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1 SOCIAL LEARNING THEORY: UNDERAGE DRINKING, BLACK MARKET ASSOCIATIONS, SUBSTANCE USE AND DEVIANCE By HEATHER STEWART A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQ UIREMENTS FOR THE DEGREE OF MASTER OF ARTS UNIVERSITY OF FLORIDA 2010
2 2010 Heather Stewart
3 To my mother and all those who nurtured my intellectual curiosity, academic interests, and sense of schol arship throughout my lifetime, making this milestone possible
4 ACKNOWLEDGMENTS I wish to thank my mentor, chair and intellectual inspiration, Ronald L. Akers, his guidance and support has been invaluable. I wish to thank my supervisory members (Lo nn L anza -Kaduce, and Marv Krohn), their expertise truly made this possible Fina lly, I wish to thank my fellow c riminology graduate students for the mutual support during the frequent stressful times.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................................... 4 ABSTRACT .......................................................................................................................................... 8 CHAPTER 1 PURPOSE OF THE STUDY ..................................................................................................... 10 Research Questions ..................................................................................................................... 10 Purpose ......................................................................................................................................... 10 Hypotheses ................................................................................................................................... 11 2 INTRODUCTION ....................................................................................................................... 13 3 LITERATURE REVIEW ........................................................................................................... 16 Theoretical Rationale and Literature Review: A Social Learning Perspective on Black Market Associations .............................................................................................................. 16 Prior Research: The Legal Drinking Age .................................................................................. 18 Prior Research: Underage Drinking ........................................................................................... 20 Prior Research: Social Learning Theory and Underage Drinking ........................................... 23 4 STUDY PROCEDURES ............................................................................................................ 25 The Present Study ........................................................................................................................ 25 Methodology................................................................................................................................ 27 Participants .................................................................................................................................. 28 Materials and Procedures ............................................................................................................ 31 Measures of Control Variables ................................................................................................... 33 Measure of Alcohol Black Market Sources ............................................................................... 34 Measures of Dependent Variables ............................................................................................. 34 Marijuana Use ...................................................................................................................... 35 Marijuana Black Market Sources ....................................................................................... 35 General Deviance................................................................................................................. 36 Specific Black Market Deviance ........................................................................................ 36 Measures of Social Learning Variables ..................................................................................... 39 Differential Reinforcement ................................................................................................. 39 Definitions/ Attitudes .......................................................................................................... 40 Differential Association ...................................................................................................... 42 Imitation/ Modeling ............................................................................................................. 45 Data Analysis ............................................................................................................................... 47
6 5 RESULTS .................................................................................................................................... 54 Alcohol Black Market Sources ................................................................................................... 54 Marijuana Black Market Sources ............................................................................................... 55 Marijuana Use ............................................................................................................................. 58 General Deviance ........................................................................................................................ 60 Support for the Hypotheses ........................................................................................................ 61 6 CONCLUSION ........................................................................................................................... 63 Discussion .................................................................................................................................... 63 Limitations and Implications ...................................................................................................... 64 APPENDIX A SOCIAL LEARNING MODEL ................................................................................................. 66 B IRB PROTOCOL FORM ........................................................................................................... 68 C INFORMED CONSENT FORM ............................................................................................... 73 D DEBRIEFING FORM ................................................................................................................ 76 E INSTRUMENT ........................................................................................................................... 78 F CORRELATION MATRICES ................................................................................................. 113 G BIOGRAPHICAL SKETCH .................................................................................................... 124
7 LIST OF TABLES Table page 4-1 Participant Characteristics ..................................................................................................... 32 4-2 Descriptive Statistics .............................................................................................................. 47 5-1 Model 1 ................................................................................................................................... 54 5-2 Model 2 and Model 3 ............................................................................................................. 56 5-3 Model 4 and Model 5 ............................................................................................................. 58 5-4 Model 6 and Model 7 ............................................................................................................. 60
8 Abstract of Thesis Presented to the Graduate School of the University of Flor ida in Partial Fulfillment of the Requirements for the Degree of Master of Arts in Criminology, Law & Society SOCIAL LEARNING THEORY: UNDERAGE DRINKING, BLACK MARKET ASSOCIATIONS, SUBSTANCE USE AND DEVIANCE By Heather Stewart August 2010 Chair: Ronald Akers Major: Criminology, Law and Society This research is the first part of a multiphase study which focuses on underage drinking, methods of obtaining alcohol while underage, and related deviance. Specifically this study examines the applicability of Akers social learning theory in this context. Youth under the legal drinking age are illegally obtaining alcohol. Previous research has revealed that underage drinkers sometimes utilize persons they are not closely associated with, or strangers of legal drinking age, to procure alcoholic beverages (Lanza -Kaduce and Richards, 1989). In the literature this method of procuring alcohol has been labeled black market In this research, I examine black market associations made while obtai ning alcohol illegally in relation to other black market associations, other black market deviance, and deviance in general. This research utilizes social learning theory as a framework within which these black market peer associations are examined speci fically whether or not they facilitate further deviance and more explicitly the extent to which they increase the likelihood of other black market deviance The study sample was 408 undergraduates drawn from the departmental participant pool at a major s outheastern university. Data were collected through an online survey instrument and analyzed with multivariate statistical techniques. Results indicated that having black market peer associations
9 for alcohol was predictive of further black market associat ions, substance use in general, and general deviance. As hypothesized, these relationships were diminished when entered into the equation with the social learning variables. Black market peer associations are viewed as a specific type of differential peer association, so the variance is explained by the model including the social learning variables.
10 CHAPTER 1 PURPOSE OF THE STUDY Research Questions Research questions were as follows : Can Alcohol Black Market Sources be predicted using social learning v ariables?; Does the use of Alcohol Black Market Sources have a significant effect on the use of Marijuana Black Market Sources, and is that relationship diminished when social learning variables are present?; Does the use of Alcohol Black Market Sources have a significant effect on the use of marijuana, and is that relationship diminished when social learning variables are utilized?; Does the use of Alcohol Black Market Sources have a significant effect on General Deviance, and is that relationship diminished when social learning variables are present? For the purposes of this study, using black market sources was defined as the utilization of any person personally unknown to the participant trying to obtain the illegal substance (be it alcohol, drugs or otherwise). Sources were only labeled black market if the participant indicated that the source was a stranger or another student that they did not really know. The illegal substances in this study included alcohol for underage drinkers and marijuana. Pu rpose This research attempted to examine the behavior of underage drinkers, specifically the manner in which they procured alcohol, and if that included black market associations, whether those participants were more likely to be involved in deviant behavior, including other black market deviance. Researchers intended to examine the black market relationships developed by underage drinkers in the context of Akers social learning theory in an attempt to indicate whether or not those relationships were sim ply a specific type of differential association, or if it was something entirely different. To date, there has been no research examining black market sources utilized by underage drinkers and the possible link to further deviance and the
11 development of other black market sources There was one published study that looked at the methods underage drinkers use to obtain alcohol (Lanza -Kaduce and Richards, 1989), but aside from determining those methods the literature is lacking Thus t he current study is unique. Black market sources developed to obtain alcohol by underage drinkers has not yet been looked at. Furthermore, social learning theory has never been applie d in this specific manner. The internet survey was designed specifically to measure both bl ack market sources and all four social learning variables utilizing completely different survey items for black market sources and differential association. These two measures are never used tautologically It is important to understand the link bet ween underage drinking, substance use and deviance If there is a link between Alco hol Black M a rket Sources, Other Black Market S ources and General Deviance, it could provide some insight for future intervention actions and policy changes. Further, conducting a study that can potentially expand the empirical support for social learning theory, and provide a unique understanding of black market associations, may allow for a full test of the social structure social learning (SSSL) model in the future Thi s second study would test these same variables on both a national level and an international level with a survey specifically designed to measure all eight variables in the SSSL model, possibly for the first time. Hypotheses Based on the findings from extant research and the theoretical framework of social learning theory, our study addressed four hypotheses: 1) The use of Alcohol Black Market Sources is predicted by social learning variables; 2) The use of Alcohol Black Market Sources has a significant effect on use of Marijuana Black Market Sources, but that effect will be reduced and become non -significant when measures of social learning variables are entered in a multiple regression model; 3) The use of Alcohol Black Market Sources has a significant relationship
12 with use of marijuana (Marijuana Use), but that relationship will become non -significant when measures of social learning variables are entered in a multiple regression model; 4) The use of Alcohol Black Market Sources has a significant relat ionship with other measures of deviant behavior (General Deviance), but that relationship will become non -significant when measures of the social learning variables are entered in a multiple regression model.
13 CHAPTER 2 INTRODUCTION Much research has b een conducted in the area of youth alcohol use. This research covers everything from deviance associated with early onset drinking to the negative results it can have on health. College students comprise a large portion of the sample populations from whic h this area of research draws (Wechsler, Davenport, Dowdall, Moeykens & Castillo, 1994, Wechsler, Dowdall, Maenner, Gledhill -Hoyt, & Lee, 1998; Wechsler, Nelson & Kuo, 2002). Underage drinking, binge drinking, and drinking in general, are thought by mains tream America to run rampant on college campuses, and to some degree they are correct. Drinking is, in fact, a problem faced by many college campuses (Akers & Jenson, 2003; Boeringer, Shehan, & Akers, 1991; Durkin, Wolfe & Clark, 2005; Durkin et al., 1996; Hood, 1996; Lanza -Kaduce, Capece & Alden, 2006; Lanza -Kaduce & Capece, 2003; Mayer, Foster, Murray & Wagenaar, 1996; Sun & Longazel, 2008; Wechsler et al., 2002). Research indicates that college students are significantly more likely to partake in heavy drinking than their peers not enrolled in college, who are the same age (Bachman, OMalley & Johnson, 1984; OMalley & Johnson, 2002; Sun & Longazel, 2008). More importantly, both and on and off college campuses, drinking has been linked to a plethora of other problems. Rape is one of the most serious issues related to drinking on college campuses, especially acquaintance rape (Durkin et al., 2001; Boeringer, Shehan, Akers, 1991; Abbey, 1991; Koss & Dinero, 1989; Muehlenhard & Linton, 1987). Drunk driving, the very catalyst for raising the LDA (legal drinking age), is also observed as a result of drinking on college campuses (Durkin et al., 2001; Robinson, Roth, Gloria, Keim & Sattler, 1993; Werch, Gorman, & Marty, 1987; Engs & Hanson, 1988; Saltz & Elandt, 1986). Students with drinking
14 problems have a propensity towards low self control and indicate increased deviant behavior (Gibson, Schreck & Miller, 2004; Haberman, 2001; Piquero, Gibson, & Tibbetts, 2002). Overall aggression, including fighting, bull ying, violence and property damage, is another concern that is positively correlated with drinking on college campuses (Durkin et al., 2001; OHare, 1990; Engs & Hanson, 1988; Werch, Gorman & Marty, 1987; Wechsler & Rohman, 1981). Poor academic performanc e is noted as a result of drinking by college students (Lanza -Kaduce, Capece, & Alden, 2006; Durkin et al., 2001; Rapaport, 1993; Haberman, 2001; Johnston, Bachman, & OMalley, 1992; Saltz & Eldant, 1986; Wechsler & Nelson, 2008). And finally, researchers combining statistics from three national surveys, and a myriad of other data sources, estimated that approximately 1,700 college students die every year from alcohol related accidents/ injuries (Higson, Heeren, Zakocs, Kopstein, & Wechsler, 2001). Thus, drawing samples from college campuses makes sense, as drinking is a problem, and there are both underage and legal age students who drink in these populations. Substance use other than alcohol is also a prevalent problem on college campuses across the Uni ted States (Gledhill Hoyt, Lee, Strote & Wechsler, 2000; Johnston, OMalley, Bachman & Schulenberg, 2004; McCabe, Schulenberg, Johnston, OMalley, Bachman & Kloska, 2005; Haberman, 2001; Strote, Lee & Wechsler, 2001). Marijuana is the most prevalent illic it substance utilized by college students (Johnson et al., 2004). It is followed by hallucinogens, amphetamines, cocaine and ecstasy or MDMA, though the use of MDMA has been increasing while other illicit drug use has remained fairly stable (Johnson et al ., 2004; Larimer, Kilmer & Lee, 2005; Strote, Lee & Wechsler, 2002). While some studies cite health reasons, increased risk taking behavior, and poor
15 academic performance as reasons for studying illicit substance use (Larimer et al., 2005; Strote et al., 2002), others allude to the fact that college students are at an age where they are without parental control, usually for the first time, able to afford illicit drugs, and have a tendency to try new, previously prohibited behaviors (Gledhill -Hoyt et al. 2000: 1656).
