{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T18:27:42Z","timestamp":1776709662384,"version":"3.51.2"},"publisher-location":"New York, NY, USA","reference-count":75,"publisher":"ACM","funder":[{"DOI":"10.13039\/100000038","name":"FDA U.S. Food and Drug Administration","doi-asserted-by":"publisher","award":["U01FD005938"],"award-info":[{"award-number":["U01FD005938"]}],"id":[{"id":"10.13039\/100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,7,5]]},"DOI":"10.1145\/3715336.3735758","type":"proceedings-article","created":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T10:12:39Z","timestamp":1751623959000},"page":"676-690","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Toward Patient-Centered AI Fact Labels: Leveraging Extrinsic Trust Cues"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2738-1096","authenticated-orcid":false,"given":"Dong Whi","family":"Yoo","sequence":"first","affiliation":[{"name":"Indiana University Indianapolis, Indianapolis, Indiana, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8695-9786","authenticated-orcid":false,"given":"Austin M.","family":"Stroud","sequence":"additional","affiliation":[{"name":"Mayo Clinic, Rochester, Minnesota, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6675-2155","authenticated-orcid":false,"given":"Xuan","family":"Zhu","sequence":"additional","affiliation":[{"name":"Mayo Clinic, Rochester, Minnesota, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3591-369X","authenticated-orcid":false,"given":"Jennifer E.","family":"Miller","sequence":"additional","affiliation":[{"name":"Yale School of Medicine, New Haven, Connecticut, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0755-6939","authenticated-orcid":false,"given":"Barbara","family":"Barry","sequence":"additional","affiliation":[{"name":"Mayo Clinic, Rochester, Minnesota, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,7,4]]},"reference":[{"key":"e_1_3_3_2_2_2","unstructured":"Naomi Alderman Raj Gupta and Kendra et\u00a0al. Lewis. 2025. Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations. The Lancet Digital Health (2025). forthcoming."},{"key":"e_1_3_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445736"},{"key":"e_1_3_3_2_4_2","doi-asserted-by":"crossref","unstructured":"Matthew Arnold Rachel\u00a0KE Bellamy Michael Hind Stephanie Houde Sameep Mehta Aleksandra Mojsilovi\u0107 Ravi Nair K\u00a0Natesan Ramamurthy Alexandra Olteanu David Piorkowski et\u00a0al. 2019. FactSheets: Increasing trust in AI services through supplier\u2019s declarations of conformity. IBM Journal of Research and Development 63 4\/5 (2019) 6\u20131.","DOI":"10.1147\/JRD.2019.2942288"},{"key":"e_1_3_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3563657.3596110"},{"key":"e_1_3_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3581518"},{"key":"e_1_3_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3534626"},{"key":"e_1_3_3_2_8_2","doi-asserted-by":"crossref","unstructured":"Karen\u00a0L Boyd. 2021. Datasheets for datasets help ML engineers notice and understand ethical issues in training data. Proceedings of the ACM on Human-Computer Interaction 5 CSCW2 (2021) 1\u201327.","DOI":"10.1145\/3479582"},{"key":"e_1_3_3_2_9_2","doi-asserted-by":"crossref","unstructured":"Virginia Braun and Victoria Clarke. 2019. Reflecting on reflexive thematic analysis. Qualitative research in sport exercise and health 11 4 (2019) 589\u2013597.","DOI":"10.1080\/2159676X.2019.1628806"},{"key":"e_1_3_3_2_10_2","first-page":"19","volume-title":"Supporting research in counselling and psychotherapy: Qualitative, quantitative, and mixed methods research","author":"Braun Virginia","year":"2023","unstructured":"Virginia Braun, Victoria Clarke, Nikki Hayfield, Louise Davey, and Elizabeth Jenkinson. 