Trust and Trade-Offs in Sharing Data for Precision Medicine: A National Survey of Singapore

被引:15
作者
Lysaght, Tamra [1 ]
Ballantyne, Angela [1 ,2 ]
Toh, Hui Jin [1 ]
Lau, Andrew [3 ]
Ong, Serene [1 ]
Schaefer, Owen [1 ]
Shiraishi, Makoto [1 ]
van den Boom, Willem [4 ]
Xafis, Vicki [1 ]
Tai, E. Shyong [5 ,6 ,7 ]
机构
[1] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Biomed Eth, Singapore 117597, Singapore
[2] Univ Otago, Dept Primary Hlth Care & Gen Practice, Wellington 6021, New Zealand
[3] Project Insights Consultants, Singapore 590003, Singapore
[4] Natl Univ Singapore, Yale NUS Coll, Singapore 138527, Singapore
[5] Natl Univ Singapore, Yong Loo Lin Sch Med, Singapore 117597, Singapore
[6] Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, Singapore 117549, Singapore
[7] Precis Hlth Res, Singapore 139234, Singapore
基金
英国医学研究理事会; 新加坡国家研究基金会;
关键词
Precision medicine; bioethics; trust; data sharing; survey; Singapore; PUBLIC PREFERENCES; CONJOINT-ANALYSIS; CONSENT; BIOBANK; PARTICIPATION; PERSPECTIVES; WILLINGNESS; ATTITUDES; OPINIONS; PRIVACY;
D O I
10.3390/jpm11090921
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Precision medicine (PM) programs typically use broad consent. This approach requires maintenance of the social license and public trust. The ultimate success of PM programs will thus likely be contingent upon understanding public expectations about data sharing and establishing appropriate governance structures. There is a lack of data on public attitudes towards PM in Asia. Methods: The aim of the research was to measure the priorities and preferences of Singaporeans for sharing health-related data for PM. We used adaptive choice-based conjoint analysis (ACBC) with four attributes: uses, users, data sensitivity and consent. We recruited a representative sample of n = 1000 respondents for an in-person household survey. Results: Of the 1000 respondents, 52% were female and majority were in the age range of 40-59 years (40%), followed by 21-39 years (33%) and 60 years and above (27%). A total of 64% were generally willing to share de-identified health data for IRB-approved research without re-consent for each study. Government agencies and public institutions were the most trusted users of data. The importance of the four attributes on respondents' willingness to share data were: users (39.5%), uses (28.5%), data sensitivity (19.5%), consent (12.6%). Most respondents found it acceptable for government agencies and hospitals to use de-identified data for health research with broad consent. Our sample was consistent with official government data on the target population with 52% being female and majority in the age range of 40-59 years (40%), followed by 21-39 years (33%) and 60 years and above (27%). Conclusions: While a significant body of prior research focuses on preferences for consent, our conjoint analysis found consent was the least important attribute for sharing data. Our findings suggest the social license for PM data sharing in Singapore currently supports linking health and genomic data, sharing with public institutions for health research and quality improvement; but does not support sharing with private health insurers or for private commercial use.
引用
收藏
页数:15
相关论文
共 31 条
[1]   "Who is watching the watchdog?": ethical perspectives of sharing health-related data for precision medicine in Singapore [J].
Lysaght, Tamra ;
Ballantyne, Angela ;
Xafis, Vicki ;
Ong, Serene ;
Schaefer, Gerald Owen ;
Ling, Jeffrey Min Than ;
Newson, Ainsley J. ;
Khor, Ing Wei ;
Tai, E. Shyong .
BMC MEDICAL ETHICS, 2020, 21 (01)
[2]   Sharing precision medicine data with private industry: Outcomes of a citizens' jury in Singapore [J].
Ballantyne, Angela ;
Lysaght, Tamra ;
Toh, Hui Jin ;
Ong, Serene ;
Lau, Andrew ;
Owen Schaefer, G. ;
Xafis, Vicki ;
Tai, E. Shyong ;
Newson, Ainsley J. ;
Carter, Stacy ;
Degeling, Chris ;
Braunack-Mayer, Annette .
BIG DATA & SOCIETY, 2022, 9 (01)
[3]   “Who is watching the watchdog?”: ethical perspectives of sharing health-related data for precision medicine in Singapore [J].
Tamra Lysaght ;
Angela Ballantyne ;
Vicki Xafis ;
Serene Ong ;
Gerald Owen Schaefer ;
Jeffrey Min Than Ling ;
Ainsley J. Newson ;
Ing Wei Khor ;
E. Shyong Tai .
BMC Medical Ethics, 21
[4]   Navigating bottlenecks and trade-offs in genomic data analysis [J].
Berger, Bonnie ;
Yu, Yun William .
NATURE REVIEWS GENETICS, 2023, 24 (04) :235-250
[5]   Household acceptability of energy efficiency policies in the European Union: Policy characteristics trade-offs and the role of trust in government and environmental identity [J].
Faure, Corinne ;
Guetlein, Marie-Charlotte ;
Schleich, Joachim ;
Tu, Gengyang ;
Whitmarsh, Lorraine ;
Whittle, Colin .
ECOLOGICAL ECONOMICS, 2022, 192
[6]   Secure Sharing Scheme of Sensitive Data in the Precision Medicine System [J].
Kim, Deukhun ;
Kim, Heejin ;
Kwak, Jin .
CMC-COMPUTERS MATERIALS & CONTINUA, 2020, 64 (03) :1527-1553
[7]   On the Trade-Offs of Combining Multiple Secure Processing Primitives for Data Analytics [J].
Carvalho, Hugo ;
Cruz, Daniel ;
Pontes, Rogerio ;
Paulo, Joao ;
Oliveira, Rui .
DISTRIBUTED APPLICATIONS AND INTEROPERABLE SYSTEMS, DAIS 2020, 2020, 12135 :3-20
[8]   The Public (Mis)Understanding of Fiscal Trade-offs - Evidence from a Survey Experiment in Poland [J].
Sawulski, Jakub ;
Kielczewska, Aneta .
EKONOMISTA, 2025, (01) :82-106
[9]   Travel-based multitasking behaviour in Singapore: Determinants and impacts on money-time-seat trade-offs [J].
Sun, Shanshan ;
Wong, Yiik Diew .
TRAVEL BEHAVIOUR AND SOCIETY, 2022, 26 :84-95
[10]   Where is the EU-UK relationship heading? A conjoint survey experiment of Brexit trade-offs [J].
Hix, Simon ;
van der Linden, Clifton ;
Massie, Joanna ;
Pickup, Mark ;
Savoie, Justin .
EUROPEAN UNION POLITICS, 2023, 24 (01) :184-205