Linked Life Data

12784831

Source:http://linkedlifedata.com/resource/pubmed/id/12784831

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2003-6-4
pubmed:abstractText
Understanding the relapse process is one of the most important issues in addictive behaviors research. To date, most studies have taken a linear approach toward predicting relapse based on risk factors. Nonlinear dynamical systems theory can be used to describe processes that are not adequately modeled using a linear approach. In particular, the authors propose that catastrophe theory, a subset of nonlinear dynamical systems theory, can be used to describe the relapse process in addictive behaviors. Two small prospective studies using 6-month follow-ups of patients with alcohol use disorders (inpatient, n = 51; outpatient, n = 43) illustrate how cusp catastrophe theory may be used to predict relapse. Results from these preliminary studies indicate that a cusp catastrophe model has more predictive utility than traditional linear models.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0021-843X
pubmed:author
pubmed:issnType
Print
pubmed:volume
112
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
219-27
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Relapse as a nonlinear dynamic system: application to patients with alcohol use disorders.
pubmed:affiliation
Department of Psychology, University of Montana, USA. mhufford@invivodata.com
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't