2023. Doing reflexive thematic analysis. In Supporting research in counselling and psychotherapy: Qualitative, quantitative, and mixed methods research. Springer, 19\u201338."},{"key":"e_1_3_3_2_11_2","doi-asserted-by":"crossref","unstructured":"Michael Bretthauer Sara Gerke Cesare Hassan Omer\u00a0F Ahmad and Yuichi Mori. 2023. The new European Medical Device Regulation: balancing innovation and patient safety. Annals of Internal Medicine 176 6 (2023) 844\u2013848.","DOI":"10.7326\/M23-0454"},{"key":"e_1_3_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3581251"},{"key":"e_1_3_3_2_13_2","doi-asserted-by":"crossref","unstructured":"David Byrne. 2022. A worked example of Braun and Clarke\u2019s approach to reflexive thematic analysis. Quality & quantity 56 3 (2022) 1391\u20131412.","DOI":"10.1007\/s11135-021-01182-y"},{"key":"e_1_3_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3580805"},{"key":"e_1_3_3_2_15_2","unstructured":"Marshall\u00a0H Chin David\u00a0R Williams et\u00a0al. 2023. Guiding Principles to Address the Impact of Algorithmic Bias on Racial and Ethnic Disparities in Health Care. JAMA Network Open 6 1 (2023) e2252823\u2013e2252823."},{"key":"e_1_3_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3593013.3594073"},{"key":"e_1_3_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533108"},{"key":"e_1_3_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533113"},{"key":"e_1_3_3_2_19_2","doi-asserted-by":"crossref","unstructured":"Marcus D\u00f6rr Vivien Nohturfft No\u00e9 Brasier Emil Bosshard Aleksandar Djurdjevic Stefan Gross Christina\u00a0J Raichle Mattias Rhinisperger Raphael St\u00f6ckli and Jens Eckstein. 2019. The WATCH AF trial: SmartWATCHes for detection of atrial fibrillation. JACC: Clinical Electrophysiology 5 2 (2019) 199\u2013208.","DOI":"10.1016\/j.jacep.2018.10.006"},{"key":"e_1_3_3_2_20_2","doi-asserted-by":"crossref","unstructured":"Glyn Elwyn Dominick Frosch Richard Thomson Natalie Joseph-Williams Amy Lloyd Paul Kinnersley Emma Cording Dave Tomson Carole Dodd Stephen Rollnick et\u00a0al. 2012. Shared decision making: a model for clinical practice. Journal of general internal medicine 27 (2012) 1361\u20131367.","DOI":"10.1007\/s11606-012-2077-6"},{"key":"e_1_3_3_2_21_2","doi-asserted-by":"crossref","unstructured":"Ronald\u00a0M Epstein and Richard\u00a0L Street. 2011. The values and value of patient-centered care. 100\u2013103\u00a0pages.","DOI":"10.1370\/afm.1239"},{"key":"e_1_3_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533202"},{"key":"e_1_3_3_2_23_2","unstructured":"Food and Drug Administration. 2024. Artificial Intelligence and Machine Learning (AI\/ML) Enabled Medical Devices. https:\/\/www.fda.gov\/medical-devices\/software-medical-device-samd\/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices. Accessed: 2024-08-08."},{"key":"e_1_3_3_2_24_2","unstructured":"Center for Devices and Radiological Health. 2023. 510(k) Clearances. https:\/\/www.fda.gov\/medical-devices\/device-approvals-denials-and-clearances\/510k- clearances. [Accessed 08-08-2024]."},{"key":"e_1_3_3_2_25_2","unstructured":"Center for Drug\u00a0Evaluation and Research.2015. OTC Drug Facts Label \u2014 fda.gov. https:\/\/www.fda.gov\/drugs\/information-consumers-and-patients-drugs\/otc-drug-facts-label. [Accessed 08-08-2024]."