Magdalena Harrington1, Wayne F Velicer2, Susan Ramsey3. 1. Cancer Prevention Research Center, University of Rhode Island, United States. 2. Cancer Prevention Research Center, University of Rhode Island, United States. Electronic address: Velicer@uri.edu. 3. The Warren Alpert Medical School, Brown University, United States; Rhode Island Hospital, United States.
Abstract
OBJECTIVE: Worldwide, alcohol is the most commonly used psychoactive substance. However, heterogeneity among alcohol users has been widely recognized. This paper presents a typology of alcohol users based on an implementation of idiographic methodology to examine longitudinal daily and cyclic (weekly) patterns of alcohol use at the individual level. METHOD: A secondary data analysis was performed on the pre-intervention data from a large randomized control trial. A time series analysis was performed at the individual level, and a dynamic cluster analysis was employed to identify homogenous longitudinal patterns of drinking behavior at the group level. The analysis employed 180 daily observations of alcohol use in a sample of 177 alcohol users. RESULTS: The first order autocorrelations ranged from -.76 to .72, and seventh order autocorrelations ranged from -.27 to .79. Eight distinct profiles of alcohol users were identified, each characterized by a unique configuration of first and seventh autoregressive terms and longitudinal trajectories of alcohol use. External validity of the profiles confirmed the theoretical relevance of different patterns of alcohol use. Significant differences among the eight subtypes were found on gender, marital status, frequency of drug use, lifetime alcohol dependence, family history of alcohol use and the Short Index of Problems. CONCLUSIONS: Our findings demonstrate that individuals can have very different temporal patterns of drinking behavior. The daily and cyclic patterns of alcohol use may be important for designing tailored interventions for problem drinkers.
OBJECTIVE: Worldwide, alcohol is the most commonly used psychoactive substance. However, heterogeneity among alcohol users has been widely recognized. This paper presents a typology of alcohol users based on an implementation of idiographic methodology to examine longitudinal daily and cyclic (weekly) patterns of alcohol use at the individual level. METHOD: A secondary data analysis was performed on the pre-intervention data from a large randomized control trial. A time series analysis was performed at the individual level, and a dynamic cluster analysis was employed to identify homogenous longitudinal patterns of drinking behavior at the group level. The analysis employed 180 daily observations of alcohol use in a sample of 177 alcohol users. RESULTS: The first order autocorrelations ranged from -.76 to .72, and seventh order autocorrelations ranged from -.27 to .79. Eight distinct profiles of alcohol users were identified, each characterized by a unique configuration of first and seventh autoregressive terms and longitudinal trajectories of alcohol use. External validity of the profiles confirmed the theoretical relevance of different patterns of alcohol use. Significant differences among the eight subtypes were found on gender, marital status, frequency of drug use, lifetime alcohol dependence, family history of alcohol use and the Short Index of Problems. CONCLUSIONS: Our findings demonstrate that individuals can have very different temporal patterns of drinking behavior. The daily and cyclic patterns of alcohol use may be important for designing tailored interventions for problem drinkers.
Authors: Debasish Basu; Samuel A Ball; Richard Feinn; Joel Gelernter; Henry R Kranzler Journal: Drug Alcohol Depend Date: 2004-03-08 Impact factor: 4.492
Authors: Kyran P Quinlan; Robert D Brewer; Paul Siegel; David A Sleet; Ali H Mokdad; Ruth A Shults; Nicole Flowers Journal: Am J Prev Med Date: 2005-05 Impact factor: 5.043
Authors: Terhi Aalto-Setälä; Mauri Marttunen; Annamari Tuulio-Henriksson; Kari Poikolainen; Jouko Lönnqvist Journal: Am J Psychiatry Date: 2002-07 Impact factor: 18.112
Authors: Lisa L Harlow; Leona Aiken; A Nayena Blankson; Gwyneth M Boodoo; Leslie Ann D Brick; Linda M Collins; Geoff Cumming; Joseph L Fava; Matthew S Goodwin; Bettina B Hoeppner; David P MacKinnon; Peter C M Molenaar; Joseph Lee Rodgers; Joseph S Rossi; Allie Scott; James H Steiger; Stephen G West Journal: Multivariate Behav Res Date: 2020-02-20 Impact factor: 5.923
Authors: Patricia Gómez; Lucía Moure-Rodríguez; Eduardo López-Caneda; Antonio Rial; Fernando Cadaveira; Francisco Caamaño-Isorna Journal: Front Psychol Date: 2017-05-15