Kelly Government Services Inc.

Bethesda, MD, United States

Kelly Government Services Inc.

Bethesda, MD, United States
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Dawson D.A.,U.S. National Institutes of Health | Dawson D.A.,Kelly Government Services Inc. | Smith S.M.,U.S. National Institutes of Health | Saha T.D.,U.S. National Institutes of Health | And 2 more authors.
Drug and Alcohol Dependence | Year: 2012

Objective: Under the proposed DSM-5 revision to the criteria for alcohol use disorder (AUD), a substantial proportion of DSM-IV AUD cases will be lost or shifted in terms of severity, with some new cases added. Accordingly, the performance of the AUDIT-C in screening for DSM-IV AUD cannot be assumed to extend to DSM-5 AUD. The objective of this paper is to compare the AUDIT-C in screening for DSM-IV and DSM-5 AUD. Methods: Using a broad range of performance metrics, the AUDIT-C was tested and contrasted as a screener for DSM-IV AUD (any AUD, abuse and dependence) and DSM-5 AUD (any AUD, moderate AUD and severe AUD) in a representative sample of U.S. adults aged 21 and older and among past-year drinkers. Results: Optimal AUDIT-C cutpoints were identical for DSM-IV and DSM-5 AUD: ≥4 for any AUD, ≥3 or ≥4 for abuse/moderate AUD and ≥4 or ≥5 for dependence/severe AUD. Screening performance was slightly better for DSM-5 severe AUD than DSM-IV dependence but did not differ for other diagnoses. At optimal screening cutpoints, positive predictive values were slightly higher for DSM-5 overall AUD and moderate AUD than for their DSM-IV counterparts. Sensitivities were slightly higher for DSM-5 severe AUD than DSM-IV dependence. Optimal screening cutpoints shifted upwards for past-year drinkers but continued to be identical for DSM-IV and DSM-5 disorders. Conclusions: Clinicians should not face any major overhaul of their current screening procedures as a result of the DSM-5 revision and should benefit from fewer false positive screening results. © 2012.


Rubinsky A.D.,Veterans Affairs Puget Sound Health Care System | Rubinsky A.D.,University of Washington | Dawson D.A.,U.S. National Institutes of Health | Dawson D.A.,Kelly Government Services Inc. | And 7 more authors.
Alcoholism: Clinical and Experimental Research | Year: 2013

Background: Brief alcohol screening questionnaires are increasingly used to identify alcohol misuse in routine care, but clinicians also need to assess the level of consumption and the severity of misuse so that appropriate intervention can be offered. Information provided by a patient's alcohol screening score might provide a practical tool for assessing the level of consumption and severity of misuse. Methods: This post hoc analysis of data from the 2001 to 2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) included 26,546 U.S. adults who reported drinking in the past year and answered additional questions about their consumption, including Alcohol Use Disorders Identification Test-Consumption questionnaire (AUDIT-C) alcohol screening. Linear or logistic regression models and postestimation methods were used to estimate mean daily drinking, the number of endorsed alcohol use disorder (AUD) criteria ("AUD severity"), and the probability of alcohol dependence associated with each individual AUDIT-C score (1 to 12), after testing for effect modification by gender and age. Results: Among eligible past-year drinkers, mean daily drinking, AUD severity, and the probability of alcohol dependence increased exponentially across increasing AUDIT-C scores. Mean daily drinking ranged from < 0.1 to 18.0 drinks/d, AUD severity ranged from < 0.1 to 5.1 endorsed AUD criteria, and probability of alcohol dependence ranged from < 1 to 65% across scores 1 to 12. AUD severity increased more steeply across AUDIT-C scores among women than men. Both AUD severity and mean daily drinking increased more steeply across AUDIT-C scores among younger versus older age groups. Conclusions: Results of this study could be used to estimate patient-specific consumption and severity based on age, gender, and alcohol screening score. This information could be integrated into electronic decision support systems to help providers estimate and provide feedback about patient-specific risks and identify those patients most likely to benefit from further diagnostic assessment. © 2013 by the Research Society on Alcoholism.

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