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Artificial Intelligence

eCBT Plus vs Multi-professional Care Team for Depression

N/A

Recruiting

Led By Nazanin Alavi, MD FRCPC

Research Sponsored by Dr. Nazanin Alavi

Eligibility Criteria Checklist

Specific guidelines that determine who can or cannot participate in a clinical trial

Must have

Be older than 18 years old

Timeline

Screening 3 weeks

Treatment Varies

Follow Up week 0, 4, 7, 10, 13, and 3, 6, and 12-month follow-up.

Awards & highlights

Study Summary

This trial aims to determine the most cost-effective way to deliver e-CBT for people with depression, comparing AI to a multi-professional care team. It will provide tailored care intensities, allowing more efficient use of resources.

Who is the study for?

This trial is for individuals diagnosed with Major Depressive Disorder (MDD) as per DSM-5, who can consent, speak and read English, and have reliable internet access. It excludes those currently in psychotherapy, experiencing psychosis or acute mania, having thoughts of suicide or homicide, or severe substance abuse issues.Check my eligibility

What is being tested?

The study compares AI decision-making to a multi-professional team's approach in assigning care levels for e-CBT treatment of depression. Participants will be randomly placed into groups receiving different intensities of e-CBT: alone; with calls; or with medication.See study design

What are the potential side effects?

While the trial primarily involves non-invasive e-CBT therapy which may not have direct side effects like medications do, potential indirect side effects could include discomfort from discussing personal issues online and possible privacy concerns.

Timeline

Screening ~ 3 weeks3 visits

Treatment ~ Varies

Follow Up ~ week 0, 4, 7, 10, 13, and 3, 6, and 12-month follow-up.

Screening ~ 3 weeks

Treatment ~ Varies

Follow Up ~week 0, 4, 7, 10, 13, and 3, 6, and 12-month follow-up.

This trial's timeline: 3 weeks for screening, Varies for treatment, and week 0, 4, 7, 10, 13, and 3, 6, and 12-month follow-up. for reporting.

Treatment Details

Study Objectives

Outcome measures can provide a clearer picture of what you can expect from a treatment.

Primary outcome measures

Change in Assessment of Quality of Life (AQoL-8D) Score

Change in Patient Health Questionnaire (PHQ-9) Score

Change in Quick Inventory of Depressive Symptoms (QIDS) Score

Trial Design

2Treatment groups

Experimental Treatment

Active Control

Group I: Artificial Intelligence AllocationExperimental Treatment3 Interventions

Allocation of treatment intensity by the proposed AI algorithm will be based on the machine learning and natural language processing (NLP) of textual data provided by participants and their PHQ-9 score collected through a pre-treatment screening module called the Triage Module. This module, developed by the research team, (1) provides psychoeducation on the effects of psychotherapy, (2) collects PHQ-9 scores, and (3) asks participants six open-ended questions regarding their mental health history, their experiences with mental health disorders, and what mental health difficulties they are currently facing. Based on the participant's answers to the open-ended questions, a variable called "Symptomatic Score" will be calculated using the NLP algorithm.

Group II: Healthcare Team AllocationActive Control3 Interventions

Allocation of treatment intensity by the multi-professional healthcare team will be based on the following criteria: The severity of MDD symptoms (using DSM-5 criteria). Mental health factors (prior treatments and responses, current and past psychotic/manic episodes, current and past suicidal/homicidal ideation/attempts, family mental health history, past psychiatric history, and hospital admissions). Medical factors (current medical conditions and medications, personal and family medical history). Social factors (support system and living situation, and occupational, social, and personal functional impairment).

Treatment

First Studied

Drug Approval Stage

How many patients have taken this drug

e-CBT

2021

N/A

~200

Do I qualify?Apply below to find out

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Who is running the clinical trial?

Dr. Nazanin AlaviLead Sponsor

12 Previous Clinical Trials

930 Total Patients Enrolled

5 Trials studying Depression

388 Patients Enrolled for Depression

Queen's UniversityLead Sponsor

366 Previous Clinical Trials

121,551 Total Patients Enrolled

32 Trials studying Depression

6,967 Patients Enrolled for Depression

Nazanin Alavi, MD FRCPCPrincipal Investigatornazanin.alavitabari@kingstonhsc.ca

2 Previous Clinical Trials

170 Total Patients Enrolled

1 Trials studying Depression

110 Patients Enrolled for Depression

Media Library

AI Technology (Artificial Intelligence) Clinical Trial Eligibility Overview. Trial Name: NCT05648175 — N/A

Depression Research Study Groups: Artificial Intelligence Allocation, Healthcare Team Allocation

Depression Clinical Trial 2023: AI Technology Highlights & Side Effects. Trial Name: NCT05648175 — N/A

AI Technology (Artificial Intelligence) 2023 Treatment Timeline for Medical Study. Trial Name: NCT05648175 — N/A

Frequently Asked Questions

These questions and answers are submitted by anonymous patients, and have not been verified by our internal team.

How many individuals have signed up to participate in this clinical investigation?

"Confirmative. As indicated by clinicaltrials.gov, this trial is actively recruiting patients from one site and requires a total of 186 participants. The original announcement was made on December 1st 2022 with the most recent update occurring on December 20th 2022"

Answered by AI

Is enrollment for this clinical trial open at this time?

"Affirmative. Clinicaltrials.gov indicates that this research effort, initially published on December 1st 2022, is currently seeking participants to join the study. The search for volunteers requires 186 individuals at one medical site."

Answered by AI

Recent research and studies

clinicaltrials.govStudy

Comparing Clinical Decision-making of AI Technology to a Multi-professional Care Team in eCBT for Depression

Dr. Nazanin Alavi 2022. "Comparing Clinical Decision-making of AI Technology to a Multi-professional Care Team in eCBT for Depression". ClinicalTrials.gov. https://clinicaltrials.gov/ct2/show/NCT05648175.