Identification of Depressive and Anxiety Symptoms Among a Sample of Emergency Department Patients Using Artificial Intelligence (AI) Technology

University Hospitals (UH)

Status: Begins enrollment in 2 months

Conditions: Artificial Intelligence (AI)

Treatments: Device: Biometrics (or AI Biomaker)

Study type: Interventional

Funder types: Other

Identifiers

NCT06473558

STUDY20240008

Details and patient eligibility

About

Behavioral health problems, such as depression and anxiety, are common yet often are not identified by emergency department doctors and nurses. These mental health conditions can be due to medical issues or can worsen medical problems. One way investigators hope to do a better job of learning about mental health is by training Artificial Intelligence (AI) software to detect anxiety and depression by analyzing facial expression and tone of voice.

Participants are invited to participate in a study which may help improve emergency department care. An audio and video recording of the participant's responses to some simple, non-psychological questions will be analyzed by a computer to determine whether investigators can assess mood and anxiety by analyzing speech and visual patterns. The audio and video will not be listened to nor watched by study personnel, only analyzed by a computer. The investigator's hope is that it will help others in the future by aiding in the assessment of psychological state. This study is being conducted at CMC ED only.

Enrollment: 30 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Adult patients (age 18 and over) who presents to the UHCMC ED voluntarily with no obvious psychological disturbance by self-report or nurse/provider initial assessment
• English-speaking
• Patients with non-emergent concerns of Emergency Severity Index (ESI) level 3, 4, or 5

Exclusion criteria

• Prisoners
• Patients who are deemed to be critically ill (including life or limb threatening illness) or unable to consent
• Non-English Speaking

Trial design

Primary purpose: Screening

Allocation: N/A

Interventional model: Single Group Assignment

Masking: None (Open label)

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30 participants in 1 patient group

Participants seen at University Hospitals Cleveland Medical Center Emergency Department

Experimental group

Description:

Eligible patients must present with non-emergent concerns of Emergency Severity Index (ESI) level 3, 4, or 5. Patients will complete assessments and questionnaires and end with being recorded reading a story to capture facial expressions and audio cues.

Treatment:

Device: Biometrics (or AI Biomaker)