Linked Life Data

16317183

Source:http://linkedlifedata.com/resource/pubmed/id/16317183

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2005-11-30
pubmed:abstractText
Qualitative researchers address many issues relevant to patient health care. Their studies appear in an array of journals, making literature searching difficult. Large databases such as EMBASE provide a means of retrieving qualitative research, but these studies represent only a minuscule fraction of published articles, making electronic retrieval problematic. Little work has been done on developing search strategies for the detection of qualitative studies. The objective of this study was to develop optimal search strategies to retrieve qualitative studies in EMBASE for the 2000 publishing year. The authors conducted an analytic survey, comparing hand searches of journals with retrievals from EMBASE for candidate search terms and combinations. Search strategies reached peak sensitivities at 94.2% and peak specificities of 99.7%. Combining search terms to optimize the combination of sensitivity and specificity resulted in values over 89% for both. The authors identified search strategies with high performance for retrieving qualitative studies in EMBASE.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
T
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1049-7323
pubmed:author
pubmed:issnType
Print
pubmed:volume
16
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
162-8
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Developing optimal search strategies for retrieving clinically relevant qualitative studies in EMBASE.
pubmed:affiliation
McMaster University in Hamilton, Ontario, Canada.
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural