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Utility of Collateral Informants to Inform Treatment for Gambling
Disorder
Megan M. Petra, MSW
Renee M. Cunningham-Williams, PhD
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Gambling Disorder (GD)
• DSM 5 now classifies Gambling Disorder (GD) as an addictive disorder
• GD occurs in ~1-2% of the population, 1-3
• But is 6.5 times more likely in those with substance use disorders
• Thus, clinicians are likely to have patients/ clients with GD
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Screening, Diagnosis, & Treatment
• Accurate information on GD is critical 4
• But no biological “gold standard” test to verify clients’ self-reports of gambling
• Collateral informants (CIs) may be able to assist clinicians by providing information
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Collateral Informants (CIs)
• Collateral informants are family or friends of the client, who can report on their gambling behavior
• If CIs’ information is accurate (concordant), clinicians can use them to verify client self-reports
• This information will inform diagnostic and treatment decisions
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Research Objective
• Investigate concordance between gambler self-reports & CI reports
• Determine if concordance is: – Associated with gambler-CI relationship– Influenced by gamblers’ comorbid substance use
disorders (SUDs) or psychiatric disorders
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Methods
• Community-recruited adults (N=128) who had gambled at least five times in their lives nominated CIs
• Gamblers & CIs interviewed separately via phone
• Psychometric study of a computerized diagnostic interview (C-Gam © 5)
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Methods: Measures
• Gambler Measures– DSM Gambling Disorder criteria (C-Gam © 5)– DSM Substance Use Disorder criteria
(GAM-DA © 5)– DSM Depression criteria (CES-D 6)– DSM Personality disorder criteria (SCID-II 7)
• CI Measures– DSM Gambling Disorder criteria for the gambler’s
behavior (GAM-CI © 5)
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Methods: Concordance
• Cohen’s kappa (κ) & Interclass Correlation Coefficient (ICC)
• Κ & ICC interpretation8:– Fair (0-.2)– Poor (.2-.4)– Moderate (.4-.6)– Substantial (.6-.8)– Almost perfect (.8-1.0)
• Comparisons made via Fisher’s Z transformation
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Results: Participant Demographics
• Gambler sex: 46% male, 54% female• Gambler race: 76% Caucasian, 19% African-
American, 6% Other• Gambler-CI relationship: 49% family member,
51% friend
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Results: Overall Concordance
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Concordance and Gambler-CI Relationship
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Concordance and Gambler Personality Disorder
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Concordance and Gambler Depression
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Concordance and Gambler Substance Use Disorders
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Implications
• Treatment providers can be confident in using CIs to verify gambler self-reports– Concordance is likely to be moderate – substantial – Concordance is unaffected by gamblers’ comorbid
conditions
• Family members are better to use as CIs than are friends
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Conclusions
• CIs are a valuable source of information which treatment providers can use to inform diagnosis of Gambling Disorder, and treatment decisions
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References
1. Shaffer, H. J., Hall, M. N., & Vander Bilt, J. (1999). Estimating the prevalence of disordered gambling behavior in the United States and Canada: A research synthesis. American Journal of Public Health, 89(9), 1369-1376.
2. Welte, J., Barnes, G., Wieczorek, W., Tidwell, M., & Parker, J. (2001). Alcohol and gambling pathology among U.S. adults: Prevalence, demographic patterns and comorbidity. Journal of Studies on Alcohol, 62, 706-712.
3. Petry, N. M., Stinson, F. S., & Grant, B. F. (2005). Comorbidity of DSM-IV pathological gambling and other psychiatric disorders: Results from the National Epidemiologic Survey on Alcohol and Related Conditions. Journal of Clinical Psychiatry, 66(5), 564-574.
4. Westphal, J. R., & Johnson, L. J. (2003). Gender differences in psychiatric comorbidity and treatment-seeking among gamblers in treatment. Electronic Journal of Gambling Issues, 8, 79-90. Retrieved from http://www.camh.net/egambling/
5. Cunningham-Williams, RM. Computerized Gambling Assessment Module (C-GAM). St Louis, Missouri: Washington University; 2003.
6. Radloff, LS. The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement 1977;1:385–401.
7. First, MB.; Spitzer, RL.; Gibbon, M.; Williams, JBW.; Benjamin, LS. Structured clinical interview for DSM-IV personality disorders (SCID-II). Washington D. C.: American Psychiatric Press; 1997.
8. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159-174.
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Acknowledgements
• NIDA grants: T32DA07313 (Megan M. Petra, Fellow; Renee M. Cunningham-Williams, Director), K01DA00430 (RCW), R01 DA015032 (RCW)
• Author contact: [email protected]