SEATTLE–(BUSINESS WIRE)–Aiberry®, a leading AI-powered mental health assessment platform, has successfully completed a clinical validation study in collaboration with The University of Texas at Austin. The study clearly demonstrates that Aiberry’s model of depression risk is clinically equivalent to gold-standard depression questionnaires and that the model showed no evidence of bias related to gender, age, or race. Aiberry’s distinctive, multi-modal approach evaluates an individual’s mental health by analyzing text, audio, and video cues during a bot-administered interview.
“Aiberry provides the nuance clinicians need that gold-standard forms lack”
Addressing the Mental Health Provider Shortage and Burnout
“The US could double its number of mental health professionals overnight and still have a severe provider shortage,” said Lynne Dunbrack, Group Vice President for IDC Health Insights. “Clinicians are overwhelmed by burgeoning caseloads and administrative demands, resulting in extended wait times for patients. AI-powered tools like Aiberry can provide clinically relevant information immediately and at scale. This information ecosystem can streamline clinical decision-making processes and simplify back-office tasks, which empowers clinicians to prioritize patient care and outcomes.”
An Enhanced Experience with Mental Health Assessment
The status quo of depression measurement requires individuals to self-rate the frequency and severity of their depression symptoms by picking a “best describes you” answer from a series of multiple-choice questions. Aiberry’s app offers the option of a novel AI assessment featuring a friendly digital animation called “Botberry” that encourages users to talk about themselves in their own words. An ensemble of machine learners aggregates the responses to these questions and outputs an overall depression risk score, along with symptom-level insights and a transcript of each response.
“Aiberry provides the nuance clinicians need that gold-standard forms lack,” said Rachel Weisenburger, lead author of the clinical validation study from The University of Texas at Austin. “Aiberry understands depression isn’t one size fits all. While gold-standard depression forms can tell you which symptoms are bothering someone, they give you no context. Aiberry paints a more complete picture, capturing the messy, human experience of depression in people’s own words.”
Conducted by The University of Texas in collaboration with Georgetown University Medical Center and the University of Arizona, this study is currently under peer review (preprint available here). Nearly 400 participants, aged 18 to 74, answered questions posed by Botberry and completed a gold-standard depression questionnaire. Aiberry then generated a depression risk score based on the Botberry-administered interview responses. In cases of meaningful discrepancies between Aiberry’s risk score and the gold-standard form, clinicians conducted a masked review to determine which they were more clinically aligned with.
User-centric Experience, with Gold Standard Insights
The post-study user experience survey revealed a clear preference for Aiberry over multiple-choice questionnaires, with 3 out of 4 users preferring Aiberry when asked which assessment type provided the best mental health information. This preference jumped to 4 out of 5 for those scored as having a mild-to-moderate depression risk—possibly because filling out a form is easier for someone with either no symptoms or constant symptoms. But depression manifests on a spectrum, and those in the middle may find it harder to reduce their subjective experience into one of four prewritten responses. Overall, 88% of all respondents—regardless of depression severity—expressed a desire to use Aiberry at least monthly for mental health monitoring.
“In an era where the demand for mental health services far outpaces the supply of providers, having a trusted, clinically validated platform for assessment is a game-changer for both patients and clinicians,” said Linda Chung, Aiberry Co-CEO. “Crossing the clinical validation threshold is a massive milestone for Aiberry, and reaching parity with the current gold standard exceeded our initial expectations. As Aiberry continues to scale and help more people, the AI model will only improve. This is only the beginning of Aiberry’s mission to make mental health screening more accessible, accurate, and human-centered.”
Aiberry (pronounced “I” + “berry”) is an innovative and practical mental health screening solution that improves efficiency and saves time for healthcare providers. Its cutting-edge AI technology is based on two decades of research bundled into a powerful solution that helps providers better serve their patients. Its Machine Learning (ML) pipelines are designed to eliminate biases, including those related to age, gender, sexual orientation and race. For more information, visit www.aiberry.com.
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