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ORIGINAL RESEARCH article
Front. Cancer Control Soc.
Sec. Behavioural Aspects in Cancer Screening and Diagnosis
Volume 3 - 2025 |
doi: 10.3389/fcacs.2025.1522609
This article is part of the Research Topic Behavioral Research into Acceptability of Cancer Early Diagnosis View all articles
The public are receptive to risk-based innovations: A multi-methods exploration of anticipated acceptability and uptake of novel technologies for cancer early detection in symptomatic and asymptomatic scenarios
Provisionally accepted- 1 University of Cambridge, Cambridge, United Kingdom
- 2 Queen Mary University of London, London, United Kingdom
Introduction: New technologies and innovations are emerging that enable stratification of individuals based on their risk of cancer and enable screening or diagnostic investigations to be targeted to those at greatest need. This study aimed to explore, in depth, attitudes of the UK public towards this concept; specifically, anticipated acceptability and uptake, including barriers and enablers towards uptake.A survey was completed independently by a representative population sample and alongside a researcher in think aloud interviews. Participants considered three of six exemplars of innovations that enable risk assessment: polygenic risk scores, geodemographic segmentation, continuous biomarker monitoring, minimally invasive tests, artificial intelligence analysis of medical records, and wearable devices. Questions about likelihood of taking up the risk assessment, acceptability of risk-stratified healthcare, and comfort about risk results being used within healthcare generally were set in asymptomatic then symptomatic scenarios.Descriptive statistics and multivariable logistic regression were used to explore differences between the exemplars and contexts and the impact of individual characteristics. Interviews were analysed using codebook thematic analysis guided by the Theoretical Framework of Acceptability. Free-text comments were also analysed thematically.Results: 999 participants completed the survey independently and 21 participants completed interviews. Most were extremely or somewhat likely to take up risk assessments, ranging from 62.0% for geodemographic segmentation to 85.2% for minimally invasive tests in the asymptomatic scenario, and from 64.2% for geodemographic segmentation to 94.0% for minimally invasive tests in the symptomatic scenario. Acceptability of using the exemplars within risk-stratified screening or referral pathways followed a similar pattern, as did comfort with the results being used widely. Qualitative analyses showed that the innovations and riskbased approach were viewed as proactive and logical. Tests requiring low burden were preferred, although most participants did not consider the burden of any of the innovations to be too high, particularly in the symptomatic context.Risk-based innovations for cancer early detection are intuitive. Study participants would be likely to engage and support their use for risk stratification, particularly for decisions about symptom investigations. These findings justify and promote ongoing research to develop these technologies and highlight features that increase public acceptability.
Keywords: cancer screening, Health Policy, personalized medicine, Risk factors, Artificial Intelligence, Genetic Risk
Received: 04 Nov 2024; Accepted: 20 Jan 2025.
Copyright: © 2025 Dennison, Clune, Tung, Schumacher, Solovyeva, Pandey, Taylor, Waller and Usher-Smith. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Rebecca A Dennison, University of Cambridge, Cambridge, United Kingdom
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