Evidence map›Paper›PMID 37010907›Full record

ArticleJournal of participatory medicine2023

Acceptability of Automated Robotic Clinical Breast Examination: Survey Study.

George P Jenkinson, Natasha Houghton, Nejra van Zalk, Jo Waller, Fernando Bello, Antonia Tzemanaki

Open access · goldAbstract read
In one paragraph

Article in Journal of participatory medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

George P Jenkinson *Bristol Robotics Laboratory, Department of Mechanical Engineering, University of Bristol, Bristol, United Kingdom.ORCID https://orcid.org/0000-0002-2489-8471
Natasha Houghton *Centre for Engagement and Simulation Science, Department of Surgery and Cancer, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-0316-9042
Nejra van ZalkDyson School of Design Engineering, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-3504-9037
Jo WallerCancer Prevention Group, School of Cancer & Pharmaceutical Sciences, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-4025-9132
Fernando BelloCentre for Engagement and Simulation Science, Department of Surgery and Cancer, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-4136-0355
Antonia TzemanakiBristol Robotics Laboratory, Department of Mechanical Engineering, University of Bristol, Bristol, United Kingdom.ORCID https://orcid.org/0000-0002-6043-1836
Imperial College London · GBUniversity of Bristol · GBDyson (United Kingdom) · GBKing's College London · GB

Funding

Cancer Research UK 30038
6 · The paper itself

Abstract

backgroundIn 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.

objectiveThis 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.

methodsThis 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.

resultsMost 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.

conclusionsThere 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.

Indexed as

automated diagnosisbreast cancerbreast cancer detectionbreast examinationhealth care roboticsmammographyparticipatory designpatient and public involvementuser acceptability

Identifiers

PMID37010907
PMCPMC10131668
OpenAlexW4321383330

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.