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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

30 participants

Study Classification

INTERVENTIONAL

Study Start Date

2026-01-01

Study Completion Date

2026-08-30

Brief Summary

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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.

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Detailed Description

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Conditions

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Artificial Intelligence (AI)

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

SCREENING

Blinding Strategy

NONE

Study Groups

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Participants seen at University Hospitals Cleveland Medical Center Emergency Department

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.

Group Type EXPERIMENTAL

Biometrics (or AI Biomaker)

Intervention Type DEVICE

Patients will be asked to read a story and their facial expressions and audio cues will be recorded.

Interventions

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Biometrics (or AI Biomaker)

Patients will be asked to read a story and their facial expressions and audio cues will be recorded.

Intervention Type DEVICE

Eligibility Criteria

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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