ADDRESSING COLLEGE GAMBLING: AN EVIDENCE-BASED SCREENING AND BRIEF INTERVENTION

Transcription

1 ADDRESSING COLLEGE GAMBLING: AN EVIDENCE-BASED SCREENING AND BRIEF INTERVENTION Clayton Neighbors, PhD Department of Psychology University of Houston Christine Reilly, MA National Center for Responsible Gaming 1

2 Acknowledgements Funding: National Center for Responsible Gaming Staff: Dipali Rinker Nicole Fossos Maigen Agana Graduate Students Dawn Foster Lindsey Rodriguez Undergraduate RAs UH Students 2

3 Gambling Behavior Continuum 3

4 4 College Students About half of US high school graduates will attend college. Emerging adulthood is a time of exploration and risk. Most students will mature out of risk as they take on adult roles.

5 Overview This project aims to evaluate a brief computerized normative feedback intervention for at-risk college students. Gambling is a significant problem for approximately 5% of college students % of college students have some level of risk related to gambling. Social influences on gambling among adolescents and adults have been well documented (Hardoon & Derevensky, 2001; Welte, Wieczorek, Barnes, & Tidwell, 2006).. Effects of normative feedback may vary as a function of identification with other students. 5

6 Why do college students gamble? N=252; SOGS 2+ Enjoyment 3.64 Social 3.08 Money 3.07 Skill 2.96 Winning 2.85 Excitement 2.84 Drinking 2.52 Chasing 2.46 Conformity 2.38 Boredom 2.31 Interest 2.25 Challenge 1.99 Risk 1.79 Compete 1.71 Luck 1.57 Cope/escape 1.56 Neighbors, C., Lostutter, T. W., Cronce, J. M., & Larimer, M. E. (2002). Exploring college student gambling motivation. Journal of Gambling Studies, 18,

7 College Student Gambling Consequences Problem gambling students report higher alcohol use, poorer academic performance, more mental health symptoms, and greater suicidal ideation (Barnes, Welte, Hoffman, & Tidwell, 2010; Crockford & el-guebaly, 1998; Lesieur et al. 1991; Takushi et al., 2002; Whiteside, et al., 2005) 7

8 Social Norms Implicit or explicit rules regarding appropriate behavior. What is it that I am supposed to do? What is normal? What is abnormal? Cultural relativism. A central construct 8

9 9 Social Norms How much $ do you think the average college student spends on gambling per occasion, month, year? Perceived Descriptive Norm Actual Descriptive Norm Behavior Perceived Injunctive Actual Injunctive Approval 9

10 Estimated Gambling Expenditure How many dollars per month do you think the average spends gambling? Russian Steel Worker Tibetan Monk Retired WNBA star 10

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12 Identification with others 12

13 Social Norms, Alcohol, and Prevention: Three Critical Points Perceived norms are among the strongest and most consistent predictors of problem drinking among college students Borsari & Carey, 2003; Neighbors et al., 2007; Perkins, 2002; Wood et al., 2001 College students overestimate descriptive drinking norms and the magnitude of overestimation has been associated with heavier drinking Baer, Stacy, & Larimer, 1991; Lewis & Neighbors, 2004; Marks, Graham, & Hanson, 1992; Neighbors, Dillard, & Lewis, Bergstrom, & Neil, 2006; Neighbors, Lee, Lewis, Fossos, & Larimer, 2007 Correction of normative misperceptions is a widely used strategy for attempting to reduce college student drinking Borsari & Carey, 2000; Lewis & Neighbors 2007; Miller et al., in press; Neighbors, Lewis, Bergstrom, & Larimer, 2006; Neighbors, Larimer, & Lewis, 2004; Perkins et al., 2006; DeJong et al.,

14 Foundation For Intervention If perceived norms cause behavior then changing perceived norms should change behavior. Normative misperceptions provide the opportunity for correcting overestimation of risk behaviors. Social norms interventions aim to change behavior by correcting normative misperceptions: Social Norms Marketing Personalized Normative Feedback In-person Feedback Mailed Feedback Clickers/interactive polling system 14

