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Sub-typing Gamblers on the Basis of Affective Motivations for Gambling: Implications for Treatment Matching

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  1. Sub-typing Gamblers on the Basis of Affective Motivations for Gambling: Implications for Treatment Matching Dr. Sherry H. Stewart, Departments of Psychiatry & Psychology, Dalhousie University, CIHR Investigator, Killam Research Professor

  2. Funding • Ontario Problem Gambling Research Centre (OPGRC) • Nova Scotia Gaming Foundation (NSGF)

  3. Dr. Sean Barrett Dr. Joel Katz Dr. Raymond Klein Dr. David Hodgins Dr. Anne-Marie Wall Dr. Martin Zack Pamela (Loba) Collins Fofo Fragopoulos Adrienne Girling Meghan Kirsch Melissa Mohan Sarah Stuart Collaborators

  4. Background: Motivational Theories • Motivational models of addiction argue that people engage in addictive behaviors to obtain desired outcomes (e.g., Cooper, 1994) • Many such theories point to desires for mood alteration as motivating addictive behavior (e.g., Cox & Klinger, 1988) • Theories abound regarding contributions of motivations involving emotional self-regulation in etiology and maintenance of pathological gambling • Desire for tension-/dysphoria-reducing effects (e.g., Beaudoin & Cox, 1999) • Desire for euphoric consequences (e.g., Hickey et al., 1986)

  5. Background: DSM-IV-TR Criteria for Pathological Gambling A. Persistent and recurrent maladaptive gambling behavior as indicated by five (or more) of the following: (1) is preoccupied with gambling *(2) needs to gamble with increasing amounts of money in order to achieve the desired excitement (3) has repeated efforts to control, cut back, or stop gambling (4) is restless or irritable when attempting to cut down or stop gambling

  6. Background: DSM-IV-TR Criteria for Pathological Gambling *(5) gambles as a way of escaping from problems or of relieving a dysphoric mood (6) after losing money gambling, often returns another day to get even ("chasing" one's losses) (7) lies to family members, therapist, or others to conceal the extent of involvement with gambling (8) has committed illegal acts such as forgery, fraud, theft, or embezzlement to finance gambling (9) has jeopardized or lost a significant relationship, job, or educational or career opportunity because of gambling (10) relies on others to provide money to relieve a desperate financial situation caused by gambling

  7. Background: Heterogeneity • Increasing recognition of the heterogeneity of gamblers (e.g., Ferris, & Wynne, 2001) • Cluster analytic studies suggest subtypes • For example, Blaszczynski & Nower (2002) suggest three clusters: • Antisocial impulsivist gamblers • Emotionally vulnerable gamblers • Behaviorally-conditioned gamblers

  8. Previous Sub-Typing Schemes Researchers Proposed Subtypes Lesieur Impulsive Impulsive (2001) (2 of 3) Escape Seekers Action Seekers McCormick Recurrently Chronically (1987) Depressed Under-Stimulated Blaszczynski et al. Depression- Boredom- (1990) Prone Prone Blaszczynski & Nower Emotionally Antisocial (2002) (2 of 3) Vulnerable Impulsivist Grant Anxious/ Pleasure/Urge & (2007 – yesterday’s Depressed/ General Impulsivity talk) Obsessional Need for Stimulation

  9. Background: Sub-typing Substance Abusers • Our previous work in the alcohol/drug abuse area involves sub-typing substance abusers according to underlying motives for substance use (Conrod et al., 2000a) • This sub-typing predicts: • Substance use patterns/preferences • Co-morbid psychopathology • Response to “matched” interventions (Conrod et al., 2000a,b, 2006; Watt et al., 2006)

  10. Matching brief interventions to motivational profiles • Random assignment to 1 of 3 90-minute interventions: • (1) Motivation-matched cognitive-behavioral training (N=94) • (2) Motivation-mismatched cognitive-behavioral training (N=97) • (3) Film control (N=52) (Conrod, Stewart et al., 2000; Psych of Addictive Behaviors)

  11. Procedure: Follow-up • Assessment at 6-months post-treatment • Telephone interview • Interviewer blind to subtype and intervention • Several substance-related outcomes assessed

  12. Six-months Remission Rates

  13. Reduction in Dependence Symptoms

  14. Lengthy Abstinence from Alcohol

  15. Our New Proposal: • What about sub-typing gamblers according to motivations for emotional regulation? • Might be a theoretically- and clinically-useful way of understanding diversity among pathological gamblers and those at risk.

  16. Study 1: Sub-Typing Problem Gamblers Who Drink When Gambling on Affective Motives for Gambling

  17. Background: Gambling and Alcohol • High co-morbidity between pathological gambling and alcohol use disorders (Ciarrocchi, 1993; Crockford & el-Guebaly, 1998; Griffiths, 1994; Stewart & Kushner, 2003). • Theories explaining co-morbidity include: • Pathological Gambling  Alcohol Abuse (Zack et al., 2005) • Alcohol Abuse  Pathological Gambling (Ellery et al., 2005) • Common Third Variable • For example, common underlying motivations for gambling/drinking

  18. Purposes • Test the validity of a gambler subtyping scheme that classifies gamblers on their primary emotion regulation motives for gambling • Test the degree of overlap in specific motives for gambling and for drinking among problem gamblers who drink when gambling • Do those who use gambling to cope with negative emotions also use drinking for the same reason? • Do those who use gambling to enhance positive states also use alcohol for the same reason?

