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Motivations for data sharing-views of research participants from four European countries: A DIRECT study.

Nisha ShahVictoria CoathupHarriet TeareIan ForgieGiuseppe Nicola GiordanoTue Haldor HansenLenka GroeneveldMichelle HudsonEwan PearsonHartmut RuettenJane Kaye
Published in: European journal of human genetics : EJHG (2019)
The purpose of this study was to explore and compare different countries in what motivated research participants' decisions whether to share their de-identified data. We investigated European DIRECT (Diabetes Research on Patient Stratification) research project participants' desire for control over sharing different types of their de-identified data, and with who data could be shared in the future after the project ends. A cross-sectional survey was disseminated among DIRECT project participants. The results found that there was a significant association between country and attitudes towards advancing research, protecting privacy, and beliefs about risks and benefits to sharing data. When given the choice to have control, some participants (<50% overall) indicated that having control over what data is shared and with whom was important; and control over what data types are shared was less important than respondents deciding who data are shared with. Danish respondents indicated higher odds of desire to control data types shared, and Dutch respondents showed higher odds of desire to control who data will be shared with. Overall, what research participants expect in terms of control over data sharing needs to be considered and aligned with sharing for future research and re-use of data. Our findings show that even with de-identified data, respondents prioritise privacy above all else. This study argues to move research participants from passive participation in biomedical research to considering their opinions about data sharing and control of de-identified biomedical data.
Keyphrases
  • electronic health record
  • big data
  • social media
  • machine learning
  • physical activity
  • artificial intelligence
  • climate change
  • risk assessment
  • insulin resistance
  • decision making