Predicting Cannabis Abuse Screening Test (CAST) Scores : A Recursive Partitioning Analysis Using Survey Data from Czech Republic, Italy, the Netherlands and Sweden

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Predicting Cannabis Abuse Screening Test (CAST) Scores : A Recursive Partitioning Analysis Using Survey Data from Czech Republic, Italy, the Netherlands and Sweden

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Publication Article, peer reviewed scientific
Title Predicting Cannabis Abuse Screening Test (CAST) Scores : A Recursive Partitioning Analysis Using Survey Data from Czech Republic, Italy, the Netherlands and Sweden
Author(s) Blankers, Matthijs ; Frijns, Tom ; Belackova, Vendula ; Rossi, Carla ; Svensson, Bengt ; Trautmann, Franz ; van Laar, Margriet
Date 2014
English abstract
Cannabis is Europe's most commonly used illicit drug. Some users do not develop dependence or other problems, whereas others do. Many factors are associated with the occurrence of cannabis-related disorders. This makes it difficult to identify key risk factors and markers to profile at-risk cannabis users using traditional hypothesis-driven approaches. Therefore, the use of a data-mining technique called binary recursive partitioning is demonstrated in this study by creating a classification tree to profile at-risk users.
DOI http://dx.doi.org/10.1371/journal.pone.0108298 (link to publisher's fulltext)
Publisher Public Library of Science
Host/Issue PLOS One;9
Volume 9
ISSN 1932-6203
Pages 11
Language eng (iso)
Subject(s) cannabis use
screening test
CAST
classification trees
Humanities/Social Sciences
Research Subject Categories::SOCIAL SCIENCES
Handle http://hdl.handle.net/2043/18157 (link to this page)

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