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Journal Article

Citation

Neal DJ, Fromme K, Boca FK, Parks KA, King LP, Pardi AM, Collins RL, Muraven M, Vetter C, Corbin WR. Alcohol Clin. Exp. Res. 2006; 30(2): 282-291.

Affiliation

Department of Psychology, The University of Texas at Austin, Austin, Texas 78712-0187, USA. neal@psy.utexas.edu

Copyright

(Copyright © 2006, John Wiley and Sons)

DOI

10.1111/j.1530-0277.2006.00025.x

PMID

16441277

Abstract

This article is a summary of a symposium presented at the 2005 Research Society on Alcoholism annual conference organized by Dan J. Neal and chaired by William R. Corbin. Event-level data, wherein each "event" (e.g., day) is captured as its own data point, capture the complex patterns of drinking and other high-risk behaviors in ways that the typical aggregate approach cannot. Because of their richness, methodologies that incorporate event-level data are becoming more common in alcohol research. At least 3 distinct forms of event-level data can be gathered: retrospective data (those collected on a single occasion, using memory aids to help each participant reconstruct all drinking events over a specific period of time), daily monitoring data (reporting on all events for that day), and momentary assessment (those recorded immediately following a drinking event or in response to a prompt from researchers). The goal of this symposium was to address many issues associated with event-level methodology, as well as demonstrate projects that are currently implementing such innovative data collection. The 4 presentations included in this symposium were "Realizing the Promise and Avoiding the Pitfalls of Retrospective Daily Estimation Assessments of Alcohol Use" by Frances K. Del Boca; "Using Interactive Voice Response Technology to Assess the Alcohol-Victimization Link" by Kathleen Parks, Linda King, and Ann Pardi; "Methodological Issues in Using Personal Data Assistants to Self-monitor Alcohol Consumption" by R. Lorraine Collins, Mark Muraven, and Charlene Vetter; and "Collecting Event-level Data Using the World Wide Web" by Dan J. Neal and Kim Fromme.


Language: en

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