Jenkinson George P, Houghton Natasha, van Zalk Nejra, Waller Jo, Bello Fernando, Tzemanaki Antonia
Bristol Robotics Laboratory, Department of Mechanical Engineering, University of Bristol, Bristol, United Kingdom.
Centre for Engagement and Simulation Science, Department of Surgery and Cancer, Imperial College London, London, United Kingdom.
J Particip Med. 2023 Apr 3;15:e42704. doi: 10.2196/42704.
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.
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.
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.
Most respondents (143/155, 92.3%) indicated that they would definitely or probably use R-CBE, with 82.6% (128/155) willing to be examined for up to 15 minutes. The most popular location for R-CBE was at a primary care setting, whereas the most accepted method for receiving the results was an on-screen display (with an option to print information) immediately after the examination. Thematic analysis of free-text responses identified the following 7 themes: women perceive that R-CBE has the potential to address limitations in current screening services; R-CBE may facilitate increased user choice and autonomy; ethical motivations for supporting R-CBE development; accuracy (and users' perceptions of accuracy) is essential; results management with clear communication is a priority for users; device usability is important; and integration with health services is key.
There is a high potential for the acceptance of R-CBE in its target user group and a high concordance between user expectations and technological feasibility. Early patient participation in the design process allowed the authors to identify key development priorities for ensuring that this new technology meets the needs of users. Ongoing patient and public involvement at each development stage is essential.
在英国,邀请50至70岁的女性进行乳房X光检查。然而,10%的浸润性乳腺癌发生在45岁及以下的女性中,这表明年轻女性的需求未得到满足。为这一人群确定合适的筛查方式具有挑战性;乳房X光检查的敏感性不足,而其他诊断方法具有侵入性或成本高昂。机器人临床乳房检查(R-CBE)——利用软机器人技术和机器学习进行全自动临床乳房检查——从理论上讲是一种很有前景的筛查方式,早期原型正在开发中。从一开始就在设计过程中了解潜在用户的观点并与患者合作,对于确保该技术以患者为中心的设计和实施至关重要。
本研究调查了女性对在乳腺癌筛查中使用软机器人技术和智能系统的态度和观点。旨在确定这种技术在理论上是否为潜在用户所接受,并确定技术和实施系统中对患者来说是优先事项的方面,以便将这些方面纳入技术设计。
本研究采用混合方法设计。我们对英国的155名女性进行了一项为期30分钟的网络调查。调查包括对提议概念的概述,随后是5个开放式问题和17个封闭式问题。通过与英国癌症研究患者参与机会网页链接的网络调查招募受访者,并通过研究网络的邮件列表进行分发。使用主题分析法对通过开放式问题生成的定性数据进行分析。使用双样本柯尔莫哥洛夫-斯米尔诺夫检验、单尾t检验和皮尔逊系数对定量数据进行分析。
大多数受访者(143/155,92.3%)表示她们肯定或可能会使用R-CBE,82.6%(128/155)愿意接受长达15分钟的检查。R-CBE最受欢迎的地点是初级保健机构,而接收结果最能接受的方式是检查后立即在屏幕上显示(并可选择打印信息)。对自由文本回复的主题分析确定了以下7个主题:女性认为R-CBE有可能解决当前筛查服务中的局限性;R-CBE可能有助于增加用户选择和自主性;支持R-CBE开发的伦理动机;准确性(以及用户对准确性的认知)至关重要;清晰沟通的结果管理是用户的优先事项;设备可用性很重要;与医疗服务的整合是关键。
R-CBE在其目标用户群体中被接受的可能性很高,并且用户期望与技术可行性之间高度一致。患者早期参与设计过程使作者能够确定关键的开发优先事项,以确保这项新技术满足用户需求。在每个开发阶段持续让患者和公众参与至关重要。