@article{Jenkinson:2023:10.2196/42704,
author = {Jenkinson, G and Houghton, N and van, Zalk N and Waller, J and Bello, F and Tzemanaki, A},
doi = {10.2196/42704},
journal = {Journal of Participatory Medicine},
pages = {1--16},
title = {Acceptability of automated robotic clinical breast examination: survey study},
url = {http://dx.doi.org/10.2196/42704},
volume = {15},
year = {2023}
}

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TY  - JOUR
AB  - Background:In the United Kingdom, women aged 50 to 70 years are invited to undergo mammography. However, 10% of invasive breast cancers occur in women aged ≤45 years, representing an unmet need for young women. Identifying a suitable screening modality for this population is challenging; mammography is insufficiently sensitive, whereas alternative diagnostic methods are invasive or costly. Robotic clinical breast examination (R-CBE)—using soft robotic technology and machine learning for fully automated clinical breast examination—is a theoretically promising screening modality with early prototypes under development. Understanding the perspectives of potential users and partnering with patients in the design process from the outset is essential for ensuring the patient-centered design and implementation of this technology.Objective:This study investigated the attitudes and perspectives of women regarding the use of soft robotics and intelligent systems in breast cancer screening. It aimed to determine whether such technology is theoretically acceptable to potential users and identify aspects of the technology and implementation system that are priorities for patients, allowing these to be integrated into technology design.Methods:This study used a mixed methods design. We conducted a 30-minute web-based survey with 155 women in the United Kingdom. The survey comprised an overview of the proposed concept followed by 5 open-ended questions and 17 closed questions. Respondents were recruited through a web-based survey linked to the Cancer Research United Kingdom patient involvement opportunities web page and distributed through research networks’ mailing lists. Qualitative data generated via the open-ended questions were analyzed using thematic analysis. Quantitative data were analyzed using 2-sample Kolmogorov-Smirnov tests, 1-tailed t tests, and Pearson coefficients.Results:Most respondents (143/155, 92.3%) indicated that they would definitely or
AU  - Jenkinson,G
AU  - Houghton,N
AU  - van,Zalk N
AU  - Waller,J
AU  - Bello,F
AU  - Tzemanaki,A
DO  - 10.2196/42704
EP  - 16
PY  - 2023///
SN  - 2152-7202
SP  - 1
TI  - Acceptability of automated robotic clinical breast examination: survey study
T2  - Journal of Participatory Medicine
UR  - http://dx.doi.org/10.2196/42704
UR  - https://jopm.jmir.org/2023/1/e42704
UR  - http://hdl.handle.net/10044/1/103235
VL  - 15
ER  - 

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