Professor Julian Higgins explains why he believes the systematic review and meta-analysis methods described in many highly cited papers are routinely misunderstood or misused. Julian Higgins is Professor of Evidence Synthesis at the Bristol Evidence Synthesis, Appraisal and Modelling (BEAM) Centre at the University of Bristol. His research has focussed on the methodology of systematic review and meta-analysis and he has been senior editor of the Cochrane Handbook for Systematic Reviews of Interventions since 2003. He is an NIHR Senior Investigator and currently co-directs the NIHR Bristol Evidence Synthesis Group.
Systematic reviews and meta-analyses have become influential and popular. Papers describing aspects of the systematic review and meta-analysis toolkit have become some of the most highly cited papers. I will review those that appear at the top of the most-cited list and explain why I believe the methods described are routinely misunderstood or misused. These include a test for asymmetry in a funnel plot, the I-squared statistic for measuring inconsistency across studies, the random-effects meta-analysis model and the PRIMSA reporting guideline.
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Professor Julian Higgins explains why he believes the systematic review and meta-analysis methods described in many highly cited papers are routinely misunderstood or misused. Julian Higgins is Professor of Evidence Synthesis at the Bristol Evidence Synthesis, Appraisal and Modelling (BEAM) Centre at the University of Bristol. His research has focussed on the methodology of systematic review and meta-analysis and he has been senior editor of the Cochrane Handbook for Systematic Reviews of Interventions since 2003. He is an NIHR Senior Investigator and currently co-directs the NIHR Bristol Evidence Synthesis Group.
Systematic reviews and meta-analyses have become influential and popular. Papers describing aspects of the systematic review and meta-analysis toolkit have become some of the most highly cited papers. I will review those that appear at the top of the most-cited list and explain why I believe the methods described are routinely misunderstood or misused. These include a test for asymmetry in a funnel plot, the I-squared statistic for measuring inconsistency across studies, the random-effects meta-analysis model and the PRIMSA reporting guideline.
The Role of Social Endometriosis Research in Improving Care and Addressing Intersectional Health Disparities
Evidence-Based Health Care
41 minutes
3 years ago
The Role of Social Endometriosis Research in Improving Care and Addressing Intersectional Health Disparities
Dr Annalise Weckesser will discuss her qualitative studies exploring women’s experiences of endometriosis and doctors’ perspectives on treating the condition and how to improve care. This episode explores what this research, and the growing body of social research on endometriosis more generally, contributes to efforts to improve care and address health disparities at the intersections of gender and race, and reflect on the ‘work to be done’ going forward in qualitative investigations of the condition. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/
Evidence-Based Health Care
Professor Julian Higgins explains why he believes the systematic review and meta-analysis methods described in many highly cited papers are routinely misunderstood or misused. Julian Higgins is Professor of Evidence Synthesis at the Bristol Evidence Synthesis, Appraisal and Modelling (BEAM) Centre at the University of Bristol. His research has focussed on the methodology of systematic review and meta-analysis and he has been senior editor of the Cochrane Handbook for Systematic Reviews of Interventions since 2003. He is an NIHR Senior Investigator and currently co-directs the NIHR Bristol Evidence Synthesis Group.
Systematic reviews and meta-analyses have become influential and popular. Papers describing aspects of the systematic review and meta-analysis toolkit have become some of the most highly cited papers. I will review those that appear at the top of the most-cited list and explain why I believe the methods described are routinely misunderstood or misused. These include a test for asymmetry in a funnel plot, the I-squared statistic for measuring inconsistency across studies, the random-effects meta-analysis model and the PRIMSA reporting guideline.
