Using natural experiments to evaluate population health interventions: new Medical Research Council guidance

Journal of Epidemiology and Community Health - Tập 66 Số 12 - Trang 1182-1186 - 2012
Peter Craig1, Cyrus Cooper2, David Gunnell3, Sally Haw4, Kenny Lawson5, Sally Macintyre6, David Ogilvie7, Mark Petticrew8, Barnaby C Reeves9, Matt Sutton10, Simon G. Thompson11
1MRC Population Health Sciences Research Network and Chief Scientist Office, Scottish Government Health Directorates, St Andrews House, Edinburgh EH1 3DG, UK.
2MRC-Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
3Bristol Medical School (PHS)
4Centre for Public Health and Population Health Research, University of Stirling, Stirling, UK
5Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
6MRClCSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
7MRC Epidemiology Unit and UKCRC Centre for Diet and Activity Research (CEDAR), Cambridge, UK
8Department of Social and Environmental Medicine, London School of Hygiene and Tropical Medicine, London, UK
9Bristol Medical School (THS)
10Health Methodology Research Group, School of Community-based Medicine, University of Manchester, Manchester, UK
11Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK

Tóm tắt

Natural experimental studies are often recommended as a way of understanding the health impact of policies and other large scale interventions. Although they have certain advantages over planned experiments, and may be the only option when it is impossible to manipulate exposure to the intervention, natural experimental studies are more susceptible to bias. This paper introduces new guidance from the Medical Research Council to help researchers and users, funders and publishers of research evidence make the best use of natural experimental approaches to evaluating population health interventions. The guidance emphasises that natural experiments can provide convincing evidence of impact even when effects are small or take time to appear. However, a good understanding is needed of the process determining exposure to the intervention, and careful choice and combination of methods, testing of assumptions and transparent reporting is vital. More could be learnt from natural experiments in future as experience of promising but lesser used methods accumulates.

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