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A data-driven method for identifying shorter symptom criteria sets: the case for DSM-5 alcohol use disorder

Published online by Cambridge University Press:  27 June 2018

Cheryl D. Raffo ,
Deborah S. Hasin ,
Paul Appelbaum  and
Melanie M. Wall
Cheryl D. Raffo
Affiliation:
Department of Biostatistics, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
Deborah S. Hasin
Affiliation:
Department of Psychiatry, College of Physicians and Surgeons, Columbia University Medical Center, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
Paul Appelbaum
Affiliation:
Department of Psychiatry, College of Physicians and Surgeons, Columbia University Medical Center, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA
Melanie M. Wall*
Affiliation:
Department of Biostatistics, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA Department of Psychiatry, College of Physicians and Surgeons, Columbia University Medical Center, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA
*
Author for correspondence: Melanie Wall, E-mail: mmwall@columbia.edu
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Abstract

Background

Although the DSM is a widely used diagnostic guide, lengthy criteria sets can be problematic and provide the primary motivation to identify short-forms. Using the 11 diagnostic criteria provided by the DSM-5 for alcohol use disorder (AUD), the present study develops a data-driven method to systematically identify subsets and associated cut-offs that yield diagnoses as similar as possible to use all 11 criteria.

Method

Relying on data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-III), our methodology identifies diagnostic short-forms for AUD by: (1) maximizing the association between the sum scores of all 11 criteria with newly constructed subscales from subsets of criteria; (2) optimizing the similarity of AUD prevalence between the current DSM-5 rule and newly constructed diagnostic short-forms; (3) maximizing sensitivity and specificity of the short-forms against the current DSM-5 rule; and (4) minimizing differences in the accuracy of the short-form across chosen covariates. Replication is shown using NESARC-Wave 2.

Results

More than 11 000 diagnostic short-forms for DSM-5 AUD can be created and our method narrows down the optimal choices to eight. Results found that ‘Neglecting major roles’ and ‘Activities given up’ could be dropped with practically no change in who is diagnosed (specificity = 100%, sensitivity ⩾ 99.6%) or the severity of those diagnosed (κ = 0.97).

Conclusions

With a continuous improvement model adopted by the APA for DSM revisions, we offer a data-driven tool (a SAS Macro) that identifies diagnostic short-forms in a systematic and reproducible way to help advance potential improvements in future DSM revisions.

Keywords

Alcohol use disorderDSM-5SAS Macroshort-forms
Type
Original Articles
Information
Psychological Medicine , Volume 49 , Issue 6 , April 2019 , pp. 931 - 939
Copyright
Copyright © Cambridge University Press 2018 

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