Mental Health, Intellectual and Neurodevelopmental Disorder Detection with Artificial Intelligence Models (MINDAIM)

Psyrin Inc.

Status: Invitation-only

Conditions: Schizophrenia Spectrum & Other Psychotic Disorders; Post Traumatic Stress Disorder; Autism Spectrum Disorder; Attention Deficit Hyperactivity Disorder (ADHD); Anxiety, Generalized; Bipolar Disorder (BD); Obsessive Compulsive Disorder (OCD); Depression - Major Depressive Disorder

Treatments: Diagnostic Test: Solicue Machine Learning Models; Diagnostic Test: Mercuria Machine Learning Models

Study type: Observational

Funder types: Industry; Other

Identifiers

NCT06792175

PSYRIN-0004

Details and patient eligibility

About

This study investigates whether AI-driven analysis of speech can accurately predict clinical diagnoses and assess risk for various mental or behavioral health conditions, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, bipolar disorder, generalized anxiety disorder, major depressive disorder, obsessive compulsive disorder (OCD), post-traumatic stress disorder (PTSD), and schizophrenia. We aim to develop tools that can support clinicians in making more accurate and efficient diagnoses.

Enrollment: 500 estimated patients

Sex: All

Ages: 16 to 60 years old

Volunteers: No Healthy Volunteers

Inclusion and exclusion criteria

Inclusion Criteria

1. Participants aged between 16 and 60 years.
2. Individuals currently undergoing or referred for clinical assessment of mental or behavioral health conditions (including but not limited to ADHD, ASD, BPAD, GAD, MDD, OCD, PTSD, SSD)
3. Fluent in English
4. Capable of providing informed consent, or in the case of minors, having a parent or legal guardian who can provide consent on their behalf.
5. Access to a device (smartphone, tablet, or computer) with a microphone and stable internet connectivity, necessary for completing the speech tasks.

Exclusion Criteria

1. Individuals experiencing acute mental health crises or severe symptoms that would preclude meaningful participation in the study, including acute intoxication.
2. Severe cognitive impairment or intellectual disability that would prevent understanding of the study procedures or completion of the speech tasks.
3. Lack of fluency in English.
4. Technical limitations: Inability to access a suitable device or internet connection for completing the speech tasks

Trial design

500 participants in 2 patient groups

Solicue (Any Mental Health Disorder)

Description:

Any participant enrolled in the study and not part of additional analysis group.

Treatment:

Diagnostic Test: Solicue Machine Learning Models

Solicue & Mercuria (Bipolar Disorder & Major Depressive Disorder)

Description:

Any participant enrolled in the study and exhibiting depressive symptoms as measured by PHQ-9 score.

Treatment:

Diagnostic Test: Mercuria Machine Learning Models

Diagnostic Test: Solicue Machine Learning Models