible relationship as to why athletes drink more heavily than college academics, if that statement ends up being supported. INTRODUCTION This Harvard study focuses on substance abuse of college students throughout the United States. I have been interested in this subject ever since I arrived at Trinity my freshman year and became involved in college athletics. Over the past few years I have become further interested in why there has been such an increase in binge drinking among college campuses as well as, what effects college teams have on the culture of drinking. As a result of this behavior, alcohol becomes a prominent issue with coaches and players with regards to alcohol abuse. While growing up with older siblings I have always been intrigued by the connection between alcohol and athletes that is why I was hoping to study this possible connection. After being around Trinity for almost two years now, I am well aware that athletes do take advantage of their one night off a week, but I am interested to see if there are still longer lasting issues from alcohol abuse in student athletes. I will be specifically looking at alcohol abuse in athletes and comparing those results

2 to alcohol abuse in non- athletes. I hope to provide reasoning for why college sports have such a negative stigma attached to their name and to provide evidence as to if the athletic community does indeed have issues with alcohol. THEORY I drew my theory from my sociological background and personal experience after reading deeply into my data and looking back on specific experiences. While drawing conclusions based on social influences and forces such as peer pressure and team camaraderie, my theory behind this subject has become extremely complicated and coming from many dimensions. I am going to focus on the internationalist theory because there is a major impact on the individual vs. the group and the equality people have separately and the power of the group as a whole. After pondering this idea of alcoholism in college athletes for many years now I have been able to use my experience this theory first hand. It is important to understand the physical and mental reasons why athletes abuse such a common substance in a college setting, even if they are 21+ with regards to the power of a group. After reading briefly through my research with regards to what specifically the Harvard Study covered I defined my research question to Are student- athletes more likely to binge drink than regular academics? There are many theories as to why this is the cause however; my hypothesis is that student athletes on college campuses abuse alcohol because they can only go out on selected nights of the week or month. I expect to see that non- athletes, per night, drink much less than athletes

3 do when they have the option to go out as non- athletes have the freedom to go out as they wish. Athletes are specifically told that they are not allowed to go out on certain nights because of practices or contests and the thought of no one controlling the athletes on their day off allows them to let loose. By the end of my research I hope to help people understand if this statement is supported or not. LITERATURE REVIEW After reading through many articles it became apparent to me that alcoholism in college athletes has become an all around problem in the United States and even Canada. The most desirable question right now is, does alcohol affect student athletes on the playing fields or in the classroom? According to Andrew Schlichting s research of 210 students in Midwest Universities, it affects students more in the classroom than it does on the playing fields. After just a few hundred surveys it became evident that athletes appear to consume alcohol more frequently than regular college students. Schlichting believes that in order for this information to be considered hard evidence there needs to more student athletes surveyed around the United States in order for his points to be supported, more surveys need to be dispersed on a larger scale. These surveys however, give a strong base for what I am looking to study through this research paper and that is the basic overconsumption of alcohol in athletes compared to non- athletes. Similarly, Hugh Klein s article written in (1994) was developed over a 10 year period of time shows females and males during their college years. Klein notices that females generally grow to be more mature and males remain relatively

4 stagnant over four years. After studying 526 institutions around the world, 2565 students on campus living in dormitories, frat houses, or off campus, Klein noted a few major points in his article: 1. College became more a developing period of adolescence for men, whereas females started to become more acclimated with the idea of drinking and learning how to drink responsibly. 2. Expected to see students who enter college as immature or irresponsible while using alcohol 3. Expected four- year college students to have a matured attitude toward drinking 4. The number of people drinking alcohol in college will continue to increase as well as their consumption per occasion. The data was studied by keeping up with females in males starting in their freshman year in college and following them until they graduated from college. This information given is very useful in showing that college does have a drastic effect on drinking and this article will be a major stepping- stone in understanding the role of alcohol in institutions. Even though this study was created many years ago the quality of the research will still be valuable when looking at the idea of binge drinking between athletes and non- athletes. Tewksbury and Klein among many other researchers also points out the importance of alcohol in college students. In Tewksbury s journal article, he studies the effects of binge drinking in college athletes and comparing them to non- athletes the margin is vast. After much observation he realizes that binge drinking for

