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

Utility of Collateral Informants to Inform Treatment for Gambling

Disorder

Megan M. Petra, MSW

Renee M. Cunningham-Williams, PhD

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

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

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

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

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)

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)

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

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

Results: Overall Concordance

Concordance and Gambler-CI Relationship

Concordance and Gambler Personality Disorder

Concordance and Gambler Depression

Concordance and Gambler Substance Use Disorders

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

Conclusions

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

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.

Acknowledgements

• NIDA grants: T32DA07313 (Megan M. Petra, Fellow; Renee M. Cunningham-Williams, Director), K01DA00430 (RCW), R01 DA015032 (RCW)

• Author contact: [email protected]