Evaluation of the continuum of gambling problems using the DSM-IV

Addiction

Volumn 102, Issue 5, 2007, Pages 713-721

  Strong, David R ^a,b   Kahler, Christopher W ^c  

^a BUTLER HOSPITAL   (United States)

^b BROWN UNIVERSITY   (United States)

^c BROWN UNIVERSITY   (United States)

Author keywords

DSM IV; Gambling; Item response theory; Pathological gambling; Rasch

Indexed keywords

ADULT; AGE DISTRIBUTION; ARTICLE; CONTROLLED STUDY; DIAGNOSTIC AND STATISTICAL MANUAL OF MENTAL DISORDERS; DISEASE SEVERITY; FEMALE; HEALTH SURVEY; HUMAN; INTERVIEW; MALE; PATHOLOGICAL GAMBLING; POPULATION RESEARCH; QUESTIONNAIRE; RELIABILITY; SAMPLE SIZE; SEX DIFFERENCE; SYMPTOM; UNITED STATES;

ADOLESCENT; ADULT; CROSS-SECTIONAL STUDIES; DIAGNOSTIC AND STATISTICAL MANUAL OF MENTAL DISORDERS; FEMALE; GAMBLING; HUMANS; MALE; MIDDLE AGED; REPRODUCIBILITY OF RESULTS; SEVERITY OF ILLNESS INDEX; UNITED STATES;

EID: 34247390476     PISSN: 09652140     EISSN: 13600443     Source Type: Journal    
DOI: 10.1111/j.1360-0443.2007.01789.x     Document Type: Article

References (28)

1. American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders: Text Revision. Arlington, VA : American Psychiatric Publishing 2000.
2. Blaszczynski A., McConaghy N. Anxiety and/or depression in the pathogenesis of addictive gambling. Int J Addict 1989 24 : 337 50.
3. Blaszczynski A., Nower L. A pathways model of problem and pathological gambling. Addiction 2002 97 : 487 99.
4. National Research Council Pathological Gambling: a critical review. Washington, DC : National Academy Press 1999.
5. Orford J. The fascination of psychometrics: commentary on Gerstein et al. (2003). Addiction 2003 98 : 1675 9.
6. Shaffer H. J., Hall M. N. Estimating the prevalence of adolescent gambling: a quantitative synthesis and guide toward standard gambling nomenclature. J Gambling Stud 1996 12 : 193 214.
7. Slutske W. S., Eisen S., True W. R., Lyons M. J., Goldberg J., Tsuang M. Common genetic vulnerability for pathological gambling and alcohol dependence in men. Arch Gen Psychiatry 2000 57 : 666 73.
8. Toce-Gerstein M., Gerstein D. R., Volberg R. A. A hierarchy of gambling disorders in the community. Addiction 2003 98 : 1661 72.
9. Orford J., Sproston K., Erens B. SOGS and DSM-IV in the British gambling prevalence survey: reliability and factor structure. Int Gambling Stud 2003 3 : 53 65.
10. Petry N. M., Stinson F. S., Grant B. F. Comorbidity of DSM-IV pathological gambling and other psychiatric disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiatry 2005 66 : 564 74.
11. Holland P. W., Wainer H. Differential Item Functioning. Hillsdale, NJ : Erlbaum 1993.
12. Lord F. Applications of Item Response Theory to Practical Testing Problems. Hillsdale, NJ : Erlbaum 1980.
13. Birnbaum A. Some latent trait models and their use in inferring an examinee's ability. In : Novick F. M., editor. Statistical Theories on Mental Test Scores. Reading, PA : Addison-Wesley 1968, pp. 397 479.
14. Rasch G. Probabilistic Models for Some Intelligence and Attainment Tests. Copenhagen : Danish Institute for Educational Research 1960.
15. Guttman L. The basis for scalogram analysis. In : Stouffer S. A., editor. Measurement and Prediction. New York : Wiley 1950, pp. 60 90.
16. Grant B. F., Moore T. C., Shepard J. Source and Accuracy Statement: Wave 1. National Epidemiological Survey on Alcohol and Related Conditions (NESARC). Bethesda, MD : National Institute on Alcohol Abuse and Alcoholism 2003.
17. Grant B. F., Stinson F. S., Dawson D. A., Chou S. P., Dufour M. C., Compton W. et al. Prevalence and co-occurrence of substance use disorders and independent mood and anxiety disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatry 2004 61 : 807 16.
18. Stinchfield R. Reliability, validity, and classification accuracy of a measure of DSM-IV diagnostic criteria for pathological gambling. Am J Psychiatry 2003 160 : 180 2.
19. Smith R. M., Miao C. Y. Assessing unidimensionality for Rasch measurement. In : Wilson M., editor. Objective Measurement:Theory Into Practice. Norwood, NJ : Ablex 1994, pp. 316 27.
20. Linacre J. M. Detecting multidimensionality: which residual data-type works best? J Outcome Measure 1998 3 : 103 22.
21. Wright B. D., Masters G. N. Rating scale analysis. Chicago : MESA Press 1982.
22. Bond T., Fox C. Applying the Rasch model: Fundamental measurement in the human sciences. Mahway, NJ : Erlbaum 2001.
23. Andrich D. Rasch Models for Measurement. Newbury Park, CA : Sage 1988.
24. Schulz E. M. DIF detection: Rasch versus Mantel-Haenszel. Rasch Measure Transact 1990 4 : 107.
25. Linacre J. M., Wright B. D. A Users Guide to BIGSTEPS: Rasch model computer programs. Chicago, IL : MESA Press 1997.
26. Wright B. D. Separation, reliability and skewed distributions. Rasch Measurement Transactions 2001 14 : 786.
27. Strong D. R., Lesieur H. R., Breen R. B., Stinchfield R., Lejuez C. W. Using a Rasch model to examine the utility of the South Oaks Gambling Screen across clinical and community samples. Addict Behav 2004 29 : 465 81.
28. Gerstein D., Murphy S., Toce M., Hoffmann J., Palmer A., Johnson R. et al. Gambling Impact and Behavior Study. Report to the National Gambling Impact Study Commission. Chicago, IL : National Opinion Research Center 1999.