},{"key":"e_1_3_3_2_26_2","doi-asserted-by":"crossref","unstructured":"Timnit Gebru Jamie Morgenstern Briana Vecchione Jennifer\u00a0Wortman Vaughan Hanna Wallach Hal\u00a0Daum\u00e9 Iii and Kate Crawford. 2021. Datasheets for datasets. Commun. ACM 64 12 (2021) 86\u201392.","DOI":"10.1145\/3458723"},{"key":"e_1_3_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300688"},{"key":"e_1_3_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3642353"},{"key":"e_1_3_3_2_29_2","doi-asserted-by":"crossref","unstructured":"Feras Hatib Zhongping Jian Sai Buddi Christine Lee Jos Settels Karen Sibert Joseph Rinehart and Maxime Cannesson. 2018. Machine-learning algorithm to predict hypotension based on high-fidelity arterial pressure waveform analysis. Anesthesiology 129 4 (2018) 663\u2013674.","DOI":"10.1097\/ALN.0000000000002300"},{"key":"e_1_3_3_2_30_2","doi-asserted-by":"crossref","unstructured":"Gillian\u00a0R Hayes. 2011. The relationship of action research to human-computer interaction. ACM Transactions on Computer-Human Interaction (TOCHI) 18 3 (2011) 1\u201320.","DOI":"10.1145\/1993060.1993065"},{"key":"e_1_3_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300809"},{"key":"e_1_3_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.1145\/3643834.3660697"},{"key":"e_1_3_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1145\/3442188.3445923"},{"key":"e_1_3_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300469"},{"key":"e_1_3_3_2_35_2","doi-asserted-by":"crossref","unstructured":"Nicholas Jenkins Michael Bloor Jan Fischer Lee Berney and Joanne Neale. 2010. Putting it in context: the use of vignettes in qualitative interviewing. Qualitative research 10 2 (2010) 175\u2013198.","DOI":"10.1177\/1468794109356737"},{"key":"e_1_3_3_2_36_2","doi-asserted-by":"crossref","unstructured":"Eunkyung Jo Rachael Zehrung Katherine Genuario Alexandra Papoutsaki and Daniel\u00a0A Epstein. 2024. Exploring Patient-Generated Annotations to Digital Clinical Symptom Measures for Patient-Centered Communication. Proceedings of the ACM on Human-Computer Interaction 8 CSCW2 (2024) 1\u201326.","DOI":"10.1145\/3686997"},{"key":"e_1_3_3_2_37_2","doi-asserted-by":"crossref","unstructured":"Geeta Joshi Aditi Jain Shalini\u00a0Reddy Araveeti Sabina Adhikari Harshit Garg and Mukund Bhandari. 2024. FDA-approved artificial intelligence and machine learning (AI\/ML)-enabled medical devices: an updated landscape. Electronics 13 3 (2024) 498.","DOI":"10.3390\/electronics13030498"},{"key":"e_1_3_3_2_38_2","doi-asserted-by":"crossref","unstructured":"Davinder Kaur Suleyman Uslu Kaley\u00a0J Rittichier and Arjan Durresi. 2022. Trustworthy artificial intelligence: a review. ACM computing surveys (CSUR) 55 2 (2022) 1\u201338.","DOI":"10.1145\/3491209"},{"key":"e_1_3_3_2_39_2","doi-asserted-by":"publisher","DOI":"10.1145\/3593013.3593986"},{"key":"e_1_3_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1145\/3643834.3661612"},{"key":"e_1_3_3_2_41_2","doi-asserted-by":"crossref","unstructured":"Chayakrit Krittanawong HongJu Zhang Zhen Wang Mehmet Aydar and Takeshi Kitai. 2017. Artificial intelligence in precision cardiovascular medicine. Journal of the American College of Cardiology 69 21 (2017) 2657\u20132664.","DOI":"10.1016\/j.jacc.2017.03.571"},{"key":"e_1_3_3_2_42_2","doi-asserted-by":"crossref","unstructured":"Audrey Lee Turner\u00a0S Baker Joshua\u00a0B Bederson and Benjamin\u00a0I Rapoport. 2024. Levels of autonomy in FDA-cleared surgical robots: a systematic review. NPJ Digital Medicine 7 1 (2024) 103.","DOI":"10.1038\/s41746-024-01102-y"},{"key":"e_1_3_3_2_43_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533182"},{"key":"e_1_3_3_2_44_2","doi-asserted-by":"publisher","unstructured":"Shih-Chieh Lin and Ling-Jyh Juang. 