Anxiety Disorders, Depression Disorders
Conditions
Brief summary
The SEQUOIA-1 study evaluates the effectiveness of Artificial Intelligence (AI) in measuring depression and anxiety severity in adults. Investigators from Deliberate Solutions, Inc. and Baylor College of Medicine are conducting this study to determine whether AI can provide reliable clinical assessments of mood and anxiety disorders. In clinical trials for new depression and anxiety treatments, human clinicians typically conduct interviews to evaluate participants' symptoms. These assessments are critical but may vary based on the clinician's experience or interview style, potentially affecting the reliability of research findings. To address this challenge, the study team developed an AI-based Clinical Outcome Assessment tool, called AICOA®, which analyzes video interviews to measure symptoms of depression and anxiety consistently and objectively. AI-COA® has been accepted by the U.S. Food and Drug Administration (FDA) into the Innovative Science and Technology Approaches for New Drugs (ISTAND) pilot program. The primary objectives of the SEQUOIA-1 study are to collect additional data to improve model accuracy and to evaluate model performance across diverse demographic groups. The study also pilots the use of an AI interviewer-an interactive digital agent-to conduct remote assessments. During the study, participants will complete questionnaires about their symptoms and perform brief tasks. Participants will also provide feedback regarding their experience interacting with the AI interviewer. All assessments will be securely video-recorded. Recorded videos will be analyzed by AICOA® to determine depression and anxiety symptom severity. These results will be compared to assessments conducted by human clinicians. The development and validation of reliable, AI-driven assessment tools through this study aim to enhance the accuracy of mental health evaluations, potentially improving the testing and approval processes for new treatments targeting depression and anxiety.
Interventions
OTHERAI-driven clinical interview
AI-driven clinical interview
Sponsors
Baylor College of Medicine
Deliberate Solutions Inc.
Study design
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
No
Inclusion criteria
* English fluency * 18 to 65 years of age. * HAM-D 17 \> 10 * Starting, or has started, a new treatment for depression or anxiety within 2-3 weeks of enrollment * Access to a laptop or other computer with a well functioning microphone and webcam, and a stable Internet connection * Stated willingness to comply with all study procedures and availability for the duration of the study * Resides in the United States at the time of consent and during completion of study
Exclusion criteria
* Any cognitive impairment that limits ability to provide informed consent or authorization * Vulnerable or protected populations (e.g. prisoners) * 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) * Acute intoxication at the time of the assessments * Concurrent medication/treatment: * Receiving any fast-acting treatment for depression or anxiety (e.g. ketamine, psychedelics, deep brain stimulation, etc.) in between initial baseline assessment (A1) and Restest (A2) , or in between Follow up assessment (B1) and Retest (B2) * Anxiolytics: Use of benzodiazepines or other anxiety-reducing medications that could affect speech or motor activity, within the past 4 weeks. * Antipsychotics and Mood Stabilizers: Medications that can alter cognitive and motor functions, within the past 6 weeks. * Stimulants: Use of medications like methylphenidate or amphetamines that affect energy levels and behavior, within the past 2 weeks * Epilepsy medication: seizure activity or medication side effects that may alter behavior, within the past 4 weeks. * Any history or evidence of any of the following conditions: * Neurodevelopmental, Neurocognitive, Neurodegenerative or movement disorders including, but not limited to: * Tourette's syndrome * Multiple Sclerosis * Amyotrophic Lateral Sclerosis * Parkinson's Disease * Stroke * Traumatic Brain Injury * Facial paralysis. * Conditions with vocal cord impact: * Vocal cord injury or cerebrovascular accident or head trauma with residual dysarthria in the past year * Disorders that may impact vocal cords such as acute or chronic laryngitis, vocal cord paresis or paralysis, or spasmodic dysphonia * Past or active heavy smokers (an average of \>20 cigarettes per day) * Schizophrenia Spectrum and Other Psychotic Disorders: * Individuals with a current or past diagnosis of Schizophrenia, Schizoaffective Disorder, or other psychotic disorders, including Delusional Disorder and Brief Psychotic Disorder. * Current hypomanic episode as defined by DSM-5 criteria. This includes those with Bipolar I Disorder, Bipolar II Disorder, or Cyclothymic Disorder who are not in a stable mood state at the time of assessment. * Chronic Pain Conditions: Such as fibromyalgia, which may affect facial expressions and vocal tone. * Prosthetic Facial Devices: Could affect facial recognition algorithms. Cosmetic Procedures: Such as Botox injections or facelifts that can impact facial expressions. * Dental Work: Major procedures that might affect speech. * Participants who have previously participated in another research project by Deliberate.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| HAM-D ICC | Between Test and Retest (within 2 days) | Concordance of HAM-D score between model and human raters |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| MADRS ICC | Between Test and Retest (within 2 days) | Concordance of MADRS score between model and human raters |
| HAM-A ICC | Between Test and Retest (within 2 days) | Concordance of HAM-A score between model and human raters |
Countries
United States
Contacts
Primary ContactEric Storch, PhD
Outcome results
None listed