JMIR Publications

ABSTRACT

Background:

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.

Objective:

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.

Methods:

The study was conducted at a community-based clinic in the U.S. 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 compared to treatment-as-usual (TAU) during the first two months of therapy. This AI platform summarizes and transcribes the therapy session, provides feedback to therapists on the usage of evidence-based practices (EBPs), 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 intention-to-treat 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.

Results:

Seventy-two patients were approached, of whom 47 (67%) agreed to participate. Participants were adults (34 [72.34%] women and 13 [27.65%] men; mean [SD] age was 30.64 [11.02] years old), 23 randomized to the AI platform group, and 24 to TAU. Participants in the AI group attended, on average, 67% more sessions (n = 5.24, SD = 2.31) than those in TAU (n = 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.

Conclusions:

In this RCT, 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. Clinical Trial: ClinicalTrials.gov NCT05745103