16 CHAPTER 3 LITERATURE REVIEW Theoretical Rationale and Literature Review : A Social Learning Perspective on Black Market Associations While this literature has highlighted the links between underage drinking and other problems, little o f it has focused on the unintended problematic consequences of underage drinkers procuring alcohol through illicit means especially that which involves contact with strangers and others, which Lanza -Kaduce and Richards (1989) refer to as black market asso ciations. The present research investigated the possible devianceenhancing effects of engaging in such black market behavior such as using the same techniques to procure other substances that are illegal for all ages such as marijuana, as well as oth er forms of deviant and illegal behavior The argument here is that using such black market sources for underage acquisition of alcohol and its links to black market sources for other substances and other deviant behavior can be understood by referencing social learning theory concepts and variables -differential association, differential reinforcement, imitation, and definitions social learning theory (Akers, 1998). Although there is research on the connections between illicit procurement of drugs and violent and other criminal behavior, to date there is no research on the connections between the black market procurement of alcohol by minors and these other f orms of crime and deviance. Social learning theory has been developed by Akers and some of h is colleagues. It has been well supported in studies dealing with substance use/ abuse crime, and deviance Indeed, social learning theory is one of the most empirically supported theories in criminology (Akers, 1973, 1977, 1985, 1994, 1998; Akers, Krohn, Lanza -Kaduce, and Radosevich, 1979; Burgess and Akers, 1966; Akers et al., 1989; Akers and Sellers 2008;
17 Akers and Jensen, 2003; 2006). However, the present research is the first to apply s ocial learning theory to use of black market sources by mino rs procuring alcohol. In social learning theory, behavior is viewed as elicited by the physical and social environments in which the person is located at any given time and through time (Akers, 1998; Akers & Se llers, 2008; Bandura, 1973, 1977; Braukmann Fixen, Phillips & Wolf, 1975). Social learning theory, as defined by Akers, encompasses four main variables that explain how behavior, conforming or deviant, is learned and maintained: differential associations, definitions, differential reinforcement and imitation. Differential association refers to the direct and indirect association with others who engage in and support different types of behavior. These associations provide the major social contexts in which all the mechanisms of social learning ope rate (Akers and Sellers, 2008). Differential peer associations are one of the strongest predictors of delinquency in youth ( Agnew, 1991; Akers, 1998; Brank, Lane, Turner, Fain & Sehgal, 2008; Dishion, McCord & Poulin, 1999; Longshore, Chang & Messina, 2005). Definitions, Akers contends, are the meanings, beliefs, and attitudes one has toward a particular behavior. The more positive the definition of the behavior, the more likely the behavior is to occur be it conforming or deviant. Differential re inforcement is the balance of perceived rewards and punishments consequential to a behavior. The more rewarding one views the behavior the more likely that person is to partake in it and repeat it in the future, thus it works both to create or dissuade, a nd maintain or desist behavior. There are two types of reinforcement, negative and positive. Negative reinforcement strengthens a behavior by rewarding a behavior that removes something negative, such as putting on sun glasses to alleviate the glare of the sun, or using a drug to alleviate a withdraw al symptom. Positive
18 reinforcement strengthens a behavior by presenting something positive, much like a pat on the back after hitting a home run, or verbal approval by a friend after certain a behavior has occurred. Punishment works in a similar fashion. Negative punishment is the removal of something pleasant after a behavior occurs that weakens that behavior (being grounded for a poor report card), while positive punishment is the presentation of an adverse stimulus subsequent to a behavior, also weakening the target behavior (a hangover after an evening of drinking). Finally, i mitation is the fourth learning variable. It is more likely to affect the acquisition of novel behavior, but continues to have some effect in the maintenance of behavior. It is exactly how it sounds; one imitates or models the behavior after observing another act out. These four variables are micro level variables, meaning they apply specifically to the individual or a small group o f individuals (Akers, 1973, 1977, 1985, 1994, 1998; Akers, Krohn, Lanza -Kaduce, and Radosevich, 1979; Burgess and Akers, 1966; Akers et al., 1989; Akers and Sellers 2008). Prior Research: The Legal Drinking Age Many studies have looked at the LDA and its implications. Wagenaar et al. completed a meta analysis of all the literature that focused on the LDA from 1960 to 2000 (2002). The overall tone of this analysis confirms what both Lanza -Kaduce and Richards found in 1989 from U.S. statistics, and what N ickerson found from Canadian data in 2001. Both lowering and raising the legal drinking age have had unintended consequences. In fact, the goal of raising the legal drinking age was to ameliorate problems associated with emerging adult/ adolescent alcoho l consumption. Lowering the age is associated with increased consumption among younger people and raising the age has unintentionally played a role in other problems (Wagenaar et al., 2002; Lanza Kaduce and Richards, 1989; Nickerson, 2001).
19 Lanza -Kaduc e and Richards experienced a unique opportunity for research when the legal drinking age was changed from 19 to 21 in Florida. All of the 19 year olds born after July 1, 1966 would have to wait until their 21st birthday to drink, while anyone born before that date was grandfathered in. Thus, researchers had access to 19 year olds that the new law affected, and 19 year olds that it did not affect (1989). Lanza -Kaduce and Richards had several research questions in mind, and among them was: whether or not raising the LDA led to derivative law breaking, and what impact it had on the social context of drinking. They had some interesting findings. Underage drinkers were much more likely to utilize persons they are not closely associated with, or strangers (bl ack market associations) to obtain alcohol, and to do so they must associate with others w ho are willing to break the law (1989). Underage drinkers were also shown to have used false IDs to obtain alcohol. Both of these methods of procuring alcohol ar e considered derivative law breaking. Researchers also found that the social context of drinking changes. Drinkers of legal age are more likely to drink in public venues, while underage drinkers preferred their dwellings. And finally, the underage drink ers were more likely to drink with unfamil iar persons (Lanza -Kaduce & Richards, 1989). This line of research is expanded upon in the present study. Other research has found that when the drinking age was lowered from 21 to 18 the levels of drinking and problems associated with drinking increased among those just below that age (16 17); when the age was increased to 21 the age at which problems were most visible rose again to 1920, just below the drinking age (Akers, 1992:220).
20 Prior Research: Underag e Drinking There is a plethora of research concerning adolescent and young adult substance use and alcohol consumption. Some of the ideas for underage drinking research are drawn from studies completed on adult drinking patterns. Situational factors have been the focus of several studies, and have been shown to be related to alcohol use. (Miller et al, 2005; Mayer et al., 1996; Casswell Zhang & Wyllie, 1993; Connolly & Silva 1992, Donnermeyer and Park, 1995; Gibbons et al, 1986) For both adults and un derage drinkers, the setting played an important role in amount of alcohol consumed. Adults tended to drink heavier in public settings such as clubs or bars (Mayer et al. 1996; Harford, 1975; Caetano and Herd, 1988; Harford 1983), while underage drinkers were more prone to heavy drinking in a private setting, such as a residential party or friends house (Lanza -Kaduce and Richards, 1989). Also, adolescents who participated in binge drinking were more likely to drink with peers and strangers, while those who did not binge drink reported drinking with their parents or siblings. This finding was most prevalent amongst the females (Mayer et al., 1996). Another study found that club settings, especially those hosting electronic music dance events, were prime public targets for facilitation of youth drug and alcohol use (Miller et al., 2005). Using anonymous surveys, breath tests, and saliva samples, Miller et al. were able to determine that while most underage drinkers showed up with alcohol in their system; some were also able to obtain it from within the club setting (2005). The most prevalent substance used at the electronic music dance events was alcohol, followed closely by marijuana. Stimulants (i.e. ecstasy and cocaine) were third on the list upon ent ering the club, but moved up to second upon exit (this may be partially due to the method of testing, marijuana only stays in the saliva for fifteen minutes, thus is harder to
21 accurately measure after time has elapsed) (Miller et al., 2005). According to Miller et al., risky behavior is associated with alcohol and drug use in clubs, including overdose, illegal possession of drugs, increases in aggressive behavior, increased risk for victimization, and driving under the influence (2005; Collins, 2004 ). Access to alcohol by minors has also been the focus of several studies. Alcohol is viewed by a substantial number of minors as easy to access. (McFadden and Wechsler, 1979; Goldsmith, 1988; Klepp, Schmid & Murray, 1996; Smart Adlaf & Walsh 1996; Wagenaar et al., 1996; Jones -Webb Toomey, Wagenaar, Wolfson & Poon, 1997; Mayer et al., 1998; Wagenaar & Toomey, 2002; and Wechsler et al., 2002). Wagenaar and Toomey reported that over 75% of teens that were surveyed reported that alcohol was easy to obtain (2002). Some common methods of acquiring alcohol included: False identification (either forged or an ID belonging to someone of age), attempts to purchase alcohol without an ID, having peers or family members provide it, and having an adult of legal drinki ng age purchase alcohol on their behalf (see appendix A) (Lanza -Kaduce and Richards, 1989; Wagenaar et al., 1996; Wagenaar and Toomey, 2002; Wechsler et al., 2002) Using false identification to procure alcohol is one of the methods mentioned above. Th ere have been numerous studies that have examined this avenue. Goldsmith explained the methods in which youth can obtain a false ID, which included: falsifying ones own ID, borrowing or stealing an ID from someone of age, using false documents to obtain an ID, or forging a fake ID (1988). In a study completed by Schwartz Farrow, Banks & Giesel, 14% of the youth they sampled reported using false identification (1998). This finding confirmed prior research that false identification is in fact a
22 common method employed by youth to purchase alcohol (Goldsmith, 1988; Durkin et al., 1996; Klepp et al., 1996) Schwartz et al.s study led nicely into a study by Durkin et al. which specifically examined the use of false identification in procurement of alcohol by underage college students (2001). Of the college students they sampled, almost half reported using a fake ID to gain access to alcohol. Greek membership was strongly related to the use of fake IDs, however, other students used them as well (Durkin et a l., 2001). This finding suggests that use of a false ID may be more prevalent among college students, than youth not enrolled in college. Durkin also tested some of the social learning variables (differential associations and definitions), and found that they explained a significant amount of variance, 30% (2001). Though using false identification to obtain alcohol is prevalent in underage youth, the most popular method employed was identified as obtaining alcohol from a person over the legal drinking ag e which includes strangers (Wagenaar & Toomey, 2002; Durkin et al., 2001; Wagenaar et al., 1996; Smart et al., 1996; Klepp et al., 1996; Lanza Kaduce and Richards, 1989; Goldsmith 1988; McFadden & Wechsler, 1979). There are several interactions noted in the research in this area. Some underage drinkers use family or friends to obtain alcohol (McFadden & Wechsler, 1979; Lanza -Kaduce & Richards, 1989; Wagenaar et al., 1993; Wagenaar et al., 1996; Klepp et. al., 1996; Smart et al., 1996; Jones -Webb et al., 1997). Many studies have failed to categorize the adults that underage drinkers utilized to procure their alcohol. Lanza -Kaduce and Richards however, found that underage drinkers do utilize strangers, family members and friends over the age of 21 to obt ain alcoholic beverages, but the degree to which each category is used is undetermined by research (1989). There is currently no research that thoroughly
23 differentiates the different methods of obtaining alcohol while underage, and more specifically diffe rentiates what relation the sources have, if any, to the underage drinker, when they are utilizing persons over the age of 21 to procure their alcohol. Prior Research: Social Learning Theory and Underage Drinking In addition to Durkin et al.s study in 1996 mentioned above, there are a number of studies that include measures of social learning in underage drinking and substance use. Durkin et al. completed another study in 2005 evaluating social learning theory in application with binge drinking in coll ege students. They found that, differential peer associations are by far the best predictor of this behavior [binge drinking]. (2005). Durkin et al. (2005) also found significant effects of definitions, as well as perceived reinforcements on drinking b ehavior Hood found that the most influential factor in underage drinking is peer influence, and the best predictors of experiencing trouble with the police are having a friend w ho has been arrested (1996). Akers, Krohn, Lanza Kaduce and Radosevich were able to explain 55% of the variance in the use of alcohol by adolescents, using the social learning variables (1979). Lanza -Kaduce and Capece also completed a study on binge drinking that employed components of social learning theory. Overall, they wer e testing the social structure social learning model (SSSL), but it encompasses the four learning variables (2003). Akers used social learning theory as the foundation for the SSSL model. In addition to the four micro level variables tested by learning theory, he added four structural variables, and hypothesized that the structural variables would be mediated by the learning variables (Akers, 1994; 1997; 1998; 2000; 2008). In Lanza -Kaduce and Capeces article, researchers found support for Akers model, though they did not test it in full. The effects of the structural variables were reduced when the learning variables were controlled for. The social learning variables
24 tested included definitions and perceived reinforcement. Even though only half of t he theory was tested, it was still able to explain 16 to 34% of the variance in binge drinking (2003). The SSSL model is tested in part again in 2006, in its applicability to gender, alcohol use and sex (Lanza -Kaduce, Capece & Alden, 2006). In a response to criticism of the SSSL model, researchers compared feminist theory with SSSL in drinking behavior and sex. It was found that the masculinist pattern in drinking before sex was partially mediated by social learning variables (Lanza -Kaduce, Capece & Alde n, 2006).
