SEQUOIA-1 Study: AI for Depression and Anxiety Assessment
The SEQUOIA-1 study is looking at how well Artificial Intelligence (AI) can measure the severity of depression and anxiety in adults. Researchers from Deliberate Solutions, Inc. and Baylor College of Medicine want to see if an AI-driven clinical interview can provide reliable assessments of these conditions. This is important because current assessments, done by human clinicians, can sometimes vary. You might be able to join if you are 18-65 years old, speak English, have a HAM-D 17 score greater than 10 (a measure of depression severity), and have recently started a new treatment for depression or anxiety. The main goal is to see how closely the AI's assessment matches a human clinician's assessment (HAM-D ICC) within two days.
- Study design
- This interventional study plans to enroll 120 participants. It is evaluating an AI-driven clinical interview.
- What's involved
- You would need access to a computer with a working microphone and webcam, and a stable internet connection. You must also be willing to follow all study procedures for the duration of the study.
- Compensation
- Not stated in the trial record.
- Follow-up
- The primary endpoint is measured between the test and retest, within two days.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
Expansion and Evaluation of AI-generated Clinical Assessment (AI-COA®) of Depression and Anxiety Severity
At a glance
Conditions
Where it's being run
1 sites across 1 statesStudy leadership
- Marc Aafjes · PRINCIPAL_INVESTIGATOR · Deliberate Solutions Inc.
Who to contact
Opens a ready-to-send draft in your own email app — review before sending.
Do you actually qualify for this trial?
Add a private profile and we'll compare every criterion below against your situation — and tell you which ones are met, uncertain, or excluding.
Inclusion
Exclusion
What this trial measures
- HAM-D ICCBetween Test and Retest (within 2 days)
Concordance of HAM-D score between model and human raters