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Clinical Trial Summary

This study examines the impact of using an algorithm to select therapy content for patients engaged with the mobile mental health platform AmDTx (Mobio Interactive). The algorithm is to be trained with three separate sources of data. Two sources of data come from self-reports by the patients themselves, provided before and after engaging with therapy content. The third source of data comes from an objective measurement of psychological stress, made possible through artificial analysis of computer vision data captured from the mobile device camera as the patient completes a 30 second selfie video before and after engaging with therapy content.


Clinical Trial Description

From 2,786 unique individuals engaging between March 2015 and December 2022 in English language psychotherapy sessions and providing pre- and post-session self-report and facial biometric data via the AmDTx mental health platform (Mobio Interactive Pte Ltd, Singapore), analysis was conducted on 67 "super users" that completed at least 28 sessions with all pre- and post-session measures. AmDTx is a clinically validated mental health platform that provides patients with audio recordings supporting mental wellbeing (asynchronous and on-demand psychotherapy). AmDTx also contains easy to use tools that rapidly assess mental wellbeing, including an objective measure of psychological stress derived from AI analysis of facial biomarkers (Objective Stress Level; ∆OSL), and ecological momentary assessments (EMAs). Two commonly used EMAs within AmDTx are self-reported stress (∆SRS) and self-reported mood (∆SRM). These three data sources were used to independently train an algorithm designed to predict what future therapy sessions would prove most efficacious for each individual. Algorithm predictions were compared against the efficacy of the individual's self-selected sessions. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT06265909
Study type Observational
Source Mobio Interactive PTE LTD
Contact
Status Completed
Phase
Start date March 1, 2015
Completion date December 31, 2022

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