Empirical Modeling of an Alcohol Expectancy Memory Network Using Multidimensional Scaling

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multidimensional scaling of alcohol expectancy memory network model, alcohol drinking college students & alcoholic patients

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Risk-related antecedent variables can be linked to later alcohol consumption by memory processes, and alcohol expectancies may be one relevant memory content. To advance research in this area, it would be useful to apply current memory models such as semantic network theory to explain drinking decision processes. Multidimensional scaling (MDS) was used to empirically model a preliminary alcohol expectancy semantic network, from which a theoretical account of drinking decision making was generated. Subanalyses showed how individuals with differing alcohol consumption histories may have had different association pathways within the expectancy network. These pathways may have in turn influenced future drinking levels and behaviors while the person was under the influence of alcohol. All individuals associated positive/prosocial effects with drinking, but heavier drinkers indicated arousing effects as their highest probability associates, whereas light drinkers expected sedation. An important early step in this MDS modeling process is the determination of iso-meaning expectancy adjective groups, which correspond to theoretical network nodes.

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Journal of Abnormal Psychology, v. 101, issue 1, p. 174-183