The Pilot Will Utilize the Ellipsis Health Technology to Generate Machine-Learning-Based Assessment of Anxiety and Depression Symptoms through Analysis of Student Speech
Ellipsis Health, pioneer of the first commercial-grade voice-based vital signs to quantify and manage depression and anxiety symptoms at scale, has announced an academic year-long pilot program with Menlo College, a private, non-profit college located in Atherton, California. The college’s Mental Health Services (MHS) Clinic will integrate Ellipsis Health’s technology solution, which empowers students to measure and manage anxiety and depression symptoms by leveraging vocal biomarker technology through analysis of their speech.
“Menlo College is dedicated to providing a broad range of cost-free support to enrolled virtual and campus-based students. Partnering with Ellipsis Health for this pilot program empowers our shared goal of meeting the mental health symptom identification needs of young adults, especially during this unprecedented time,” said Angela Schmiede, Vice President for Student Success at Menlo College. “Ellipsis Health’s technology pairs students’ comfort with their own smartphone for a voice-based emotional health vital sign. This way, we can support students that need assistance much sooner for well managed behavioral health.”
According to the National Institute of Mental Health, young adults aged 18-25 years have the highest prevalence of any mental illness (25.8%) compared to adults aged 26-49 years (22.2%) and aged 50 and older (13.8%). A recent survey by the Healthy Minds Network and the American College Health Association also found that 60% of students report that the pandemic has made it more difficult to access mental health care.
To help curb the prevalence of mental health conditions in young adults, Silicon Valley-based Ellipsis Health and Menlo College partnered for this pilot program to provide scalable mental health screening services to all students. Student leaders worked with Ellipsis Health to set the tone of the pilot through a series of collaborative working sessions with the goal of supporting the emotional wellbeing of their student community. The roll out of expanded health services directly reflects on Menlo College’s strong commitment to addressing the individual needs of all students within the college’s diverse population.
“When we as young people are able to use resources such as Ellipsis Health’s technology, it not only benefits our emotional health, which is extremely important, but can set a trend of ending generational traumas,” explained Lina Lakoczky-Torres, Wellness Representative, Menlo College Student Government Association, and entrepreneurship major. “When we are able to take our wellbeing into our own hands and accept and manage these different feelings when they arise, that is when we are empowered to be the best version of ourselves.”
Integration of Ellipsis Health’s technology solution at the MHS Clinic will allow for quantification of behavioral health vital signs via dual acoustic and semantic-based assessments of student speech. Through student screening for anxiety or depression symptoms, students will also be offered resources for extra support to improve health outcomes.
“Ellipsis Health is proud to collaborate with Menlo College to expand access to mental health screening through identification and management of anxiety and depression symptoms in students,” said Michael Aratow, Co-Founder and CMO, Ellipsis Health. “Especially now with students learning virtually, it is critical that colleges and universities roll out a solution that allows for clinical insight into a student’s wellbeing outside of a provider encounter, as many early warning signs of emotional challenges often occur at home. Leveraging the ubiquity of smartphones, we enable behavioral health measurement anytime and anywhere. Not only is this improving overall student health, but it is also helping to remove the stigma related to mental health conditions and symptom identification for young adults.”
Ellipsis Health works through cloud-based machine learning algorithms that assess patient voice data and generate predictions of depression, anxiety or other behavioral health conditions. The HIPAA-compliant platform facilitates visibility into these behavioral health symptoms for enhanced clinical decision support.