Acceptability of Automated Robotic Clinical Breast Examination: Survey Study

Area of Science:

• Biomedical Engineering
• Oncology
• Medical Robotics

Background:

• Mammography screening in the UK targets women aged 50-70, missing younger women (≤45 years) who account for 10% of invasive breast cancers.
• Current screening methods for younger women are limited, with mammography lacking sensitivity and alternatives being invasive or costly.
• Robotic clinical breast examination (R-CBE), utilizing soft robotics and machine learning, presents a promising, automated screening alternative.

Purpose of the Study:

• To investigate women's attitudes towards soft robotics and intelligent systems for breast cancer screening.
• To assess the theoretical acceptability of R-CBE among potential users.
• To identify patient priorities for R-CBE technology and implementation to guide patient-centered design.

Main Methods:

• A mixed-methods approach was employed, including a 30-minute web-based survey for 155 UK women.
• The survey incorporated an overview of R-CBE, 5 open-ended, and 17 closed questions.
• Qualitative data were analyzed thematically, and quantitative data using statistical tests (Kolmogorov-Smirnov, t-tests, Pearson coefficients).

Main Results:

• Over 92% of respondents (143/155) expressed willingness to use R-CBE, with 82.6% (128/155) comfortable with a 15-minute examination duration.
• Primary care settings were preferred for R-CBE, and immediate on-screen results were favored.
• Thematic analysis revealed key user priorities: addressing current screening limitations, enhancing user autonomy, ethical considerations, perceived accuracy, clear results management, device usability, and health service integration.

Conclusions:

• R-CBE demonstrates high potential for acceptance among its target user group, aligning user expectations with technological capabilities.
• Early patient involvement identified crucial development priorities for user-centered R-CBE design.
• Continuous patient and public engagement throughout the development lifecycle is vital for successful implementation.