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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

From: Developing pathways for community-led research with big data: a content analysis of stakeholder interviews

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