25 CHAPTER 4 STUDY PROCEDURES The Present Study The term black market associations as used by Lanza -Kaduce and Richards (1989) may itself be viewed as a specific type of deviant association. Alcohol black market associations are expected t o lead to further deviance, both in general and in the form of substance use. Thus, according to the implications of social learning theory, these deviant associations should increase the risk of engaging in further deviance. Social learning theory would view underage drinking, using various legal and illegal substances, obtaining supplies through illicit or black market means, and engaging in other forms of deviance as inter related and all explicable in terms of the variables implicated in the social le arning process. Black market associations (Lanza -Kaduce & Richards, 1989) because they involve association with non-conforming others may be correctly viewed as a specific type of deviant association. As such, they may be seen as indirect indicators of the process of differential association in social learning theory. But the meaning and measure of black market associations are simply reports of contact or interaction by the person with others for the specific purpose of using them to help obtain, or a s a source for, the substance. They are not the common measure of differential association which is the proportion of deviant and conforming others with whom one is in association. Therefore, they will not be used as measures of differential association in this study. To emphasize that, and to avoid possible confusion with the measures of differential association that are used in this study, black market sources may be a better term and will be the term regularly used here to refer to interaction with others for procurement of alcohol and marijuana. Both are behavior assumed to result
26 from social learning processes of differential association, differential reinforcement, imitation, and definitions. Therefore, social learning variables should be able to account for use of black market sources for both alcohol and marijuana and for the relationship between them. Since those who use marijuana and other drugs are very likely to have previously used alcohol, the expectation is that use of black market s ou rces for alcohol precedes and provides a social context which facilitates, or leads to, a higher probability of using black market s ources to obtain marijuana, and should also be related to involvement in other forms of substance use and deviance. Therefo re, use of black market s ources for alcohol is hypothesized to be predictive of Marijuana Black Market Sources, use of marijuana, and deviance. However, since all of these are hypothesized to result from the same underlying social learning process it is expected that when measures of the social learning variables of differential association, imitation, differential reinforcement, and definitions are entered into the model, the net effects of the use of black market sources for alcohol on these other forms of deviance will be lower than their main effects and be statistically non -significant. It may be said that this renders the relationships between the Alcohol Black Market Sources and the other forms of deviance spurious or simply that they are all indi cators of the social learning process in substance use, obtaining substances for that use, and therefore correlated with other forms of deviant behavior. As mentioned on pages 11 12, b ased on this social learning perspective and prior research this study addresses the following hypotheses (they are mentioned here again with reference to the models and tables presented later, relevant to each hypothesis):
27 Hypothesis 1 : Use of Alcohol Black Market Sources is predicted by social learning variables (for the fi ndings on this hypothesis see Model 1, Table 5-1 page 54). Hereafter, this variable (Alcohol Black Market Sources) is hypothesized as an independent variable, along with the social learning variables which remain as independent variables in all of the analyses. Hypothesis 2 : Use of Alcohol Black Market Sources has a significant effect on use of Marijuana Black Market Sources, but that effect will be reduced and become non significant when measures of social learning variables are entered in a multipl e regression model (see Models 2 & 3, Table 5-2 page 56). Hypothesis 3 : Use of Alcohol Black Market Sources has a significant relationship with use of marijuana (Marijuana Use), but that relationship will become non -significant when measures of social lea rning variables are entered in a multiple regression model (see Models 4 & 5, Table 53, page 58). Hypothesis 4 : Use of Alcohol Black Market Sources has a significant relationship with other measures of deviant behavior (General Deviance), but that relationship will become non -significant when measures of the social learning variables are entered in a multiple regression model (see Models 6 & 7, Table 5-4 page 60). Methodology Thesis Research Protocol Approved by the University of Florida Internal Revi ew Board The protocol for this research was submitted the UFIRB 02 on September 25th, 2008. The proposal was passed by UFIRB 02 on October 3, 2008 and was issued a protocol number, #2008-U886. The letter of approval was typed and sent out October 6, 2008. The UFIRB 02 protocol form can be found in Appendix D,
28 followed by the Informed Consent form, and the Debriefing forms in Appendixes E and F. Participants The outcome analysis reported here is based on a cross -sectional survey completed by s tudents in attendance of classes offered through the University of Floridas Department of Criminology, Law and Society during the fall 2008 and spring 2009 semesters. Students enrolled in criminology classes are given the option to participate in research for a certain number of points in their classes. Participation in research is completely voluntary, and alternative assignments of an equal time investment are offered in all classes requiring participation points. Participants sign ed up through the Participa nt Pool, which is an online listing of current research within the department. Students could choose which studies to participate in, as several studies were posted at any one time. An alternative assignment was ava ilable for those students who did not wi sh to participate in research The survey was posted on a survey website, www.surveymonkey.com which students could get to by signing up for this study through the Participant Pool. SurveyMonkey has two types of subscriptions, free and paid. I chose to use the paid service due to the length of the survey, the number of participants anticipated, and for data encryption to protect the privacy of the participants and their responses. At the very beginning of the survey, the students were provided with an informed consent form to read over, they were required to click next to indicate their agreement to participate in the study (see Appendix D). Participants were able to print or save a copy of the informed consent. The Informed consent form list ed contact information for resea rchers, in case respondents had any questions in the future. Upon giving their informed consent
29 by clicking next, the participants were directed to the online survey (see Appendix G ) and requested to fill it out to the best of their ability. Students were reminded in the informed consent that they are not to put their name on the survey, and there is no blank field for them to do so. The survey was completely anonymous. Upon completing the survey, s tudents were debriefed as to the purpose of the study and provided a description of what the researchers are looking for (see Appendix F) again the participants could print or save a copy of the debriefing form. The Participant Pool is used not only to collect data, but also to introduce the students to research in academia. This questionnaire was designed to ask questions about general demographics, campus environment, underage drinking, methods of obtaining alcohol, substance use methods of obtaining substances, deviance of friends, friends substance use, substance use of other students and other forms of deviance. Several questions from the survey will be used as measures of the social learning variables while others will be us ed to measure the outcome variables of interest (substance use, deviance, other black market associations). This survey was developed under the supervision of Ronald Akers, Ph.D. and Lonn Lanza -Kaduce, Ph.D., to ensure proper measurement of the social lea rning variables and deviance. Most of the attitudinal questions, activity questions, demographic questions, and substance use questions were derived from the questions asked in the CORE survey. This survey was chosen because it has been used to examine s ubstance use in college aged persons over a period of 30 years. It was also recommended by one of the authors of Raising the minimum drinking age: Some unintended consequences of good intentions, that lead to the development of the current research (La nza -Kaduce and Richards, 1989) The CORE survey on drug and alcohol
30 use has been utilized since the 1980s, and was developed by the US Department of Education, in affiliation with several universities. Originally, the CORE survey asked double barreled qu estions in reference to drug and alcohol use, combining them in each measure, such as Does your campus have alcohol or drug policies?. These questions were further developed by separating measures of alcohol, marijuana and other drug use into three sepa rate categories Questions measuring black market deviance, and black market peer associations were included to further the prior line of research and there were also questions added to correctly capture the other social learning variables Skip lo gic was included in the online survey, to ensure that the students did not spend any unneeded time filling out the survey. If the students chose an answer that made later questions irrelevant, those questions were automatically skipped for them. Thus far 408 students have responded and are included in this analysis. Data collection is still ongoing, and a maximum of 600 students will be sampled for this phase, however only 408 were included in this analysis. For this thesis, a ll participants were eight een and older, and were currently enrolled in classes at the University of Florida. Both male and female students were sampled, and all races were included Two groups of students were identified through survey questions: students of legal drinking age and students under the legal drinking age. Within these two groups, sub-groups were identified: those who have used persons they are not closely associated with, or strangers, of legal drinking age to procure alcoholic beverages (Alcohol Black Market Sour ces) and those who have not. The students of legal drinking age were asked to recall the time when they were underage, and were asked if they had ever used alcohol during that time, and if so they were questioned in the same manner as the underage group.
