|Appears in Collections:||Economics Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Women 's responses to information about overdiagnosis in the UK breast cancer screening programme: A qualitative study|
Whitaker, Katriina L
|Citation:||Waller J, Douglas E, Whitaker KL & Wardle J (2013) Women 's responses to information about overdiagnosis in the UK breast cancer screening programme: A qualitative study, BMJ Open, 3 (4), Art. No.: e002703.|
|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.|
|Rights:||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|
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact email@example.com providing details and we will remove the Work from public display in STORRE and investigate your claim.