In Episode 4 of The Human Side of Clinical Trials, host Brian S. McGowan, PhD, FACEHP, chief learning officer and co-founder of ArcheMedX, Inc., speaks with Jason Riis, PhD, CEO and chief behavioral scientist at Behavioralize, about how capturing friction closer to the moment it happens can reveal unclear instructions, technology friction, and workarounds that retrospective surveys and debriefs tend to miss.
What could clinical trial teams learn if they captured friction closer to the moment it happens? In Episode 4 of The Human Side of Clinical Trials, Brian S. McGowan, PhD, FACEHP, chief learning officer and co-founder of ArcheMedX, Inc., welcomes back behavioral scientist Jason Riis, PhD, CEO and chief behavioral scientist at Behavioralize, to explore experience sampling and its potential to uncover site burden before it becomes downstream risk.
The conversation begins with a distinction between the experiencing self, what people feel and do in a particular moment, and the evaluating self, the story they later tell about that experience. Memory is imperfect, and retrospective surveys and debriefs can miss the uncertainty, variation, and small workarounds that shape daily trial execution.
Drawing on research with patients, physicians, and pharmaceutical professionals, Jason explains how brief, timely questions can reveal patterns that broader recollections overlook. Brian shares his own experience participating in a study of daily AI use, where simple check-ins exposed a gap between his intentions and actions and prompted changes in how he worked.
Together, they consider how similar methods could help clinical operations teams identify unclear instructions, technology friction, role confusion, and emerging workarounds, particularly during a trial’s early days. They also discuss an important consideration: tracking can influence behavior, and collecting information should add as little burden as possible.
The practical starting point is simple: ask a few coordinators what they were most uncertain about that day, using an accessible channel and a supportive approach. The goal is to understand what makes execution difficult and use those insights to better support the people doing the work.
