Artificial intelligence (AI) holds great promise for improving mental health, but it also is a rapidly changing field with much to learn and discover. Together with top AI experts at Rice University's Ken Kennedy Institute, Menninger researchers are exploring AI’s potential application in intensive mental health care settings and leveraging the institute’s deep expertise to study ethical concerns, privacy issues and the importance of human oversight in AI efforts.
Researchers believe that AI informed by mental health professionals and patients with lived experience could help to bridge care gaps and improve patient outcomes. By combining big data from sources like health records and wearable technology, AI might offer deeper data-driven insights that improve care. For example, following a hospital stay, AI could assist clinicians in predicting low moods or knowing the best timing to send encouraging messages. While we’re not there yet, the goal is to ensure a personalized and supportive mental health journey.
“We know that when patients in intensive mental health care settings have control, contribute to the direction of their care, and feel safe, it results in better clinical outcomes," says Michelle Patriquin, PhD, ABPP, Menninger’s director of Research and an associate professor at in the Menninger Department of Psychiatry & Behavioral Sciences at Baylor College of Medicine.
So, what is artificial intelligence, exactly? Put simply, AI involves computer systems capable of human-like thinking, such as problem-solving, learning and decision-making. In mental health care, this technology is being harnessed to create tools for improved diagnosis and personalized treatments, ranging from mood and behavior tracking apps to virtual therapists. Importantly, AI should be designed to complement, not replace, human clinicians who bring care, compassion and years of training and experience to the therapeutic and assessment process.
In research settings, AI tools are frequently used to analyze “big data,” helping generate new hypotheses and speeding advances that otherwise would require years of study. At Menninger, our researchers use machine-learning to analyze biological information and mental health symptoms collected from 800 study participants of the McNair Initiative for Neuroscience Discovery at Menninger and Baylor College of Medicine (MIND-MB). The tool is helping researchers uncover biological factors linked to mental health disorders, potentially transforming the diagnosis and treatment of conditions like depression, anxiety and suicide, where clear biological markers are often lacking.
Teaming up with world renowned AI experts at Rice enables Menninger to increase the clinical actions and insights we can discover and, ultimately, develop strategies that improve mental health care for everyone. United in purpose, Rice and Menninger are shaping a brighter future for mental health through collaboration and data-driven solutions.