1. 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.  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

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

6. Total Population Completes (N=1808) N% Age13-15 Year Olds 18-20 23-25 43-45 63-65 436 315 341 402 314 24.1 17.4 18.9 22.2 17.4 Gender Male Female 837 971 46.3 53.7 Location Calgary Edmonton Grande Prairie Lethbridge 754 536 224 294 41.7 29.6 12.4 16.3 Marital Status (Adults Only) Single, Never Married Married/Common-law Divorced /Separated/Widowed 570 643 156 41.6 47.0 11.4 Level of Education Less than High School Completed High School Some Technical/College Completed Tech/College Some University University Degree 549 279 203 225 236 315 30.4 15.4 11.2 12.5 13.1 17.5 Current Employment Status Not Currently Employed Employed Part-Time Employed Full-Time 746 430 631 41.3 23.8 34.9

7.  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

9.  For all participants who met the criteria for age, residence, etc., there was the following at Wave 1:  Telephone interview by subcontract  Adolescent interviews (~ 30 minutes)  Majority of demographic & gambling questions  Face-to-face interview  Adolescent interviews (~ 2 hrs)  Parent interviews (~ 40 minutes)

10. Non-Gambler Population (N = 196) Gambler Population (N = 240) Total Population (N =436) n%n%n% Age: 13 yrs7739.38435.016136.9 14yrs7136.27631.714733.7 15-16yrs4824.5 8033.3 12829.4 Gender: Male9146.4 14460.0 23553.9 Female10553.69640.020146.1 Location: Calgary7538.310242.517740.6 Edmonton5628.67531.313130.0 Grande Prairie2412.23012.55412.4 Lethbridge4120.93313.87417.0 Employment: Not Employed15880.617673.333476.6 Part OR Full-Time3819.4 6426.7 10223.4 Household Income: $0 TO $29,999136.572.9204.5 $30,000 TO $49,999178.7229.2399.0 $50,000 TO $79,9995930.14920.410824.8 $80,000 OR Greater10754.6 16267.5 26961.7

11. Constructs from Figure 1ConstructMeasure Biological RiskDemographicsGender Internalizing and Externalizing Problems Psychopathology/Delinquent Activity/ Temperament/Personality Child Behavior Checklist (CBC) Alcohol, Substance & Tobacco UseCanadian Community Health Survey (CCHS) CognitiveIntelligenceWechsler Abbreviated Scale of Intelligence (WASI) Family Environment Abuse ExperiencesChildhood Trauma Questionnaire (CTQ) General Functioning/Family SupportFamily Environment Scale Extra-Familial Environment Social SupportLubben Social Network Scale (LSNS) ReligiosityRohrbaugh Jessor Religiosity Scale (RJRS) CultureYork Ethnicity Scale Social OrganizationBuckner Neighborhood Cohesion Scale (2 questions ) Stressors/Life Events Life EventsLife Events Questionnaire Physical HealthSF-10 Health Survey Gambling InvolvementFrequency, Expenditure, Type, Range, Context, Motivation, & Knowledge Canadian Problem Gambling Index (CPGI) AttitudeGambling Attitude Questionnaire Gambling DisordersProblem GamblingFisher DSM-IV-MR-J

13. nMean $ Spent Lottery & Raffle Tickets 1206.25 Instant Win Tickets 254.64 VLTs & Casinos 66.06 Private Games 9410.84 Sport Betting 417.71 Other [Bingo, Horse Racing, High Risk Stocks ] 18 62.22 n% Never Gambled or Not in Last 12 Months23754.4 Gambled in Last 12 Months19945.6 Non-Gambler or Non Problem Gambler33376.4 Low Risk Gambler7216.6 Moderate Risk / Problem Gambler317.0

14.  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

15.  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

16. Male Adolescent Correlations Female Adolescent Correlations Total Correlations Drug Use.26**.11.17** Alcohol Consumption.26**.18**.22** CBC: Somatic.16*.14*.12** Thought.10.20**.15* Attention.02.19**.11* Rule Breaking.24**.15*.21** Aggressive.14*.07.11* Contact Friends.18**.00.10* Anxious.09.14*.08 Religiosity -.03 -.05 FES: Conflict.29**.10.19** Active/Recreational.23**.08.14** Moral Religious -.14* -.15** Age.28**.02.15** Gender -.11* Location.16*.18**.16** Household Income.15*.07.12** Employment.06.08 Peer Gambling.32**.30**.31** Sibling Gambling -.09.09.01 WASI IQ Score.00.17**.09* **. Correlation is significant at the 0.01 level (2-tailed) *. Correlation is significant at the 0.05 level (2-tailed)

17. Male Adolescents Female Adolescents Adjusted Odds Ratio (OR) (95% Confidence Intervals) Non-Gambler (N = 95) Gambler (N = 108) Non-Gambler (N = 143) Gambler (N = 91) Male OR p-value Female OR p-value Religiosity11.9911.3413.6813.051.08 (0.98,1.18).0551.09 (0.97,1.21).013 FES - Conflict2.113.472.513.111.27 (1.01,1.61).003 Active5.756.716.336.641.52 (1.15,2.02).0001.22 (0.90,1.57).043 Moral4.783.964.864.24.78 (0.61,1.00).020.78 (0.57,1.04).005 Peer Gambling2.249.931.194.181.05 (1.01,1.10).010 Age13.7414.2113.8913.971.53 (0.89,2.62).051 Drug Use.02%.15%.09%.16&.18 (0.03,1.19).044

18. Male Adolescents Female Adolescents Adjusted Odds Ratio (OR) (95% Confidence Intervals) Non- Gambler (N = 95) Gambler (N = 108) Non-Gambler (N = 143) Gambler (N = 91) Male OR p- value Female OR p- value CBC – Attention 4.204.323.824.791.26 (0.94,1.64).012 Thought3.544.273.615.491.22 (0.98,1.41).006 Rule Break3.094.532.813.951.20 (0.93,1.49).036 Aggressive6.227.986.287.790.87 (0.75,1.03).040 Religiosity11.9911.3413.6813.051.08 (0.98,1.18).0551.09 (0.97,1.21).013 FES – Active5.756.716.336.641.52 (1.15,2.02).0001.22 (0.90,1.57).043 Moral4.783.964.864.24.78 (0.61,1.00).020.78 (0.57,1.04).005 Location89.9%95.9%93.2%99.7%0.04 (0.01, 0.15).088 Household Income * 100341115099930351183411.00 (1.00,1.00).029 WASI IQ Score107.70107.74104.48107.821.04 (0.99,1.08).014 * Household Income in Thousands, rounded to the nearest dollar

20.  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

21.  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

22.  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?

23.  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

24.  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

25. 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)

27.  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

28.  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

29.  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%

30.  Differences for males and females  Pattern of relationship with predictor variables was different  Logistic regressions were separate for males and females

31. Constructs from Figure 1ConstructMeasure Internalizing and Externalizing Problems Individual Risk TakingRisk Taking Family Environment Parental MonitoringParental Monitoring (Adolescent & Parent) Extra-Familial Environment Social SupportLoneliness and Social Dissatisfaction Scale (16 items) Stressors/Life Events CopingCoping Inventory for Stressful Situations (CISS) Physical Health – Eating Disorders Eating Disorder Examination Questionnaire (EDE-Q 6.0) Physical and Mental HealthWellness Index

32.  Difficulty to recruit using 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

33.  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