OBJECTIVE: The Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA) yields Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) diagnoses for a variety of psychiatric disorders, including alcohol and drug dependence. Using generalizability theory, we sought to ascertain the sources of unreliability for DSM-IV substance-dependence diagnoses and their criterion counts. METHOD: Two hundred ninety-three subjects (52.2% women) were interviewed twice over a 2-week period, and a generalizability coefficient and an index of dependability (with confidence intervals) were calculated for each dependence category. RESULTS: Overall, there were good-to-excellent reliabilities for the more common diagnoses and criterion counts, including tobacco, alcohol, cocaine, and opioid dependence. The reliabilities were not as good for marijuana dependence and the less common diagnoses of stimulant, sedative, and other drug dependence. There was greater variability between interviewers (inter-rater reliability) than occasions (test-retest reliability). However, for most diagnoses, the subject by occasion variability was larger than the subject by interviewer variability, indicative of greater consistency in the contribution by interviewers to the ordering of subjects than in the contribution by subjects themselves between the two interviews. CONCLUSIONS: These results are consistent with prior findings that the SSADDA yields reliable diagnoses and criterion counts for the more prevalent substance-dependence diagnoses. The present analysis extends these findings by showing that the greatest source of unreliability was the subjects' report. This underscores the need for efforts to increase the reliability of substance-dependence diagnoses (and by extension other self-reported phenotypic features) by enhancing the consistency of the information provided by the subjects interviewed.
OBJECTIVE: The Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA) yields Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) diagnoses for a variety of psychiatric disorders, including alcohol and drug dependence. Using generalizability theory, we sought to ascertain the sources of unreliability for DSM-IV substance-dependence diagnoses and their criterion counts. METHOD: Two hundred ninety-three subjects (52.2% women) were interviewed twice over a 2-week period, and a generalizability coefficient and an index of dependability (with confidence intervals) were calculated for each dependence category. RESULTS: Overall, there were good-to-excellent reliabilities for the more common diagnoses and criterion counts, including tobacco, alcohol, cocaine, and opioid dependence. The reliabilities were not as good for marijuana dependence and the less common diagnoses of stimulant, sedative, and other drug dependence. There was greater variability between interviewers (inter-rater reliability) than occasions (test-retest reliability). However, for most diagnoses, the subject by occasion variability was larger than the subject by interviewer variability, indicative of greater consistency in the contribution by interviewers to the ordering of subjects than in the contribution by subjects themselves between the two interviews. CONCLUSIONS: These results are consistent with prior findings that the SSADDA yields reliable diagnoses and criterion counts for the more prevalent substance-dependence diagnoses. The present analysis extends these findings by showing that the greatest source of unreliability was the subjects' report. This underscores the need for efforts to increase the reliability of substance-dependence diagnoses (and by extension other self-reported phenotypic features) by enhancing the consistency of the information provided by the subjects interviewed.
Authors: J B Williams; M Gibbon; M B First; R L Spitzer; M Davies; J Borus; M J Howes; J Kane; H G Pope; B Rounsaville Journal: Arch Gen Psychiatry Date: 1992-08
Authors: Amira Pierucci-Lagha; Joel Gelernter; Richard Feinn; Joseph F Cubells; Deborah Pearson; Alisha Pollastri; Lindsay Farrer; Henry R Kranzler Journal: Drug Alcohol Depend Date: 2005-12-12 Impact factor: 4.492
Authors: Alexandre Berney; Martin Preisig; Marie-Louise Matthey; François Ferrero; Brenda T Fenton Journal: Drug Alcohol Depend Date: 2002-01-01 Impact factor: 4.492
Authors: K K Bucholz; R Cadoret; C R Cloninger; S H Dinwiddie; V M Hesselbrock; J I Nurnberger; T Reich; I Schmidt; M A Schuckit Journal: J Stud Alcohol Date: 1994-03
Authors: Amira Pierucci-Lagha; Joel Gelernter; Grace Chan; Albert Arias; Joseph F Cubells; Lindsay Farrer; Henry R Kranzler Journal: Drug Alcohol Depend Date: 2007-06-27 Impact factor: 4.492
Authors: Geoffrey M Reed; Pratap Sharan; Tahilia J Rebello; Jared W Keeley; María Elena Medina-Mora; Oye Gureje; José Luis Ayuso-Mateos; Shigenobu Kanba; Brigitte Khoury; Cary S Kogan; Valery N Krasnov; Mario Maj; Jair de Jesus Mari; Dan J Stein; Min Zhao; Tsuyoshi Akiyama; Howard F Andrews; Elson Asevedo; Majda Cheour; Tecelli Domínguez-Martínez; Joseph El-Khoury; Andrea Fiorillo; Jean Grenier; Nitin Gupta; Lola Kola; Maya Kulygina; Itziar Leal-Leturia; Mario Luciano; Bulumko Lusu; J Nicolas; I Martínez-López; Chihiro Matsumoto; Lucky Umukoro Onofa; Sabrina Paterniti; Shivani Purnima; Rebeca Robles; Manoj K Sahu; Goodman Sibeko; Na Zhong; Michael B First; Wolfgang Gaebel; Anne M Lovell; Toshimasa Maruta; Michael C Roberts; Kathleen M Pike Journal: World Psychiatry Date: 2018-06 Impact factor: 49.548
Authors: Henry R Kranzler; Richard Feinn; Elliot C Nelson; Jonathan Covault; Raymond F Anton; Lindsay Farrer; Joel Gelernter Journal: Am J Med Genet B Neuropsychiatr Genet Date: 2011-10-13 Impact factor: 3.568
Authors: Kara Douglas; Grace Chan; Joel Gelernter; Albert J Arias; Raymond F Anton; James Poling; Lindsay Farrer; Henry R Kranzler Journal: Psychiatr Genet Date: 2011-10 Impact factor: 2.458