5 athletes is primary due to the fact of sex- appeal as well as a form of socialization such as going to the bar and going out with guy friends who also drink. For the non- athletes binge drinking is more due to the amount of time they commit to studying and their racial background. This is a tough article to collect valid data from as a whole because the data was collected in purely southern schools, however it will give me as a researcher a broader idea of how the United States portrays deviant behavior. To me this says that alcoholism is being measured in many different ways throughout the United States. Even in a Canadian University Athletes study and it was determined that Canadian- athletes as whole drink more (94.1%) than Americans do, even though Canadians do not use as many different types of illegal drugs and anabolic steroids, as well as crack/cocaine. While Patrick O Malley studied the average college student alcohol consumption which is two out of every five students were heavy drinkers, even though males were much more apt to drinking more than females. This observation is not necessary showing why athletes drink more than non- athletes it shows that depending on different countries, different standards are set for their athletes with regards to substance abusers. Another major article that focuses on the social aspect of drinking is written by Joel Grossbard whom talks about drinking games and the competitive influences they have on others. There are distinct differences between athletes and non- athletes in terms of being competitive or not and in this article the social aspect of rough housing and competing has a great amount to do with why there is a greater amount of binge drinking within athletes.

6 In conclusion, after many observations and articles it is apparent to that college athletes drink a vast majority more than regular students according to the authors above. Even though there is not precise data to conclude such evidence this theory can be supported through the data collected in my research. METHODS Starting from the beginning of picking through my topic ideas, I pondered the number of ways I could support or not my hypothesis. I realized that using deductive logic as well as my personal experience was the best way to start with developing a topic. After choosing my topic I decided that using secondary research was the best and most efficient way of receiving a large sample of results. I decided to use this study because I thought it was important to receive results from colleges and universities around the United States. I decided that the best way to collect data was through a census. If I were to collect my own data to get results on this subject, I would not get nearly as many participants and my results would end up being sectioned according to what school they went to; as a result, there would be many more errors and it would not directly apply to the broader population. I used a study conducted by the HARVARD SCHOOL OF PUBLIC ALCOHOL STUDY. There was a random sample of student selected from 129 schools according to my ICPSR data. The data was collected by a mail questionnaire and allowed people to send back their answers confidently. If the participants wanted to see the results of this test they were required to get IRB approval, which truly shows how confidential this study was. After this study there were two more of similar studies

7 conducted by the Harvard school, none of which is available now for analysis. This data is incredibly useful and displays my hypothesis to be supported. Even though there was a similar survey conducted a few years later the more recent data could be more precise, however, the question I wanted to answer in this research paper was specified in this data. I analyzed this data through SPSS (Statistical Package for Social Sciences). While using this database I was easily able to comprise data and make worthy inferences. I did this by first separating my dependent and independent variables. My dependent variable being: Alcohol abuse and my independent variables being Athletes and non- athletes. I started out with running my dependent variable and comparing those results from athletes who answered them and non- athletes. However, after running a frequency distribution as well as many other tables I noticed that the table size was much too large; meaning the number of variables was large. I recoded the number of drinks (which was in fact the number of times the participants drank each month) to 1, 2, 3, 4 and 5+. I recoded this data to make my results easier to read and after doing so the data became much more useful. I realized that because the frequency tables were not a useful way of displaying my results therefore, I decided to use the crosstabs option on SPSS and manipulating my variables to my specific study. In the findings section below you will see the many types of graphs and charts that I used to insure the validity of my results as well as easily displaying them by using chi- square, crosstabs, and bivariate data tables.

8 Specifically speaking in terms of analyzing this data s validity, I believe that the tables are the only way to truly discover if my data is valid or not. I used control variables such as age and gender to test the validity as a whole. Even though the exact number of participants is skewed in terms of sex, while implementing the ordinal measurement such as age I was able to draw inferences from that. Because I was studying college level student- athletes I specifically looked at people aged from and checked the validity of my results that way. FINDINGS According to the tables listed below, Table one being a bivariate table below which shows the importance of athletics and the amount of instances people binge drank per night that directly correlate with my hypothesis. As shown in the bivariate table the percentage of people who say that athletics are very important binge drink in the majority of the columns displayed. People that binge drank one night according to this data and who say that athletics are not at all important consist of 67.9% of the total votes who responded that athletics are not at all important in that column. In the row that stated the participants binge drank 4 times a month 17.8% if people said that athletics were very important where, as the people who believed athletics are not important at all consisted of 9.2% of the vote. To me this data says because there was a vast majority of people who responded to not at all interested in sports says that the researcher s largest sample in this survey were people who do not find athletics to be important binge drank the smallest amount. This however, does not throw off the results of my data because for the rest of binge drinkers interviewed were relatively the same sample size. According to the participants who identified themselves with binge drinking 5 or times during that month

