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Enrolling by invitation NCT06792175

Mental Health, Intellectual and Neurodevelopmental Disorder Detection With Artificial Intelligence Models

— Observational Autism Spectrum Disorder Depression - Major Depressive Disorder Anxiety, Generalized Bipolar Disorder (BD)

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: Solicue Machine Learning Models, Mercuria Machine Learning Models.
Who it may be relevant to
Registry conditions: Autism Spectrum Disorder, Depression - Major Depressive Disorder, Anxiety, Generalized, Bipolar Disorder (BD). Basic parameters: 13 years — 60 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
United States
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

Unsure about the terms? Read our patient guide →

Official title

Mental Health, Intellectual and Neurodevelopmental Disorder Detection With Artificial Intelligence Models: Testing Speech-Based Machine Learning Algorithms for Clinical Assessment and Risk Stratification in Mental Health Presentations

Overview

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.

Interventions

  • Diagnostic test Solicue Machine Learning Models
    A comprehensive machine-learning tool aimed at providing probability estimates for several compatible disorders, including Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Bipolar Affective Disorder (BPAD), Generalized Anxiety Disorder (GAD), Major Depressive Disorder (MDD), Obsessive Compulsive Disorder (OCD), Post-Traumatic Stress Disorder (PTSD), and Schizophrenia Spectrum Disorders (SSD). By offering a multi-diagnostic assessment based on speech analysis, Soli
  • Diagnostic test Mercuria Machine Learning Models
    Mercuria is designed to stratify the risk of bipolar disorder in individuals presenting with depressive symptoms. This is a critical clinical need, as misdiagnosis of bipolar disorder as unipolar depression is common and can lead to inappropriate treatment, potentially worsening outcomes. By analyzing speech patterns characteristic of bipolar disorder, Mercuria aims to provide an additional tool for clinicians to differentiate between these conditions more accurately, guiding appropriate treatme

Primary outcome measures

  • Speech Battery ("PSY-10") audio [Time frame: At initial assessment]
  • Clinical diagnosis [Time frame: 0 months, 3 months, 6 months]
  • Performance of AI models [Time frame: 0 months, 3 months, 6 months]
Secondary outcome measures (4)
  • Patient Health Questionnaire-9 (PHQ-9) [Time frame: At initial assessment]
  • Mood Disorder Questionnaire (MDQ) [Time frame: At initial assessment]
  • DSM-5 Level 1 Cross-Cutting Symptom Measure (DSM-XC) [Time frame: At initial assessment]
  • Reported Distress [Time frame: After initial assessment]

Eligibility criteria

Inclusion criteria

  • Participants aged between 16 and 60 years.
  • 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)
  • Fluent in English
  • Capable of providing informed consent, or in the case of minors, having a parent or legal guardian who can provide consent on their behalf.
  • Access to a device (smartphone, tablet, or computer) with a microphone and stable internet connectivity, necessary for completing the speech tasks.

Exclusion criteria

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Study design

Observational model
Cohort

Study locations

United States · 2 centers
  • The Brookline Center — Brookline
  • Allwell Behavioral Health Services — Zanesville

Identifiers

NCT: NCT06792175 · PSYRIN-0004

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