Clinical trial NCT05745103: Optimizing Behavioral Healthcare Delivery Through Technology
Official title: Optimizing Behavioral Healthcare Delivery Through Technology
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Mood Disorders
Anxiety Disorders
Keywords: Mood Disorders
Anxiety Disorders
Evidence-Based Practices
Community-Based Clinics
Artificial Intelligence
Lead sponsor: Eleos Health
Sponsor class: INDUSTRY
Collaborators: name: Missouri Department of Mental Health
First posted: 2023-02-27
Enrollment: 46
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Open Randomized Controlled Trial
Primary purpose: TREATMENT

Brief summary: The goal of this randomized controlled clinical trial is to determine the feasibility, acceptability, and preliminary efficacy of an artificial intelligence platform )שׁ( for behavioral health in facilitating better clinical outcomes for adult patients receiving outpatient therapy.

The main question\[s\] it aims to answer are:

* whether an AI platform designed for behavioral healthcare would be feasible and acceptable to patients and therapists.
* whether the depression and anxiety outcomes of adults receiving outpatient cognitive-behavioral therapy (CBT) in a community-based clinic would be superior among patients whose therapists used an AI-based platform to support clinical decision making and administrative tasks compared to patients receiving treatment-as-usual (TAU).

Participants will receive CBT for depression or anxiety and complete standardized assessments. Participants will be followed for the first two months of therapy.

Detailed description: The need for scalable delivery of mental health care services that are efficient and effective is now a major public health priority. Artificial intelligence (AI) tools have the potential to improve behavioral healthcare services by helping clinicians collect objective data on patients' progress, streamline their workflow, and automate administrative tasks.

The goal of this study is to determine the feasibility, acceptability, and preliminary efficacy of an AI platform for behavioral health in facilitating better clinical outcomes for patients receiving outpatient therapy.

This open randomized clinical trial will compare an AI platform provided by Eleos Health to treatment-as-usual (TAU) during the first 2 months of therapy. The study will be conducted at a community-based clinic in the U.S. Participants will be adults referred for outpatient, individual cognitive behavioral therapy for a main diagnosis of a depressive or anxiety disorder. Patients will be randomized to receive either therapy provided with the support of an AI platform developed by Eleos Health or TAU at the same clinic.

Data analysis will be carried out based on intention-to-treat principle. The primary outcomes include the feasibility and acceptability of the AI platform. Secondary outcomes include changes in depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7) scores as well as treatment attendance and satisfaction.

Findings of this study will inform the optimization of future trials and services offered to individuals seeking mental health support in the U.S.

Eligibility criteria: Inclusion Criteria:

1. Older than 18 years old.
2. Presenting for an outpatient CBT for a depressive or anxiety disorder.

Exclusion Criteria:

1. Age \<18.
2. individuals who are medically unstable for outpatient treatment.
3. a severe mental health condition that might interfere with treatment compliance (e.g., psychotic depression, psychosis, active substance dependence).

Primary outcomes:
measure: Patient Health Questionnaire-9 (PHQ-9)
timeFrame: Baseline
measure: Patient Health Questionnaire-9 (PHQ-9)
timeFrame: 1 month
measure: Patient Health Questionnaire-9 (PHQ-9)
timeFrame: 2 months
measure: Generalized Anxiety Disorder-7 (GAD-7)
timeFrame: Baseline
measure: Generalized Anxiety Disorder-7 (GAD-7)
timeFrame: 1 month
measure: Generalized Anxiety Disorder-7 (GAD-7)
timeFrame: 2 months
Secondary outcomes:
Other outcomes:
Locations:
city: Joplin
country: United States
facility: The Ozark Center
state: Missouri
Study officials:
References:
citation: Peretz G, Taylor CB, Ruzek JI, Jefroykin S, Sadeh-Sharvit S. Machine Learning Model to Predict Assignment of Therapy Homework in Behavioral Treatments: Algorithm Development and Validation. JMIR Form Res. 2023 May 15;7:e45156. doi: 10.2196/45156.
citation: Kellogg KC, Sadeh-Sharvit S. Pragmatic AI-augmentation in mental healthcare: Key technologies, potential benefits, and real-world challenges and solutions for frontline clinicians. Front Psychiatry. 2022 Sep 6;13:990370. doi: 10.3389/fpsyt.2022.990370. eCollection 2022.
citation: Sadeh-Sharvit S, Rego SA, Jefroykin S, Peretz G, Kupershmidt T. A Comparison Between Clinical Guidelines and Real-World Treatment Data in Examining the Use of Session Summaries: Retrospective Study. JMIR Form Res. 2022 Aug 16;6(8):e39846. doi: 10.2196/39846.
citation: Sadeh-Sharvit S, Camp TD, Horton SE, Hefner JD, Berry JM, Grossman E, Hollon SD. Effects of an Artificial Intelligence Platform for Behavioral Interventions on Depression and Anxiety Symptoms: Randomized Clinical Trial. J Med Internet Res. 2023 Jul 10;25:e46781. doi: 10.2196/46781.