Faculty Articles

Assessing Drinking Outcomes in Alcohol Treatment Efficacy Studies: Selecting a Yardstick of Success

Document Type

Article

Publication Title

Alcoholism: Clinical and Experimental Research

ISSN

0145-6008

Publication Date

10-2003

Abstract

Background: Although the number of alcohol treatment efficacy trials has mushroomed, there is no consensus on how best to measure outcomes. To advance the goal of establishing cross-trial consistency in measuring outcomes in clinical efficacy studies, the National Institute on Alcohol Abuse and Alcoholism convened a panel of experts and charged them with exploring, debating, and, ultimately, selecting a “sentinel” or “optimal” outcome measure to be used in future alcohol treatment studies. The goal of this article, one in a series of several presented at the National Institute on Alcohol Abuse and Alcoholism conference, is to discuss (1) the rationale underlying selection of an optimal outcome measure, (2) the necessary characteristics of an optimal outcome measure, (3) the utility of selecting an optimal measure, and (4) which drinking assessment methods could be used to collect data to portray the optimal outcome measure.

Methods: At a minimum, the criteria for an “optimal” measure include that it be psychometrically sound. In addition, it should have considerable currency in the field, thereby increasing its prospects for adoption. The measure should also be consistent with the concepts of greatest interest and relevance to the field (e.g., directly reflect the fundamental goal of alcohol treatment). In light of these highly desired features, percent of days heavy drinking was chosen at the conference as a practical and relevant measure of alcohol treatment outcome.

Conclusions: Percent of days heavy drinking should be the optimal measure of alcohol treatment outcome. Currently, daily drinking estimation methods are the most useful for gathering data that can reflect the optimal measure. In addition, data gathered by daily drinking estimation methods can be used to study a variety of other outcome variables of interest to clinical researchers.

DOI

10.1097/01.ALC.0000091227.26627.75

Volume

27

Issue

10

First Page

1661

Last Page

1666

Peer Reviewed

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