31 Materials and Procedures A survey was administered to measure the variables of interest (see Appendix D ). No identifying information was requested from respondents, and it was noted on the survey that all information provided was completely anonymous. Each question required an answer so that students could not skip around in the survey, so every question also had an option listed as I do not wish to answer. R esponses to survey questions were utilized to determine if there was any relationship betwee n using black market associations to obtain alcohol and using other black market associations. Survey data were also utilized to determine if there was a relationship between black market associations in general and deviance, substance use (not alcohol or marijuana) and specifically black market deviance. The survey data was used to specify measures of the social learning variables, and the outcome behaviors of interest (incidents of underage drinking, incidents of using alcohol black market ties inciden ts of using other black market means to commit deviance, etc.). The broader variables were operationally specified as including the various sociodemographic measures of race (white, black, Asian, American Indian, Hispanic, other); education (freshman, s ophomore, junior, senior); student status (part time, half time, full time); living status (on campus, off campus); l iving arrangements (house/ apartment, residence hall, campus housing, fraternity or sorority, other); l iving situation (live with parents, other students, friends, spouse, children, alone, other); religious affiliation (no religion, cult religion, Jewish, Catholic, Mainline Protestant, Evangelical Protestant); school performance (approximate gpa) and age. These variables were used as contro l variables
32 For the current study, 61% of the sample was under 21, 32% were 21 22, and the remaining 7% were 23 years of age or older. Males represented 34.8% of the sample, while females covered 65.2% of the sample. The racial composition of particip ants was as follows: 64.7% were Caucasian, 14.8% were African American, 14.8% were Hispanic, 3% were Asian/ Pacific Islander and the remaining 2.7% chose other; 97.2% of the sample was single, 97% was also considered full time status as a student, and 25. 5% lived on campus, while 74.1% lived off campus. Table 4 1. Participant Characteristics Characteristics Frequency Gender Male 34.8% Female Age Under 21 61% 21 22 32% 23+ 7% Race African American 14.8% Asian/Pacific Islander 3% Caucasian 64.7% Hispanic/Latino 14.8% Other 2.7% Student Status Full time 97% Part time 3% Living Arrangement On Campus 25.5% Off Campus 74.1% In comparison to the demographic makeup of the student body at the University of Florida, females and minorities may have been over represented in this sample. The University of Florida had a student population of 50,912 in the fall of 2006. Females compromised 53% and males 47% of the student body. The minorities are as follows:
33 7.9% are Afri can American, around 11.2% are Hispanic, and about 7% are Asian American or Pacific Islanders ( University of Florida -Demographics nd.). There were two types of substance use questions in this survey, specific and general. For the specific substance use questions the survey clearly indicated one of the following: Alcohol, Marijuana, or Other Drugs and usually asked the same question separately for all three substances. In the past, CORE combined alcohol and drugs into the same question, and did not break out marijuana at all, thus it could not be determined which, if any, of the substances had different usage rates. For the general substance use questions, the survey indicated a list of substances: Tobacco, alcohol, marijuana, cocaine, amphetamines, sed atives, hallucinogens, opiates, inhalants, designer drugs, steroids, or other illegal drugs this list will be hence forth referred to as the general substance use list. General deviance was also used throughout the survey. It included 14 measures on beh avior violating laws/ social norms: damaged property, getting into a physical altercation, driving under the influence, missing class, stealing things worth less than $50.00, stealing things worth more than $50.00, buying stolen goods worth less than $50.00, buying stolen goods worth more than $50.00, pawning or selling stolen goods worth less than $50.00, pawning or selling goods worth more than $50.00, getting into a fight serious enough to cause injury, cheating on an exam or assignment, selling illegal drugs, making unwelcomed sexual advances toward someone, and using a substance to obtain sex. Responses were set up differently depending on the question. This list will hence forth be termed the general deviance list. Measures of Control Variables A ll included variables are summarized in Table 4-2. Control variables included in all analyses consisted of Gender and Race. Gender was coded as female (0), and male
34 (1). Race included five classifications: African American (1), Asian/ Pacific Islander (2), Caucasian (3), Hispanic (4), and other (5). For ease of analysis, and due to nonsignificance, Race was set up under a dummy variable, and coded as either Caucasian (1) or non Caucasion (0) (see Table 1. Descriptive Statistics in Table 4 2, page 46). Other control variables were available, but were not significant in any model, so were not utilized for model assessment. Measure of Alcohol Black Market Sources The Alcohol Black Market Sources measure was created by scaling questions designed to deter mine how the participant was obtaining the alcohol. Four questions were included in the scale: I have asked someone I dont know to buy it [alcohol] for me, I have paid someone I dont know to buy it for me, I asked a student I am not really associated with to buy it for me, and I have paid a student I am not really associated with to buy it for me. Answer choices included: no (0), yes (1) and I do not wish to answer. Those who chose I do not wish to answer were coded as missing. Because this was a sc ale created from dichotomized items, the Kuder Richardson Formula 20 (KR 20) test of internal consistency reliability was utilized rather than a Chronbachs alpha. The KR 20 is designed for dichotomous item scales and it is interpreted the same as a Chron bachs alpha. The Alcohol Black Market Sources scale was assessed and was found reliable (KR 20= 0.762). Measures of Dependent Variables The measure of Alcohol Black Market Sources given above was utilized as a dependent variable in only one model, a model that used social learning variables specific to drinking and underage drinking behavior (see Table 2, Model 1). As stated above, the measure of black market sources or associations are simply reports of contact or
35 interaction by the person with oth ers for the specific purpose of using them to help obtain, or as a source for, the substance desired. Also, all of the black market measures were different from the differential association measures. Black Market Sources were measured only using stranger s, persons not known to the participant and students not known to the participant. Alcohol Black Market Sources were not used as measures of differential association in this study. Marijuana Use To measure Underage Drinking and Marijuana Use four ques tions were asked: In the following series of questions you will be asked in what ways you obtained alcohol while underage. If you have never obtained alcohol while underage (if you are underage now, or drank back when you were underage), please indicate so below. Answer options included: I never drank while underage (0); At some point in time, I drank while under the legal drinking age (1); and I do not wish to answer (missing). Similar questions were asked for marijuana: In the following series of questions you will be asked in what ways you have obtained [marijuana, other drugs]. If you have never used [marijuana, other drugs], please indicate so below. Answers were dichotomized as: I have never used [marijuana, other drugs] (0), At some point in time, I have used [marijuana, other drugs] (1), and I do not wish to answer (missing). Since these were single item measures, no scale was created. Marijuana Black Market Sources For the question, do Alcohol Black Market Sources lead to involvement w ith other black market sources, a scale for Marijuana Black Market Sources If the participant answered that they had, at some point in time used marijuana, skip logic automatically progressed them to this question: have you used the following ways to obtain
36 [marijuana/other drugs]?. There were four items measuring black market sources for both marijuana and other drugs: I buy it from someone a friend introduced me to, I buy it from someone I dont know, I buy it from a student I am not really associat ed with, and I have attempted to buy it without a contact. The answer choices were dichotomized for these scales with options including no (0), yes (1) and I do not wish to answer was treated again as missing. To create the scale items were summed and th en coded into a dummy variable including no (0 remained 0) and yes (all other values were recoded to 1, indicating that they have utilized that method of obtaining the substance). Th is scale w as assessed with the KR 20 (Marijuana Black Market Sources yiel ded a KR 20 of 0.818). General Deviance The scale for General Deviance was constructed using the general deviance list (noted above). Answer items were set up on a six item ordinal scale, ranging from never (0) to ten or more times (5), and I do not wis h to answer (missing). Scale reliability was assessed and yielded a Cronbachs alpha of 0.729. There are some limitations of this study in using General Deviance as an outcome variable. Specifically, the concepts of differential reinforcement and imitat ion were not measured for General Deviance, but only for use of alcohol, marijuana. There was one set of deviance specific question s that measured att itude and that was Risk Deviant Behavior (see below, social learning measures, Definitions/ Attitudes) To be more accurate measures of social learning variables as independent variables in General Deviance, it would be better to have these explanatory variables measured specifically with regard to general deviant behavior. Specific Black Market Devian ce If a participant answered that they had, at some point in their lives, used [alcohol/ marijuana ] they were asked in what ways they obtained it. To measure the relationship
37 between the method of obtaining a substance and deviance associated with it, a series of questions was asked. Of interest is the black market deviance (Specific Black Market Deviance) that is associated directly with Black Market Sources, measured in the following: Did any of the following occur when you had a stranger get you [a lcohol/ marijuana]? and the 14 general deviance measures were listed. Next, Did any of the following occur when you had a student you dont really know get you [alcohol/ marijuana ]? and the 14 general deviance measures were listed. In addition, for ma rijuana and other drugs, it was also asked Did any of the following occur when you tried to get [marijuana] without a contact? and again the 14 general deviance measures were listed. Answers for each of these questions were set up on a binary yes/no (1/ 0). Within the general deviance measures, there are 5 questions that indicate black market deviance. They are: you bought stolen goods worth less than $50.00, you bought stolen goods worth more than $50.00, you pawned or old stolen goods worth less tha n $50.00, you pawned or sold stolen goods worth more than $50.00, and you sold illegal drugs. The responses for the questions (yes/no) were scaled to indicate black market deviance specifically associated with utilizing black market sources (Specific Bla ck Market Deviance). The reliability of Specific Black Market Deviance was tested, and yielded a KR 20 of 0.988. There was also a measure of deviance in general (General Black Market Deviance), that included deviant behavior that was specific to the ti mes the participants used black market sources to obtain alcohol, but was not considered black market deviance (such as dealing in stolen goods). For this scale, the deviance questions (listed above) specific to Black Market Sources were summed and recode d into a dummy variable including no (0 remained 0) and yes (all other values were recoded to 1,
38 indicating that they have committed deviance while obtaining alcohol via black market sources). Deviance specific to Alcohol Black Market Sources yielded a KR 20 of 0.980 (Specific Black Market Deviance). Due to the low response rate, validity of the models analyzing Specific Black Market Deviance was questioned, and thus these models were dropped from the analysis. It will be interesting to see if the respon se rate for these questions increases with larger and broader sample sizes in the next study. The models with these dependent variables were analyzed with Alcohol Black Market Sources as the only independent variable, and then the next model shown in the tables added the measures of the social learning variables (see below ). Recall, that it was hypothesized that when entered into the equation, the social learning variables would explain most of the variance in Marijuana use, Marijuana Black Market Sources and General Deviance. Again, since the use of marijuana most likely occurred after the initial use of alcohol, the expectation was that use of Alcohol Black Market Sources preceded and created a social context which led to a higher probability of using Marijuana Black Market Sources, Marijuana Use and Deviance. However, since all of these were hypothesized to result from the same underlying social learning process it was expected that when measures of the social learning variables of differential reinforcement, definitions differential association and imitation were entered into the model, the net effects of the use of black market sources for alcohol (Alcohol Black Market Sources) on these other forms of deviance would be lower than their main ef fects and be statistically non -significant.
39 Measures of Social Learning Variables Differential Reinforcement Differential reinforcement was measured in several different ways. As previously stated, the balance of reinforcement and punishment, both fall under the category of differential reinforcement. So, differential reinforcement by definition includes measures of both reinforcing and punishing stimuli, as it is the balance of reinforcement and punishment that yields the maintenance or desistance of a particular behavior. Consequences were measured for alcohol use and marijuana use by asking, From what you have experienced, have the consequences of your substance use been overall:. Answers were as follows: I dont use this substance (0), more bad than good (1), about the same for good/bad (2), more good than bad (3), and I do not wish to answer (missing). Because these were single item measures, no scale was created (Alcohol Con sequence, Marijuana Consequence ). After thesis defense, the Consequence items were dropped from all models, and are not reported in any of the findings, per committee members request. Potential punishment (Alcohol Punish and Marijuana Punish) was measured in a question on experiences with alcohol and marijuana (reporte d separately) using a seven item inquiry, Please indicate how ofte n, if ever, the use of [alcohol/ marijuana] has lead to each of the following experiences: The items included: been criticized by someone I know, been hurt or injured, been the victim of unwanted sexual intercourse, done something I later regretted, endured threats of physical violence or actual physical violence, missed a class, performed poorly on a test or important project. Answers were offered on a six item ordinal scale ranging from never (0) to 10 or more times (6). I do not wish to answer was coded as missing. These questions were asked both of students
40 who had used each substance, and students who had not used them. Participants indicating that they had not used [alcohol/ marij uana] were asked, You indicat ed you have never used [alcohol/ marijuana]. In this question, please imagine how often, if ever, you think the use of [alcohol/ marijuana] would lead to the following experiences. The experiences and answers were the same. To scale these items, first the questions for the users and nonusers were combined, to yield one measure for punishment for each substance. Then all seven items were summed and divided by seven to create the punishment scales for each substance (Alcohol Punish yielded a Cronbachs alpha of 0.880, Marijuana Punish yielded a Cronbachs alpha of 0.923, and Other Drug Punish yielded a Cronbachs alpha of 0.972). Differential reinforcement was also measured by items requesting information on positively viewe d effects of alcohol, marijuana and other drugs, individually (A lcohol Reward, Marijuana Reward ). This question also included seven items, but for possible positive outcomes, and was listed as: Do you think [alcohol / marijuana] have any of the following effects? The items included were: It is an ice breaker, It enhances social activity, It makes it easier to deal with stress, It facilitates a connection with peers, It allows people to have more fun, It makes me sexier, It facilitates sexual opportuniti es with answers set up on a binary response (yes/no), and I do not wish to answers were coded as missing. A scale was then created f or Alcohol Reward (KR 20=0.733) and Marijuana Reward (KR 20 = 0.787) by summing the responses and dividing by seven. Def initions/ Attitudes The social learning concept of definitions favorable and unfavorable to substance use was measured with several types of questions throughout the survey. The first inquires about attitudes on u sing alcohol (Attitude Alcohol) and mariju ana (Attitude
