AI-Driven Clinical Interview for Depression and Anxiety

(SEQUOIA-1 Trial)

Overseen By Eric Storch, PhD

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Deliberate Solutions Inc.

Must not be taking: Benzodiazepines, Antipsychotics, Stimulants, others

Disqualifiers: Cognitive impairment, Schizophrenia, Neurodegenerative, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

120 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to determine if an AI tool can accurately measure depression and anxiety symptoms by analyzing video interviews, potentially improving mental health evaluations. It compares AI assessments with those by human clinicians to ensure consistent and objective results. Participants will interact with an AI interviewer, answer questions about their symptoms, and perform tasks while providing feedback on the process. Ideal candidates are adults in the U.S. who have started new treatments for depression or anxiety within the last few weeks and have access to a computer with internet. As an unphased trial, this study offers participants the chance to contribute to innovative research that could transform mental health evaluations.

Do I need to stop taking my current medications to join the trial?

The trial requires that you stop taking certain medications, such as fast-acting treatments for depression or anxiety, benzodiazepines, antipsychotics, mood stabilizers, stimulants, and epilepsy medications, for specific periods before joining. If you're on any of these, you may need to stop them for 2 to 6 weeks, depending on the medication.

What prior data suggests that this AI-based assessment tool is safe for evaluating depression and anxiety?

Research has shown that the AI-COA® tool is safe for users. This system analyzes video interviews to detect signs of depression and anxiety. While specific safety data is not available, its acceptance into the FDA's ISTAND program highlights its innovative approach. Participants have generally reported positive experiences with the AI, feeling at ease during AI-led interviews.

The AI-COA® is not a drug or traditional medical treatment, so it lacks the side effects associated with medications. Instead, it offers a new way to consistently and objectively measure mental health symptoms. This study aims to improve the accuracy of mental health assessments, which can aid in developing better treatments for depression and anxiety. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the AI-Driven Clinical Interview for Depression and Anxiety because it introduces a novel approach to improving mental health assessments. Unlike traditional methods, which often rely on subjective evaluations by human clinicians, this AI-powered tool aims to provide more consistent and objective assessments by analyzing verbal and non-verbal cues. The potential for AI to enhance the accuracy and efficiency of diagnosing depression and anxiety is particularly promising, as it could lead to more personalized treatment plans. Additionally, this technology has the potential to be more accessible, offering support to areas with limited mental health resources. Overall, this trial could pave the way for significant advancements in how we understand and treat these common mental health conditions.

What evidence suggests that AI-COA® is effective for assessing depression and anxiety?

Research has shown that AI tools, such as AI-COA®, provide a consistent and clear way to assess mental health conditions. In this trial, participants will undergo different sequences of AI interviews and assessment measures. Studies have found that AI can analyze open-ended answers to deliver a detailed evaluation of mental health, offering more insights than traditional methods. AI systems improve mental health evaluations by reducing variability that might occur with different clinicians. These systems ensure that assessments of depression and anxiety remain reliable and consistent for everyone. AI-COA® is part of ongoing efforts to enhance the diagnosis and monitoring of mental health conditions. ^{1 6 7 8 9}

Who Is on the Research Team?

Marc Aafjes

Principal Investigator

Deliberate Solutions Inc.

Are You a Good Fit for This Trial?

The SEQUOIA-1 study is for adults with depression or anxiety who are interested in contributing to the development of an AI tool that assesses mental health. Participants should be willing to complete questionnaires, perform tasks, and interact with an AI interviewer on video.

Inclusion Criteria

HAM-D 17 score greater than 10

English fluency

Access to a laptop or other computer with a well-functioning microphone and webcam, and a stable Internet connection

Exclusion Criteria

Vulnerable or protected populations (e.g. prisoners)

Acute intoxication at the time of the assessments

Impairment that would prevent participants from completing an online survey and/or engaging in clinician assessment interviews (e.g., visual impairment, motor impairment, hearing impairment)

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

AI Interview and Assessment

Participants undergo AI-based video interviews and complete questionnaires about their symptoms. Feedback is collected regarding their experience with the AI interviewer.

2 days

Remote assessments

Follow-up

Participants are monitored for concordance of AI and human assessments of depression and anxiety symptoms.

2 days

What Are the Treatments Tested in This Trial?

Interventions

• AI-COA®

Trial Overview This trial tests an AI-driven clinical interview tool called AI-COA® designed to measure depression and anxiety severity more consistently than human clinicians. It involves participants completing assessments which will be compared against traditional clinician evaluations.

How Is the Trial Designed?

