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Frontiers in Digital Health Publication Presents Feel


SAN FRANCISCO, Aug. 12, 2022 (GLOBE NEWSWIRE) — Feel Therapeutics Inc., a leader in digital precision medicine for Mental Health, today announced the publication in Frontiers in Digital Health of a landmark clinical feasibility study showing the effectiveness of Feel’s digital biodata-driven intervention program for anxiety and depression.

The publication, “Feasibility, engagement, and preliminary clinical outcomes of a digital biodata-driven intervention for anxiety and depression”, presented the results of a real-world-data study designed to evaluate different aspects of the Feel Program. The Feel Program is a 16-week, fully-remote, digital mental health support program created by Feel Therapeutics to bring objective data and precise support into the management of mental health. The program combines remote patient monitoring, using a proprietary emotion-sensing wearable device, with digital interventions and coaching to provide mental health support on a 24/7/365 basis.

In this study, 48 participants suffering from mild or moderate Major Depressive Disorder (MDD) and Generalized Anxiety Disorders (GAD) symptoms participated in the Feel Program and were assessed across three key metrics: feasibility of the program, participant engagement, and symptom improvement. The results demonstrated a very high average precision level (87%) in identifying emotional events passively through the wearable device. Furthermore, the study showed high engagement rates of >60 minutes per week of app usage, and 4 out of 5 participants were very likely to recommend the program.

Most important, for both MDD and GAD symptoms—reflected by PHQ-9 and GAD-7 scores, respectively—the average reduction in both scales during the 16-week program was over 50%, while 93.5% of participants presented a decrease in at least one of the depressive or anxiety symptoms. Notably, this symptom improvement was followed by an average increase of 15% in quality of life and 24% in life satisfaction metrics.

“Almost every medical field has been using objective measurement tools, such as the glucose monitor in diabetes or blood pressure monitor in heart disease, for decades already. However, when it comes to Mental Health, we still rely on self-reported questionnaires to track symptoms and offer episodic care, leading to suboptimal and delayed interventions,” said Haris Tsimpras, PhD, co-founder and CTO of Feel Therapeutics. “This study is an important milestone that shows how our remote, data-driven, digital mental health solution helps us objectively and continuously monitor mental health and offer improved outcomes to patients suffering from depressive and anxiety disorders.”

This article comes as an addition to two peer-reviewed publications that showed the effectiveness and accuracy of monitoring psychophysiological reactions, namely Electrodermal Activity (EDA) and Heart Rate Variance (HRV), using Feel’s proprietary emotion-sensing wearable device, to assess chronic and acute stress conditions. The findings showed that HRV and EDA could serve as objective biomarkers for both scientific and clinical insights, promising to be a global psychophysiological index of stress resilience. These studies can be found in Elsevier-Physiology & Behavior and the International Journal of Environmental Research and Public Health.

About Feel Therapeutics

Feel Therapeutics, Inc. is developing Digital Biomarkers and Therapeutics to bring objective data and measurement in the way we diagnose, manage, and care for Mental Health. The company is backed by top-tier investors (Felicis, Anthemis, SOSV) and partners with large pharmaceutical companies to develop novel digital biomarkers and bring digital health solutions to market as standalone programs or alongside medications. Feel Therapeutics is headquartered in San Francisco, with additional offices in Europe. For more information, visit http://www.feeltherapeutics.com or contact us at info@feeltherapeutics.com.

KEYWORDS data-driven therapeutics, major depressive disorder, generalized anxiety disorder, psychophysiological data, emotion detection, digital therapeutics, mental health biomarkers



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