41 Marijuana)(each asked separately): Which statement best represents your own attitude about the f ollowing substance use: [Alcohol/ Marijuana] ? Answers were listed on a 5 item Likert scale ranging from strongly disapprove (1) to strongly appr ove (5). These items were not scaled and used respectively as measures of the variables shown in the tables as Attitude Alcohol and Attitude Marijuana Participants were also asked about their preferences of availability of alcohol, marijuana and other d rugs on campus: There are differing views with regards to the availability of alcohol and drugs at parties on or around campus. Some students believe that the availability of drugs and alcohol is a bad thing, decreasing their enjoyment and leading to neg ative situations. Other students think that having drugs and alcohol at these parties increases enjoyment and is a positive thing. Which view would you say you are most like to side with? I would rather have [alcohol, marijuana, other illicit drugs]: An swer options included not available (0), Available (1), and I do not wish to answer (treated as missing). This question was asked individually for Available Alcohol and Available Marijuana. Because availability of alcohol, marijuana and other drugs were s ingle item measures, no scales were needed. This variable [Available Alcohol/ Available Marijuana] was subsequently dropped from the models, as it only reached statistical significance in a few of the models and was deemed as unnecessary for overall explanatory power. The last Definitions/Attitudes measure included in the analyses was perceived risk (Risk Heavy Drinking, Risk Marijuana Risk Deviant Behavior). The questions asked, By partaking in the following activities, how much do you think people r isk harming themselves? (physically, mentally, spiritually, emotionally). The question was asked for each item on the general substance use list (see above for an explanation of the general
42 substance use list), and answers were set up on a Likert scale, ranging from no risk (0) to great risk (4). Scales were created for Risk Heavy Drinking (Cronbachs alpha = 0.770) by summing the three alcohol items and dividing by three, and Risk Marijuana (Cronbachs alpha = .892) by summing the three marijuana items and dividing by three. Questions were also asked about risky/ deviant behaviors (Risk Deviant Behavior) such as: How much to do you think people harm themselves by: consuming alcohol prior to being sexually active, using marijuana prior to being sexuall y active, using other drugs prior to being sexually active, regularly engaging in unprotected sexual activity with multiple partners. Answers were set up on the same ordinal scale as the other risk questions. The four items were summed and divided by fo ur to create the Risk Deviant Behavior variable (Cronbachs alpha = 0.828). Differential Association The concept of differential association was captured via several different questions in the survey instrument. Family substance use was measured for both alcohol and marijuana separately. The same question was asked for alcohol (Family Alcohol) and marijuana (Family Marijuana): Which members of your family, if any, have ever had problems with [alcohol/ marijuana]? Answers included: none, mother, father, stepmother, stepfather and sibling and were originally coded from 0 -5 Dummy variables were created for each relative so that a 0 indicated no problem and a 1 indicated that the relative had a problem with the substance. Items were then summed on a five item scale, and again dichotomized to indicate that either no family members has had an issue with the substance (0), or that at least one of their family members had experienced a problem with the substance (1). The reliability of these two scales was assessed and
43 Family Alcohol yielded a KR 20 of 0.46, Family Marijuana yielded a KR 20 of 0.50. These were the least reliable scales constructed Deviance of peers was measured in several ways:, friend general deviance (Deviant Peers), Fri end Substance Use, Friend Alcohol Consequence, Friend Marijuana Consequence, and Friend Buy Alcohol Under the LDA. Friends general deviance (Deviant Peers) was measured using the general deviance list (see above for question details in general deviance l ist), and the question was posed, Please indicate how many of your friends have ever experienced the following:. Answers included: none of my friends (0), a couple of my friends (1), a few of my friends (2) half of my friends (3), a majority of my frien ds (4), all of my friends (5) and I do not wish to answer (treated as missing). Items were scaled to create the deviant peers measure (Chronbachs alpha = 0.912). These were the only three differential association measures utilized in this study. For F riend Substance U se the question read: Have your friends ever told you they have: smoked marijuana once or twice, smoked marijuana occasionally, smoked marijuana regularly, tried cocaine once or twice, done cocaine regularly, tried LSD once or twice, d one LSD regularly, tried amphetamines once or twice, done amphetamines regularly, tried club drugs once or twice done club drugs regularly, tried antidepressants once or twice, done antidepressants regularly, tried prescription drugs once or twice, done pr escription drugs regularly, Had one or two alcoholic drinks nearly every day, had four or five alcoholic drinks nearly every day, had five more drinks in one setting, purchased alcohol while underage, taken steroids for body building or improved athletic p erformance. The answers were coded on a binary response (yes/no) and I do not wish to answer was treated as a missing variable. For this scale, purchased alcohol while
44 underage was removed and treated as a separate item indicating friend deviance (Se e Table 4 2 variable Friend Bought Alcohol Under LDA). The response was dichotomous. Also, all questions for each substance were first summed, and then recoded into a dummy variable, before scaling. So there are three friend substance use variables, Friend Problem Drinking, Friend Marijuana Use, and Friend Substance Use. For example, there are three questions on Marijuana (Have your friends ever told you they have: smoked marijuana once or twice, smoked marijuana occasionally, smoked marijuana regul arly?). All three marijuana questions were summed, and then recoded into no (0 remained 0) and yes (all other values were recoded to 1, indicating that their friends have told them they have used marijuana, but not indicating to what degree). This was done so that duplicate measures of each substance were not included in the scale, but yet each item was still accounted for. Once all substance questions were collapsed in this manner, a scale was created for friends substance use (KR 20 = 0.825). Friend consequences were measured for alcohol use and marijuana use (Friend Alcohol Consequence, Friend Marijuana Consequence) by asking, From what you have observed, or know about from your friends, have the consequences of their [alcohol/ marijuana] use been overall:. Answers were as follows: My friends dont use this substance (0), more bad than good (1), about the same for good/bad (2), more good than bad (3), and I do not wish to answer (missing). Because these were single item measures, no scale was created (Friend Alcohol Consequence, Friend Marijuana Consequence). These consequence measures were also dropped from each model at the behest of committee members, post thesis defense.
45 Imitation/ Modeling The final social learning concept, Imitation, i s measured with one series of questions and a single item question Have you ever directly observed your friends: smoking marijuana once or twice, smoking marijuana occasionally, smoking marijuana regularly, trying cocaine once or twice, doing cocaine r egularly, trying LSD once or twice, doing LSD regularly, trying amphetamines once or twice, doing amphetamines regularly, trying club drugs once or twice doing club drugs regularly, trying antidepressants once or twice, doing antidepressants regularly, trying prescription drugs once or twice, doing prescription drugs regularly Having one or two alcoholic drinks nearly every day, having four or five alcoholic drinks nearly every day, having five more drinks in one setting, purchasing alcohol while underage, taking steroids for body building or improved athletic performance. The answers are coded on a binary yes/no scale with the option I do not wish to answer coded as missing. Purchasing alcohol while underage was not included in the scaled items, and w as treated as a separate measure of imitation, as a single item question. The three alcohol questions was also not included in this scale, but in a separate scale. To capture imitation of substance use, measures for each substance were first summed, and then coded into a dummy variable. For example, there are three questions on marijuana (Have you ever observed your friends: smoking marijuana once or twice, smoking marijuana occasionally, and smoking marijuana regularly?). All three marijuana questions were summed, and then recoded into no (0 remained 0) and yes (all other values were recoded to 1, indicating that they have observed their friends using marijuana, but not indicating to what degree). This was done so that duplicate measures of each subst ance were not included in the scale, but yet
46 each item was still accounted for. Once all substance questions were collapsed in this manner, a scale was created for Observed Friend Substance Use (KR 20 = 0.691). For Model 1 only (see Table 51, p. 54) a measure on observation of friend problem drinking (Observed Friend Problem Drinking) was also included. This measure was a three item scale created from questions that asked specifically about observation of friend problem drinking. These questions asked if the person had observed their friends: Having one or two alcoholic drinks nearly every day, having four or five alcoholic drinks nearly every day, having five more drinks in one setting, purchasing alcohol while underage, Answers were dichotomized o n a yes/no response. (KR 20 = 0.672). This variable was not used in later model s to eliminate tautology issues with the Alcohol Black Market Sources variable, as it was subsequently used in the remaining models as an independent variable. It is recogn ized that the empirical measure of imitation of peers has presented some problems in that its measures and effects are difficult to separate from those of differential peer association and that may be implicated in the relative strong effects of imitation in these findings compared to the effects of imitation in some previous research (Akers, 1998). Asking about directly observing peers engaged in various acts is, of course, a clear indicator and reflection of the concept of imitation as observational lea rning. But since one may not directly observe the behavior of someone with whom one is in face to face contact without in effect associating with that person, it also may be seen as partly a reflection of the concept of differential peer association.
47 Table 4 2. Descriptive Statistics Variables Observations Mean Standard Deviation Minimum Maximum Dependent variables *Alcohol Black Market Sources 335 0.50 0.99 0 1 Marijuana Black Market Sources 154 0.25 0.43 0 1 General Deviance 387 0.32 0.34 0 7 Marijuana Use 373 0.42 0.49 0 1 Control Variables Gender 408 0.35 0.47 0 1 Race 405 3.73 0.44 0 1 Differential Reinforcement Alcohol Reward 386 4.58 1.78 0 7 Marijuana Reward 382 2.55 2.10 0 7 Alcohol Punish 405 0.87 0.93 0 5 Ma rijuana Punish 399 0.89 1.11 0 5 Friend React Heavy Drinking 404 2.15 0.90 1 5 Friend React Marijuana 403 2.34 0.93 1 5 Friend React Substance Use 402 1.48 0.72 1 5 Definitions/ Attitudes Risk Heavy Drinking 406 2.15 0.71 0 3 Risk Marijuana 406 1.41 0.88 0 3 Risk Deviance 406 2.18 0.73 0 3 Attitude Alcohol 407 3.51 0.91 1 5 Attitude Marijuana 407 2.43 1.10 1 5 Differential Association Family Alcohol 408 0.34 0.67 0 1 Family Marijuana 408 0.21 0.56 0 1 Deviant Peers 377 0.38 0.28 0 7 Friend Substance Use 393 3.52 2.31 0 8 Friend Buy Alcohol Under LDA 398 0.78 0.47 0 1 Imitation/ Modeling Imitation 396 2.19 1.78 0 9 Imitation Friend Buy Alcohol Under LDA 397 0.55 0.50 0 1 Observed Friend Problem Drinking 396 0.71 0.46 0 1 Alcohol Black Market Sources is used as a dependen t variable in Model 1, Table 5 1 only, in all subsequent models it is an independent variable. Data Analysis The analyses were completed using SPSS version 17 for graduate students and Stata version 1 0 for graduate students Descriptive statistics for all the variables that were used, as well as frequencies were run to determine case counts and variance (See
48 Table 4-2). The analysis and reporting of the data was quantitative by design. The scales a nd measures explained above were utilized in a series of either logistic regression or ordinary least squares regression depending on whether or not the dependent variable was dichotomous. Models that included dichotomized outcome variables were assessed via logistic regression as not to violate any of the assumptions for linear regression. The logit model is a method of estimation for equations with dummy variables, or binary response variables. Utilizing the logit model, avoids the unboundedness probl em of the liner probability modelthe dependent variable can be thought of as the log of the odds that the choice in question will be made (Studenmund, 2001: 442). Because logit models report natural log odds as the coefficient, the percent change was c alculated so that the coefficients were easily interpreted. The odds is the ratio of the probability that something is true divided by the probability that it is not true. Before any models were conducted, data were checked for outliers. There were no cas es that appeared to be problematic. Listwise deletion was used for missing data. Of the 408 participants, only 335 had (a t some point in their lives) dru nk while under age. Of those 335, 302 participants answered all of the questions that were included in Model 1 (Page 54). Ordinary least squares regression was completed for the first model (Model 1 see Table 51 page 54). In this model being involved with Alcohol Black Market Sources was predicted with a set of social learning variables that were sp ecific to drinking and underage drinking behavior. The social learning variables assessed in this model included: attitudes favorable or unfavorable towards alcohol (Attitude Alcohol), whether or not their friends told them they had purchased alcohol whi le under the LDA (Friend Bought Alcohol Under LDA), whether they had seen their
49 friends purchase alcohol under the LDA (Imitation Friend Buy Alcohol Under LDA), whether their friends told them they had problem drinking behaviors (Friend Problem Drinking i.e. binge drinking), whether they had seen their friends partake in problem drinking behaviors (Imitation Friend Problem Drinking), whether they had seen their friends drink (Imitation), how they thought their friends would react to their own problem drinking behaviors (Friend React Heavy Drinking), whether or not their drinking behavior had been rewarded (Alcohol Reward), whether or not their drinking behavior had been punished (Alcohol Punish, in the behavioral sense of punishment), whether they felt the consequences of alcohol were good or bad (Alcohol Consequence), family alcohol use (Family Alcohol), consequences of friend alcohol use (Friend Alcohol Consequence) and finally a measure of Deviant Peers was included. The model was tested for heterosked asticity using the Shapiro -Wilk test for normal data, it was determined that the residuals were normally distributed, so there were no issues with heteroskedasticity. Collinearity diagnostics were run on all the variables included in this model, and there were no issues with collinearity or tolerance. Leverage was tested for by calculating the leverage cut off value (2x13/302= .086). There were few cases observed over the leverage cut off, and so these cases were not removed. The DFbeta was created by d ividing 2 by the square root of 302, yielding a cut off value of .115. There were several cases noted in each variable that were over the cut off, however the number of cases was low and this author did not think the outcome would be substantially affecte d by the removal of so few cases. After thesis defense, committee members felt it wise to delete the variables Alcohol Consequence and Friend Alcohol Consequence, and so these variables do not appear in the new analyses.
