The Use of Bayesian Networks to Assess the Quality of Evidence from Research Synthesis: 1.
Publication Date
April 02, 2015
Journal
PLOS ONE
Authors
Gavin B. Stewart, Julian P. T. Higgins, Holger Schünemann & Nick Meader
Volume
10
Issue
4
Pages
e0114497
DOI
https://dx.plos.org/10.1371/journal.pone.0114497
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0114497
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/25837450
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4383525
Europe PMC
http://europepmc.org/abstract/MED/25837450
Web of Science
000352139000001
Scopus
84926629957
Mendeley
http://www.mendeley.com/research/bayesian-networks-assess-quality-evidence-research-synthesis-1-7
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Mendeley | Further Information

{"title"=>"The Use of Bayesian Networks to Assess the Quality of Evidence from Research Synthesis: 1.", "type"=>"journal", "authors"=>[{"first_name"=>"Gavin B.", "last_name"=>"Stewart"}, {"first_name"=>"Julian P. T.", "last_name"=>"Higgins"}, {"first_name"=>"Holger", "last_name"=>"Schünemann"}, {"first_name"=>"Nick", "last_name"=>"Meader"}], "year"=>2015, "source"=>"PLOS ONE", "identifiers"=>{"pui"=>"603600100", "sgr"=>"84926629957", "doi"=>"10.1371/journal.pone.0114497", "issn"=>"1932-6203"}, "id"=>"9a2410e6-7148-386d-89b3-d9c1df4130cd", "abstract"=>"Background The grades of recommendation, assessment, development and evaluation (GRADE) approach is widely implemented in systematic reviews, health technology assessment and guideline development organisations throughout the world. A key advantage to this approach is that it aids transparency regarding judgments on the quality of evidence. However, the intricacies of making judgments about research methodology and evidence make the GRADE system complex and challenging to apply without training. Methods We have developed a semi-automated quality assessment tool (SAQAT) l based on GRADE. This is informed by responses by reviewers to checklist questions regarding characteristics that may lead to unreliability. These responses are then entered into the Bayesian network to ascertain the probabilities of risk of bias, inconsistency, indirectness, imprecision and publication bias conditional on review characteristics. The model then combines these probabilities to provide a probability for each of the GRADE overall quality categories. We tested the model using a range of plausible scenarios that guideline developers or review authors could encounter. Results Overall, the model reproduced GRADE judgements for a range of scenarios. Potential advantages over standard assessment are use of explicit and consistent weightings for different review characteristics, forcing consideration of important but sometimes neglected characteristics and principled downgrading where small but important probabilities of downgrading are accrued across domains.", "link"=>"http://www.mendeley.com/research/bayesian-networks-assess-quality-evidence-research-synthesis-1-7", "reader_count"=>21, "reader_count_by_academic_status"=>{"Student > Doctoral Student"=>2, "Researcher"=>7, "Student > Ph. D. Student"=>4, "Student > Postgraduate"=>1, "Student > Master"=>4, "Other"=>1, "Student > Bachelor"=>1, "Lecturer"=>1}, "reader_count_by_user_role"=>{"Student > Doctoral Student"=>2, "Researcher"=>7, "Student > Ph. D. Student"=>4, "Student > Postgraduate"=>1, "Student > Master"=>4, "Other"=>1, "Student > Bachelor"=>1, "Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Environmental Science"=>4, "Nursing and Health Professions"=>1, "Medicine and Dentistry"=>6, "Psychology"=>1, "Social Sciences"=>1, "Computer Science"=>4, "Decision Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>6}, "Social Sciences"=>{"Social Sciences"=>1}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Psychology"=>{"Psychology"=>1}, "Computer Science"=>{"Computer Science"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>4}}, "reader_count_by_country"=>{"United States"=>1, "United Kingdom"=>1, "Kenya"=>1, "Germany"=>1}, "group_count"=>2}

Scopus | Further Information

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Figshare

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Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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