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Meta-analysis of DSM alcohol use disorder criteria severities: structural consistency is only ‘skin deep’

Published online by Cambridge University Press:  28 March 2016

S. P. Lane*
Affiliation:
University of Missouri and the Midwest Alcoholism Research Center, Columbia, MO, USA
D. Steinley
Affiliation:
University of Missouri and the Midwest Alcoholism Research Center, Columbia, MO, USA
K. J. Sher
Affiliation:
University of Missouri and the Midwest Alcoholism Research Center, Columbia, MO, USA
*
*Address for correspondence: S. P. Lane, Ph.D., Department of Psychological Sciences, Psychology Building, 200 South Seventh Street, Columbia, MO 65211, USA. (Email: [email protected])

Abstract

Background

Item response theory (IRT) analyses of alcohol use disorder (AUD) and other psychological disorders are a predominant method for assessing overall and individual criterion severity for psychiatric diagnosis. However, no investigation has established the consistency of the relative criteria severities across different samples.

Method

PubMed/Medline, PsycINFO, Web of Science and ProQuest databases were queried for entries relating to alcohol use and IRT. Study data were extracted using a standardized data entry sheet. Consistency of reported criteria severities across studies was analysed using generalizability theory to estimate generalized intraclass correlations (ICCs).

Results

A total of 451 citations were screened and 34 papers (30 unique samples) included in the research synthesis. The AUD criteria set exhibited low consistency in the ordering of criteria using both traditional [ICC = 0.16, 95% confidence interval (CI) 0.06–0.56] and generalized (ICC = 0.18, 95% CI 0.15–0.21) approaches. These results were partially accounted for by previously studied factors such as age and type of sample (e.g. clinical v. community), but the largest source of unreliability was the diagnostic instrument employed.

Conclusions

Despite the robust finding of unidimensional structure of AUDs, inconsistency in the relative severities across studies suggests low replicability, challenging the generalizability of findings from any given study. Explicit modeling of well-studied factors like age and sample type is essential and increases the generalizability of findings. Moreover, while the development of structured diagnostic interviews is considered a landmark contribution toward improving psychiatric research, variability across instruments has not been fully appreciated and is substantial.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2016 

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