15 Personalized feedback interventions: Recent review of 41 studies including 66 interventions Drinking profile Patterns of quantity and frequency of alcohol consumption 98% Normative comparison Comparison of personal data (either behavior or perceptions) 98% to a reference group Didactic information Educational information about alcohol, its effects, or tips on using 86% alcohol safely Risk factors for future consequences Individual factors that place individuals at increased risk for developing AUD or for encountering health or social consequences 77% Level of intoxication (BAC) Estimated level of intoxication achieved for typical or peak drinking 72% occasions Strategies to limit risk Behavioral strategies to limit consumption or intoxication or 65% protective strategies to limit risk exposure Negative consequences of List of consequences reported by individual 60% alcohol use Practical costs Reframing alcohol consumption patterns in other terms 53% Local resources Contact information for local referral or information sources 33% Alcohol expectancies Decisional balance Psychological, physical, emotional, or social effects that individuals expect to occur as a result of alcohol consumption Summary of individual s reported pros and cons of current drinking behavior and/or of making changes to that behavior 30% 28% Miller, M. B., Leffingwell, T., Claborn, K., Meier, E., Walters, S., & Neighbors, C. (in press). Personalized feedback interventions for college alcohol misuse: An update of Walters & Neighbors (2005). Psychology of Addictive Behaviors. 15

16 Personalized Normative Feedback (PNF) Students respond to questions about typical college student drinking as well as their own drinking behavior. Feedback is then provided to students that is personally tailored based on their responses. Presents two discrepancies to heavy drinking students: Estimate of drinking norm > Actual drinking norm Own drinking > Typical students drinking 16

17 Sample Feedback Example of PNF According to the information you provided us during the computer assessment, the number of occasions you drank (frequency) was 4 times a week. The average amount you drank on each occasion (quantity) was 6 drinks. You completed questions asking you what you believed the average frequency and quantity of alcohol consumed by other college students. You told us that you believed that the average student drank 5 times a week and during each occasion, s/he consumed 7 drinks. The actual drinking norm for students at the University of Washington is 1.5 times a week drinking about 3.5 drinks on each occasion. Your percentile rank (comparing you to other college students is 91%, which suggests that you drink more than 91% of other college students. Days per Week Number of Drinks per Week Frequency of Alcohol Consumption How frequently the average UW student ACTUALLY drinks Your estimation of how frequently the average UW student drinks Quantity of Alcohol Consumption How much the average UW student ACTUALLY drinks The frequency that you drink Your estimation The amount that of how much you drink the average UW student drinks

18 Participants and Procedure Study 1: 252 (104 men and 148 women) heavy drinking students at the University of Washington. All assessments completed in lab on computer. Participants were randomly assigned to receive normative feedback versus assessment only following the baseline assessment. Personalized Normative Feedback Screening 5/4 Previous Month Baseline Assessment 3 Month Follow-up 6 Month Follow-up 18

19 Evidence of Efficacy Legend Baseline 3-Month Follow-up 6-Month Follow-up Perceived Norms Perceived Typical Weekly Quantity Control Feedback Perceived Typical Quantity Per Occasion Drinking Behavior Drinks Per Week in Previous 3 Months Control Feedback Drinks on Peak Occasion in Previous 3 Months Effect Sizes: Perceived norms d s =.61, Control Feedback Perceived Typical Frequency Control Feedback Negative Consequences in Previous 3 Months 8 Drinking d s =.35, Control Feedback 5 Control Feedback 19

20 Summary: Personalized Normative Feedback For Heavy Drinking Successful replication. Intervention effects on alcohol related problems moderated by controlled orientation. Neighbors, C., Lewis, M. A., Bergstrom, R. L., & Larimer, M. E. (2006). Being controlled by normative influences: Self-determination as a moderator of a normative feedback alcohol intervention. Health Psychology, 25, Successful replication. Gender specific normative feedback works better for women who are higher in gender identity. Lewis, M. A., & Neighbors, C. (2007). Optimizing personalized normative feedback: The use of gender-specific referents. Journal of Studies on Alcohol and Drugs, 68, Successful replication using freshman specific normative feedback. Lewis, M. A., Neighbors, C., Oster-Aaland, L., Kirkeby, B., & Larimer, M. E. (2007). Indicated prevention for incoming college freshmen: Personalized feedback and high risk drinking. Addictive Behaviors, 32, Repeated administration of web-based gender-specific personalized normative feedback reduces drinking over two year period. Neighbors, C., Lewis, M. A., Atkins, D. C., Jensen, M. M., Walter, T., Fossos, N., Lee, C. M., & Larimer, M. E. (2010). Efficacy of web-based personalized normative feedback: A two-year randomized controlled trial. Journal of Consulting and Clinical Psychology, 78,

21 Will this work for gambling? 21

22 Normative Misperceptions for Gambling College students overestimate gambling norms. Perceived norms are associated with gambling behavior Larimer, M. E., & Neighbors, C. (2003). Normative misperceptions and the impact of description and injunctive norms on college student gambling. Psychology of Addictive Behaviors, 17,

23 Gambling Norms College students overestimate gambling norms. Perceived norms are associated with gambling behavior Foster, D. W., Neighbors, C., Rodriguez, L. M., Lazorwitz, B., Gonzales, R. (in press). Self-identification as a moderator of the relationship between gambling-related perceived norms and gambling behavior. Journal of Gambling Studies. 23

