Development of an efficient search filter to retrieve systematic reviews from PubMed.
Objective: Locating systematic reviews is essential for clinicians and researchers when creating or updating reviews and for decision-making in health care. This study aimed to develop a search filter for retrieving systematic reviews that improves upon the performance of the PubMed systematic revie...
| Publicado en: | Journal of the Medical Library Association Vol. 109; no. 4; pp. 561 - 575 |
|---|---|
| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
University of Pittsburgh, University Library System
Oct2021
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=153765037&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 153765037 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15365050 PI8 jtl: Journal of the Medical Library Association issn: 15365050 maglogo: N pubinfo: dt: Oct2021 vid: 109 iid: 4 pid: 60406 pub: University of Pittsburgh, University Library System place: Pittsburgh, Pennsylvania artinfo: ui: 153765037 153765037 153765037 10.5195/jmla.2021.1223 153765037 ppf: 561 ppct: 14 formats: fmt: @attributes: type: P tig: atl: Development of an efficient search filter to retrieve systematic reviews from PubMed. aug: au: Salvador-Oliván, José Antonio Marco-Cuenca, Gonzalo Arquero-Avilés, Rosario affil: Professor, Department of Library and Information Science, University of Zaragoza, Spain sug: subj: Computerized Literature Searching Systematic Review PubMed Web Search Engines Information Retrieval ab: Objective: Locating systematic reviews is essential for clinicians and researchers when creating or updating reviews and for decision-making in health care. This study aimed to develop a search filter for retrieving systematic reviews that improves upon the performance of the PubMed systematic review search filter. Methods: Search terms were identified from abstracts of reviews published in Cochrane Database of Systematic Reviews and the titles of articles indexed as systematic reviews in PubMed. Both the precision of the candidate terms and the number of systematic reviews retrieved from PubMed were evaluated after excluding the subset of articles retrieved by the PubMed systematic review filter. Terms that achieved a precision greater than 70% and relevant publication types indexed with MeSH terms were included in the filter search strategy. Results: The search strategy used in our filter added specific terms not included in PubMed's systematic review filter and achieved a 61.3% increase in the number of retrieved articles that are potential systematic reviews. Moreover, it achieved an average precision that is likely greater than 80%. Conclusions: The developed search filter will enable users to identify more systematic reviews from PubMed than the PubMed systematic review filter with high precision. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|