9 and describe athletics as very important to them have the highest percentage of times of binge drinking than all other columns (athletics being labeled as important, somewhat important, and not at all important) The column itself that shows athletics being very important is the smallest sample size of them all but displays a trend that athletes (for the most part) consist of the greater percentage in binge drinking 1-5+ times per month. However, while looking at the average of people who believe athletics are somewhat important, important, and very important and comparing that half to the amount of 3 + occurrences of binge drinking per month consist of nearly 90% of the votes. To put this in plain terms the people who believe athletics is at least somewhat important and binge drank more than 3+ is approximately 90% of the total votes in this survey, thus supporting my hypothesis correct by saying that binge drinking in athletes is more prevalent than non-athletes. This data states that athletes who get 1-2 days off per week display those free days as time spent binge drinking; whereas, people who do not include athletics to be in their schedule average nearly 1-2 times of binge drinking per month. I believe this hypothesis was proven correct because there was a large enough sample size for even the smaller samples to conclude a positive reasoning for my data. In this bivariate table the numbers directly correlated because there were many different variables tested throughout this experiment and this specific survey that was answered consisted of an appropriate number of participants. According to table two shown below, I believe shows the best possible correlation between athletes and binge drinking which is the chi-square test. The chi-square chart simply tests my secondary data and compares that too what I thought the data should be, that being that athletics and alcohol are positively correlated. In this chart the number

10 under Asmp. Sig. (2-sided) displays the number.000. By just looking at that number, this data says that because.000 is a perfect correlation and because.000 is less than.05 significance level, it is necessary for me to reject my null hypothesis and accept my hypothesis. The.000 says that there was absolutely no error in my data meaning that none of the numbers in my data were skewed and there is a positive correlation between my dependent and independent variables, which were proved to be, correct. The value to the right of Pearson Chi-square is also relatively high which says that the data is as I expected it to be. This chi-square chart showed a positive correlation between my hypothesis and the data below because the survey conducted was precise enough to prove my hypothesis correct. In tables 3 and 4, which include my control variable, gender. After looking over my results with regards to adding a control variable I noticed there were similarities between gender and occurrences of binge drinking. The male section of binge drink highlighted in blue shows me that people who believe athletics are very important have the highest percent of binge drinking in every column except when they only binge drink one night a month. For the men, my hypothesis is supported because even though there is 3.6% (5+ binge drinks per month in the very important column) that is still the highest percentage under the amount of 5+ times per month. While looking at 3 binge drinking events and 4 binge drinking events the results are relatively the same as the 5+ binge drinking events which state that sports are very important to them and on average the athletes who believe sports are most important to them are still averaging (as a whole) going out 1-2 nights a week, which consist of their off days. In the female section while

11 looking at the occurrences of binge drinking I noticed relatively similar results the women who binge drank 3-5+ nights a month had the highest percentage of believing athletics are very important. However, while looking at one binge drinking occurrence and 2 binge drinking occurrences I noticed they have the smallest numbers under the very important column, those being 42.90% of one count and 12.40% of two counts of binge drinking per month. In conclusion, after controlling for my variable of gender, my results remained stagnant, however, males overall did have a higher percentage of binge drinking under the very important column as a whole. The chi-square tables showed me that there is a positive correlation in all categories and that there is nearly no room for error in my data. Table 1: Binge drinking per month and athletics- Cross tabulation Activity: athletics Number of times participants Somewhat binge drank per month Very Import Important Imp. Not At All Total Binge 1 Count drink %: athletics 47.80% 53.90% 60.10% 67.90% 60.80% 2 Count %: athletics 14.40% 12.80% 12.30% 11.30% 12.30% 3 Count %: athletics 12.60% 10.70% 10.00% 8.50% 9.80% 4 Count %: athletics 17.80% 16.30% 12.80% 9.20% 12.50% 5 Count %: athletics 7.30% 6.30% 4.80% 3.10% 4.70% Total Count %: athletics % % % % % Table 2: Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square a

