Join Stephanie David, Vital Findings, and Elena Scheer-Moser, iRhythm, for lessons from a hybrid qual study exploring how patients feel about AI’s role in cardiac monitoring and health data. The project used human-moderated focus groups, AI-moderated interviews, and quantitative validation to understand what patients think about AI in healthcare, as well as what AI can and cannot do well as a research method.
When to Use AI in Qual Research and When Human Moderation Still Matters:
Lessons from a hybrid qual study on patient trust, health data, and AI
AI-moderated research moves fast, reaches more people, and helps teams pressure-test emerging insights. But it does not replace the role of skilled human moderation, especially when the topic involves emotion, risk, uncertainty, or trust.
In this webinar, Stephanie David from Vital Findings and Elena Scheer-Moser from iRhythm will share lessons from a hybrid qual study exploring how patients feel about AI’s role in cardiac monitoring and health data. The project used human-moderated focus groups, AI-moderated interviews, and quantitative validation to understand what patients think about AI in healthcare, as well as what AI can and cannot do well as a research method.
In this webinar, we’ll cover:
- Where AI-moderated interviews add the most value: speed, scale, iteration, and pressure-testing.
- Where human moderation remains essential: emotion, nuance, trust, judgment, and high-stakes topics.
- How patients think about AI in health data, including the need for clinician oversight, explanation, and a clear AI-to-human handoff.
- How to avoid AI framing bias when testing AI-enabled concepts, products, or experiences.
- A simple framework for hybrid qual design: humans to uncover meaning, AI to scale patterns, quant to size and validate.
Presented by:
Elena Scheer-Moser, Senior Research & Insights Manager, iRhythm Technologies
Stephanie David, VP, Health & Wellness, Vital Findings
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