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BackgroundHealth data platforms and biobanks worldwide face challenges in maintaining social licence to operate (SLO) while enabling beneficial research. While technical safeguards can mitigate privacy risks, public expectations for governance oversight processes remain unclear. This study examines public attitudes toward health data governance oversight using Singapore's national TRUST platform as a case study. MethodsWe conducted an online survey of 453 respondents from the Health Opinion Panel Singapore (HOPS) panel in Singapore between September and October 2024. Respondents evaluated four hypothetical research scenarios involving different data users (government agencies, overseas private companies, international universities) and indicated whether additional Ministry of Health (MOH) review should be required despite 2-5 weeks procedural delays. We analysed support rates for this additional review, reasons for support or opposition, and responses about privacy-utility trade-offs. ResultsStrong public support for MOH oversight emerged across all scenarios (80-89%), with government accountability as the primary reason (68-76% of supporters). Support was the highest for research involving overseas private companies (89%) and lowest for domestic government research (80%). Respondents demonstrated sophisticated risk-benefit, context-dependent reasoning: 69% accepted privacy risks for direct personal benefits (retaining contact information for cancer risk notification), while 82% endorsed stringent protections for vulnerable populations (CCTV monitoring for rare disease research despite research impediments). ConclusionsThe Singaporean public expects comprehensive ethical oversight extending beyond privacy protection to encompass accountability, scientific validity, and social justice considerations. Consistent acceptance of procedural delays demonstrates that SLO depends on procedural justice rather than operational efficiency. These findings support implementing risk-proportionate governance frameworks that maintain robust baseline oversight while allowing context-sensitive intensification based on research characteristics and stakeholder involvement.
Published in: International Journal for Population Data Science
Volume 11, Issue 1