Title |
Developing optimal search strategies for detecting clinically sound and relevant causation studies in EMBASE
|
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Published in |
BMC Medical Informatics and Decision Making, March 2005
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DOI | 10.1186/1472-6947-5-8 |
Pubmed ID | |
Authors |
R Brian Haynes, Monika Kastner, Nancy L Wilczynski, the Hedges Team |
Abstract |
Evaluating the existence and strength of an association between a putative cause and adverse clinical outcome is complex and best done by assessing all available evidence. With the increasing burden of chronic disease, greater time demands on health professionals, and the explosion of information, effective retrieval of best evidence has become both more important and more difficult. Optimal search retrieval can be hampered by a number of obstacles, especially poor search strategies, but using empirically tested methodological search filters can enhance the accuracy of searches for sound evidence concerning etiology. Although such filters have previously been developed for studies of relevance to causation in MEDLINE, no empirically tested search strategy exists for EMBASE. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 4 | 5% |
Brazil | 2 | 2% |
United Kingdom | 2 | 2% |
Peru | 1 | 1% |
Canada | 1 | 1% |
Nigeria | 1 | 1% |
United States | 1 | 1% |
Unknown | 69 | 85% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 17 | 21% |
Librarian | 9 | 11% |
Student > Master | 9 | 11% |
Student > Doctoral Student | 7 | 9% |
Professor > Associate Professor | 7 | 9% |
Other | 19 | 23% |
Unknown | 13 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 36 | 44% |
Nursing and Health Professions | 4 | 5% |
Psychology | 4 | 5% |
Computer Science | 3 | 4% |
Agricultural and Biological Sciences | 2 | 2% |
Other | 12 | 15% |
Unknown | 20 | 25% |