title: Brazilian academic search filter: application to the scientific literature on physical activity.
abstract: OBJECTIVE
  To develop a search filter in order to retrieve scientific publications on physical activity from Brazilian academic institutions.
  
  
  METHODS
  The academic search filter consisted of the descriptor "exercise" associated through the term AND, to the names of the respective academic institutions, which were connected by the term OR. The MEDLINE search was performed with PubMed on 11/16/2008. The institutions were selected according to the classification from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for interuniversity agreements.
  
  
  RESULTS
  A total of 407 references were retrieved, corresponding to about 0.9% of all articles about physical activity and 0.5% of the Brazilian academic publications indexed in MEDLINE on the search date. When compared with the manual search undertaken, the search filter (descriptor + institutional filter) showed a sensitivity of 99% and a specificity of 100%.
  
  
  CONCLUSIONS
  The institutional search filter showed high sensitivity and specificity, and is applicable to other areas of knowledge in health sciences. It is desirable that every Brazilian academic institution establish its "standard name/brand" in order to efficiently retrieve their scientific literature.
authors.affiliation: Departamento de Salud Pública, Historia de Ciencia y Ginecología, Universidad Miguel Hernández, Elche, España. jsanz@umh.es
authors.forename: Javier
authors.initials: J
authors.lastname: Sanz-Valero
authors.forename: Marcos Santos
authors.initials: MS
authors.lastname: Ferreira
authors.forename: Luis David
authors.initials: LD
authors.lastname: Castiel
authors.forename: Carmina
authors.initials: C
authors.lastname: Wanden-Berghe
authors.forename: Maria Cristina Rodrigues
authors.initials: MC
authors.lastname: Guilam
mesh_terms: D022126:Access to Information; D015706:Bibliometrics; D035843:Biomedical Research; D001938:Brazil; D057225:Data Mining / Q000379:methods*; D006801:Humans; D016239:MEDLINE / Q000706:statistics & numerical data*; D046650:Medical Subject Headings; D009043:Motor Activity; D010506:Periodicals as Topic; D012680:Sensitivity and Specificity; D014495:Universities / Q000706:statistics & numerical data*