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Background: Chronic, heavy alcohol use is associated with multiple health problems, including premature death. Further, the clinical presentation of alcohol dependence may differentially affect and predict the long-term health consequences of affected individuals. Subtypes of alcohol dependence based upon treatment intake information can help identify homogenous groups of patients for treatment purposes, but have not been used to predict long-term outcomes. The current study examined mortality in a 36-year posttreatment interval among 4 subtypes of alcohol-dependent patients based upon their initial intake data., Methods: Extensive baseline data were collected from n = 316 male and female patients receiving inpatient treatment for alcohol dependence between 1980 and 1982. Four alcohol dependent subtypes (Del Boca & Hesselbrock, Alcohol Health Res World, 20:56, 1996) derived from the baseline data were used to examine the 1-year posttreatment drinking status and the risk of death 36 years postdischarge. Public records were used to determine patient deaths in the 36 years since discharge., Results: At the 36-year follow-up interval since discharge, 68.4% of the sample had died. The 4 subtypes were found to be associated with different rates of resumption of regular drinking in the first year posttreatment and a differential risk of mortality. An increased risk for returning to regular drinking (once a week or more) and early death were associated with subtypes defined, in part, by conduct problems and externalizing disorders. Regardless of subtype membership, women had the highest risk of death following treatment., Conclusions: This study demonstrates the clinical usefulness of subtypes of alcohol dependence for examining different alcohol use outcomes, including predicting mortality. The increased risks for returning to regular drinking once a week or more and early death posttreatment among subtypes associated with conduct problems and externalizing disorders suggest the need for continued monitoring and possible additional intervention postdischarge., (© 2020 Research Society on Alcoholism.)

In previous research using timeline follow-back methods to closely monitor drinking and related variables over the first year of college (9 months), we showed that drinking varied considerably over time in accord with academic requirements and holidays. In a new community sample (N = 576) of emerging adults (18- and 19-year-olds who reported having begun drinking prior to recruitment), we used similar methods to compare drinking patterns in college and noncollege individuals over a full calendar year (including summer). To reduce the extreme distortion in computations of average drinking over restricted time spans (i.e., 1 week) that arise because large numbers of even regular drinkers may not consume any alcohol, we analyzed data using recently developed two-part latent growth curve modeling. This modeling distinguished consumption levels from numbers of individuals drinking in a given period. Results showed that drinking levels and patterns generally did not differ between college and noncollege drinkers, and that both groups responded similarly to even those contexts that may have seemed unique to one (i.e., spring break). We also showed that computation of drinking amounts without accounting for "zero drinkers" could seriously distort estimates of mean drinking on some occasions; for example, mean consumption in the total sample appeared to increase on Thanksgiving, whereas actual average consumption for those who were drinking diminished.

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. [ABSTRACT FROM AUTHOR]

Surveys have documented excessive drinking among college students and tracked annual changes in consumption over time. This study extended previous work by examining drinking changes during the freshman year, using latent growth curve (LGC) analysis to model individual change, and relating risk factors for heavy drinking to growth factors in the model. Retrospective monthly assessments of daily drinking were used to generate weekly estimates. Drinking varied considerably by week, apparently as a function of academic requirements and holidays. A 4-factor LGC model adequately fit the data. In univariate analyses, gender, race/ethnicity, alcohol expectancies, sensation seeking, residence, and data completeness predicted growth factors (ps < .05); gender, expectancies, residence, and data completeness remained significant when covariates were tested simultaneously. Substantive, methodological, and policy implications are discussed. [ABSTRACT FROM AUTHOR]

Discusses the validity of self-report inventories of alcohol consumption, factors that influence response accuracy, relative merits of different self-report approaches, and the utility of using alternative measures to confirm verbal reports. Interaction of social context factors, respondent characteristics, and task attributes; Use of biochemical markers and collateral informant reports to confirm self-reports.

Presents an overview of research and theory on gender in relation to alcoholism subtyping. Questions addressed on the study; Distinctions among alcoholics; Implications of alcoholism for etiology; Suggestions for alcoholism treatment; Limitations of the study.

Examines the Youth Evaluation Services (Y.E.S.) program for early identification, referral, and treatment of adolescent abusers of alcohol and other drugs. Dramatic increase in the number of adolescents with behavioral and psychological disorders; Toward a new concept of adolescent treatment services; Screening and recruitment; Treatment planning; Case management procedures; Program monitoring; Obstacles encountered during early phases of Y.E.S.