Ethnic gender differences in youth problem gambling
Download
1 / 51

Ethnic Gender Differences in - PowerPoint PPT Presentation


  • 405 Views
  • Updated On :

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

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Ethnic Gender Differences in ' - elina


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Ethnic gender differences in youth problem gambling l.jpg

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


Slide2 l.jpg

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


Early identification of problem gamblers among adolescents l.jpg
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


Early indicators among adults with gambling problems l.jpg
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


Risks for problem gambling among minorities l.jpg
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


Gender differences in problem gambling l.jpg
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


Gender differences in gambling problems treatment l.jpg
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


Females with disordered gambling l.jpg
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


Slide9 l.jpg

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


Male model may not generalize to females with gambling problems l.jpg
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


Gender differences in gambling tx l.jpg
Gender Differences in Gambling Tx Problems

  • 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


Methodological foundations l.jpg
Methodological Foundations Problems

  • 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


Objectives l.jpg
Objectives Problems

  • 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


Method l.jpg
Method Problems

  • 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


Demographics for criminal justice sample l.jpg
Demographics for Criminal Justice Sample Problems

  • (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


Results objective 1 frequency of participation l.jpg
Results Objective 1: Frequency of Participation Problems

  • 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


Comparison of frequent play at licensed games by gender l.jpg
Comparison of Frequent Play at Licensed Games by Gender Problems

***All differences significant to .001.

Johnson & Westphal 2001


Comparison of frequent play at unlicensed games by gender l.jpg
Comparison of Frequent Play at Unlicensed Games by Gender Problems

*

***All differences significant to .001.

Johnson & Westphal 2001


Comparison of frequency at licensed games by ethnicity l.jpg
Comparison of Frequency at Licensed Games by Ethnicity Problems

*** All differences significant to .001 except **Lotto at .01

Johnson & Westphal 2001


Comparison of frequency at unlicensed games by ethnicity l.jpg
Comparison of Frequency at Unlicensed Games by Ethnicity Problems

***All differences significant to .001

Johnson & Westphal 2001


Results objective 2 estimate prevalence of pathological gambling l.jpg
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


Pathology among adolescents l.jpg
Pathology Among Adolescents Gambling

Johnson & Westphal 2001


Gender within pathology l.jpg
Gender within Pathology Gambling

*** All differences significant to .001.

Johnson & Westphal 2001


Ethnicity within pathology l.jpg
Ethnicity within Pathology Gambling

*** All differences significant to .001.

Johnson & Westphal 2001


Gender ethnicity within pathology l.jpg
Gender & Ethnicity Within Pathology Gambling

***

**

Johnson & Westphal 2001


Frequency ethnicity gender l.jpg
Frequency, Ethnicity & Gender Gambling

  • 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


Layout l.jpg
Layout Gambling

Johnson & Westphal 2001


Slide28 l.jpg

Adolescents Gambling

Johnson & Westphal 2001


Slide29 l.jpg

Males Gambling

Johnson & Westphal 2001


Slide30 l.jpg

Females Gambling

Johnson & Westphal 2001


Slide31 l.jpg

African American Gambling

Johnson & Westphal 2001


Slide32 l.jpg

Caucasian Gambling

Johnson & Westphal 2001


Slide33 l.jpg

Native American Gambling

Johnson & Westphal 2001


Slide34 l.jpg

African American Males Gambling

Johnson & Westphal 2001


Slide35 l.jpg

African American Females Gambling

Johnson & Westphal 2001


Slide36 l.jpg

Caucasian Males Gambling

Johnson & Westphal 2001


Slide37 l.jpg

Caucasian Females Gambling

Johnson & Westphal 2001


Slide38 l.jpg

Native American Males Gambling

Johnson & Westphal 2001


Slide39 l.jpg

Native American Females Gambling

Johnson & Westphal 2001


Cards prevalence of frequent play alone does not predict pathology l.jpg
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


Slide41 l.jpg
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


Dice prevalence of frequent play alone does not predict pathology l.jpg
Dice: Prevalence of Frequent Play Alone Does Not Predict Pathology***

Predicted

Pathology

Johnson & Westphal 2001


Slide43 l.jpg
Riverboat Casinos: Prevalence of Frequent Play Alone Does Not Predict Pathology***Significant to .001 AfrAmer & Cauc; * .05 NatAmer

Predicted

Pathology

.057

Johnson & Westphal 2001


Slots prevalence of frequent play alone does not predict pathology l.jpg
Slots: Prevalence of Frequent Play Alone Does Not Predict Pathology***

Predicted

Pathology

Johnson & Westphal 2001


Bingo prevalence of frequent play alone does not predict pathology l.jpg
Bingo: Prevalence of Frequent Play Alone Does Not Predict Pathology***

Predicted

Pathology

Johnson & Westphal 2001


Betting on sports teams prevalence of frequent play alone does not predict pathology l.jpg
Betting on Sports Teams: Prevalence of Frequent Play Alone Does Not Predict Pathology***

Predicted

Pathology

Johnson & Westphal 2001


Slide47 l.jpg
Scratch Lottery: Prevalence of Frequent Play Alone Does Not Predict PathologyNS for Males; Significant to .001 Females

Predicted

Pathology

Johnson & Westphal 2001


Video poker prevalence of frequent play alone does not predict pathology l.jpg
Video Poker: Prevalence of Frequent Play Alone Does Not Predict Pathology***

Predicted

Pathology

Johnson & Westphal 2001


Lotto prevalence of frequent play alone does not predict pathology ns for males 01 for females l.jpg
Lotto: Prevalence of Frequent Play Alone Does Not Predict PathologyNS for Males; *.01 for Females

Predicted

Pathology

Johnson & Westphal 2001


Coins prevalence of frequent play alone does not predict pathology l.jpg
Coins: Prevalence of Frequent Play Alone Does Not Predict Pathology***

Predicted

Pathology

Johnson & Westphal 2001


Conclusions l.jpg
Conclusions Pathology***

  • 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

Johnson & Westphal 2001


ad