Signature Project leads: Michelle Craske, PhD, and Kate Wolitzky-Taylor, PhD
Signature Project summary: In this project, we compare two different methods of triaging and adapting to the appropriate level of care for each individual within STAND.
Signature Project goal: This project compares a novel, personalized decision-making process for assigning patients to a specific treatment tier to a traditional, standard decision-making process for depression and anxiety treatment.
Why this research is important: This research has the potential to improve treatment effectiveness for depression and anxiety by allowing for greater precision in matching treatment-seeking individuals to the most appropriate/suitable treatment "tier" (level of care).
Anticipated duration: Two phases over five years.
Phase 1: Phase 1 involves testing the initial triaging algorithm while collecting data that will help to build a machine learning algorithm for the novel, personalized decision-making process for treatment tier adaptation. Phase 1 will extend for approximately 1 year with approximately 200 participants.
Phase 2: Phase 2 involves refining both the adaptation and triaging algorithms taking into account learnings from the prior cohorts. Throughout the project, annual enhancements will be made to the data-driven decision-making process, with the goal of rolling out the enhancements on an annual basis to allow for comparisons between cohorts.
Affiliated staff:
