NCT05745103

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.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
46

participants targeted

Target at P25-P50 for not_applicable

Timeline
Completed

Started Sep 2021

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

September 1, 2021

Completed
1.4 years until next milestone

First Submitted

Initial submission to the registry

February 7, 2023

Completed
20 days until next milestone

First Posted

Study publicly available on registry

February 27, 2023

Completed
2 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 30, 2023

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

April 30, 2023

Completed
Last Updated

January 31, 2024

Status Verified

January 1, 2024

Enrollment Period

1.7 years

First QC Date

February 7, 2023

Last Update Submit

January 30, 2024

Conditions

Mood DisordersAnxiety Disorders

Keywords

Mood DisordersAnxiety DisordersEvidence-Based PracticesCommunity-Based ClinicsArtificial Intelligence

Outcome Measures

Primary Outcomes (6)

  • Patient Health Questionnaire-9 (PHQ-9)

    The PHQ-9 is intended as a tool to assist clinicians with identifying and diagnosing depression.

    Baseline

  • Patient Health Questionnaire-9 (PHQ-9)

    The PHQ-9 is intended as a tool to assist clinicians with identifying and diagnosing depression.

    1 month

  • Patient Health Questionnaire-9 (PHQ-9)

    The PHQ-9 is intended as a tool to assist clinicians with identifying and diagnosing depression.

    2 months

  • Generalized Anxiety Disorder-7 (GAD-7)

    The GAD-7 is intended as a tool to assist clinicians with identifying and diagnosing anxiety.

    Baseline

  • Generalized Anxiety Disorder-7 (GAD-7)

    The GAD-7 is intended as a tool to assist clinicians with identifying and diagnosing anxiety.

    1 month

  • Generalized Anxiety Disorder-7 (GAD-7)

    The GAD-7 is intended as a tool to assist clinicians with identifying and diagnosing anxiety.

    2 months

Study Arms (2)

The Eleos Health Platform

EXPERIMENTAL

Therapists in the AI group will use the HIPAA-compliant, secure, password-protected Eleos Health platform. This AI tool was designed for behavioral health to support clinical decision-making and automation of administrative tasks. The platform captures the therapist and patient's utterances during a treatment session, analyzes the data, and offers feedback on the implementation of EBPs. The platform also incorporates a measurement-based care component, wherein standardized assessment scales completed by clients are immediately summarized and graphed for the therapist, who can use these data to inform therapy and share them with the patient. Insights and key indicators from the session data and MBC are summarized into a progress note draft which the therapist can then submit or edit as needed.

Behavioral: Cognitive behavioral therapy with AI

Treatment as Usual

ACTIVE COMPARATOR

Participants randomized to the control group will receive the routine services provided in the center. Therapists providing TAU will be permitted to use the strategies they deen would be most successful.

Behavioral: Cognitive behavioral therapy

Interventions

Cognitive behavioral therapy with AIBEHAVIORAL

Cognitive behavioral therapy is a psycho-social intervention that aims to reduce symptoms of various mental health conditions, primarily depression and anxiety disorders. The Eleos Health platform provides real-time data that optimizes this therapy and helps the provider tailor the intervention to the specific client.

The Eleos Health Platform
Cognitive behavioral therapyBEHAVIORAL

Cognitive behavioral therapy is a psycho-social intervention that aims to reduce symptoms of various mental health conditions, primarily depression and anxiety disorders.

Treatment as Usual

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

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

You may not qualify if:

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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

The Ozark Center

Joplin, Missouri, 64804, United States

Location

Related Publications (4)

  • 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.

    PMID: 37184927BACKGROUND

  • 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.

    PMID: 36147984BACKGROUND

  • 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.

    PMID: 35972782BACKGROUND

  • 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.

    PMID: 37428547RESULT

MeSH Terms

Conditions

Mood DisordersAnxiety Disorders

Interventions

Cognitive Behavioral Therapy

Condition Hierarchy (Ancestors)

Mental Disorders

Intervention Hierarchy (Ancestors)

Behavior TherapyPsychotherapyBehavioral Disciplines and Activities

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Purpose
TREATMENT
Intervention Model
PARALLEL
Model Details: Open Randomized Controlled Trial
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

February 7, 2023

First Posted

February 27, 2023

Study Start

September 1, 2021

Primary Completion

April 30, 2023

Study Completion

April 30, 2023

Last Updated

January 31, 2024

Record last verified: 2024-01

Locations

US(1)