{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T19:47:37Z","timestamp":1788378457292,"version":"build-2803163510"},"reference-count":52,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"\n Background<\/jats:title>\n Before meaningful progress toward precision psychiatry is possible, objective (unbiased) assessment of patient mental well-being must be validated and adopted broadly.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aims to compare the fidelity of a precision psychiatry therapy recommendation algorithm when trained with an objective quantification of psychological stress versus subjective ecological momentary assessments (EMAs) of stress and mood.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n From 2786 unique individuals engaging between March 2015 and December 2022 in English language psychotherapy sessions and providing pre- and postsession self-report and facial biometric data via a mobile health platform (Mobio Interactive Pte Ltd, Singapore), analysis was conducted on 67 \u201csuper users\u201d that completed a minimum of 28 sessions with all pre- and postsession measures. The platform used has previously demonstrated reduced psychiatric symptom severity and improved overall mental well-being. Psychotherapy recordings (\u201csessions\u201d) within the platform, available asynchronously and on demand, span mindfulness, meditation, cognitive behavioral therapy, client-centered therapy, music therapy, and self-hypnosis. The platform also has the unusual ability to rapidly assess mental well-being without bias via an easy-to-use objective measure of psychological stress derived from artificial intelligence\u2013based analysis of facial biomarkers (objective stress level [OSL]). In tandem with the objective measure, EMAs obtain self-reported values of stress (SRS) and mood (SRM). \u2206OSL, \u2206SRS, and \u2206SRM (with delta referring to the presession subtracted from the postsession measurement) were used to independently train a therapy recommendation algorithm designed to predict what future sessions would prove most efficacious for each individual. Algorithm predictions were compared against the efficacy of the individual\u2019s self-selected sessions.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n The objective measure of psychological stress provided a differentiated delta for the measurement of therapeutic efficacy compared to the 2 EMA deltas, as shown by clear divergence in \u2206OSL vs \u2206SRS or \u2206SRM (r<0.03), while the EMA deltas showed significant convergence (r=0.53, P<.01). The recommendation algorithm selected increasingly efficacious therapy sessions as a function of training data when trained with either \u2206OSL (F1,16=5.37, P=.03) or \u2206SRM data (F1,16=3.69, P<.05). However, the sequential improvement in prediction efficacy only surpassed the efficacy of self-selected therapy when the algorithm was trained using objective data (P<.01). Training the algorithm with EMA data showed potential trends that did not reach significance (\u2206SRS: P=.09; \u2206SRM: P=.12). As a final insight, self-selected therapy sessions were overrepresented among the algorithmically recommended sessions, an effect most pronounced when the algorithm was trained with \u2206OSL data (F1,14=30.94, P<.001).<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n These prospective data demonstrate that a rapid, scalable, and objective measure of psychological stress, in combination with a robust recommendation algorithm, can autonomously identify clinically meaningful therapy for individuals. More broadly, this work illustrates the potential for objective data on mental well-being to improve precision psychiatry and the capacity for mental health care professionals to match global demand.<\/jats:p>\n <\/jats:sec>\n \n Trial Registration<\/jats:title>\n ClinicalTrials.gov NCT06265909; https:\/\/clinicaltrials.gov\/ct2\/show\/NCT06265909<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/56086","type":"journal-article","created":{"date-parts":[[2025,4,29]],"date-time":"2025-04-29T01:55:06Z","timestamp":1745891706000},"page":"e56086","source":"Crossref","is-referenced-by-count":6,"title":["Scalable Precision Psychiatry With an Objective Measure of Psychological Stress: Prospective Real-World 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