2023. A Survey of Digital Twin Technology and its Applications: Healthcare Smart Grid and Future Internet. Comput. Surveys 55 10 (2023). 10.1145\/3555803","DOI":"10.1145\/3555803"},{"key":"e_1_3_3_2_45_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mayocp.2020.01.038"},{"key":"e_1_3_3_2_46_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3581058"},{"key":"e_1_3_3_2_47_2","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376445"},{"key":"e_1_3_3_2_48_2","doi-asserted-by":"publisher","DOI":"10.1145\/3630106.3658964"},{"key":"e_1_3_3_2_49_2","doi-asserted-by":"publisher","DOI":"10.1145\/3563657.3595979"},{"key":"e_1_3_3_2_50_2","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287596"},{"key":"e_1_3_3_2_51_2","doi-asserted-by":"crossref","unstructured":"Ziad Obermeyer Brian Powers Christine Vogeli and Sendhil Mullainathan. 2019. Dissecting racial bias in an algorithm used to manage the health of populations. Science 366 6464 (2019) 447\u2013453.","DOI":"10.1126\/science.aax2342"},{"key":"e_1_3_3_2_52_2","doi-asserted-by":"crossref","unstructured":"Marco\u00a0V Perez Kenneth\u00a0W Mahaffey Haley Hedlin John\u00a0S Rumsfeld Ariadna Garcia Todd Ferris Vidhya Balasubramanian Andrea\u00a0M Russo Amol Rajmane Lauren Cheung et\u00a0al. 2019. Large-scale assessment of a smartwatch to identify atrial fibrillation. New England Journal of Medicine 381 20 (2019) 1909\u20131917.","DOI":"10.1056\/NEJMoa1901183"},{"key":"e_1_3_3_2_53_2","doi-asserted-by":"crossref","unstructured":"Brian\u00a0S Peters Priscila\u00a0R Armijo Crystal Krause Songita\u00a0A Choudhury and Dmitry Oleynikov. 2018. Review of emerging surgical robotic technology. Surgical endoscopy 32 (2018) 1636\u20131655.","DOI":"10.1007\/s00464-018-6079-2"},{"key":"e_1_3_3_2_54_2","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376818"},{"key":"e_1_3_3_2_55_2","doi-asserted-by":"crossref","unstructured":"Rashmika Potdar Arun Thomas Matthew DiMeglio Kamran Mohiuddin Djeneba\u00a0Audrey Djibo Krzysztof Laudanski Claudia\u00a0M Dourado John\u00a0Charles Leighton and Jean\u00a0G Ford. 2020. Access to internet smartphone usage and acceptability of mobile health technology among cancer patients. Supportive Care in Cancer 28 (2020) 5455\u20135461.","DOI":"10.1007\/s00520-020-05393-1"},{"key":"e_1_3_3_2_56_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533231"},{"key":"e_1_3_3_2_57_2","doi-asserted-by":"publisher","DOI":"10.1145\/3514094.3534181"},{"key":"e_1_3_3_2_58_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533239"},{"key":"e_1_3_3_2_59_2","doi-asserted-by":"publisher","DOI":"10.1145\/3593013.3593994"},{"key":"e_1_3_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-57321-8_12"},{"key":"e_1_3_3_2_61_2","doi-asserted-by":"crossref","unstructured":"Isabelle Scholl J\u00f6rdis\u00a0M Zill Martin H\u00e4rter and J\u00f6rg Dirmaier. 2014. An integrative model of patient-centeredness\u2013a systematic review and concept analysis. PloS one 9 9 (2014) e107828.","DOI":"10.1371\/journal.pone.0107828"},{"key":"e_1_3_3_2_62_2","doi-asserted-by":"crossref","unstructured":"Lisa\u00a0M Schwartz and Steven Woloshin. 2013. The Drug Facts Box: Improving the communication of prescription drug information. Proceedings of the National Academy of Sciences 110 supplement_3 (2013) 14069\u201314074.","DOI":"10.1073\/pnas.1214646110"},{"key":"e_1_3_3_2_63_2","doi-asserted-by":"crossref","unstructured":"Mark\u00a0P Sendak Michael Gao Nathan Brajer and Suresh Balu. 2020. Presenting machine learning model information to clinical end users with model facts labels. NPJ digital medicine 3 1 (2020) 41.","DOI":"10.1038\/s41746-020-0253-3"},{"key":"e_1_3_3_2_64_2","unstructured":"Parth Shah Imani Thornton Danielle Turrin and John\u00a0E Hipskind. 