50 For the next two models, a serie s of logistic regression was conducted (see Table 52 on page 56). Of the 335 participants who had, at some point in their lives, used alcohol while under the le gal drinking age, 151 had used M arijuana Black Market Sources In Model 2 there are 151 observations reported. In Model 3, 135 of those 151 participants answered all the questions and were included in that analysis B oth of these models were also run using only the 135 participants included in Model 3 of the original analysis ; however; results did not differ, so the original analysis is reported here The first model in this series (Model 2) utilized Alcohol Black Market Sources, along with control variables, to predict contact with Marijuana Black Market Sources. The second model in this series (Model 3) included the same outcome variable (Marijuana Black Market Sources), but contained measures of the social learning variables (different from those used in model 1), along with the control variables and Alcohol Black Market Sources as independent variables. The social learning variables assessed in this model included: Family Marijuana, Risk Marijuana, Imitation, Attitude Marijuana, and Friend Marijuana Consequence. Collinearity diagnostics indicated no issues of tolerance or collinearity. Percen t change in odds was also calculated for each variable in both models. The same series of models was attempted for the dependent variable Other Drug Black Market Sources, however the response rate was not high enough to calculate the models. Under the Def inition/Attitude portion of the model, there is not a measure of the perceived risk of alcohol use, thus Risk Alcohol was not included in this model. Note, in these models Friend Buy Alcohol Under LDA and Imitation Buy Alcohol Under the LDA were dropped a s they were not relevant to these analyses. ( Also, Marijuana Consequence, and
51 Friend Marijuana Consequence were removed as suggested by committee members, and are not reported in these analyses. The next series of models (see Table 5 3, page 58) focu sed on the use of marijuana (Marijuana Use) as the outcome v ariable of interest (Models 4 -5 ). Model 4 utilized Alcohol Black Market Sources, controlling for Race and Gender to predict Marijuana Use (see Table 5 3, page 59 ). Of the 335 participants who h ad drank while underage, 316 had used marijuana (Model 4). Of those 316 people, 281 participants answered all the questions required for Model 5. ( These two models were run again, using only the 281 participants from Model 5. There were no differences i n the results in significance, and thus original analyses are reported here). M odel 5 included the same variables, but also had the social learning variables specific to Marijuana Use. Collinearity diagnostics indicated no issues of tolerance or colli nearity. Percent change in odds was also calculated for each of the models. This author originally ran two models predicting Other Drug Use utilizing the same variables listed above, but due to a low response rate, the validity of the significance was qu estionable, and thus those two models were dropped. Note, in these models Friend Buy Alcohol Under LDA and Imitation Buy Alcohol Under the LDA were dropped as they were not relevant to these analyses. Next, two linear regression models were conducted (see Table 54, page 60 ). The first, Model 6 was to assess the relationship between Alcohol Black Market Sources, control variables, and General Deviance. The second, Model 7 included the same variables, but also included social learning measures Of the 335 participants who had used alcohol while underage, 322 had participated in some sort of general deviance
52 (Model 6), and of those 322 participants, 295 participants answered all the questions to be included in Model 7. (Post thesis defense, again based on suggestions of committee members, these two models were run a second time, utilizing only the 295 participants that answered all the questions. There was virtually no difference in the results, and no difference in the statistical significance, so the origin al models were reported here.) The variable, Imitation Friend Buy Alcohol Under the LDA, was included in this model because it was observed deviance, and thus relevant to the analysis. The learning variables utilized in these models were somew hat weaker in that only two series of questions specifically targeted deviance (Deviant Peers and Risk Deviant Behavior) throughout the survey. There were no other questions that assessed attitudes/definitions towards deviance, and there were no direct me asures of imitation of deviance. Substance use measures were utilized however, and were still valid predictors. The model was tested for heteroskedasticity using the Shapiro -Wilk test for normal data, it was determined that the residuals were not normall y distributed. To account for this lack of normal distribution robust standard errors were calculated. In comparing the p -values between the two, it was determined that there was a difference in the standard errors, and thus the robust standard errors a re reported. Collinearity diagnostics were run on all the variables included in this model, and there were no issues with collinearity, there were also no issues with tolerance. Leverage was tested for by calculating the leverage cut off value (2x9/299= .06). There were only 14 cases observed over the leverage cut off, and so these cases were not removed. The DFbeta was created by dividing 2 by the square root of 299, yielding a cut off value of .116. There were several cases noted in each
53 variable that were over the cut off, however the number of cases was low and this author did not think the outcome would be substantially affected by the removal of so few cases. This researcher had planned to conduct analyses testing the relationship between Alcoho l Black Market Sources and both General Black Market Deviance, and black market deviance specific to utilizing black market sources to obtain illicit substances (Specific Black Market Deviance). The response rate for these items, however, was too low to a ccurately predict any type of relationship, and thus these analyses were dropped.
54 CHAPTER 5 RESULTS Alcohol Black Market Sources Table 5 1. Model 1 Variables Model 1 b SE t Control Variables Gender 0.02 0.12 0.14 Race 0.07 0.04 1.58 Differential Reinfor cement Alcohol Reward 0.07 0.04 1.86* Alcohol Punish 0.18 0.08 2.29** Friend React Heavy Drinking 0.11 0.07 1.56* Definitions/ Attitudes Att itude Alcohol 0.13 0.07 1.75* Risk Heavy Drinking 0 .05 0 .09 0.55 Differential Association Family Alcohol 0.09 0.07 1.17 Deviant Peers 0.12 0.21 0.57 Frie nd Buy Alcohol Under LDA 0.15 0.17 0.86 Imitation/ Modeling Obs erved Friend Problem Drinking 0.28 0.16 1.78* Imita tion Buy Alcohol Und er LDA 0.05 0.14 0.40 Imitation 0.18 0.04 4.51*** F = 6.49 n=302 R2= .23 *P Model 1: Ordinary Least Squares Regression Predicting involvement with Alcohol Black Market Sources with Social Learning Variables The first model was assessed via ordinary least squares regression. The act of obtaining alcohol through the black market (Alcohol Black Market Sources) is considered deviant and generally perceived to precede procurement and use of other illicit substance s. Alcohol Black Market involvement (Sources) was first predicted with social learning variables as measured with regard to specific drinking behaviors. Model 1 achieved statistical significance (p -value<.01) and successfully explained 23% of the variance in Alcohol Black Market Sources. The results summarized in Table 5-1 indicate that several of the variables were statistically significant, including: Alcohol Reward (p -
55 value <.10); Alcohol Punishment (p-value <.05); Friend React Heavy Drinking (p -value <.10); Attitude Alcohol (p -value <.10); observing your friend during problem drinking behavior ( Observed Friend Problem Drinking p -value < .10); and Imitation (p -value < .01). None of the control variables reached statistical significance. Imitation had the largest effect on Alcoho l Black M arket Sources (beta= .32 ), followed by Alcohol Punishment (beta = .1 5 ), observing friend problem drinking behavior (Observed Friend Problem Drinking beta = -.12, meaning the more problem drinking behavior observed, the less like ly the participant was to have Alcohol Black M arket S ources), Alcohol Reward (beta= .11), and Attitude Alcohol (beta =. 10). For a one unit increase in Imitation there was a 0 .1 7 unit increase in Alcohol Black Market Sources. The more positively one viewed alcohol (Attitude Alcohol ) the more likely they were to have Alcohol Black Market Sources (a one unit increase in attitude yielded a 0.13 increase in Alcohol Black Market Sources), the more rewarding one viewed alcohol (Alcohol Reward) the more likely they were to have Alcohol Bla ck Market Sources (1:0. 07) and the more negatively punishing (Alcohol Punish) the participant viewed alcohol, the less likely they were to have Alco hol Black Market Sources (1:0.17). Marijuana Black Market Sources Findings on use of Marijuana Black M arket Sources are presented in Table 5-2 (page 57). When analyzed separately from the social learning variables, Alcohol Black Market sources were statistically significant in predicting further black market sources (Model 2, p-value < .01). Because this was tested with logistic regression, the R2 was not included. This author does not know how to calculate the Roncek Pseudo R2, which would be an accurate representation of explained variance. This first model of this series included control variables ra ce and gender, and overall was statistically significant (p -
56 value < .01). Only the Alcohol Black Market Source measure reached statistical significance. For a one unit increase in Alcohol Black Market Sources, an 80.2% unit increase is noted in Marijuana Black Market Sources. In other words, participants who responded that they had used Alcohol Black Market Sources were 80.2% more likely to have used Marijuana Black Market Sources. Table 5 2. Model 2 and Model 3 Variables Model 2 Model 3 b SE z Percent Change b SE z Percent Change Control Variables Gender 0.28 0.42 0.66 32.4 0.52 0.65 0.79 67.4 Race 0.03 0.23 0.12 2.8 0.08 0.30 0.27 7.8 Independent variables Alcohol Black Market Sources 0.59 0.18 3.32*** 80.2 0.33 0.25 1.29 39.1 Differential Reinforcement Marijuana Reward ----0.08 0.17 0.48 7.8 Marijuana Punish ----0.18 0.65 0.28 19.9 Friend React Marijuana Use ----0.20 0.45 0.44 22.2 Definitions/ Attitudes Risk Marijuana ----0.82 0.52 1.56* 55.8 Attitude Marijuana -----0.88 0.37 2.36*** 141.6 Differential Association Family Marijuana ----0.58 0.44 1.32* 44.1 Deviant Peers ----0.23 1.01 0.22 25.4 Im itation/ Modeling Imitation ----0.45 0.16 2.76*** 57.0 *P X 2 =12.44 n=151 X 2 =54.99 n= 135 Model 2: Logistic regression predicting Marijuana Black Mark et Sources using Alcohol Black Market Sources. Model 3: Logistic regression predicting Marijuana Black Market Sources with both Alcohol Black Market Sources and Social Learning variables. The overall pattern of the findings in Table 5-2 indicates that the effects of Alcohol Black Market Sou rces are diminished when entered into a logistic regression equation
57 with social learning variables. Model 3 was statistically significant in predicting Marijuana Black Market Sources (p value < .01). Several of the learning variable s entered into the eq uation was statistically significant; these included : perceived risk of marijuana use (Risk Marijuana, p -value < .05); attitudes specific to marijuana use (Attitude Marijuana, p -value< .01); the effects of family problems with marijuana use (Family Marijua na, p -value < .05); and Imitation (p -value < .01). The less risky the participant felt about marijuana use (Risk Marijuana), the more likely they were to have Marijuana Black Market Sources, and thus for a one unit increase in risk there is a 55.8% decrea se in the likelihood of having Marijuana Black Market Sources. If students were less disapproving of using marijuana (Attitude Marijuana), they were more likely to have utilized Marijuana Black Market Sources (a one unit decrease in dis approval led to a 1 33.7% increase in the odds of having used Marijuana Black Market Sources ). Also, for a one unit increase in family problems with marijuana (Family Marijuana) there was a decrease of 44.1% in the odds of having black market associations for marijuana (Mari juana Black Market Sources). Friend Marijuana Consequence was removed from the model, because of issues raised in the thesis defense, it is worthy to note that when it is included a one unit increase in perceived negative Friend Marijuana Consequence yie lded a 70.1% decrease in the odds of having black market involvement for marijuana ). Finally, e ach unit increase in Imitation yielded a 57 % increase in the odds of utilizing Marijuana Black Market Sources. As hypothesized, when the effects of social learning variables are taken into account, having Alcohol Black Market Sources was no longer predictive of having other black market sources.
