title: Can abstract screening workload be reduced using text mining? User experiences of the tool Rayyan.
abstract: BACKGROUND
  One time-consuming aspect of conducting systematic reviews is the task of sifting through abstracts to identify relevant studies. One promising approach for reducing this burden uses text mining technology to identify those abstracts that are potentially most relevant for a project, allowing those abstracts to be screened first.
  
  
  OBJECTIVE
  To examine the effectiveness of the text mining functionality of the abstract screening tool Rayyan. User experiences were collected.
  
  
  METHODS
  Rayyan was used to screen abstracts for 6 reviews in 2015. After screening 25%, 50%, and 75% of the abstracts, the screeners logged the relevant references identified. A survey was sent to users.
  
  
  RESULTS
  After screening half of the search result with Rayyan, 86% to 99% of the references deemed relevant to the study were identified. Of those studies included in the final reports, 96% to 100% were already identified in the first half of the screening process. Users rated Rayyan 4.5 out of 5.
  
  
  CONCLUSIONS
  The text mining function in Rayyan successfully helped reviewers identify relevant studies early in the screening process.
authors.affiliation: Swedish Agency for Health Technology Assessment and Assessment of Social Services, Stockholm, Sweden.
authors.forename: Hanna
authors.identifier: http://orcid.org/0000-0002-5349-8266
authors.initials: H
authors.lastname: Olofsson
authors.affiliation: Swedish Agency for Health Technology Assessment and Assessment of Social Services, Stockholm, Sweden.
authors.forename: Agneta
authors.initials: A
authors.lastname: Brolund
authors.affiliation: Swedish Agency for Health Technology Assessment and Assessment of Social Services, Stockholm, Sweden.
authors.forename: Christel
authors.initials: C
authors.lastname: Hellberg
authors.affiliation: Swedish Agency for Health Technology Assessment and Assessment of Social Services, Stockholm, Sweden.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Silverstein
authors.affiliation: Swedish Agency for Health Technology Assessment and Assessment of Social Services, Stockholm, Sweden.
authors.forename: Karin
authors.initials: K
authors.lastname: Stenström
authors.affiliation: Swedish Agency for Health Technology Assessment and Assessment of Social Services, Stockholm, Sweden.
authors.forename: Marie
authors.initials: M
authors.lastname: Österberg
authors.affiliation: Swedish Agency for Health Technology Assessment and Assessment of Social Services, Stockholm, Sweden.
authors.forename: Jessica
authors.initials: J
authors.lastname: Dagerhamn
mesh_terms: D057225:Data Mining / Q000379:methods; D006801:Humans; D012196:Review Literature as Topic; D016526:Workload
keywords: abstract screening; review efficiency; systematic reviews; text mining