(MENAFN- EIN Presswire)
Dr. Girish Srinivasan - Chief Science Officer and Co-founder at Behavidence
Behavidence Care - Clinician's Platform
Dr. Janine Ellenberger, Chief Medical Officer and Co-founder at Behavidence
New study shows Behavidence's AI predicts PHQ-9 scores daily with passive biomarkers, ensuring privacy, and high accuracy in mental health tracking.
By removing the need for repetitive questionnaires, we're making mental health monitoring more accessible and less intrusive, while still delivering clinically valuable insights,” - Dr. Janine EllenbergerNEW YORK, NY, UNITED STATES, January 8, 2025 /EINPresswire / -- Behavidence, a leader in mental health technology, has introduced a pioneering research demonstrating how digital behaviors can passively predict responses to PHQ-9 questions, eliminating the need for traditional mental health questionnaires.
The study , published on JMIR Preprints, highlights how this innovation transforms mental health monitoring into a seamless, automated process that benefits both patients and clinicians.
The PHQ-9 questionnaire, originally created by Pfizer , is a cornerstone in assessing depressive symptoms, but its reliance on self-reported answers can present challenges for both patients and providers. Behavidence's cutting-edge technology uses AI-driven models to analyze passive data from smartphones-such as app usage patterns and device interactions-to predict specific PHQ-9 responses on a daily basis. This passive, automated approach reduces the burden of self-reporting while offering real-time insights into mental health trends.
Key Findings:
Behavidence's AI models accurately predict individual PHQ-9 items, such as sleep patterns, mood, and energy levels, using passive digital biomarkers.
Daily predictions are generated without the need for manual patient input or questionnaires.
The technology maintains clinical accuracy while enhancing scalability and usability for both patients and healthcare providers.
Key Differentiators Identified in the Study:
Privacy-Focused: No personalized data was collected, ensuring a safer and more privacy-conscious approach for patients.
Effortless Monitoring: The biomarkers did not require any active participation, making the system seamless and user-friendly while reducing stigma.
Unmatched Accuracy: The models demonstrated higher daily accuracy compared to other biomarkers available, setting a new standard in mental health prediction.
Expert Perspectives on the Study
“This innovation addresses one of the major barriers in mental health care-sustained patient engagement. By removing the need for repetitive questionnaires, we're making mental health monitoring more accessible and less intrusive, while still delivering clinically valuable insights,” said Dr. Janine Ellenberger, Chief Medical Officer at Behavidence.“This is particularly valuable for patients managing long-term mental health conditions or for clinicians looking to monitor larger populations efficiently.”
Dr. Girish Srinivasan, Chief Science Officer at Behavidence, added,“This study is a testament to the power of AI and digital biomarkers in mental health care. We're not just predicting scores; we're uncovering patterns and trends that can guide personalized treatment strategies and interventions. Our ability to passively and accurately predict specific PHQ-9 responses daily represents a new era of real-time mental health management.”
Potential for Clinical Studies in Pharma
The findings from this study have significant implications for pharmaceutical companies with extensive psychiatric portfolios. The ability to passively and accurately track depressive symptoms daily offers a powerful tool for enhancing clinical trials. This technology can streamline data collection, improve patient compliance, and provide real-time insights into treatment efficacy. Companies like Pfizer, Janssen Pharmaceuticals (a division of Johnson & Johnson), Lundbeck, Otsuka Pharmaceutical, and Eli Lilly, all of which have robust pipelines in psychiatry, could benefit from incorporating these digital biomarkers to advance their research and improve patient outcomes.
Transforming Mental Health Monitoring
The implications of Behavidence's technology extend far beyond individual patient care. By enabling continuous and passive data collection, clinicians gain unprecedented insights into patient well-being between visits, facilitating earlier interventions and more personalized treatment. For patients, this innovation offers a low-effort solution that integrates seamlessly into daily life, reducing the stigma and inconvenience of traditional assessments.
A New Standard for Mental Health Care
This passive monitoring approach has broad applications across clinical settings, research, corporate wellness programs, and population health initiatives, making it a scalable solution for addressing mental health challenges on a global scale.
The preprint of the study is available here:
Roy Cohen
Behavidence
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