58 Marijuana Use Table 5 3. Model 4 and Model 5 Variables Model 4 Model 5 b SE z Percent Change b SE z Percent Change Control Variables Gender 0 .10 0.25 0.38 9.1 0.08 0.40 0.20 8.7 Race 0.19 0.10 1.94** 21.3 0.08 0.16 0.50 8.4 Independent variables Alcohol Black Market Sources 0.32 0.12 2.61*** 38.2 0.14 0.19 0.75 12.9 Differential Reinforcement Marijuana Reward ----0.02 0.10 0.15 1.5 Marijuana Punish ----1.87 0.34 5.55*** 84.6 Friend React Marijuana Use ----0.47 0.28 1.72* 60.7 Definitions/ Attitudes Risk Marijuana ----0.35 0.30 1.18 42.1 Attitude Marijuana ----1.04 0.27 3.84*** 181.7 Differential Association Family Marijuana ----0.81 0.36 2.26** 125.9 Deviant Peers ----1.04 0.81 1.29* 183.8 Imitation/ Modeling Imitation ----0.74 0.17 4.34*** 109.8 *P X 2 =11.04 n=316 X 2 =199.75 n= 281 Model 4: Logistic regression predicting Marijuana Use with A lcohol Black M arket Sour ces Model 5: Logistic regression predicting Marijuana Use with Alcohol Black Market Sources and Social L earning variab le s. Table 5-3 presents two models (Model s 45) Model 4 captures the relationship between Alcohol Black Market Sources and Marijuana Use (Model 4) while Model 5 include s social learning variables in addition to measures of Alcohol Black Market Sources. Logistic regression indicates that overall, Model 4 is statistically significant in predicting Marijuana Use (p value<.05). Both Alcohol Black Market Sources and Race
59 are statistically s ignificant (p -value<.01 and p-value <.05 respectively). A one unit increase in Alcohol Black Market Sources increases the odds of using marijuana by 38.2%. When the model (Model 5) includes the learning variables however, the effects of Alcohol Black Mar ket Sources diminish. Model 5, including both social learning variables and Alcohol Black Market Sources, was statistically significant (p -value<.01). Out of the variables measured however, only six had effects that were stati stically significant: Mariju ana Punishment (p-value<.01); the perceived reaction of friends for personal marijuana use (Friend React Marijuana Use, p value<.10); Attitude Marijuana (p-value<.01) family marijuana use (Family Marijuana, p -value<.10); Deviant Peers (p value<. 05); and Im itation (p -value<.01). The more one viewed punishment for marijuana use (Marijuana Punish) the less likely they were to have used marijuana (Marijuana Use ) a one unit increase in negative expectations lead to an 8 4.6 % decrease in using marijuana. The m ore positively one perceived their friends would react to their marijuana use, the more likely they were to have used marijuana (a one unit increase in Friend React Marijuana Use yielded a 60 .7% increase in marijuana use). A one unit increase in Family Ma rijuana use lead to a 125.9% increase in having used marijuana (Marijuana Use). A one unit increase in Deviant Peers increases the odds of having used marijuana (Marijuana Use) by 183.3%, while a one unit increase in Imitation increases the odds of using marijuana (Marijuana Use) by 109.8%. The odds of this event is simply the chance that it is true divided by the chance that it is not, therefore the chance that someone uses marijuana (Marijuana Use) increases by 109.8% when Imitation is increased by one. When social learning variables were included in the logit model, t here was no longer a significant effect for Alcohol Black Market Sources in predicting Marijuana Use.
60 General Deviance Table 5-4. Model 6 and Model 7 Variables Model 6 Model 7 Control Variables b SE t b SE t Gender .11 .04 2.64*** 0.08 0.04 2.23** Race .01 .02 0.91 0.03 0.01 2.41** Independent Variables Alcohol Black Market Sources .05 .02 2.63*** 0.01 0.02 0.51 Differential Reinforcement Alcohol Reward ---0.00 0.01 0.04 Alcohol Punish ---0.15 0.03 6.08*** Friend React Substance Use ---0.02 0.02 0.65 Def initions/ Attitudes Risk Deviant Behavior ---0.07 0.03 2.67*** Attitude Alcohol ---0.01 0.03 0.17 Differential Association Family Alcohol ---0.01 0.02 0.24 Deviant Peers ---0.51 0.07 7.23*** Imitation / Modeling Imitation ---0.02 0.01 1.43* Imitation Friend Buy Alcohol Under LDA ---0.07 0.04 1.97** *P F=5.21 R2=.05 n=322 F=19.20 R2=.45 n= 295 Model 6: Ordinary Least Squares Regression Predicting General Deviance with Alcohol Black Market Sources Model 7: Ordinary Least Squares Regression Predicting General Deviance with Alcohol Black Market Sources and Social Learning Variables These models were calculated using robust standard errors due to the fact that that the residuals were non -normal, and robust stander errors are reported here. The final two models were assessed with ordinary least squares regression and are summarized in Table 54. T he first model of this series (Model 6 p -value<.01) successfully predicted 5 % of the variance in General Deviance utilizing Alcohol Black Market Sources (p -value <.01), and the control variables. For each unit increase noted in Alcohol Black Market Sources, there was a 05 unit increase in General Deviance. The second model in this series included the variables from Model 6 and added in social learning variables. Model 7 (p-value<.01) successfully explained 45 % of the variance in
61 General Deviance. Several variables achieved statistic al significance in this model, including: Alcohol Punish (p -value<.001); perceived risk in deviant behavior (Risk Deviant Behavior, p -value <.05); Deviant Peers (p -value <.01); having witnessed friends utilize substance s (Imitation p -value<.10); having wit nessed friends purchase alcohol under the LDA (Imitation Buy Alcohol U nder LDA p -value <.05); and both the control variables: Gender and Race (p -values<.05). Deviant Peers had the largest effect on General Deviance (beta = .3 7 ). For a one unit increase in Deviant Peers, a .5 unit increase was noted in General Deviance. Alcohol Punishment was the second strongest predictor of General Deviance (beta=.35), followed by perceived risk (Risk Deviant Behavior, beta= .13) and having friends purchase alcohol wh ile underage (Imitation Buy Alcohol U nder LDA beta= -.09) and imitation (beta= -.08) Support for the Hypotheses The first h ypothesis stated that the use of Alcohol Black Market Sources is predicted by social learning variables and was well supporte d with the Ordinary Least Squares Regression. Specifically, Differential Reinforcement, Definitions and Imitation variables were statistically significant. Again, researchers believe that Black Market Associations involve association with non -conforming others may be correct l y viewed as a specific type of deviant association. These Black Market Sources may be seen as indirect indicators of the process of differential association in social learning theory. Some may say that this renders the relationships between the Alcohol Black Market Sources and o ther forms of deviance spurious; however I contend that they are all indicators of the social learning process in substance use, obtaining substances for that use, and therefore correlated with other forms of deviant behavior.
62 Hypothesis 2 stated that the use of Alcohol Black Market Sources has a significant effect on the use of Marijuana Black Market Sources, and was statistically significant (p<.001), however; it also stated that the effect would be reduce d and become nonsignificant when measures of social learning variables were entered into the model. This was supported by the Model 3 Logistic Regression, reve a ling that once social learning variables were entered into the equation, the effects of Alcoho l Black Market Sources were no longer significant. Definitions/Attitudes, Differential Association and Imitation/Modeling variables were significant. Hypothesis 3 stated that the use of Alcohol Black Market Sources has a significant relationship w ith Ma rijuana Use, which it did; however, the relationship will become non -significant when measures of social learning variables were entered into the model. This was supported by the Model 5 Logistic Regression as Alcohol Black Market Sources were no longer significant, but Differential Reinforcement, Differential Association, and Imitation variables were. Hypothesis 4 stated that Alcohol Black Market Sources would have a significant relationship with measures of general deviance, which it did, but that the relationship would be rendered insignificant when the social learning variables were accounted for. Ordinary Least Squares Regression, reflected in Model 7, supported this hypothesis. Both gender and race were significant (as supported by the literature ), as were all four social learning variables.
63 CHAPTER 6 CONCLUSION Discussion This research examined the social learning variables predictive of having Alcohol Black Market Sources, and the effect of having Alcohol Black Market Sources (along with othe r social learning variables) Marijuana Black Market Sources, Marijuana Use and General Deviance. As hypothesized, i t was found that Alcohol Black Market Sources had significant effects on each of these deviant behaviors. These significant main effects diminished when included in the models with measures of social learning variables. This is important because it demonstrates that differential peer associations account for specific types of associations, such as black market ties. Results also indicated that a separate set of social learning variables, specifically aimed at drinking behavior, were effective in predicting Alcohol Black Market Sources. Findings have demonstrated that these black market sources are associated with deviant behaviors (using other black market sources, partaking in deviance, using illicit substances), and the involvement in Alcohol Black Market Sources itself is indicative of deviant behavior (illegally purchasing alcohol). Based on the current literature linking social learning variables to many forms of deviance, the finding that social learning variables were significant in predicting these associations was as expected Also, given the assumption that all of these were implicated in and outcomes of the same underlying soci al learning process the findings that the effects of Alcohol Black Market Sources were reduced to statistical non -significance when entered in the same models as the social learning variables were also as expected and supportive of the hypotheses.
64 Limitat ions and Implications There are several limitations in this study, the first of which involve the sample. First off, the sample size was small (N=408), yielding a low response rate for particular outcome variables of interest (black market deviance for i nstance). This prohibited analysis of important relationships with regard to black market deviance, which was of central importance to the goals of this research. Second, the sample was not randomly drawn; it was a convenience sample, recruited through t he participant pool. Students who never fulfilled their research requirements were not captured in this study, and may have been fundamentally different from those students completing their research requirements. Also, this sample was comprised of studen ts in criminology classes, most of whom are criminology majors. Considering the focus of criminology, it is doubtful that criminology majors accurately represent all college students, and may be involved in less deviance than other majors. In addition, t he survey instrument lacked appropriate measures on the social learning variables relevant to general deviance. When constructed, the main focus was substance use and abuse, though there were some deviance measures included. This inhibited more sophistic ated analyses in predicting deviance in general. The results from the models predicting general deviance were also dampened by this limitation. Many of the models were assessed with logistic regression, which is not as straight forward and easily interpreted as linear regression. The dichotomous outcome variables were the cause for this method of assessment. While there is little reason to believe that the effects of the social learning and other variables in the sample in this study would be opposite of, or very different from effects found elsewhere, there is always the question
65 of how much findings from a sample of college students on only one campus, in one part of the country, may be generalizable to other populations. This thesis is th e first phase of a planned twophased research project. It utilizes data drawn from the participant pool that is set up through the Department of Sociology and Criminology & Law at the University of Florida. Some of the limitations of the present research will be addressed in the second phase. The plans for the second phase includes expand ing to encompass a larger sample drawn from multiple universities South Eastern region of the United S tates and also international data collected from South Korea. Thi s will provide more generalizable findings With the expansion to different locations in the country and the world and different university atmospheres, the theory being utilized may also be expanded to include structural variables. Social structure soc ial learning model s (Akers, 1998) will be useful to build on the results of this study, and to compare the effects of the social structural components among the different populations. Along with the inclusion of structural variables to measure macrolevel differences, items more appropriate for deviance measures, especially social learning measures, will be included in the revised instrument. Larger samples will be utilized in an effort to capture a higher frequency of involvement for the black market devi ance and use of other drug black market sources.
