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BMJ Open 3:e002703 doi:10.1136/bmjopen-2013-002703
  • Public health
    • Research

Women's responses to information about overdiagnosis in the UK breast cancer screening programme: a qualitative study

  1. Jane Wardle
  1. Department of Epidemiology and Public Health, Health Behaviour Research Centre, University College London, London, UK
  1. Correspondence to Dr Jo Waller; j.waller{at}ucl.ac.uk
  • Received 7 February 2013
  • Revised 10 March 2013
  • Accepted 12 March 2013
  • Published 22 April 2013

Abstract

Objectives To explore the influence of overdiagnosis information on women's decisions about mammography.

Design A qualitative focus group study with purposive sampling and thematic analysis, in which overdiagnosis information was presented.

Setting Community and university settings in London.

Participants 40 women within the breast screening age range (50–71 years) including attenders and non-attenders were recruited using a recruitment agency as well as convenience sampling methods.

Results Women expressed surprise at the possible extent of overdiagnosis and recognised the information as important, although many struggled to interpret the numerical data. Overdiagnosis was viewed as less-personally relevant than the possibility of ‘under diagnosis’ (false negatives), and often considered to be an issue for follow-up care decisions rather than screening participation. Women also expressed concern that information on overdiagnosis could deter others from attending screening, although they rarely saw it as a deterrent. After discussing overdiagnosis, few women felt that they would make different decisions about breast screening in the future.

Conclusions Women regard it as important to be informed about overdiagnosis to get a complete picture of the risks and benefits of mammography, but the results of this study indicate that understanding overdiagnosis may not always influence women's attitudes towards participation in breast screening. The results also highlight the challenge of communicating the individual significance of information derived from population-level modelling.

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/3.0/ and http://creativecommons.org/licenses/by-nc/3.0/legalcode

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