SilverCloud Health and Microsoft Announce New Key Findings Linking Engagement

In largest dataset of its kind, digital mental health study published in JAMA Network Open serves as foundation for delivering personalized patient treatment based on AI and machine learning

SilverCloud Health, the world’s leading digital mental health platform, announced that JAMA Network Open has published clinical findings from an ongoing study with Microsoft that aims to advance personalized internet-delivered cognitive behavioral therapy (iCBT) interventions for the treatment of symptoms of depression, anxiety and stress. The JAMA paper discusses a 14-week study of 54,604 patients’ anonymized data as part of a 2-year research project between SilverCloud Health and Microsoft Research Cambridge. The research explores how artificial intelligence can be used to enhance SilverCloud Health’s digital mental health services to a large and growing number of people in need of effective and accessible care.

The key findings from the study, “A Machine Learning Approach to Understanding Patterns of Engagement with Internet-delivered Mental Health Interventions,” include the identification of five heterogeneous subtypes based on patient engagement with online intervention; these subtypes are associated with different patterns of patient behaviors and different levels of improvement in symptoms of depression and anxiety. Patterns of behavior may elucidate different modalities of engagement, which can help SilverCloud better triage patients for personalized therapeutic activities to improve outcomes and have a positive impact on those with mental health conditions. Understanding each heterogeneous subtype and pattern behavior will enable SilverCloud to predict future interactions with iCBT and create earlier intervention strategies.

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“By using artificial intelligence and machine learning, we’re making important strides toward more deeply understanding different types of engagement behaviors related to our best-in-class digital mental health platform,” said Ken Cahill, CEO of SilverCloud Health. “We hope that using Microsoft’s findings may pave the way for us to deliver even more personalized interventions that maximize engagement and improve patients’ clinical outcomes. Delivering the right content to the right person at the right time results in better clinical outcomes and even higher engagements.”

The fluctuating and sensitive nature of mental health symptomology has engendered a need for increased access to treatments that meet each person’s needs and desired outcomes. SilverCloud and Microsoft’s collaboration, called Project Talia, uses probabilistic machine learning frameworks to identify new routes for personalizing treatment while improving patient engagement and clinical outcomes.

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“Our work with SilverCloud focuses on how machine learning can meaningfully assist in the detection, diagnosis, and treatment of mental health problems,” said Danielle Belgrave, principal researcher, Microsoft Research, Cambridge, UK. “Through our collaboration, we’re learning how internet-delivered cognitive behavioral therapy can be more effective when personalized treatment recommendations are provided to patients”

The study’s findings arrive amidst globally rising symptoms of stress, anxiety and depression catalyzed by the SARS CoV-2 (COVID-19) pandemic, where expanded access to digital mental health therapeutics is paramount. With traditional face-to-face therapeutic services disrupted, online interventions continue to offer proven equivalent clinical outcomes. In 2019, SilverCloud Health released a whitepaper about how patients who implemented digital mental health tools achieved up to 65% reduction in symptom scores.

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