Artificial Intelligence for Mental Health Diagnoses and Treatment Plans: A Protocol for Actors and Patients

Artificial intelligence (AI) is becoming prevalent in modern medicine and psychiatry. AI is based on a wide variety of computer algorithms classified under machine learning (ML).

The purpose of the present study is to evaluate the potential for mental health diagnosis using AI.

In the first part of the study, the AI will conduct an interview with standardized patients \[SP\] (actors) presenting a psychiatric illness. The AI will present a differential diagnosis and treatment plan. Immediately afterward, the actors will be interviewed by a board-certified psychiatrist, who will also give a differential diagnosis and a treatment plan. The results of the AI and psychiatrist will be compared.

In the second part of the study, AI will examine patients coming for consultation by a psychiatrist in the inpatient units, outpatient units, or in the emergency room (ER) at Sheba Medical center. The AI results will be compered to the psychiatrist diagnosis.

Procedure:

In the firs part of the study, The AI will conduct an interview with standardized SP patients (actors) presenting a psychiatric illness. The actors will be trained in one of 5 scenarios: depression, anxiety, PTSD with cannabis abuse, psychosis, and control patients with no diagnosis. Each scenario will have 2 levels of severity. The actors will present demographic and medical backgrounds, symptoms and signs, including disorders of thought and affect. based on the interview, the AI will present a differential diagnosis and treatment plan. Immediately afterward, the actors will be interviewed by a board-certified psychiatrist, who will also give a differential diagnosis and a treatment plan. The results of the AI and psychiatrist will be compared.

In the second part of the study, AI will examine patients patients treated in the Division of Psychiatry, patients who applied for treatment in the psychiatric clinic but are not yet treated there, and patients treated in the psychiatric emergency room (ER) in Sheba Medical center. In additional, a recruitment ad will be published in the media and on social networks, to include patients who will come in specifically to participate in the study.

The patient will give informed consent and will be interviewed by AI. The interview will be done either digitally or will use voice-to-text and text-to-voice technology that will allow the patient to speak with the computer instead of typing questions into the computer. Future studies, not included in the current proposal, will use voice analysis, face recognition, and computerized emotion recognition as part of AI.

Participants:

* Actors SPs (n=10), each time employed by "MSR"- the Israeli Center for Medical Simulation, trained to simulate symptoms of psychiatric illnesses.
* Board-certified Psychiatrists from the Drora and Pinchas Zachai Division of Psychiatry in the Sheba Medical Center.
* Patients (n=150) examined in the psychiatric division and emergency room (ER) of Sheba. Or patient that recruited from the media.
* Control group (n=50) Patients who came to the ER at the hospital due to physical problems, and no psychiatric history. They will be offered while waiting for the doctor to participate in the study and be examined by the AI and a psychiatrist.

Outcome:

The primary outcome of the study will be a comparison of the interviews, differential diagnoses, and recommendations for treatment assigned by the AI with those assigned by the board-certified psychiatrist. The rates of agreement will be the outcome of interest.

Eligibility Criteria:
Inclusion Criteria:

For the SPs part:

* Actors SPs employed by "MSR"- the Israeli Center for Medical Simulation, trained to simulate symptoms of psychiatric illnesses.
* Over the age of 18
* Sign an informed consent

For the patient part:

* Patients arriving for intake at the psychiatric clinic, the various psychiatric departments and the ER at the Sheba Medical Center.
* Patients over the age of 18
* Sign an informed consent

Exclusion Criteria:

* Patients participating in another study
* Patients under hospitalization order or court order