Using Machine Learning to Optimize User Engagement and Clinical Response to Digital Mental Health Interventions
NCT05567640
This study is recruiting at 1 US site in 1 state, according to its ClinicalTrials.gov record last updated .
Summary
Digital mental health interventions are a cost-effective and efficient approach to expanding the accessibility and impact of psychological treatments; however, little guidance exists for selecting the most effective program for a given individual. In the proposed study, decision rules will develop for selecting the digital program that is most likely to be the optimal intervention for each user. These treatment recommendations can be implemented in the context of large healthcare delivery systems to improve the delivery of digital mental health interventions at scale.
Shortened from the sponsor's brief summary. View official record on ClinicalTrials.gov
Conditions studied
- Anxiety Disorders and Symptoms
- Depressive Symptoms
Eligibility basics and study details
- Study type
- Interventional
- Phase
- Not applicable
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Sponsor
- Boston University Charles River Campus
- Last updated on ClinicalTrials.gov
- July 31, 2026
These are the basic criteria only. The full inclusion and exclusion criteria are on the official record, and the study team decides who can take part.
US recruiting sites
Massachusetts · 1
- Center for Anxiety and Related Disorders · Boston, MA
Source: ClinicalTrials.gov, data processed . Recruiting US sites filtered by distance and site status; summaries shortened.