Your browser doesn't support javascript.
loading
Searching for Mr. Hyde: A Five-Factor Approach to Characterizing "Types of Drunks".
Winograd, Rachel Pearl; Steinley, Douglas; Sher, Kenneth.
  • Winograd RP; Department of Psychological Sciences, University of Missouri-Columbia, Columbia, SC, USA.
  • Steinley D; Department of Psychological Sciences, University of Missouri-Columbia, Columbia, SC, USA.
  • Sher K; Department of Psychological Sciences, University of Missouri-Columbia, Columbia, SC, USA.
Addict Res Theory ; 24(1): 1-8, 2016.
Article en En | MEDLINE | ID: mdl-27429607
ABSTRACT
Some individuals "change" more dramatically than others when intoxicated, and the nature and magnitude of these changes can result in harmful outcomes. This study utilized reports (N»374) of participants' "typical" five-factor model (FFM) characteristics across sober and intoxicated states and assessed the degree to which these reports could be grouped into meaningful clusters, as well as the association of cluster membership with negative alcoholrelated consequences. Results from finite mixture model clustering revealed a four cluster solution. Cluster 1, "Hemingway," was the largest and defined by intoxication-related decreases in Conscientiousness and Intellect that were below average; Cluster 2, "Mary Poppins," was defined by being high in Agreeableness when sober, decreasing less than average in Conscientiousness and Intellect and increasing more than average in Extraversion when drunk; Cluster 3, "Mr. Hyde," reported larger drunk decreases in Conscientiousness and Intellect and smaller increases in Extraversion; Cluster 4, "The Nutty Professor," was defined by being low in Extraversion when sober, increasing more than average in Extraversion and decreasing less than average in Conscientiousness when drunk. Cluster membership was associated with experiencing more alcohol consequences. These results support use of the FFM to characterize clinically meaningful subgroups of sober-to-drunk differences in trait expression.
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2016 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2016 Tipo del documento: Article