Ethnic

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.

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

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).

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).

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)

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)

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)

9
Westphal, Johnson, Stephens, 2000
Gender Differences in Gambling Career

• Females reported significantly (p gambling careers 4.34 years vs. 8.3 years for
  males
• Females reported significantly (p onset of gambling (males23.2 females 31.4
  yrs), later onset of weekly gambling (males 29
  females 37 yrs) (p problem gambling (p 39.4 yrs).
• No significant differences in gambling behavior
  (mostly casino and video poker).

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)

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

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 not analyze ethnicity and
  gender together.

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

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 N11,736
  criminal justice population including
• 343 jail
• 1293 prison
• all juvenile offenders were ages 10 to 19

15
Demographics for Criminal Justice Sample

• (N1636)
• 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

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

17
Comparison of Frequent Play at Licensed Games by
Gender
All differences significant to .001.
18
Comparison of Frequent Play at Unlicensed Games
by Gender

All differences significant to .001.
19
Comparison of Frequency at Licensed Games by
Ethnicity
All differences significant to .001 except
Lotto at .01
20
Comparison of Frequency at Unlicensed Games by
Ethnicity
All differences significant to .001
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

22
Pathology Among Adolescents
23
Gender within Pathology
All differences significant to .001.
24
Ethnicity within Pathology
All differences significant to .001.
25
Gender Ethnicity Within Pathology


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

27
Layout
28
Adolescents
29
Males
30
Females
31
African American
32
Caucasian
33
Native American
34
African American Males
35
African American Females
36
Caucasian Males
37
Caucasian Females
38
Native American Males
39
Native American Females
40
Cards Prevalence of Frequent Play Alone Does Not
Predict Pathology
?
?
?
Predicted Pathology
?
?
?
?
?
?
?
Frequent play at cards was not predictive for
Native American females
41
Horse/Dog Races Prevalence of Frequent Play
Alone Does Not Predict Pathology Significant
to .001 AfrAmer Cauc NS for NatAmer
?
?
Predicted Pathology
?
42
Dice Prevalence of Frequent Play Alone Does Not
Predict Pathology
?
?
Predicted Pathology
?
?
?
?
43
Riverboat Casinos Prevalence of Frequent Play
Alone Does Not Predict PathologySignificant
to .001 AfrAmer Cauc .05 NatAmer
?
?
?
Predicted Pathology
.057
?
44
Slots Prevalence of Frequent Play Alone Does Not
Predict Pathology
Predicted Pathology
?
?
45
Bingo Prevalence of Frequent Play Alone Does Not
Predict Pathology
Predicted Pathology
?
?
46
Betting on Sports Teams Prevalence of Frequent
Play Alone Does Not Predict Pathology
Predicted Pathology
?
?
?
47
Scratch Lottery Prevalence of Frequent Play
Alone Does Not Predict PathologyNS for Males
Significant to .001 Females
Predicted Pathology
?
?
48
Video Poker Prevalence of Frequent Play Alone
Does Not Predict Pathology
Predicted Pathology
?
?
49
Lotto Prevalence of Frequent Play Alone Does Not
Predict PathologyNS for Males .01 for Females
Predicted Pathology
?
?
50
Coins Prevalence of Frequent Play Alone Does Not
Predict Pathology
Predicted Pathology
?
?
51
Conclusions

• Gender ethnicity, when analyzed together,
  present a different profile for each subgroup
  than when pathology is predicted without gender
  or ethnicity, or when predicted by ethnicity or
  gender alone
• Frequency of play in any of the gambling
  activities tested ALONE did not predict pathology
  among adolescents as well as when ethnicity and
  gender were included in the analysis that is,
  frequency can only be judged when you know the
  pattern of play among genders within ethnic
  subgroups