1. Utility of Collateral Informants to Inform Treatment for Gambling Disorder Megan M. Petra, MSW Renee M. Cunningham-Williams, PhD

2. 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

3. 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

4. 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

5. 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

6. 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 )

7. 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 )

8. Methods: Concordance Cohen’s kappa (κ) & Interclass Correlation Coefficient (ICC) Κ & ICC interpretation 8 : –Fair (0-.2) –Poor (.2-.4) –Moderate (.4-.6) –Substantial (.6-.8) –Almost perfect (.8-1.0) Comparisons made via Fisher’s Z transformation

9. 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

10. Results: Overall Concordance

11. Concordance and Gambler-CI Relationship

12. Concordance and Gambler Personality Disorder

13. Concordance and Gambler Depression

14. Concordance and Gambler Substance Use Disorders

15. 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

16. Conclusions CIs are a valuable source of information which treatment providers can use to inform diagnosis of Gambling Disorder, and treatment decisions

17. 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/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.

18. Acknowledgements NIDA grants: T32DA07313 (Megan M. Petra, Fellow; Renee M. Cunningham-Williams, Director), K01DA00430 (RCW), R01 DA015032 (RCW) Author contact: mpetra@wustl.edu