Psychological Factors Related to Adolescent Gambling

1. Psychological Factors Related to Adolescent Gambling David Casey*, Annik Mossière, Rob Williams, Nady el-Guebaly, David Hodgins, Garry Smith, Rob Williams, Don Schopflocher, & Rob Wood *Research Coordinator, Leisure, Lifestyle, Lifecycle Project (LLLP), Psychology Department, University of Calgary

2. Goals of the Presentation • Background on the Leisure, Lifestyle, Lifecycle Project (LLLP) • Explain the biopsychosocial model • Describe: • Adolescent Sample • Measures • Present the results of logistic regression analysis for adolescents • Discuss the conclusions • Plans for the future: • Examining patterns of relationship over three more collection points • Changes in gambling behavior over time

3. Background: The Leisure, Lifestyle, Lifecycle Project (LLLP)

4. Background • Cohort longitudinal study of gambling behavior • Over 5 years, with 4 data collections • Initial sample • Most recruited through Random Digit Dialing (RDD) • Stratified by region of the province (urban & rural) • 5 age groups (13-15, 18-20, 23-25, 43-45, 63-65) • Divided into at-risk gamblers & general population • Data collection at Wave 1: • Telephone, computer-based, & face-to-face interviews • Data collection at Wave 2: • Web-based survey • Data collection at Wave 3: • Just wrapped-up this month using web-based survey • Data collection at Wave 4: (in 12-16 months) • Testing a biopsychosocial model of gambling

5. Biopsychosocial Model for Gambling • BIOLOGICAL RISK • Neuropsychological functioning • - Frontal lobe • Neurotransmitter • - DA (blood & saliva DNA) • - MAOI activity • Gender • DEMOGRAPHICS • Religion • Age • SES • Family background • Ethnicity • TEMPERAMENT/PERSONALITY • Impulsivity • Trait anxiety • Moral disengagement • Self-esteem • EXTERNALIZING PROBLEMS • Alcohol use • Substance use • Tobacco use • Delinquent activity • Sexual activity • COGNITIVE • Intelligence • Attentional Ability • Gambling fallacies • Coping Skills • FAMILY HISTORY • Social & problem gambling • Substance use disorders • - Psychiatric disorders • - Deviance • STRESSORS • Physical health/disability • School/work • Familial/peer • Legal • GAMBLING INVOLVEMENT • Frequency & Duration • Type & Range • Context • INTERNALIZING PROBLEMS • Depression • Anxiety • FAMILY ENVIRONMENT • Parental behavior • Marital Status/conflict • Abuse experiences • GAMBLING DISORDERS • Frequency & Duration • Type & Range • Context • EXTRA FAMILIAL ENVIRONMENT • Social Support • Friendships/peers • Religion/Spirituality • Ethnicity/Culture • Social organization PREVENTION & TREATMENT • BROADER SOCIO-CULTURAL FACTORS • Availability of gambling; public attitudes; prevention programs; legislative changes; gambling knowledge

6. Table 1. Leisure, Lifestyle, Lifecycle Project: Demographics

7. Today’s Presentation • This talk will present findings from Wave 1 data only • Focus on adolescent sample • Examining relationship between gambling, family environment, religiosity, externalizing and internalizing problems

8. Methods

9. Table 2. Demographics for Adolescents at Wave1

10. Table 3. Measures in LLLP at Wave 1: Adolescent Participants

11. Results

12. Adolescent Gambling Table 4. Gambling Prevalence and Risk Table 5. Frequency of Gambling Activities and $ Spent

13. Preliminary Analysis • First Step in analysis of adolescent gambling: • Univariate analysis were used to compare: • Non-gamblers vs. Gamblers • Those significant at the univariate level were used in logistic regression analysis

14. Logistic Regression • Why Logistic Regression? • Allows categorization into groups based on predictors • Can use continuous and categorical variables • Data was weighted based on gender, age, and demographic location for Alberta • Bootstrap weights were used in the present analysis • Refine the confidence interval in logistic regression

15. Table 6. Correlations for Variables– All Adolescents ** . Correlation is significant at the 0.01 level (2-tailed) *. Correlation is significant at the 0.05 level (2-tailed)

16. Logistic Regression Results Table 7. 7 Most Significant Variables for Males

17. Logistic Regression Results Table 8. 10 Most Significant Variables for Females * Household Income in Thousands, rounded to the nearest dollar

