Search Articles

View query in Help articles search

Search Results (1 to 10 of 549 Results)

Download search results: CSV END BibTex RIS


Developing a Behavioral Phenotyping Layer for Artificial Intelligence–Driven Predictive Analytics in a Digital Resiliency Course: Protocol for a Randomized Controlled Trial

Developing a Behavioral Phenotyping Layer for Artificial Intelligence–Driven Predictive Analytics in a Digital Resiliency Course: Protocol for a Randomized Controlled Trial

Specifically, we did not examine how the intersection of demographic characteristics and cognitive or behavioral phenotypes influenced engagement, if individual engagement followed properties of power laws [61], or if we could leverage economic tools such as the Gini coefficient to plot participation inequality [62]. Understanding these patterns is important for optimizing future interventions for full personalization and maximizing the effectiveness of digital health tools.

Trevor van Mierlo, Rachel Fournier, Siu Kit Yeung, Sofiia Lahutina

JMIR Res Protoc 2025;14:e73773