Literature DB >> 19683413

Systematic review data extraction: cross-sectional study showed that experience did not increase accuracy.

Jennifer Horton1, Ben Vandermeer, Lisa Hartling, Lisa Tjosvold, Terry P Klassen, Nina Buscemi.   

Abstract

OBJECTIVE: This study assessed the impact of systematic review and data extraction experience on the accuracy and efficiency of data extraction in systematic reviews. STUDY DESIGN AND
SETTING: We conducted a prospective cross-sectional study from October to December 2006. Participants were classified as having minimal, moderate, or substantial experience in systematic reviews and data extraction. Three studies on insomnia treatment were extracted. Our primary outcome was the accuracy of data extraction. Data sets of each experience level were analyzed for errors in data extraction and results of meta-analyses. Additionally, the time required for completion of data extraction was compared.
RESULTS: Error rates were similar across the various levels of experience and ranged from 28.3% to 31.2%. Mean rates for errors of omission (11.3-16.4%) were generally lower than those for errors of inaccuracy (13.9-17.9%). There were no significant differences in error rates or accuracy of meta-analysis results between groups. Time required approached significance, with minimally experienced participants requiring the most time.
CONCLUSION: Overall, there were high error rates by participants at all experience levels; however, time required for extraction tended to decrease with experience. These results illustrate the need to develop strategies aimed at mastery of data extraction, rather than reliance on previous data extraction experience alone.

Entities:  

Mesh:

Year:  2009        PMID: 19683413     DOI: 10.1016/j.jclinepi.2009.04.007

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  18 in total

1.  Evidence-Based Decision-Making 2: Systematic Reviews and Meta-Analysis.

Authors:  Aminu Bello; Ben Vandermeer; Natasha Wiebe; Amit X Garg; Marcello Tonelli
Journal:  Methods Mol Biol       Date:  2021

2.  Meta-assessment of bias in science.

Authors:  Daniele Fanelli; Rodrigo Costas; John P A Ioannidis
Journal:  Proc Natl Acad Sci U S A       Date:  2017-03-20       Impact factor: 11.205

3.  Automatic extraction of quantitative data from ClinicalTrials.gov to conduct meta-analyses.

Authors:  Richeek Pradhan; David C Hoaglin; Matthew Cornell; Weisong Liu; Victoria Wang; Hong Yu
Journal:  J Clin Epidemiol       Date:  2018-09-23       Impact factor: 6.437

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

Authors:  Jens Jap; Ian J Saldanha; Bryant T Smith; Joseph Lau; Christopher H Schmid; Tianjing Li
Journal:  Res Synth Methods       Date:  2018-11-19       Impact factor: 5.273

5.  Title and Abstract Screening and Evaluation in Systematic Reviews (TASER): a pilot randomised controlled trial of title and abstract screening by medical students.

Authors:  Lauren Ng; Veronica Pitt; Kit Huckvale; Ornella Clavisi; Tari Turner; Russell Gruen; Julian H Elliott
Journal:  Syst Rev       Date:  2014-10-21

6.  On the reproducibility of meta-analyses: six practical recommendations.

Authors:  Daniël Lakens; Joe Hilgard; Janneke Staaks
Journal:  BMC Psychol       Date:  2016-05-31

7.  Evaluating Data Abstraction Assistant, a novel software application for data abstraction during systematic reviews: protocol for a randomized controlled trial.

Authors:  Ian J Saldanha; Christopher H Schmid; Joseph Lau; Kay Dickersin; Jesse A Berlin; Jens Jap; Bryant T Smith; Simona Carini; Wiley Chan; Berry De Bruijn; Byron C Wallace; Susan M Hutfless; Ida Sim; M Hassan Murad; Sandra A Walsh; Elizabeth J Whamond; Tianjing Li
Journal:  Syst Rev       Date:  2016-11-22

8.  Inter-rater and test-retest reliability of quality assessments by novice student raters using the Jadad and Newcastle-Ottawa Scales.

Authors:  Mark Oremus; Carolina Oremus; Geoffrey B C Hall; Margaret C McKinnon
Journal:  BMJ Open       Date:  2012-07-31       Impact factor: 2.692

9.  A case study of binary outcome data extraction across three systematic reviews of hip arthroplasty: errors and differences of selection.

Authors:  Christopher Carroll; Alison Scope; Eva Kaltenthaler
Journal:  BMC Res Notes       Date:  2013-12-17

10.  Data extraction from machine-translated versus original language randomized trial reports: a comparative study.

Authors:  Ethan M Balk; Mei Chung; Minghua L Chen; Lina Kong Win Chang; Thomas A Trikalinos
Journal:  Syst Rev       Date:  2013-11-07
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.