Table 2.

Summary of responses by a priori content codes. Key findings from the directed content analysis of key informant interviews (n = 16) summarized by content codes: Use cases, Desires and visions, Tools and supports, Barriers, Facilitators, and Attitudes

Content code	Summary of responses
Use cases	• Improve screening, treatment and prevention options • Nuanced risk prediction and decision-making tools • Investigate broad range of health determinants • Provide community agency via data access
Desires and visions	• Legitimise career paths for citizen scientists and patient advocates • Improve science and health literacy • Authentic collaborations • Accessible and affordable genetic tests
Tools and supports	• Mentorship and partnerships • Reliable and sustainable funding sources • Data tools and training • Data sharing platforms
Barriers	• Disconnect between healthcare, research and community needs • Data capacity challenges • Competing community priorities • Unfamiliarity with Big Data and research • Fear, trauma and mistrust associated with research experiences
Facilitators	• Collaboration frameworks and shared resources • Interoperability and centrality of data • Trust in leaders and political will
Attitudes	• Data are valuable and personal • Big Data currently lacks bidirectionality • Superficial community engagement • Data interpretation requires cultural context