Linked Life Data

20887686

Source:http://linkedlifedata.com/resource/pubmed/id/20887686

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2010-10-4
pubmed:abstractText
Theory and methodology from nonlinear dynamical systems (NDS) may provide considerable advantage to health scientists as well as health care professionals. For instance, NDS methodologies and topics in health care share a focus upon the potentially complex interactions of biological, psychological and social factors over time. Nevertheless, a number of challenges remain in creating the necessary bridges in understanding to allow researchers to apply NDS techniques and to enable practitioners to use the resulting evidence to improve patient care. This article aims to provide such a bridge. First, common concepts pertaining to self-organizing complex adaptive systems are outlined as a general approach to understanding resilience across biological, psychological, and social scales. Next, four data analytic techniques from NDS are compared and contrasted with respect to the information they may provide about some common processes underlying resilience. These techniques are: time-series analysis, state-space grids, catastrophe modeling, and network modeling. Implications for health scientists and practitioners are discussed.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1090-0578
pubmed:author
pubmed:issnType
Print
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
353-80
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Nonlinear dynamics in biopsychosocial resilience.
pubmed:affiliation
Department of Psychology, Chapman University, Orange, CA 92866, USA. pincus@chapman.edu
pubmed:publicationType
Journal Article