by A groundbreaking mental health assessment powered by artificial intelligence (AI) has been found to be just as effective as standard questionnaires in evaluating depression symptoms, according to researchers from The University of Texas at Austin. The AI technology could potentially help address the national shortage of mental health professionals.
The study, published in the Journal of Affective Disorders, showcased the AI platform developed by Aiberry, which can accurately assess an individual’s mental health by analyzing text, audio, and video cues during an interview conducted by a chatbot. Importantly, the AI system did not display any bias related to gender, age, or race.
The discovery that depression can be accurately evaluated through an AI-driven interview is an intriguing and significant finding, commented Christopher Beevers, a co-author of the study and the Wayne H. Holtzman Regents Chair in Psychology and director of UT’s Institute for Mental Health Research.
The ability to monitor depression symptoms on a regular basis and at scale could revolutionize the identification of individuals in need of intervention. The reliable identification of those suffering from depression removes a significant obstacle in achieving this broader goal.
Traditionally, the measurement of depression requires individuals to self-assess the frequency and severity of their symptoms by selecting the answer that best describes their experience from a series of multiple-choice questions.
Aiberry’s app offers an alternative AI assessment, featuring a digital animation called Botberry, which encourages users to express themselves in their own words. Through machine learning software, the app aggregates the responses to these questions and produces an overall depression risk score, along with insights into individual symptoms and a transcript of each response.
This platform provides the nuance that clinicians need, which is lacking in traditional assessment forms, said Rachel Weisenburger, who led the study and is a doctoral student in UT’s Mood Disorders Laboratory. While standard depression forms can indicate which symptoms are affecting someone, they do not provide any context. Depression is not a one-size-fits-all condition, and the results of this AI-powered interview offer a more comprehensive picture, capturing the complex and personal experience of depression through individuals’ own words.
In collaboration with Georgetown University Medical Center and the University of Arizona, the study involved 400 participants aged between 18 and 74, who answered questions from Botberry and completed a depression questionnaire. Based on the interview responses, the app generated a depression symptom severity score.
In cases where there were significant discrepancies between Aiberry’s score and the questionnaire results, clinicians conducted a masked review to determine which assessment was more clinically aligned. However, there was generally agreement between clinician ratings and Aiberry scores. Overall, 88% of respondents expressed a desire to use Aiberry on a monthly basis for mental health monitoring, regardless of the severity of their depression.
As technology and mental health assessment continue to converge, having a clinically validated platform for assessment is crucial in establishing trust, said Linda Chung, co-CEO of Aiberry. Our AI-powered platform has the potential to reshape mental health identification and support, marking a significant step toward accessibility for all. At Aiberry, we are dedicated to promoting mental well-being by empowering individuals and healthcare professionals alike.
Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
