Bias in research

Our mission is to ensure that policy decisions rest on strong and unbiased pillars of evidence. The Charles Perkins Centre is the perfect place to collaborate with content area experts to achieve this goal. 

With the growing threat of complex conditions such as obesity, diabetes and cardiovascular disease – considered complex because they’re the result of a mix of biological, social, cultural and other factors – producing unbiased evidence and promoting evidence-based decision making is as important today as it’s ever been.

Methodologists can’t work in isolation to tackle these complex issues.

We use quantitative and qualitative methods to examine the cultural, social, corporate, political and other influences on the design, conduct and publication of research.

Participating researchers are also involved in designing and testing rigorous interventions to:

• reduce bias in research
• promote research integrity
• improve the uptake of research in the policy process.

Part of the Evidence, Influence and Policy Collaborative (EPIC) Research Group, this node has more than 30 local and international members.

Our research is already having an impact.

• We have exposed bias and conflicts of interest in health-related research, including in the areas of pharmaceutical, environmental, nutrition, and tobacco control.
• We have also worked with diverse communities, including journalists, lawyers, judges, and consumers, to increase their skills in evaluating bias in research.
• Our work is being used to make the new gold standards for synthesising evidence for a wide variety of health policy decisions.
• Our research has spawned international efforts to advance methods for assessing bias and conducting systematic reviews in new areas, such as environmental risk assessment and complex public health questions.
• Our research also forms the basis for a number of collaborative efforts among governments and researchers to develop empirically based tools for assessing bias in research. Our methodology for assessing bias also supports agencies such as the NHMRC and the World Health Organization.
• Another important impact of our work in detecting bias has been the growing recognition that selective reporting of research outcomes, as well as of entire studies, can make it impossible to identify data for systematic reviews. This work has led to international reforms to make data more accessible, conflicts of interest and funding more transparent, and to calls for stricter standards and policies for managing conflicts of interest, critiquing and reporting evidence, and conducting systematic reviews.

Internal collaborators

• Professor Margaret Allman-Farinelli
• Professor Lisa Askie
• Professor Adrian Bauman
• Professor Louise Baur
• Professor Lisa Bero (Project Node Leader)
• Professor Nicholas Buckley
• Associate Professor Teresa Davis
• Dr Melody Ding
• Dr Joanna Diong
• Professor Tim Gill
• Professor Paul Griffiths
• Dr Quinn Grundy
• Dr Tracey-Lea Laba
• Dr Wendy Lipworth
• Dr Barbara Mintzes
• Professor Sallie-Anne Pearson
• Dr Jonathan Penm
• Professor David Raubenheimer
• Dr Kieron Rooney
• Professor Emmanuel Stamatakis
• Professor Merrilyn Walton
• Professor Angela Webster

External collaborators

• Dr Jon Jureidini, University of Adelaide
• Professor Mark Lawrence, Health, Deakin University
• Professor Joel Lexchin, York University
• Dr Daniele Mandrioli, John Hopkins University
• Gabriel Axel Montes, University of Newcastle
• Professor Nicolas Rasmussen, University of New South Wales
• Dr Gyorgy Scrinis, University of Melbourne
• Dr Anne Springer, University of Saskatchewan
• Dr Anna Stoklosa, NHMRC Clinical Trials Centre
• Associate Professor Luke Wolfenden, University of Newcastle