The PRECIS-2 tool: designing trials that are fit for purpose
BMJ 2015; 350 doi: https://doi.org/10.1136/bmj.h2147 (Published 08 May 2015) Cite this as: BMJ 2015;350:h2147- Kirsty Loudon, research assistant1,
- Shaun Treweek, professor of health services research1,
- Frank Sullivan, director of University of Toronto Practice-Based Research Network (UTOPIAN), Gordon F Cheesbrough chair in family and community medicine2,
- Peter Donnan, professor of epidemiology and biostatistics, director of Dundee Epidemiology & Biostatistics Unit (DEBU), co-director of Tayside Clinical Trials Unit (TCTU)3,
- Kevin E Thorpe, assistant professor; head of biostatistics4,
- Merrick Zwarenstein, director5
- 1Health Services Research Unit, University of Aberdeen,
- 2North York General Hospital, Toronto, ON M2K 1E1, Canada
- 3Division of Population Health Sciences, University of Dundee, Dundee DD2 4BF, UK
- 4Dalla Lana School of Public Health, University of Toronto; Applied Health Research Centre (AHRC), Li Ka Shing Knowledge Institute of St Michael’s, Toronto, Canada
- 5Centre for Studies in Family Medicine, Schulich School of Medicine & Dentistry, Western University, Western Centre for Public Health and Family Medicine, London, ON N6A 3K7, Canada
- Correspondence to: K Loudon kirsty.loudon{at}abdn.ac.uk
- Accepted 12 February 2015
Summary points
PRECIS (2009) was a tool with 10 domains to design clinical trials on a continuum of explanatory attitude (ideal situation) to more pragmatic attitude (usual care)
Cited over 300 times by end of 2014, but weaknesses have been highlighted: no rating scale, problems with some domains, needing better guidance, and not validated
This paper presents PRECIS-2—a validated, improved version of the tool—together with guidance for how to use it
PRECIS-2 has nine domains including three new ones (recruitment, setting, and organisation), each scored on a 5-point Likert continuum (from 1=very explanatory “ideal conditions” to 5=very pragmatic “usual care conditions”) so that trialists, clinicians, and policymakers can more easily consider whether design decisions match their intended purpose
Randomised trials are hard work. Like much that is hard, this toil is only worth it because of the prospect of a substantial reward. For many important stakeholders (patients or others who may benefit from an intervention, funders of healthcare and of research, practitioners who may deliver clinical care and often the researchers themselves) the anticipated reward for a trial is that the results can be used to directly support decisions on delivering an intervention …