AI-Powered Mental Health Screening in University Students

Wenzhou Medical University

Status: Completed

Conditions: Mental Disease

Treatments: Diagnostic Test: AI model

Study type: Observational

Funder types: Other

Identifiers

NCT07092085

Mental Health

Details and patient eligibility

About

The goal of this observational study is to test an artificial intelligence (AI) tool that can help screen for mental health risks . The main questions it aims to answer are:

Can an AI model that analyzes a person's voice, facial expressions, and language accurately identify students who may be at high risk for mental health conditions, such as depression or OCD?

How accurate is the AI model when compared to results from standard mental health questionnaires?

Participants will be asked to:

Complete a standard mental health questionnaire.

Provide consent for their data to be used in the research.

Participate in a recorded session to collect video and audio data for the AI model to analyze.

Full description

This large-scale, multi-center observational study aims to develop and validate a novel artificial intelligence (AI) model for the early and objective screening of mental health risks, such as depression and OCD, in university students. The model will be trained and internally validated on multimodal data (including vocal, facial, and linguistic features) from a large student cohort. A subsequent neuroscience sub-study will explore the neurobiological correlates of the AI-identified risk levels using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to establish biological validity. The primary outcome is to assess the final model's diagnostic accuracy, quantified by its sensitivity, specificity, and AUC, with the ultimate goal of providing a scalable and efficient early warning tool to facilitate timely clinical intervention for university populations.

Enrollment: 17,386 patients

Sex: All

Ages: 14 to 40 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Enrolled as a student at a participating university.
• Age between 14 and 40 years, inclusive.
• Willing and able to provide written informed consent.
• Fluent in the language required for the study.

Exclusion criteria

• Inability to provide video or audio data of sufficient quality for analysis.

Trial design

17,386 participants in 2 patient groups

Healthy Control

Description:

without mental healthy problem

Treatment:

Diagnostic Test: AI model

Mental Diseases

Description:

with mental problem, such as depression, OCD

Treatment:

Diagnostic Test: AI model