Attitudes towards risk-stratified breast cancer screening among women in England: A cross-sectional survey.


Journal

Journal of medical screening
ISSN: 1475-5793
Titre abrégé: J Med Screen
Pays: England
ID NLM: 9433359

Informations de publication

Date de publication:
09 2020
Historique:
pubmed: 9 11 2019
medline: 11 5 2021
entrez: 9 11 2019
Statut: ppublish

Résumé

Risk stratification may improve the benefit/harm ratio of breast screening. Research on acceptability among potential invitees is necessary to guide implementation. We assessed women's attitudes towards and willingness to undergo risk assessment and stratified screening. Women in England aged 40-70 received summary information about the topic, and completed face-to-face computer-assisted interviews. Questions assessed willingness to undergo multifactorial breast cancer risk assessment, more frequent breast screening (if at very high risk), or less frequent or no screening (if at very low risk), and preferences for delivery of assessment results. Among 933 women, 85% considered breast cancer risk assessment a good idea, and 74% were willing to have it. Among 125 women unwilling to have risk assessment, reasons commonly related to 'worry' (14%) and 'preferring not to know' (14%). Among those willing to have risk assessment ( Women were generally in favour of multifactorial breast cancer risk assessment and risk-stratified screening. Some were unwilling to accept less or no screening if at very low risk.

Identifiants

pubmed: 31701797
doi: 10.1177/0969141319883662
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

138-145

Subventions

Organisme : Cancer Research UK
ID : 14134
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C1418/A14134
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C7492/A17219
Pays : United Kingdom

Auteurs

Alex Ghanouni (A)

Research Department of Behavioural Science and Health, University College London, London, UK.

Saskia C Sanderson (SC)

Institute of Health Informatics, University College London, London, UK.

Nora Pashayan (N)

Department of Applied Health Research, University College London, London, UK.

Cristina Renzi (C)

Research Department of Behavioural Science and Health, University College London, London, UK.

Christian von Wagner (C)

Research Department of Behavioural Science and Health, University College London, London, UK.

Jo Waller (J)

Research Department of Behavioural Science and Health, University College London, London, UK.

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Classifications MeSH