66 APPENDIX A SOCIAL LEARNING MODE L
67 SOCIAL LEARNING THEORY Differential associations Balance of con forming and deviant peers Differential Reinforcement Balance of Reward and Punishment Definitions Favorable and unfavorable to deviant or conforming behavior Imitation Modeling and imitation of peer groups (primary tertiary) Behavior Deviant or Conforming behavior
68 APPENDIX B IRB PROTOCOL FORM
69 UFIRB 02 Social & Behavioral Research Protocol Submission Ti tle of Protocol: Social Learning Theory: Underage Drinking and Black Market Deviance Principal Investigator: Heather Stewart UFID #: 6393 8765 Degree / Title: B.A., B.S. Department: Department of Criminology, Law and Society Mailing Address: Depar tment of Criminology, Law and Society University of Florida PO Box 115950 Gainesville, Florida 326115950 Email Address & Telephone Number: email@example.com 352.258.4335 Co Investigator(s): UFID#: Supervisor: Ronald L. Akers UFID#: D egree / Title: Ph.D., Professor Department: Department of Criminology, Law and Society Mailing Address: Department of Criminology, Law and Society University of Florida PO Box 115950 Gainesville, Florida 326115950 Email Addr ess & Telephone Number: firstname.lastname@example.org 352.392.1025 ext 204 Date of Proposed Research: July 2008 December 2008 Source of Funding (A copy of the grant proposal must be submitted with this protocol if fundi ng is involved): No external source of funding. Scientific Purpose of the Study: The scientific purpose of this study lies in examining the social learning variables in the context of underage drinking substance use and various forms of devian ce From a previous study, Raising the Minimum Drinking Age: Some Unintended Consequences of Good Intentions (Lanza -Kaduce, 1989), it was determined that underage drinkers obtain their alcohol from different sources than legal age drinkers. Some of those sources are unknown persons, and in the literature have been titled black market associations. These sources of alcohol are considered black market ties to illegal alcohol consumption. The goal of this research is to determine if using black market sources to obtain alcohol, leads to further black market ties or differential peer associations (i.e. black market drug associations, stolen goods dealers) In addition, we want to know if these differential peer associations lead to other deviance, incl uding other black market deviance (dealing in stolen goods, pawning stolen goods)
70 Describe the Research Methodology in Non Technical Language: ( Explain what will be done with or to the research participant. ) Participants of the study will be college students recruited either through the Participant Pool run through the Department of Criminology, Law and Society, and through in class recruitment A research assistant will always be utilized for the in class recruitment, and the instructor for the course will be asked to leave, so the students do not feel pressure to participate, and know that the participation is purely voluntary. If students are recruited through the Participant Pool, students will sign up for the experiment online, and will be awarded class credit. Generally there are several studies posted in the Participant Pool during the semester, and students pick the ones they want to participate in. An alternative assignment will be available for students that do not want to partici pate in research. The survey is posted on a survey website, www.surveymonkey.com Researchers paid for data encryption to protect the privacy of the participants and their responses. At the very beginning of the survey, the students are provided with an informed consent form to read over, they must click next to indicate their agreement to participate in this study (see Appendix A). Upon giving their informed consent by clicking next, the participants wi ll be directed to the online survey (see Appendix C) and requested to fill it out to the best of their ability. Students are reminded in the informed consent that they are not to put their name on the survey, and there is no blank field for them to do so. The survey will be completely anonymous. This questionnaire is designed to ask questions about underage drinking, methods of obtaining alcohol, substance use methods of obtaining substances, and other forms of deviance. Several questions from the sur vey will be used as measures of the social learning variables while others will be used to measure the outcome variables of interest (substance use, deviance, black market deviance, etc.) This survey was developed in corroboration with Ronald Akers, Ph.D and Lonn Lanza -Kaduce, Ph.D., to ensure proper measurement of the social learning variables and deviance. Most of the attitudinal questions, activity questions, demographic questions, and substance use questions were derived from the questions asked in the CORE survey. The CORE survey on drug and alcohol use has been in utilized since the 1980s, and was developed by the US Department of Education, in affiliation with several universities. These questions were further developed by separating measures of alcohol, marijuana and other drug use. Skip logic is included in the online survey, to ensure that the students do not spend any unneeded time filling out the survey. If the students choose an answer that makes later questions irrelevant, those ques tions will be skipped for them. After filling out the questionnaire, students will be debriefed in detail as to the purpose of our study, provided a copy of the debriefing form (see Appendix B), and thanked for their participation. Describe Potential Benefits and Anticipated Risks: ( If risk of physical, psychological or economic harm may be involved, describe the steps taken to protect participant.) There are minimal anticipated ris ks associated with this survey, no more so than what the par ticipant is exposed to in daily conversation, daily television, or other daily media. The survey being administered will co ntain no personal identifiers, their responses are encrypted, and the participants will be briefed after taking the survey as to what the survey was trying to measure. They will be given a debriefing synopsis (see Appendix B), that explains the purpose of the study, and they will also be provided with telephone numbers for the primary investigator and supervisor, should they have furt her questions.
71 Potential Benefits: Each student who participates in either the study or the alternative assignment will learn about academic research as a benefit of participating. Participants who sign up through the participant pool will rec eive course credit for either participating in the study or completing an alternative assignment. Participants that are recruited through in class solicitation also may be offered course credit or extra credit at the discretion of their instructor. Eithe r way, the student learns about academic research. Other Potential Benefits : This research has the potential to contribute greatly to the field. To date, no survey measures all four social learning variables while also measuring alcohol use, marijuana use, and other drug use separately, as well as several different forms of criminal deviance. Also, no current research focuses on the black market ties developed by underage drinkers in obtaining alcohol illegally. Describe How Participant(s ) Will Be Recruited, the Number and AGE of the Participants, and Proposed Compensation: Participants will be recru ited through either the online Participant P ool set up through the Department of C riminology, Law and Society, though in class recruitm ent. All participants will be eighteen and older, and students taking classes at the University of Florida. Both male and female students will be sampled, and all races are included. If the participants are recruited through the participant po ol, they are offered two avenues to obtain points for certain classes. Research is posted online in a program designed for the participant pool, and participants are allowed to choose which research they wish to participate in. If the students do not wish to participate in research, they may choose to do an alternative assignment. Both are supposed to be about equal in time and effort, and both are geared to educate the student about academic research. Credit for the research is awarded through the websi te, so the instructor will have no idea who participated in research and who completed the alternative assignment. Participants who are recruited in the classroom, will be of eighteen years of age and older, both male and female, and all races are included. They will participate in the research on a voluntary basis, and may receive course credit or extra credit at the discretion of their instructor.) The survey is posted on www.surveymonkey.com An alter native assignment will be available for those students who do not wish to participate in research if the instructor chooses to offer course credit in exchange for participation. The professor will be asked to leave the room during recruitment, so that the y will have no idea who participated in research, and who completed the alternative assignment for credit (if it is offered). This precaution is taken to minimize pressure on the students to participate in research. A maximum number of 6 00 students will be sampled. Describe the Informed Consent Process. Include a Copy of the Informed Consent Document: Before completing the survey, when students select this survey to participate in, the students will be required to read over the infor med consent form (see Appendix A) before they are redirected to the
72 survey If they agree to participate in the study they requested to click next and have the option to print a copy to keep. After completing the survey (see Appendix C), the students w ill be debriefed as to the purpose of the study, and have the option to print the debriefing form that explains the study (see Appendix B), and will be advised of their right to ask questions. Principal Investigator(s) Signature: Supervisor Signature: Department Chair/Center Director Signature: Date:
73 APPENDIX C INFORMED CONSENT FORM
74 Protocol Title: Social Learning Theory: Underage Drinking and Black Market Deviance Please read this consent document carefully before you decide to continue your participation in this study. Purpose of the research study : The scientific purpose of this study lies in examining the social learning variables in the context of underage drinking, substance use, and different forms of deviance. A description of s ocial learning theory and a full explanation of the variables of interest will be provided in a debriefing form upon completion of the survey, as not to bias any of your answers. What you will be asked to do in the study: You will be asked to complete a n anonymous survey on some varying topics: Demographics, basic information, activities, campus life, association with peers, substance use, methods of obtaining substances, experiences you have had, and any type of deviance that you may have been involved in. Responses to the survey are completely anonymous, and are encrypted through survey monkey. No personal identifying information is requested in this survey. If at anytime you feel uncomfortable, and wish to withdraw from the study, you may exit the survey, and your responses will be deleted. Upon completion of the survey, you will receive a confirmation of completion and a debriefing form. Time required : 90 minutes or less Risks and Benefits : There are minimal risks associated with this research, n o more than what you would be exposed to by watching television. The benefits include getting a closer look at academic research through being provided a description of this project. If you signed up for this project through the Participant Pool, you will receive credit for research. If you were solicited from a class, your professor may decide to give you credit, or extra credit. Either way, should you choose not to participate in research, there are alternative assignments available, that are of equal tim e and effort. Compensation: If you signed up through the participant pool, you will earn the amount of credit determined by the participant pool coordinators for participating in the study. If you are solicited from a class room, credit for your partici pation is left to your instructors discretion. Confidentiality: We are not asking for your personal information. There is no place in the survey to put your name. All responses are anonymous, and all data provided in this survey is encrypted by survey monkey. Researchers paid to have this service provided to ensure
75 your privacy. Your identity will be kept completely anonymous as nothing to identify you is being asked in this survey. If you are participating for class credit, your instructor will not know whether you completed research, or an alternative assignment. Voluntary participation : Your participation in this study is completely voluntary. There is no penalty for not participating. Right to withdraw from the study: You have the right to withdraw from the study at anytime without consequence. Whom to contact if you have questions about the study: Heather Stewart, Graduate Student Department of Criminology Law and Society University of Florida PO Box 115950 Gainesville, Florida 326115950 Pho ne: 352.392.1025 ext. 777 Ronald L. Akers, Ph.D. Department of Criminology Law and Society Phone: 352.392.1025 ext. 204 Whom to contact about your rights as a research participant in the study: IRB02 Office, Box 112250, University of Florida, Gainesville, FL 326112250; phone 3920433. Agreement : I have read the procedure described above. I voluntarily agree to participate in the procedure. By clicking "next" you acknowledge that you have read this informed consent, and agree to participate in this research. You may print this page if you wish to have a copy of the informed consent.
76 APPEND IX D DEBRIEFING FORM
77 Appendix F : Debriefing form Survey Complete! Thank you for your participation! The purpose of this research is to build on prior rese arch completed in the area of underage drinking. In previous research it was found that underage drinkers often times use strangers and/or students they do not really know, who are of the legal drinking age to get alcohol for them. This method of obtaining alcohol is termed black market in the literature. To expand on this research, we predicted that underage drinkers who utilize these black market ties will be score higher on other types of deviance, including other black market deviance, drug use, poor academic performance, criminal behaviors, and so on. We are specifically investigating these black market ties, and the relationships they have with deviance using the variables from Ronald Akers, Ph.D., social learning theory. Social learning theory e ncompasses four variables that explain how behavior, conforming or deviant, is learned and maintained: differential associations, definitions, differential reinforcement and imitation. Differential associations have to do with the direct and indirect assoc iation with others who model different types of behavior. These associations provide the major social contexts in which all the mechanisms of social lea rning operate (Akers and Sellers, 2004). Definitions, Akers contends, are the meanings, beliefs, and a ttitudes one has toward a particular behavior. The more positive the definition of the behavior, the more likely the behavior is to occur be it conforming or deviant. Differential reinforcement is the balance of perceived rewards and punishments conseque ntial to a behavior. The more rewarding one views the behavior the more likely they are to partake in it and repeat it in the future, thus it works both to create or dissuade, and maintain or desist behavior. Imitation is most important in the acquisition of novel behavior, but continues to have a minute effect once a behavior is learned. It is exactly how it sounds; one imitates or models the behavior they observe another act out. These four variables are micro level variables, meaning they apply specifica lly to the individual or a small group of individuals. Measures of all four social learning variables were included in the survey that you completed. Researchers will code your answers into numerical values, and use statistical analysis to determine if th e relationship predicted, drinkers who use black market ties to obtain in alcohol will be higher in other forms of deviance, is significant. If you wish to have your data not included in the study, you are free to withdraw your data from the sample, and i t will be destroyed immediately. So you know your data is completely confidential no identifying information was asked in the survey. Your results are confidential to the researchers, and all results are published anonymously.
78 APPENDIX E INSTRUMENT
113 APPENDIX F CORRELATION MATRICES
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124 BIO GRAPHICAL SKETCH Heather Brianna Stewart was born in San Diego, California Heather moved all over the country until finally settling in Florida in 1999. Heather has always had an affinity for both sp orts and intellectual pursuits. Her love of athletics was exhibited in her participation in volleyball, swimming and riding horses, and later her coaching of swimming. Heathers academic career has been diverse. The first year of her undergraduate career was spent at University of Alabama in Huntsville, and after a span of inactivity, she returned to obtain her Associate of Arts at Santa Fe College graduating Phi Theta Kappa with honors. She continued her education at the University of Florida, earning a Bachelor of Arts in c riminology, Summa Cumme Laude and a Bachelor of Science in p sychology, Cumme Laude, all while working full time in law enforcement. Heather was accepted as a graduate student in the Department of Sociology and Criminology & Law at the University of Florida in Gainesville, Florida. She received her Master of Arts in the summer of 2010. She received her Ph.D. from the University of Florida in the spring of 2012.