Evidence map›Paper›PMID 37428547›Full record

Trial reportJournal of medical Internet research2023

Effects of an Artificial Intelligence Platform for Behavioral Interventions on Depression and Anxiety Symptoms: Randomized Clinical Trial.

Shiri Sadeh-Sharvit, T Del Camp, Sarah E Horton, Jacob D Hefner, Jennifer M Berry, Eyal Grossman, Steven D Hollon

3 registry-linked trialsOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 29 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 3 pooled it
11.4field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05745103 nacompletednot on this map

Optimizing Behavioral Healthcare Delivery Through Technology

TypeinterventionalSponsorEleos HealthRan2021 to 2023Enrolled46ConditionsMood Disorders, Anxiety DisordersArmsCognitive behavioral therapy with AI, Cognitive behavioral therapy
NCT06280170 naunknown statusnot on this mapstarted 2024, after this paper: background citation

AI for All: Harnessing the Power of Artificial Intelligence in Mental Health Case Management

TypeinterventionalSponsorEleos HealthRan2024 to 2025Enrolled280ConditionsDepressive Disorder, Anxiety Disorders, Substance Use Disorders, Post Traumatic Stress DisorderArmsArtificial Intelligence platform for case managers
NCT07171944 nanot yet recruitingnot on this mapstarted 2025, after this paper: background citation

Effects of AINurse Orientation Program on Psychological Outcomes and Length of Hospital Stay: A Randomized Controlled Trial

TypeinterventionalSponsorKoç UniversityRan2025 to 2026Enrolled10ConditionsDelirium, Anxiety and Depression, Intensive Care Units (ICUs), Artificial Intelligence (AI)ArmsStructured orientation program, Human Nurse
3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 3 syntheses or guidelines pooled it, 58 citations in OpenAlex.

  1. Pooled it
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  4. An AI Perspective on Counseling Supervision.Behavioral sciences (Basel, Switzerland) · 2026
    Review
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  6. Acceptability of Using Large Language Models to Support Smoking Cessation Attempts: a Qualitative Study Among African Americans Who Smoke.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2026
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  9. Building EVA (Journal of medical Internet research · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Shiri Sadeh-SharvitEleos Health, Waltham, MA, United States.ORCID 0000-0001-6499-9034
T Del CampOzark Center, Freeman Health System, Joplin, MO, United States.ORCID 0000-0001-8869-4489
Sarah E HortonOzark Center, Freeman Health System, Joplin, MO, United States.ORCID 0000-0002-5565-4699
Jacob D HefnerOzark Center, Freeman Health System, Joplin, MO, United States.ORCID 0000-0003-0193-9848
Jennifer M BerryOzark Center, Freeman Health System, Joplin, MO, United States.ORCID 0000-0003-2802-3100
Eyal GrossmanEleos Health, Waltham, MA, United States.ORCID 0000-0003-4083-1557
Steven D HollonVanderbilt University, Nashville, TN, United States.ORCID 0000-0001-5005-3862
Freeman Health System · USPalo Alto University · USSyneos Health (United States) · USVanderbilt University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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 health care services by helping clinicians collect objective data on patients' progress, streamline their workflow, and automate administrative tasks.

objectiveThe aim of this study was 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.

methodsThe study was conducted at a community-based clinic in the United States. Participants were 47 adults referred for outpatient, individual cognitive behavioral therapy for a main diagnosis of a depressive or anxiety disorder. The platform provided by Eleos Health was compared to a treatment-as-usual (TAU) approach during the first 2 months of therapy. This AI platform summarizes and transcribes the therapy session, provides feedback to therapists on the use of evidence-based practices, and integrates these data with routine standardized questionnaires completed by patients. The information is also used to draft the session's progress note. Patients were 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 was carried out based on an intention-to-treat approach from December 2022 to January 2023. The primary outcomes included the feasibility and acceptability of the AI platform. Secondary outcomes included changes in depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7) scores as well as treatment attendance, satisfaction, and perceived helpfulness.

resultsA total of 72 patients were approached, of whom 47 (67%) agreed to participate. Participants were adults (34/47, 72% women and 13/47, 28% men; mean age 30.64, SD 11.02 years), with 23 randomized to the AI platform group, and 24 to TAU. Participants in the AI group attended, on average, 67% (mean 5.24, SD 2.31) more sessions compared to those in TAU (mean 3.14, SD 1.99). Depression and anxiety symptoms were reduced by 34% and 29% in the AI platform group versus 20% and 8% for TAU, respectively, with large effect sizes for the therapy delivered with the support of the AI platform. No group difference was found in 2-month treatment satisfaction and perceived helpfulness. Further, therapists using the AI platform submitted their progress notes, on average, 55 hours earlier than therapists in the TAU group (t=-0.73; P<.001).

conclusionsIn this randomized controlled trial, therapy provided with the support of Eleos Health demonstrated superior depression and anxiety outcomes as well as patient retention, compared with TAU. These findings suggest that complementing the mental health services provided in community-based clinics with an AI platform specializing in behavioral treatment was more effective in reducing key symptoms than standard therapy.

trial registrationClinicalTrials.gov NCT05745103; https://classic.clinicaltrials.gov/ct2/show/NCT05745103.

Indexed as

AnxietyCognitive Behavioral TherapyDepressionAdultArtificial IntelligenceBehavior TherapyFemaleHumansMaleTreatment Outcomeanxietyartificial intelligenceaugmentationcognitive-behavioral therapycommunity-based centerdepressiondepressiveevidence-based practiceshealth force burnout

Identifiers

PMID37428547
PMCPMC10366966
OpenAlexW4381999428

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.