  19. Hypotheses • (1) At least two clusters or subtypes of pathological gamblers would emerge using gambling situations as indirect measure of motives • those gambling in response to “negative” contexts (e.g., unpleasant emotional states) – COP gamblers. • those gambling in response to “positive” contexts (e.g., pleasant emotional states) – ENH gamblers. • (2) Clusters of gamblers identified using the Inventory of Gambling Situations (indirect) would be validated using Gambling Motives Questionnaire (direct). • (3) The ENH gamblers would evidence greater gambling behavior than other cluster(s) • (4) The COP gamblers would evidence greater gambling problems than other cluster(s)

  20. Hypotheses (continued) • (5) We expected to observe associations between gambling motives and drinking motivations on the Drinking Motives Questionnaire • (6) We hypothesized that the ENH gamblers would show higher quantities of drinking, and more alcohol related problems on the Brief Michigan Alcoholism Screening Test, than other cluster(s)

  21. Method - Participants • A sample of 158 gamblers (77%M; mean (SD) age = 36.0 (10.7) years) was recruited from the community using newspaper and television advertisements. • All were probable pathological gamblers (scoring > 5 on the SOGS). • All reported consuming alcohol at least 50% of the times when they gamble. • All were 19 years of age or older

  22. Results: Hypothesis 1a Pattern Matrix from Principal Components Analysis of subscale scores from the Inventory of Gambling Situations (IGS; Turner & Littman-Sharp, 2006) following Oblique Rotation (n = 158) Factor 1 – Factor 2 – IGS Subscale Negative Situations Positive Situations Communality Unpleasant Emotions .976* -.029 .918 Worried Over Debt .945* -.072 .812 Conflict With Others .938* -.034 .840 Testing Personal Control .886* .032 .821 Winning and Chasing Losses .764* .202 .821 Pleasant Emotions -.105 .930* .751 Social Pressure -.036 .899* .768 Need for Excitement .246 .757* .872 Confidence in Skills .173 .678* .639 Urges and Temptations .603*.423* .873 Note: A two-factor solution was selected based on Kaiser’s rule. Salient loadings (> .40) are indicated with an asterisk (*).

  23. Results: H1b: Cluster Analysis • 3 cluster solution • Cluster 1 – high positive situation scores/low negative situation scores – labeled Enhancement (ENH) gamblers (n = 94) • Cluster 2 – high negative/high positive situation scores, but particularly high negative scores – labeled Coping (COP) gamblers (n = 36) • Cluster 3 – low negative/low positive situation scores – labeled Low Emotion Regulation (Low ER) gamblers (n = 28)

  24. Results: H2: Factor Scores on Gambling Motives Questionnaire (GMQ) by Subtype cluster group x subscale interaction (F (2, 151) = 3.44, p < .05)

  25. Results: H3: Number of Lifetime Gambling Activities (SOGS) by Subtype a a b cluster group effect (F (2, 155) = 19.90, p < .001)

  26. Results: H4: Gambling Problems on DSM-IV-Based Measure by Subtype b a c cluster group effect (F (2, 151) = 33.23, p < .001)

  27. Results: H5: Factor Scores on Cooper’s (1994) Drinking Motives Questionnaire (DMQ) by Subtype cluster group x subscale interaction (F (2, 151) = 7.42, p < .005)

  28. Results: H6a: Drinking Quantity (drinks per occasion) by Subtype a b a cluster group effect (F (2, 150) = 7.57, p < .005)

  29. Results: H6b: Drinking Problems by Subtype a b b cluster group effect (F (2, 147) = 13.13, p < .001)

  30. Some Remaining Questions • Do the clusters represent trait-like subtypes or stages? • Do the clusters simply reflect correlates of gambling problem severity? • Are the sub-typing findings specific to pathological gamblers who drink when gambling?

