J
John W Williams
Researcher at Duke University
Publications - 418
Citations - 45036
John W Williams is an academic researcher from Duke University. The author has contributed to research in topics: Health care & Randomized controlled trial. The author has an hindex of 84, co-authored 390 publications receiving 39736 citations. Previous affiliations of John W Williams include McMaster University & Lyons.
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Journal ArticleDOI
Grading quality of evidence and strength of recommendations.
David C. Atkins,Dana Best,Peter A. Briss,Martin P Eccles,Yngve Falck-Ytter,Signe Flottorp,Gordon H. Guyatt,Robin Harbour,Margaret C Haugh,David Henry,Suzanne Hill,Roman Jaeschke,Gillian Leng,Alessandro Liberati,Nicola Magrini,James Mason,Philippa Middleton,Jacek Mrukowicz,Dianne L. O'Connell,Andrew D Oxman,Bob Phillips,Holger J. Schünemann,Tessa Tan-Torres Edejer,H. Varonen,Gunn Elisabeth Vist,John W Williams,Stephanie Zaza +26 more
TL;DR: A system for grading the quality of evidence and the strength of recommendations that can be applied across a wide range of interventions and contexts is developed, and a summary of the approach from the perspective of a guideline user is presented.
Journal ArticleDOI
Collaborative Care Management of Late-Life Depression in the Primary Care Setting: A Randomized Controlled Trial
Jürgen Unützer,Wayne Katon,Christopher M. Callahan,John W Williams,Enid M. Hunkeler,Linda H. Harpole,Marc Hoffing,Richard Della Penna,Polly H. Noël,Elizabeth H. B. Lin,Patricia A. Areán,Mark T. Hegel,Lingqi Tang,Thomas R. Belin,Sabine M. Oishi,Christopher Langston +15 more
TL;DR: The IMPACT collaborative care model appears to be feasible and significantly more effective than usual care for depression in a wide range of primary care practices.
Journal ArticleDOI
GRADE guidelines: 4. Rating the quality of evidence—study limitations (risk of bias)
Gordon H. Guyatt,Andrew D Oxman,Gunn Elisabeth Vist,Regina Kunz,Jan Brozek,Pablo Alonso-Coello,Victor M. Montori,Elie A. Akl,Ben Djulbegovic,Yngve Falck-Ytter,Susan L Norris,John W Williams,David C. Atkins,Joerg J Meerpohl,Holger J. Schünemann +14 more
TL;DR: In the GRADE approach, randomized trials start as high-quality evidence and observational studies as low- quality evidence, but both can be rated down if most of the relevant evidence comes from studies that suffer from a high risk of bias.
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GRADE guidelines: 6. Rating the quality of evidence-imprecision
Gordon H. Guyatt,Andrew D Oxman,Regina Kunz,Jan Brozek,Pablo Alonso-Coello,David Rind,Philip J. Devereaux,Victor M. Montori,Bo Freyschuss,Gunn Elisabeth Vist,Roman Jaeschke,John W Williams,Mohammad Hassan Murad,David A. Sinclair,Yngve Falck-Ytter,Joerg J Meerpohl,Craig Whittington,Kristian Thorlund,Jeffrey C Andrews,Holger J. Schünemann +19 more
TL;DR: It is suggested that examination of 95% confidence intervals (CIs) provides the optimal primary approach to decisions regarding imprecision and rating down the quality of evidence is required if clinical action would differ if the upper versus the lower boundary of the CI represented the truth.
Journal ArticleDOI
GRADE guidelines: 5. Rating the quality of evidence--publication bias
Gordon H. Guyatt,Andrew D Oxman,Victor M. Montori,Gunn Elisabeth Vist,Regina Kunz,Jan Brozek,Pablo Alonso-Coello,Ben Djulbegovic,David C. Atkins,Yngve Falck-Ytter,John W Williams,Joerg J Meerpohl,Susan L Norris,Elie A. Akl,Holger J. Schünemann +14 more
TL;DR: In the GRADE approach, randomized trials start as high-quality evidence and observational studies as low- quality evidence, but both can be rated down if a body of evidence is associated with a high risk of publication bias.