Scientific Methods For Detecting Mental Health Disorders

The mental health epidemic in the US is growing: according to the National Health Institute, 18.9% of all U.S. adults self-diagnose as having a mental health disorder. Digital solutions, many with artificial intelligence (AI) at their core, offer hope for combating the rise of mental illness.

Many diagnostic tools for mental illness work by analyzing common speech habits associated with specific mental illnesses, as well as other tracking tools for analyzing data. The onset of digital tools for mental health have serious, positive implications for addressing America’s mental health crisis at a reasonable cost, especially in lacking communities. 

AI-Based Diagnosis 

Digital methods for diagnosing mental health are particularly useful for assessing different types of personality disorders, many of which are hard to differentiate and detect among young adults. In 2015, a team of researchers developed an AI model that correctly predicted, which members of a group of young people would go on to develop psychosis—a major feature of schizophrenia—by analyzing their speech habits.  This model focused on tracing conventional verbal cues indicative of psychosis, such as confusing and frequent use of words like “this” or “that” and short, abrupt sentences with muddled intention

Refined Accuracy And Precision

One of the issues with traditional methods for diagnosing mental illness is that the process relies on humans, who are prone to bias and, occasionally, miscalculation. Recent estimates suggest that 69% of patients with bipolar disorder are initially misdiagnosed, with one-third of patients with bipolar disorder misdiagnosed for 10 years or more. AI diagnostic tools for mental health are working to sharpen the exactitude of obtaining a diagnosis, along with preemptively detecting illnesses before the onset of symptoms. Currently, researchers at the Alan Turing Institute are developing an AI model for predicting mental health disorders before the onset of symptoms, which may help individuals obtain preemptive treatment as needed.

Addressing A Personnel Crisis

The demand for digital and tech solutions for treating mental health emerges out of a dire shortage of mental health professionals. In the US, nearly 40% of the federal population lives in areas designated by the government as having a shortage in mental health professionals. Often, the hiring shortage in mental health professionals leads to exorbitant costs for treatment, especially for Americans without health insurance. As an alternative, tech solutions for mental health offer affordable treatment options to Americans in need. A small-scale example of this is the rise of mental health-related smartphone apps, many of which are designed to offer treatment solutions and diagnostic tools to users without direct engagement with a mental health professional.

The intersection of AI-based digital methods and mental health assessment offers patients the possibility of obtaining early and accurate diagnoses for their conditions. Jointly, tech giants and university laboratories are racing to determine the precision needed for detecting mental health issues, even before symptoms begin to arise. Their research has major, potentially life-changing, implications for negotiating America’s crisis in mental healthcare.