Features and functioning of Data Abstraction Assistant, a software application for data abstraction during systematic reviews

on behalf of the Data Abstraction Assistant Investigators

Research output: Contribution to journalReview articlepeer-review

Abstract

Introduction: During systematic reviews, data abstraction is labor- and time-intensive and error-prone. Existing data abstraction systems do not track specific locations and contexts of abstracted information. To address this limitation, we developed a software application, the Data Abstraction Assistant (DAA) and surveyed early users about their experience using DAA. Features of DAA: We designed DAA to encompass three essential features: (1) a platform for indicating the source of abstracted information, (2) compatibility with a variety of data abstraction systems, and (3) user-friendliness. How DAA functions: DAA (1) converts source documents from PDF to HTML format (to enable tracking of source of abstracted information), (2) transmits the HTML to the data abstraction system, and (3) displays the HTML in an area adjacent to the data abstraction form in the data abstraction system. The data abstractor can mark locations on the HTML that DAA associates with items on the data abstraction form. Experiences of early users of DAA: When we surveyed 52 early users of DAA, 83% reported that using DAA was either very or somewhat easy; 71% are very or somewhat likely to use DAA in the future; and 87% are very or somewhat likely to recommend that others use DAA in the future. Discussion: DAA, a user-friendly software for linking abstracted data with their exact source, is likely to be a very useful tool in the toolbox of systematic reviewers. DAA facilitates verification of abstracted data and provides an audit trail that is crucial for reproducible research.

Original languageEnglish (US)
Pages (from-to)2-14
Number of pages13
JournalResearch Synthesis Methods
Volume10
Issue number1
DOIs
StatePublished - Mar 2019

Keywords

  • data abstraction
  • data exchange
  • data tracking
  • software
  • systematic reviews

ASJC Scopus subject areas

  • Education

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