Maame Esi Woode, Udeni De Silva Perera, Chris Degeling, Yves Saint James Aquino, Nehmat Houssami, Stacy M Carter, Gang Chen
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This study examined the preferences of Australian women regarding AI use in breast cancer screening and the impact of information on preferences using discrete choice experiments.</p><p><strong>Methods: </strong>The experiment presented two alternative screening services based on seven attributes (reading method, screening sensitivity, screening specificity, time between screening and receiving results, supporting evidence, fair representation, and who should be held accountable) to 2063 women aged between 40 and 74 years recruited from an online panel. Participants were randomised into two arms. Both received standard information on AI use in breast screening, but one arm received additional information on its potential benefits. Preferences for hypothetical breast cancer screening services were modelled using a random parameter logit model. Relative attribute importance and uptake rates were estimated.</p><p><strong>Results: </strong>Participants preferred mixed reading (radiologist + AI system) over the other two reading methods. They showed a strong preference for fewer missed cases with a high attribute relative importance. Fewer false positives and a shorter waiting time for results were also preferred. Strength of preferences for mixed reading was significantly higher compared to two radiologists when additional information on AI is provided, highlighting the impact of information.</p><p><strong>Conclusions: </strong>This study revealed the preferences among Australian women for the use of AI-driven breast cancer screening services. Results generally suggest women are open to their mammograms being read by both a radiologist and an AI-based system under certain conditions.</p>","PeriodicalId":51271,"journal":{"name":"Patient-Patient Centered Outcomes Research","volume":" ","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment.\",\"authors\":\"Maame Esi Woode, Udeni De Silva Perera, Chris Degeling, Yves Saint James Aquino, Nehmat Houssami, Stacy M Carter, Gang Chen\",\"doi\":\"10.1007/s40271-025-00742-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Breast cancer screening is considered an effective early detection strategy. 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Preferences for hypothetical breast cancer screening services were modelled using a random parameter logit model. Relative attribute importance and uptake rates were estimated.</p><p><strong>Results: </strong>Participants preferred mixed reading (radiologist + AI system) over the other two reading methods. They showed a strong preference for fewer missed cases with a high attribute relative importance. Fewer false positives and a shorter waiting time for results were also preferred. Strength of preferences for mixed reading was significantly higher compared to two radiologists when additional information on AI is provided, highlighting the impact of information.</p><p><strong>Conclusions: </strong>This study revealed the preferences among Australian women for the use of AI-driven breast cancer screening services. 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Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment.
Background: Breast cancer screening is considered an effective early detection strategy. Artificial intelligence (AI) may both offer benefits and create risks for breast screening programmes. To use AI in health screening services, the views and expectations of consumers are critical. This study examined the preferences of Australian women regarding AI use in breast cancer screening and the impact of information on preferences using discrete choice experiments.
Methods: The experiment presented two alternative screening services based on seven attributes (reading method, screening sensitivity, screening specificity, time between screening and receiving results, supporting evidence, fair representation, and who should be held accountable) to 2063 women aged between 40 and 74 years recruited from an online panel. Participants were randomised into two arms. Both received standard information on AI use in breast screening, but one arm received additional information on its potential benefits. Preferences for hypothetical breast cancer screening services were modelled using a random parameter logit model. Relative attribute importance and uptake rates were estimated.
Results: Participants preferred mixed reading (radiologist + AI system) over the other two reading methods. They showed a strong preference for fewer missed cases with a high attribute relative importance. Fewer false positives and a shorter waiting time for results were also preferred. Strength of preferences for mixed reading was significantly higher compared to two radiologists when additional information on AI is provided, highlighting the impact of information.
Conclusions: This study revealed the preferences among Australian women for the use of AI-driven breast cancer screening services. Results generally suggest women are open to their mammograms being read by both a radiologist and an AI-based system under certain conditions.
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The Patient provides a venue for scientifically rigorous, timely, and relevant research to promote the development, evaluation and implementation of therapies, technologies, and innovations that will enhance the patient experience. It is an international forum for research that advances and/or applies qualitative or quantitative methods to promote the generation, synthesis, or interpretation of evidence.
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