2014. Informed consent. StatPearls (2014)."},{"key":"e_1_3_3_2_65_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533110"},{"key":"e_1_3_3_2_66_2","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372870"},{"key":"e_1_3_3_2_67_2","doi-asserted-by":"crossref","unstructured":"Alexander\u00a0F Stevens and Pete Stetson. 2023. Theory of trust and acceptance of artificial intelligence technology (TrAAIT): An instrument to assess clinician trust and acceptance of artificial intelligence. Journal of biomedical informatics 148 (2023) 104550.","DOI":"10.1016\/j.jbi.2023.104550"},{"key":"e_1_3_3_2_68_2","doi-asserted-by":"crossref","unstructured":"Anne\u00a0M Stiggelbout Trudy Van\u00a0der Weijden Maarten\u00a0PT De\u00a0Wit Dominick Frosch France L\u00e9gar\u00e9 Victor\u00a0M Montori Lyndal Trevena and Glenn Elwyn. 2012. Shared decision making: really putting patients at the centre of healthcare. Bmj 344 (2012).","DOI":"10.1136\/bmj.e256"},{"key":"e_1_3_3_2_69_2","unstructured":"Apple Support. 2024. About iOS 17 Updates. https:\/\/support.apple.com\/en-us\/120276. Accessed: 2024-08-08."},{"key":"e_1_3_3_2_70_2","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372834"},{"key":"e_1_3_3_2_71_2","doi-asserted-by":"crossref","unstructured":"Mintu\u00a0P Turakhia Manisha Desai Haley Hedlin Amol Rajmane Nisha Talati Todd Ferris Sumbul Desai Divya Nag Mithun Patel Peter Kowey et\u00a0al. 2019. Rationale and design of a large-scale app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study. American heart journal 207 (2019) 66\u201375.","DOI":"10.1016\/j.ahj.2018.09.002"},{"key":"e_1_3_3_2_72_2","doi-asserted-by":"publisher","DOI":"10.4108\/icst.pervasivehealth.2014.254975"},{"key":"e_1_3_3_2_73_2","doi-asserted-by":"crossref","unstructured":"Christoph Wilhelm Anke Steckelberg and Felix\u00a0G Rebitschek. 2025. Benefits and harms associated with the use of AI-related algorithmic decision-making systems by healthcare professionals: a systematic review. The Lancet Regional Health\u2013Europe 48 (2025).","DOI":"10.1016\/j.lanepe.2024.101145"},{"key":"e_1_3_3_2_74_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300509"},{"key":"e_1_3_3_2_75_2","doi-asserted-by":"crossref","unstructured":"Kun-Hsing Yu Andrew\u00a0L Beam and Isaac\u00a0S Kohane. 2018. Artificial intelligence in healthcare. Nature biomedical engineering 2 10 (2018) 719\u2013731.","DOI":"10.1038\/s41551-018-0305-z"},{"key":"e_1_3_3_2_76_2","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372852"}],"event":{"name":"DIS '25: Designing Interactive Systems Conference","location":"Madeira Portugal","acronym":"DIS '25","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["Proceedings of the 2025 ACM Designing Interactive Systems Conference"],"original-title":[],"deposited":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T11:25:37Z","timestamp":1751628337000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3715336.3735758"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,4]]},"references-count":75,"alternative-id":["10.1145\/3715336.3735758","10.1145\/3715336"],"URL":"https:\/\/doi.org\/10.1145\/3715336.3735758","relation":{},"subject":[],"published":{"date-parts":[[2025,7,4]]},"assertion":[{"value":"2025-07-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}