Introduction
To improve participant engagement and data quality on Evidation Health's digital health studies platform, we need to carefully analyze user behavior, pain points, and potential solutions. I'll approach this by examining key stakeholders, identifying critical pain points, generating innovative solutions, and proposing metrics to measure success.
Step 1
Clarifying Questions
Why it matters: This helps tailor solutions to specific study types and user groups. Expected answer: A mix of short-term and longitudinal studies across various health conditions, with participants ranging from young adults to seniors. Impact on approach: Would influence feature prioritization based on study complexity and user tech-savviness.
Why it matters: Identifies where engagement drops off and potential areas for improvement. Expected answer: Higher engagement in short-term studies (80%), dropping to 60% for long-term studies after 3 months. Impact on approach: Would focus on features to maintain long-term engagement for extended studies.
Why it matters: Helps prioritize features that directly impact data integrity. Expected answer: Inconsistent data entry, missed check-ins, and potential bias in self-reported data. Impact on approach: Would emphasize solutions for data validation and automated data collection.
Why it matters: Identifies areas where we can differentiate and improve relative to competitors. Expected answer: Strong in user interface but lagging in personalization and gamification features. Impact on approach: Would explore innovative engagement features to set the platform apart.
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