Group I: B2: A1: AI interview second and measures set 2 Experimental Treatment 1 Intervention

Group II: B1: AI interview second, and measures set 1 Experimental Treatment 1 Intervention

Group III: A2: AI interview first, and measures set 2 Experimental Treatment 1 Intervention

A2: AI interview first, and measures set 2

Group IV: A1: AI interview first, and measures set 1 Experimental Treatment 1 Intervention

A1: AI interview first, and measures set 1

Who Is Running the Clinical Trial?

Deliberate Solutions Inc.

Lead Sponsor

Baylor College of Medicine

Collaborator

Trials

1,044

Recruited

6,031,000+

Published Research Related to This Trial

Project AFFECT aims to create an AI-based software, LyssnCBT, to automatically assess the quality of cognitive behavioral therapy (CBT) sessions, which could enhance training and supervision for therapists and improve treatment outcomes for clients.

In a planned Phase II trial involving 1,875 clients, the effectiveness of LyssnCBT will be evaluated to see if it can improve therapist skills, client outcomes, and reduce client drop-out rates, marking a significant step towards scalable quality assurance in psychotherapy.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Enhancing the quality of cognitive behavioral therapy in community mental health through artificial intelligence generated fidelity feedback (Project AFFECT): a study protocol. Creed, TA., Salama, L., Slevin, R., et al.[2023]

In a study involving 1,205 users of the Wysa app for mental health, users reported a strong therapeutic alliance with the AI conversational agent, with scores comparable to traditional therapy methods like CBT.

Over a brief period of 3 days, users' perceptions of their bond with Wysa improved, indicating that digital mental health services can effectively foster a therapeutic relationship similar to that found in face-to-face therapy.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluating the Therapeutic Alliance With a Free-Text CBT Conversational Agent (Wysa): A Mixed-Methods Study. Beatty, C., Malik, T., Meheli, S., et al.[2022]

A study involving 308 participants with subclinical depression demonstrated that a conversational agent can effectively collect thought record data, making it feasible for patients to engage in cognitive therapy techniques.

Participants preferred discussing interpersonal situations over achievement-related ones, highlighting the importance of social contexts in their thought processes, but providing richer feedback did not increase motivation for recording thoughts.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Using a conversational agent for thought recording as a cognitive therapy task: Feasibility, content, and feedback. Burger, F., Neerincx, MA., Brinkman, WP.[2023]

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12120367/

Effectiveness of AI-Driven Conversational Agents in Improving ... This study aims to examine the effectiveness of AI-driven CAs for mental health among young people, and explore the potential moderators of efficacy.

2. sciencedirect.com sciencedirect.com/science/article/pii/S0165032725005555

AI-driven analyzes of open-ended responses to assess ... AI-driven analysis offers a comprehensive evaluation of mental health improvements beyond traditional rating scales.

3. withpower.com withpower.com/trial/ai-driven-clinical-interview-for-depression-and-anxiety-a5cb6

AI-Driven Clinical Interview for Depression and Anxiety · ... The SEQUOIA-1 study evaluates the effectiveness of Artificial Intelligence (AI) in measuring depression and anxiety severity in adults.

4. clinicaltrials.gov clinicaltrials.gov/study/NCT07061132

AI-Powered Interview Simulation to Improve Employability ... Key outcome measures include the Perceived Future Employability Scale (PFE), the Interview Anxiety Scale (MASI-T), and a simulation experience ...

5. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC8349367/

Artificial Intelligence for Mental Healthcare: Clinical ... It provides an overview of AI approaches in mental healthcare, seeking to help with clinical diagnosis, prognosis, and treatment.

6. bioworld.com bioworld.com/articles/705061-deliberate-ai-anxiety-depression-model-accepted-into-istand?v=preview

Deliberate AI anxiety/depression model accepted into ISTAND AI-COA employs multi-modal behavioral signal processing and machine learning to capture and quantify mental health symptoms, providing a more objective method ...

7. nature.com nature.com/articles/s41598-024-82192-2

GPT-4 shows potential for identifying social anxiety from ... We investigated the ability of the large language model (LLM) GPT-4 to correctly infer social anxiety symptom strength from transcripts obtained from semi- ...

8. frontiersin.org frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1626428/full

Participatory development and proof-of-concept of a dyadic ... This study aims to develop and test a dyadic, AI-driven Just-In-Time Adaptive Intervention app (DyAI-JITAI) for the prevention of anxiety and ...

9. pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov/40187428/

AI-driven analyzes of open-ended responses to assess ... Language responses analyzed using AI-methods assessed outcomes with fewer items, demonstrating effectiveness and accuracy comparable to traditional rating ...