ERIC Number: EJ1254440
Record Type: Journal
Publication Date: 2019-Mar
Pages: 13
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1759-2879
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Available Date: N/A
Features and Functioning of D ata A bstraction A ssistant, a Software Application for Data Abstraction during Systematic Reviews
Jap, Jens; Saldanha, Ian J.; Smith, Bryant T.; Lau, Joseph; Schmid, Christopher H.; Li, Tianjing
Research Synthesis Methods, v10 n1 p2-14 Mar 2019
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. [This article was written on behalf of the Data Abstraction Assistant Investigators.]
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
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