Using dataflow diagrams to support research informed consent data management communications: participant perspectives

Area of Science:

• Digital Health
• Informed Consent
• Data Management

Background:

• Digital health research generates large volumes of personal health data, complicating informed consent processes.
• Effectively communicating data management practices and associated risks to participants is a significant challenge.

Purpose of the Study:

• To explore the utility of dataflow diagrams (DFDs) in complementing informed consent for digital health research.
• To assess whether DFDs can improve participants' understanding of data management and associated risks.

Main Methods:

• Conducted eight semi-structured focus groups with 34 participants.
• Explored participants' perceptions of DFDs for conveying data management and sharing practices.

Main Results:

• DFDs can supplement text-based informed consent by clarifying data management and sharing, prompting participant questions.
• Participants emphasized the need for clear, simple, participant-centered DFDs, especially for high-risk areas like third-party data access.
• DFDs complement, but do not replace, traditional informed consent documents.

Conclusions:

• Prospective participants value diverse methods, including visualizations like DFDs, to understand research risks and benefits.
• Visualizing consent information can help overcome digital and data literacy barriers in research participation.
• Developing DFDs requires significant effort; shared infrastructure and incentives are needed to support their creation.