18. Conclusions Regarding the Present Analysis

19. Conclusions for Adolescents • Compared to non-gamblers, male gamblers were: • Older • Identified more conflict in their family • Involved in more activity and recreation with their family • More likely to have used drugs in the past 12 months • More likely to have peers who also gambled • Compared to non-gamblers, female gamblers: • Scored higher on attention problems, thought problems, rule-breaking, and aggression • Were more involved with activity and recreation with their family • Came from households with a higher annual income • Scored higher on the measure of intelligence

20. Conclusions Cont’d • Moral and religious beliefs were protective factors for both adolescent males and females • Both males and females – less likely to gamble if they identified having strong moral and religious beliefs, either themselves or their families • Adolescents identified as having strong moral and religious beliefs associate gambling with immoral behavior, and thus it would be seen negatively, by their families and communities, for them to partake in the activity

21. Plans for Follow-Up Analysis • Compare findings with data collected at Waves 2, 3, & 4: • Do the results remain consistent or change? • Are there still gender differences? • Availability to consider other constructs: • Do they help distinguish between non-gamblers and gamblers?

22. Future Directions • Examining change in gambling behavior over time: • How does the pattern change over 5 years? • LLLP Waves 2-4: provide opportunity to examine changes in behaviors associated with : • Gambling • Changes as they mature into young adulthood • Changes in family environment • Changes in moral and religious beliefs • Other lifestyle altercations • What changes occur once they are of legal age to gamble? • Important to examine changes in intensity of gambling over the years, and expenditure in relation to their psychological health • The influence of other risky behaviors, such as the use of drugs and alcohol, will be important to consider as these adolescents mature into adulthood

23. Implications • Findings highlight interesting factors related to gambling behavior among a sample of adolescent males and females • Identifying the relationship between adolescent gambling, their peers gambling behavior, family, religion, and alcohol and substance abuse • can offer insight into guiding treatment approaches adolescents with gambling problems • Agencies could use these findings to: • educate the public about the dangers of gambling • creating awareness of the potential harm it can have on youth • the role that religiosity, family, peers, and substance use can play • Legislators could develop more effective laws and policies regarding age restrictions associated with gambling, advertisement regulations, and access to gambling

24. Thanks Questions? David Casey, PhD dcasey@ucalgary.ca University of Calgary Psychology Department We Would Like to Acknowledge Funding for this Study from the Alberta Gambling Research Institute (AGRI)

25. Additional Slides

26. Background • Gambling in Alberta • 82% of adults gambled in previous year • Few studies of determinants of gambling & disordered gambling • Interested in better understanding: • Factors that promote responsible gambling • Factors that make some susceptible to problem gambling • Low prevalence of problem gambling requires over-sampling of at-risk groups • Longitudinal study as optimal methodology • Over 5 years, with 4 data collections

27. Methods - Procedures • Recruited through Random Digit Dialing (RDD) at 4 locations: • Calgary • Edmonton • Grande Prairie (and surrounding communities) • Lethbridge (and surrounding communities) • Start and end for data collection was staggered between sites • Start: Feb 8, 2006 to Mar 20, 2006 • End: Aug 26, 2006 to Oct 21, 2006 • Recruited the following: • Participants from the general population • Participants at-risk of developing gambling problems • Based on frequency & amount of gambling

28. Methods - Procedures • For all participants who met the criteria for age, residence, etc., there was the following at Wave 1: • Telephone interview by subcontract • Adult interviews (~ 45 minutes) • Adolescent interviews (~ 30 minutes) • Majority of demographic & gambling questions • Face-to-face interview by RA’s • Adult interviews (~ 3 hrs) • Adolescent interviews (~ 2 hrs) • Parent interviews (~ 40 minutes) • Response rate <10%

29. Examining Gender Differences • Differences for males and females • Pattern of relationship with predictor variables was different • Logistic regressions were separate for males and females

30. New Constructs at Wave 2 or 3

31. What did We Learn? • Difficulty to recruitusing Random Digit Dialing: • Used Computer-Assisted Telephone Interview (CATI) • Call display; Blocking; “Do not call” lists • Saturation of the saturation • Difficulty to recruit at-risk or high-risk gamblers • Supplemental recruitment techniques N=30 only! • Media release; Ads in local papers; Posters in casinos; “Snowball” e-mail • Telephone to face-to-face interview loss: • Some did not feel $75 was enough incentive • Booming economy vs. recession • Ability to look at changes in patterns of gambling behavior over time

32. Plans for Future Data Collection • 3 more data collections: • Wave 2 completed from Nov. 2007 to Jun. 2008 • Wave 3 started in Jul. 2009 to April 2010 • Wave 4 will begin in the Winter of 2010 • Wave 2 to 4 participants will complete web-based surveys • Gambling behavior will be tracked over all 5 years • Constructs associated with biological, psychological, & social factors will also be tracked