24 Social Identity The more students identity with other students, the more likely the stronger the association between their perceived norms and their own behavior. Foster, D. W., Neighbors, C., Rodriguez, L. M., Lazorwitz, B., Gonzales, R. (in press). Self-identification as a moderator of the relationship between gambling-related perceived norms and gambling behavior. Journal of Gambling Studies. 24

25 Study Flow Baseline N=252 3 Month N=227 90% 6 Month N=220 87% 25

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27 Measures Neighbors, C., Lostutter, T.W., Larimer, M. E., & Takushi, R.Y. (2002). Measuring gambling outcomes among college students. Journal of Gambling Studies 18,

28 Measures Frequency-behavior and norms bfreq=0; bfreq=1; bfreq=3; bfreq=6; bfreq=12; bfreq=30; bfreq=52; bfreq=104; bfreq=183; bfreq=365; Neighbors, C., Lostutter, T.W., Larimer, M. E., & Takushi, R.Y. (2002). Measuring gambling outcomes among college students. Journal of Gambling Studies 18,

29 Measures Losses and wins Behavior Perceived Norms 29

30 Measures Problems Gambling Problems Index 20 items; Examples: Missed a day (or part of a day) of school or work because of your gambling? Missed out on other things because you spent too much money on gambling? Kept gambling when you promised yourself not to. Had a fight, argument, or bad feelings with a family member because of your gambling? Neighbors, C., Lostutter, T.W., Larimer, M. E., & Takushi, R.Y. (2002). Measuring gambling outcomes among college students. Journal of Gambling Studies 18,

31 Measure of Identification with Group (MIG) The following items consist of statements about University of Houston students. The term "group" refers to "UH students". Please indicate how much you agree or disagree with the following statements. 31 I feel strongly affiliated with this group. Belonging to this group is an important part of my identity. I am glad to contribute to this group. It is important to me that I view myself as a member of this group. I am strongly committed to this group. It is important to me that others see me as a member of this group. It is disloyal to criticize this group. I like to help this group. This group is better than other groups in all respects. Example Items 31

32 Participants (N=252) 150 Men (59.5% ) 102 Women (40.5%) Mean age years, SD = Ethnicity: 22.3% were Latino/a. 11% 5% 11% Caucasian 34% Asian/Asian American Black/African American Multi-Ethnic 39% Other 32

33 Type of gambling Any Weekly Cards 87% 11% Lottery 81% 10% Bingo 71% 5.50% Casino 67% 1.20% Machines 66% 2.40% Skill (billiards; golf ) 63% 5% Dice 55% 2% Sports 51% 6% Track 24% 5% 33

34 Types of problems (top 13) Problem Past 3 months Had a bad time? 31% Missed out on other things because you spent too much money on gambling? 24% Tried to cut down or quit gambling? 24% Neglected your responsibilities? 22% Not able to do your homework or study for a test? 16% Felt that you needed to gamble more frequently or place higher wagers than you used to use in order to get the same effect? 16% Noticed a change in your personality? 16% Tried to control your gambling by trying to gamble only at certain times of the day or in certain places? 15% Kept gambling when you prompised yourself not to? 14% Felt that you had a problem with gambling? 13% Had a fight, argument, or bad feelings with a friend? 12% Got into fights, acted badly, or did mean things? 10% Was told by a friend or neighbor to stop or cut down gambling? 10% 34

35 Personalized Normative Feedback Students respond to questions about typical college student gambling as well as their own gambling behavior. Feedback is then provided to students that is personally tailored based on their responses. Presents two discrepancies to at-risk gambling students: Estimate of gambling norm > Actual gambling norm Own gambling > Typical students gambling 35

36 Feedback for UH Men 36

37 Feedback for UH Women 37

38 Attention Control Feedback 38

39 Analyses All gambling outcomes were negatively skewed and did not follow a normal distribution. A generalized linear model approach was used where negative binomial distributions were specified for all outcomes (Atkins & Gallop, 2007; Hilbe, 2011). Negative Binomial Analyses * Note. Results did not change when ethnicity, race, and sex were included as covariates. Y ln = B 0 +B 1 (BCov) +B 1 (BInt)+e 39

40 Frequency Perceived Norm Treatment Frequency Norms b t p 3 months months Behavior Treatment Frequency Norms b t p 3 months months Perceived Frequency Frequency Control Feedback 0 Control Feedback

41 Gambling Expenditure: $ Lost Perceived Norm Treatment Frequency Norms b t p 3 months months Behavior Treatment Frequency Norms b t p 3 months months Dollars Lost per Month Control Feedback Dollars Lost per Month Control Feedback

