How AI is Increasing Accessibility to Mental Health Care

Jul 3, 2018 · 3 min read

Since nearly one in five American adults experience some mental health challenge, health care providers are designing new ways to support patients. In recent years, data scientists and engineers have been applying techniques from artificial intelligence to provide mental health care.

Access to counseling in moments of despair is critical, but may be inaccessible when needed most. Additionally, counseling is often expensive, creating an often insurmountable barrier for those who cannot afford it. Several startups are deploying artificial intelligence to mitigate those challenges.

For example, X2AI is developing a mental health chatbot that they call Tess, which is “available 24/7 and accessible by any cell phone, from any location to deliver support using an integrative mental health approach, including: CBT, SFBT, Mindfulness and more.”

X2AI has tested the app with Northwestern University to determine its efficacy in reducing symptoms of depression and anxiety in college students. The company reported that students who used the app for 2–4 weeks experienced a “reduction in symptoms” of depression by 13% and a reduction in symptoms of anxiety of 18% against the control group.

Other chatbots like Woebot, and are making similar advances. uses AI in conjunction with a network of clinical professionals, referring users to next steps of treatment. In other words, the company leverages the unique capabilities of machines and humans to treat patients.

“Using digital technology and machine learning, we can make behavioral health more accessible and convenient, while reducing the stigma attached to the traditional solutions,” Rebecca Chiu, Head of Business Development at, said.

It is also possible that the accessibility of such solutions will make it easier for people who are skeptical about or afraid of counseling to seek the help they need. Some may find it easier to speak with an AI that they may view as a neutral observer.

Chatbots may also be especially useful in moments of crisis. Recognizing the need to give people in crisis the human connection that is needed, the Crisis Text Line is using machine learning to identify the most urgent cases. As Vox explained, “the computer tells them who on hold needs to jump to the front of the line to be helped.”

The Crisis Text Line’s data has also generated new insights for mental health professionals. Their data indicates the states with the most severe crises, recurring issues in conversations, times of day that are the most acute, and many more useful data points for future researchers.

The influence of AI in mental health care is not limited to chatbots, however. Charlotte Stix, a Policy Officer and Postdoctoral Research Associate on Artificial Intelligence (AI) Policy at the Leverhulme Centre for the Future of Intelligence in the University of Cambridge, explained that AI can help doctors detect signs of depression earlier.

Stix highlighted IBM’s deployment of natural language processing to detect differences in speech patterns between patients who develop psychosis and those who do not. “After training this AI system over two studies, IBM achieved an incredible 83% of retrospective accuracy of detection in the second study group. It was a quantifiable demonstration of the power of listening,” she wrote.

Although the new technologies will not replace the need for human connection or support other areas that impact mental health, these narrow applications of artificial intelligence are a positive development for all.


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