AI and Digital Tools: Revolutionizing Depression Diagnosis and Treatment

Apps and AI could help personalize depression diag | Newswise

Newswise -- New research at the University of Illinois Chicago is testing whether digital tools can help predict which patients with depression will benefit from specific treatments and help deliver those treatments to them on demand. Two new grants awarding over $10 million to UIC will help Dr. Jun Ma and colleagues in the College of Medicine investigate the use of a smartphone app, an AI voice assistant and other technologies to diagnose and treat depression. The researchers hope these tools will both broaden access to psychiatric care and help realize the promise of precision psychiatry, a paradigm of medicine where health care is more personalized, predictive and preventive. "We want to use new digital assessment tools to better monitor and predict the disease trajectory and treatment response of people with depression," said Ma, the Beth Fowler Vitoux and George Vitoux Distinguished Professor at UIC. "Then we can provide patients with the kind of precision treatment that can work for them now, instead of waiting for weeks, months or even a year to see how they respond, and also use new digital tools to deliver proven therapies at scale." Treating different types of depression Psychiatrists know there is no one-size-fits-all treatment for depression. In fact, evidence suggests the disorder may be comprised of several clinical subtypes. Recently, Ma and researchers at Stanford University published a study in Nature Medicine that identified six depression biotypes using brain scans and machine learning. Some of these subtypes were more responsive to antidepressant medication, while others benefitted more from therapy. With a grant to Stanford and UIC from the National Institute of Mental Health's precision medicine in psychiatry initiative, Ma and her collaborators will build on these findings by adding new diagnostic tools to the brain-scan data and launching a clinical trial. Of the grant, $6.8 million will go to UIC researchers. The study will use BiAffect, a smartphone app created by UIC researchers Dr. Alex Leow and Peter Nelson that measures cognitive health through changes in typing behavior during everyday tasks such as texting friends or posting on social media. With BiAffect, researchers will be able to assess patients between clinic visits to generate new information that may help identify additional subtypes of depression, said UI Center on Depression and Resilience Professor of Psychiatry Dr. Olusola Ajilore. "There's an increasing understanding of the importance of how we think and how alterations in how we think play a role in mood disorders," Ajilore said. "For a long time, we've just focused on the emotional part of mood disorders -- feeling depressed, feeling manic -- but there's a cognitive part that's also really important." Based on this new information, researchers will sort study participants into groups who have cognitive dysfunction and those who don't, then give them either an antidepressant or an antidepressant plus a blood-pressure drug currently used for ADHD and PTSD. "The grand goal of the study is to stratify patients so that we can better tailor treatments for them, rather than treating everybody with depression and putting them all in the same bucket," Ajilore said. A fully digital intervention for depression and obesity Among middle-age and older adults, depression often coincides with obesity, particularly in Black and Latino people. Ma and her team in the Vitoux Program on Aging and Prevention at UIC previously showed that combining behavioral interventions for the two conditions could be more effective than addressing them one at a time. A second grant of $4 million from the National Institute on Aging will fund a new trial that uses an AI virtual coach to provide behavioral therapy for depression, paired with a video-based anti-obesity program to create a fully digital intervention for patients. Lumen, an app on the Amazon Alexa platform, guides patients through problem-solving therapy. In a pilot study, the app intervention was associated with reduced depression and anxiety in patients. There were especially promising results in women and non-white patients. The new study will primarily enroll Black and Latino adults between the ages of 50 and 74 -- groups that generally have poor access to psychiatric treatment. As with the other study, researchers will assess which individuals and groups respond best to the paired interventions to further customize treatments to patients in the future. "By using these latest digital interventions to help deliver care at scale, with a particular emphasis on medically underserved populations, we can help address accessibility and also deliver the right treatment to the right patient at the right time," Ma said. "And this aligns with the mission of the Vitoux Program."

UIC researchers explore digital tools to personalize depression treatment

University of Illinois ChicagoJul 16 2024 New research at the University of Illinois Chicago is testing whether digital tools can help predict which patients with depression will benefit from specific treatments and help deliver those treatments to them on demand. Two new grants awarding over $10 million to UIC will help Dr. Jun Ma and colleagues in the College of Medicine investigate the use of a smartphone app, an AI voice assistant and other technologies to diagnose and treat depression. The researchers hope these tools will both broaden access to psychiatric care and help realize the promise of precision psychiatry, a paradigm of medicine where health care is more personalized, predictive and preventive. We want to use new digital assessment tools to better monitor and predict the disease trajectory and treatment response of people with depression. Then we can provide patients with the kind of precision treatment that can work for them now, instead of waiting for weeks, months or even a year to see how they respond, and also use new digital tools to deliver proven therapies at scale." Dr. Jun Ma, the Beth Fowler Vitoux and George Vitoux Distinguished Professor at UIC Treating different types of depression Psychiatrists know there is no one-size-fits-all treatment for depression. In fact, evidence suggests the disorder may be comprised of several clinical subtypes. Recently, Ma and researchers at Stanford University published a study in Nature Medicine that identified six depression biotypes using brain scans and machine learning. Some of these subtypes were more responsive to antidepressant medication, while others benefitted more from therapy. With a grant to Stanford and UIC from the National Institute of Mental Health's precision medicine in psychiatry initiative, Ma and her collaborators will build on these findings by adding new diagnostic tools to the brain-scan data and launching a clinical trial. Of the grant, $6.8 million will go to UIC researchers. The study will use BiAffect, a smartphone app created by UIC researchers Dr. Alex Leow and Peter Nelson that measures cognitive health through changes in typing behavior during everyday tasks such as texting friends or posting on social media. With BiAffect, researchers will be able to assess patients between clinic visits to generate new information that may help identify additional subtypes of depression, said UI Center on Depression and Resilience Professor of Psychiatry Dr. Olusola Ajilore. "There's an increasing understanding of the importance of how we think and how alterations in how we think play a role in mood disorders," Ajilore said. "For a long time, we've just focused on the emotional part of mood disorders -; feeling depressed, feeling manic -; but there's a cognitive part that's also really important." Based on this new information, researchers will sort study participants into groups who have cognitive dysfunction and those who don't, then give them either an antidepressant or an antidepressant plus a blood-pressure drug currently used for ADHD and PTSD. "The grand goal of the study is to stratify patients so that we can better tailor treatments for them, rather than treating everybody with depression and putting them all in the same bucket," Ajilore said. A fully digital intervention for depression and obesity Among middle-age and older adults, depression often coincides with obesity, particularly in Black and Latino people. Ma and her team in the Vitoux Program on Aging and Prevention at UIC previously showed that combining behavioral interventions for the two conditions could be more effective than addressing them one at a time. A second grant of $4 million from the National Institute on Aging will fund a new trial that uses an AI virtual coach to provide behavioral therapy for depression, paired with a video-based anti-obesity program to create a fully digital intervention for patients. Lumen, an app on the Amazon Alexa platform, guides patients through problem-solving therapy. In a pilot study, the app intervention was associated with reduced depression and anxiety in patients. There were especially promising results in women and non-white patients. The new study will primarily enroll Black and Latino adults between the ages of 50 and 74 -; groups that generally have poor access to psychiatric treatment. As with the other study, researchers will assess which individuals and groups respond best to the paired interventions to further customize treatments to patients in the future. "By using these latest digital interventions to help deliver care at scale, with a particular emphasis on medically underserved populations, we can help address accessibility and also deliver the right treatment to the right patient at the right time," Ma said. "And this aligns with the mission of the Vitoux Program." University of Illinois Chicago