42 $ Won Perceived Norm Treatment Frequency Norms b t p 3 months months Behavior Treatment Frequency Norms b t p 3 months months Dollars Won per Month Control Feedback Dollars Won per Month Control Feedback

43 Gambling Problems Treatment Frequency Norms b t p 3 months months Problems Control Feedback 43

44 Social Identity as of outcomes at 3-month follow-up Perceived Norms for Frequency Frequency 12 Control group 12 Control group Frequency past 90 days Feedback group Frequency past 90 days Feedback group 0 MIG 1 MIG 2 MIG 3 MIG 4 MIG 5 MIG 6 MIG 7 0 MIG 1 MIG 2 MIG 3 MIG 4 MIG 5 MIG 6 MIG 7 b=-.29, t=-2.55, p=.01 b=-.60, t=-4.44, p<

45 Social Identity as of outcomes at 3-month follow-up Gambling Wins Dollars Won Past Month Control group Feedback group 0 MIG 1 MIG 2 MIG 3 MIG 4 MIG 5 MIG 6 MIG 7 45

46 Summary Perceived Norms Frequency Intervention reductions at 3 months for those higher in social identity Perceived Norms Money Lost Intervention reductions at 3 months and 6 months Perceived Norms Money Won Intervention reductions at 3 months and 6 months Gambling Frequency Intervention reductions at 3 months for those higher in social identity Money Lost Intervention reductions at 3 months and 6 months Money Won Intervention reductions at 3 months for those higher in social identity Gambling Problems Intervention reductions at 3 months 46

47 47 Mediation Feedback Perceived Norms for Money Lost at 3 Months Money Lost at 3 Months Feedback Perceived Norms for Money Lost at 3 Months Money Lost at 6 Months Feedback Perceived Norms for Money Lost at 3 Months Gambling Problems at 3 Months 47

48 Normative feedback Can be effective for gambling prevention. Effects may vary by referents. A lot A whole lot Not that much Duration of effect? You Perceived Actual Necessary and/or sufficient? 48

49 Implementation Thoughts Future feedback could provide more specific expenditure norms (wins and losses). Need to make sure norms items and behavior items match exactly. Consider norms for problems. Remote web. Mobile friendly. 49

50 What you need to do PNF For in person Norms information in a form you can use (example to follow). May or may not require a survey Campus level data would be ideal Computer/web based-- automated Programming of survey and feedback Computer programming knowledge (e.g., php, mysql; IT help; or a good computer engineering student). 50

51 How do I do it in person and how much will it cost? If you have norms specific information for your population, inperson PNF can be done for $0. Read Miller & Rollnick s book on motivational interviewing before you try this!!! 51

52 Where can I get specific norms? Ideally, you can present norms that are specific to your population. School and gender-specific are probably ideal. You may have existing data (e.g., Campus wide surveys). You may want to collect your own. Get help from IT department. Design your own survey. Survey monkey may be a good option if your population has web-access. $25/month, unlimited questions and response with question & answer piping. 52

53 What about computer/web PNF? Caution: Most of the support for PNF with alcohol comes from computer delivered inperson feedback. Remote web-feedback works, but not as well as when students come in and do it on a computer. To set up a web-based or computer based PNF delivery system you need some programming know-how and/or a budget to pay someone to set it up. If you have an IT department they can probably help at low cost. A good computer science student can do it for cheap. Professional set up can range from $500 - $5000 or more. Shop around! We paid $500 for the first one of these with alcohol in 2000 and it was done by a senior computer science student who programmed the survey and feedback in php and mysql. 53

54 Steps in setting up web/computer PNF for drinking 1) Get norms in a form you can use. Ask frequency and expenditure questions. You may have these already (Campus survey). Design your own survey. Consider a cheap option (e.g., Survey Monkey; Catalyst) Consider the GPQN and GPI 2) Program survey and feedback. 3) Test it! 4) Invite members of your target population. 5) Evaluate if possible with a follow-up survey. 54

55 Sample questionnaire GPQN 55

56 Sample questionnaire GPI 56

57 Percentile Rank Only XX% of students gamble more than you. You gamble as much or more than XX% of students. Percentile rank can be tricky. Decide how you want to frame it. BFBFREQY Male Percentile BFBFREQY FemalePercentile You gamble more than XX% of students

58 Percentile Rank Only XX% of students gamble more than you. You gamble as much or more than XX% of students. Percentile rank can be tricky. Decide how you want to frame it. BFBFREQY Male Percentile Gambling Frequency BFBFREQY More than you 3% FemalePercentile You gamble more than XX% of students. Less than you %

59 What if you don t have the time or resources? 59

60 60 Questions? 60