Ethnic & Gender Differences in Youth Problem Gambling

1. Ethnic & Gender Differences in Youth Problem Gambling Lera Joyce Johnson, Ph.D. Centenary College of Louisiana James R. Westphal, M.D. Louisiana State University Health Science Center Shreveport LA Paper presented at “Innovation 2001” Conference hosted by the Canadian Foundation on Compulsive Gambling, Toronto, Ontario, April 22-25, 2001

2. Gender Differences in Health Behaviors • Males have earlier and higher mortality rates • Males use substances (tobacco, alcohol, street drugs) more than females • Females use more health services, medications & mental health services than males • Males have more substance use disorders except for prescribed medications • Females have more psychiatric disorders especially in the anxiety/depression cluster. • Males have traditionally outnumbered females in gambling disorders by a 6 to 1 margin. Johnson & Westphal 2001

3. Early Identification of Problem Gamblers Among Adolescents • Adults with gambling problems typically show early onset of gambling activities • Early identification of potential problem gambling indicators during adolescence could foster timely interventions • There are minimal studies on the interaction of gender and ethnicity in adolescent gamblers Johnson & Westphal 2001

4. Early Indicators Among Adults with Gambling Problems • Robins & Przybeck (1985) conducted a large scale study of adults in New Haven, Baltimore & St. Louis. They found that if drug use began before the age of 15, the user was at greater risk for a drug disorder, & that drug disorders were associated with other psychiatric disorders. Subsequently, research attention has been directed at adolescents. • Research has shown that many adult pathological gamblers began their careers during adolescence (Ladouceur, 1991; Ide-Smith & Lea, 1988; Ladouceur & Mirault, 1988; Lesieur & Klein, 1987; Custer, 1982; Dell, Ruzika, & Palisi, 1981). Johnson & Westphal 2001

5. Risks for Problem Gambling Among Minorities • Risks for addictive behaviors are disproportionately high among Native American (Elia & Jacobs, 1993; Jacobs, 1991) & African Americans (Jacobs, 1991). • Comparisons showed significantly higher gambling problems among Native Americans than non-Indian adults in a Northern Plains reservation ( Zitzow, 1996). • A study of close to 3,000 adolescents in 7th, 9th, & 11th grades in Ventura California found that Native American youths were exposed to more risk factors leading to substance abuse than were Asians, Blacks, Hispanics or Whites (Newcomb et al., 1987). Johnson & Westphal 2001

6. Gender Differences In Problem Gambling • The literature on gender differences in gambling is relatively sparse& focused on adults. • Women tend to gamble at fewer types of gambling activities than men (Volberg & Banks, 1984). • Adult women tend to gamble at legalized gambling activities such as bingo, while males tend to play lotteries, casino games, sports betting, and stock/commodities speculation (Downes, 1976; Kallick, Suits, Dielman, & Hybels, 1979; Lundgren et al., 1987) • Prevalence rates of women with gambling problems are increasing (Volberg, 1999; Johnson, Nora, & Bustos, 1992; McAleavy, 1995) Johnson & Westphal 2001

7. Gender Differences in Gambling Problems & Treatment • Crisp et al. (2000) noted that: • Females make up the majority of clients for health service agencies (Australian Inst. Of Health & Welfare, 1996; Cokerham, 1997) & are more than 2X as likely as males to seek treatment in their lifetime (Collier, 1982) • More males are in treatment for problem gambling (Ciarrocchi & Richardson 1989; Taber, McCormick, Russo, Adkins, & Ramirez, 1987) with 86% to 93% male clients in TX in 5 American states (Volberg, 1994), even though females are just as likely as males to experience problem gambling (Hraba & Lee, 1996; Ohtsuka, Bruton, DeLuca, & Borg, 1997), and many women may need help (Reed, 1985) Johnson & Westphal 2001

8. Females with Disordered Gambling • Females who do seek tx for gambling problems present a different profile than males. Females are: • more likely to have been victims of child abuse • more likely to have attempted suicide • more likely to have a mother who has a compulsive gambling problem • less likely to have been arrested(Ciarrocchi & Richardson, 1989). • less likely to be screened for gambling problems (Downing, 1991; Mark & Lesieur, 1992) Johnson & Westphal 2001

9. Westphal, Johnson, & Stephens, 2000 Gender Differences in Gambling Career • Females reported significantly (p < .05) shorter gambling careers 4.34 years vs. 8.3 years for males • Females reported significantly (p < .01) later onset of gambling (males=23.2; females = 31.4 yrs), later onset of weekly gambling (males = 29; females 37 yrs) (p < .01) & later onset of problem gambling (p < .05) (males = 32.5; females = 39.4 yrs). • No significant differences in gambling behavior (mostly casino and video poker). Johnson & Westphal 2001

10. Male Model May Not Generalize to Females with Gambling Problems • When women enter gambling treatment programs that are designed for the male prototype, staff may not be able to deal with gender-specific problems (Reed, 1985) • Tx programs may fit males better b/c of research on all-male samples (Brown, 1986, 1987a,b,c), use of all-male controls (Zimmerman, Meeland, & Krug, 1985), or lack of gender analyses(Mark & Lesieur, 1992) Johnson & Westphal 2001

11. Gender Differences in Gambling Tx • Crisp et al. (2000) studied 1520 cases (half male, half female) in Victoria, Australia; • Differences in presenting symptoms: • males report employment & legal matters • females report problems with physical & intrapersonal functioning • Differences in treatment outcomes: • males more likely to have cases closed & be referred to other agencies • females more likely to report resolution Johnson & Westphal 2001