  31. Study 2: The Relationship of Gambler Subtypes to Gambling Expectancies in Regular Gamblers

  32. Background: Expectancies • Expectancies = beliefs about consequences of engaging in a specific behavior • “If-then” statements making connections between behavior and expected outcome (Goldman et al., 1999) • Distinct from motives (Birch et al., 2004) • Many domains, but two higher-order • Reward • Relief (Birch et al., 2004)

  33. Background: Expectancies • In addictions field, expectancies exert powerful influence on addictive behavior • e.g., expectancies about effects of alcohol strong determinants of heavy and problem drinking (Goldman et al., 1999) • Surprisingly, little research on expectancies in gambling area

  34. Purposes • Replicate typology of gamblers identified in Study 1, with sub-typing on the basis of gambling situations (inferred motives) • Determine if gambler subtypes differ in gambling outcome expectancies on a new mood-regulation Gambling Expectancies Questionnaire (GEQ) modeled after a similar alcohol outcome expectancies measure (Birch et al., 2004; Singleton et al., 1994) • Relief expectancies (e.g., “I would feel less irritable if I gambled now”) • Reward expectancies (e.g., “It would be great to gamble now”)

  35. Hypotheses • (1) Three clusters or subtypes of regular gamblers would emerge on basis of IGS positive and negative situation factors: • Pure enhancement gamblers (ENH) • Primarily coping gamblers (COP) • Low emotion-regulation gamblers (LOW ER) • (2) Gambler subtypes would differ in mood-regulation gambling outcome expectancies on the GEQ • Reward expectancies: ENH = COP > LOW ER • Relief expectancies: COP > ENH = LOW ER

  36. Method - Participants • A sample of 181 regular gamblers (56% M; mean age = 37.7 years) was recruited from the community using newspaper and television advertisements. • Approximately half recruited in Halifax (n=84) and the other half in Toronto (n=97) • No restrictions regarding SOGS scores or alcohol consumption; M SOGS = 3.88 (4.23)

  37. Results: Hypothesis 1a Pattern Matrix from Principal Components Analysis of subscale scores from the IGS following Oblique Rotation (n = 179) Factor 1 – Factor 2 – IGS Subscale Negative Situations Positive Situations Communality Conflict With Others .938* -.093 .789 Worried Over Debts .904* -.100 .724 Testing Personal Control .794* .130 .766 Unpleasant Emotions .786* .144 .768 Need To Be In Control .775* .141 .745 Pleasant Emotions -.201 .952* .727 Social Pressure .029 .750* .588 Need for Excitement .192 .725* .720 Confidence in Skills .205 .704* .702 Urges and Temptations .403*.580* .766 Winning and Chasing Losses .448*.500* .707 Note: A two-factor solution was selected based on Kaiser’s rule. Salient loadings (> .40) are indicated with an asterisk (*).

  38. Results: Hypothesis 1bGambling situation factor scores of the three clusters of regular gamblers

  39. Results: Hypothesis 2GEQ factor scores as a function of gambler subtype cluster group x expectancy domain interaction (F (2, 171) = 25.80, p < .001)

  40. Study 3: Validity of Sub-Typing Undergraduate Gamblers on Affective Motives for Gambling

  41. Purposes • Test the validity of a gambler subtyping scheme that classifies gamblers on their primary emotion regulation motives for gambling, as applied to undergraduate gambling behavior • Does the three subtype scheme hold in undergraduate gamblers? • Do the subtypes vary as expected on gambling behaviors and gambling problems?

  42. Method - Participants • A sample of 168 regular gamblers (58% M; mean age = 20.3 years) was recruited from the undergraduate student population • Approximately half recruited at Dalhousie University (n = 82) and the other half recruited at York University (n = 86) • No restrictions regarding gambling problems or alcohol consumption

  43. Results: Hypothesis 1a Pattern Matrix from Principal Components Analysis of subscale scores from the IGS following Oblique Rotation (n = 168 university student gamblers) Factor 1 – Factor 2 – IGS Subscale Positive Situations Negative Situations Pleasant Emotions 1.101* -.234 Social Pressure .818* .025 Confidence in Skills .796* .025 Need for Excitement .790* .146 Conflict with Others -.071 .982* Negative Emotions .044 .900* Worried about Debt -.027 .886* Testing Personal Control .241 .761* Urges and Temptations .597*.456* Winning and Chasing Losses .580*.401* Note: A two-factor solution was selected based on Kaiser’s rule. Salient loadings (> .40) are indicated with an asterisk (*).

  44. Results: H1b: Gambling Situation Factor Scores of the 3 Clusters of Gamblers 1 = COP (n=22); 2 = ENH (n=65); 3 = Low ER (n=81)

  45. Results: Percentage High Risk Gamblers (on CPGI) as a function of Subtype Cluster 1 = COP (n=22); 2 = ENH (n=65); 3 = Low ER (n=81)

  46. Study 4: Heart Rate Increase to Alcohol and VLT Play as a Function of Gambler Subtype

  47. Background: Heart Rate & Reward • Alcohol intake leads to resting heart rate increases (e.g., Conrod et al., 2001; Stewart et al., 1992) • Positively related to feeling energized in regular drinkers (Conrod et al., 2001) • Suggested marker for susceptibility to alcohol reward and reinforcement (e.g., Brunelle et al., 2003; Peterson et al., 1993)

  48. Background: Heart Rate & Reward • Heart rate increases may apply to a variety of addictive behaviours • Heart rate increases have also been seen in gamblers when gambling (e.g., Coventry & Norman, 1997; Meyer et al., 2004) • Two prior studies show heart rate increases to alcohol and gambling alone and in combination in regular gamblers (Stewart et al., 2005, 2006).