12 Table 3: Binge drink- athletics- gender Cross tabulation Gender Very Import Important Some- what Imp Not At All Total Binge- drink 1 Count Male % : athletics 54.90% 62.50% 65.30% 72.30% 67.50% 2 Count %: athletics 17.40% 12.70% 12.40% 10.70% 12.00% 3 Count %: athletics 11.50% 9.20% 9.20% 7.60% 8.60% 4 Count %: athletics 12.70% 12.50% 10.30% 7.20% 9.30% 5 Count %: athletics 3.60% 2.90% 2.80% 2.20% 2.60% Total Count %: athletics % % % % % Binge- drink 1 Count Female %: athletics 42.90% 46.80% 52.10% 56.20% 50.30% 2 Count % : athletics 12.40% 12.90% 12.10% 13.00% 12.60% 3 Count %: athletics 13.30% 12.00% 11.30% 10.70% 11.70% 4 Count %: athletics 21.40% 19.20% 16.60% 14.40% 17.50% 5 Count %: athletics 10.00% 9.10% 7.90% 5.60% 7.90% Total Count %: athletics % % % % % Total Count Table 4: Chi- Square Test with control GENDER Value df Asymp. Sig. (2- sided) Female Pearson Chi- Square a 12 0 Male Pearson Chi- Square b 12 0 Total Pearson Chi- Square c 12 0

13 CONCLUSION After analyzing my research the findings displayed confirmed my hypothesis to be correct. This data says that for (on average) every 1-2 day(s) athletes have off from their sport they are taking that time and binge drinking. Whereas, the participants who do not compete in athletic events binge drink half that amount of time per month. From looking at this date from a logical standpoint however, there could be a third variable that could interrupt my data, such as sex. The data that I used was collected by a number of males and females however, I did not dissect that data specifically because I believe that getting the fuller understanding of my data was the most important part of receiving the best possible results. There was not a specific number of males or females displayed that took part in the survey, but the methods section displayed that both males and females were sent questionnaires and did complete them. It is obvious to me that the Harvard school decided that more comprehensive research and samples were necessary to get fuller results. This entails that the number of athletes could increase per school; alcohol consumption is increasing regardless of whether they are athletes or academics, and more questions were probably asked. While looking at each activity specifically, through a certain sport, could be more or less apt to drink. That is why after further research through understanding my data I realized that looking at the importance of athletics, as a whole was a more efficient way of analyzing my data. The importance of alcohol in general is becoming an important topic in today s era, whether that means in the college setting or in high school there has

14 been an extremely abundance in alcohol itself. After analyzing my data thoroughly I did not realize how much of effect athletics, specifically students being in a group setting has on an individual. It has become apparent that because athletes have such a negative stigma attached to the title of being an athlete has created for a negative environment allowing athletes to accept the role of being deviant. It is important that further research is done each year to understand the trend of alcohol and whether there is a certain sport has a greater bond with alcohol and approaching that to decrease the abundance of alcohol abusers. WORKS CITED Klein, Hugh Changes in College Students Use and Abuse of Alcohol, and their Attitudes towards drinking over the course of college years. Journal of Youth and Adolescence 23(2): Martens, Matthew P Predictors of Alcohol- related outcomes in College athletes: The roles of trait urgency and drinking motives. 36(5): Tewksbury, Richard. Higgins, George E., Mustaine, Elizabeth Ehrhardt Binge Drinking Among College Athletes and Non- Athletes. Deviant Behavior 29(3): Spence, John C., Gauvin, Lise Drug and Alcohol Use by Canadian University Athletes: A National Survey Journal of Drug Education 26 (3): Schlichting, Andrew W How Alcohol Affects College Student- Athletes Masters Abstracts International 47(02): 1226 Grossbard, J., Geisner, I., Neighbors, C Are Drinking Games Sports? College Athlete Participation in Drinking Games and Alcohol- Related Problems Journal of Studies on Alcohol and Drugs 68.1 (Jan 2007): Snyder, Eldon E. Interpretations and Explanations of Deviance among College Athletes: A case study Sociology of Sport Journal.

15 11. 3 (Sep 1994): Grossbard, J., Geisner, I., Neighbors, C Athletic Identity, descriptive norms, and drinking among athletes transitioning to college Journal of Addictive behaviors (April 2009):

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