12. Methodological Foundations • Gambling research has been both “gender insensitive” & overgeneralized (Eichler, 1986; c.f., Delfabbro, 2000). Findings from male-only studies may not form a sufficient basis for intervention strategies (Crisp, 1998) • Gender differences may reflect traditional gender roles, different motivations for participation, sex-role socialization, & cultural factors (Delfabbro, 2000) as well as which gaming activities are being compared • Robins & Przybeck (1985) found gender differences (males > females for drug disorders) & ethnic differences ( Blacks > ‘Whites & Other’ drug disorders), but did notanalyze ethnicity and gender together. Johnson & Westphal 2001

13. Objectives • 1. Derive a frequency index for games played by adolescents in Louisiana on a daily or weekly basis • 2. Calculate the estimated prevalence of pathological gambling among students with DSM-IV J criteria • 3. Regress on pathological classification with ethnicity & gender, separately & together Johnson & Westphal 2001

14. Method • Survey of gambling behavior including DSM IV-J criteria was administered to randomized stratified sample of grades 6-12 in 57/64 parishes, public & private schools N=11,736 & criminal justice population including: • 343 jail • 1293 prison • all juvenile offenders were ages 10 to 19 Johnson & Westphal 2001

15. Demographics for Criminal Justice Sample • (N=1636) • predominantly male (88.3%) • majority black (73.7%; Caucasian 13.4%; 4.5% Native American; 7.9% other or missing) • Age distribution: 9.2% 13 or under; 13.4% age 14; 22.4% age 15; 28.9% age 16; 16.8% age 17; 9.4% age 18 or older Johnson & Westphal 2001

16. Results Objective 1: Frequency of Participation • School & justice samples were pooled for analyses • Frequency of participation in licensed & unlicensed games were observed • Overall • By Gender only • By Ethnicity only Johnson & Westphal 2001

17. Comparison of Frequent Play at Licensed Games by Gender ***All differences significant to .001. Johnson & Westphal 2001

18. Comparison of Frequent Play at Unlicensed Games by Gender * ***All differences significant to .001. Johnson & Westphal 2001

19. Comparison of Frequency at Licensed Games by Ethnicity *** All differences significant to .001 except **Lotto at .01 Johnson & Westphal 2001

20. Comparison of Frequency at Unlicensed Games by Ethnicity ***All differences significant to .001 Johnson & Westphal 2001

21. Results: Objective 2 Estimate Prevalence of Pathological Gambling • Pathological estimates based on DSM IV-J • Observed by Gender only • Observed by Ethnicity only • Observed by Gender and Ethnicity Johnson & Westphal 2001

22. Pathology Among Adolescents Johnson & Westphal 2001

23. Gender within Pathology *** All differences significant to .001. Johnson & Westphal 2001

24. Ethnicity within Pathology *** All differences significant to .001. Johnson & Westphal 2001

25. Gender & Ethnicity Within Pathology *** ** Johnson & Westphal 2001

26. Frequency, Ethnicity & Gender • School & justice samples of adolescents were pooled • Categorical regressions were performed on estimated pathological classification (using DSM IV-J) on each game with frequency of play, ethnicity, & gender as predictors • Some sub-groups showed more frequent participation, yet frequency alone was not a significant predictor of pathology apart from gender & ethnicity Johnson & Westphal 2001

27. Layout Johnson & Westphal 2001

28. Adolescents Johnson & Westphal 2001

29. Males Johnson & Westphal 2001

30. Females Johnson & Westphal 2001

31. African American Johnson & Westphal 2001

32. Caucasian Johnson & Westphal 2001

33. Native American Johnson & Westphal 2001

34. African American Males Johnson & Westphal 2001

35. African American Females Johnson & Westphal 2001

36. Caucasian Males Johnson & Westphal 2001

37. Caucasian Females Johnson & Westphal 2001

38. Native American Males Johnson & Westphal 2001

39. Native American Females Johnson & Westphal 2001

40. Cards: Prevalence of Frequent Play Alone Does Not Predict Pathology***    Predicted Pathology        Frequent play at cards was not predictive for Native American females Johnson & Westphal 2001

41. Horse/Dog Races: Prevalence of Frequent Play Alone Does Not Predict Pathology***Significant to .001 AfrAmer & Cauc; NS for NatAmer   Predicted Pathology  Johnson & Westphal 2001

42. Dice: Prevalence of Frequent Play Alone Does Not Predict Pathology***   Predicted Pathology     Johnson & Westphal 2001

43. Riverboat Casinos: Prevalence of Frequent Play Alone Does Not Predict Pathology***Significant to .001 AfrAmer & Cauc; * .05 NatAmer    Predicted Pathology .057  Johnson & Westphal 2001

44. Slots: Prevalence of Frequent Play Alone Does Not Predict Pathology*** Predicted Pathology   Johnson & Westphal 2001

45. Bingo: Prevalence of Frequent Play Alone Does Not Predict Pathology*** Predicted Pathology   Johnson & Westphal 2001

46. Betting on Sports Teams: Prevalence of Frequent Play Alone Does Not Predict Pathology*** Predicted Pathology    Johnson & Westphal 2001

47. Scratch Lottery: Prevalence of Frequent Play Alone Does Not Predict PathologyNS for Males; Significant to .001 Females Predicted Pathology   Johnson & Westphal 2001

48. Video Poker: Prevalence of Frequent Play Alone Does Not Predict Pathology*** Predicted Pathology   Johnson & Westphal 2001

49. Lotto: Prevalence of Frequent Play Alone Does Not Predict PathologyNS for Males; *.01 for Females Predicted Pathology   Johnson & Westphal 2001

50. Coins: Prevalence of Frequent Play Alone Does Not Predict Pathology*** Predicted Pathology   Johnson & Westphal 2001