How AI Can Help Therapists Improve Therapy


The COVID-19 pandemic has taken a toll on the physical and mental well-being of humanity. The side effects of the impact have led to an increase in the number of people seeking help to cope with illness, unemployment and social isolation, all in an increasingly fast-paced and pressured world. However, the digital revolution that has transformed many aspects of our daily lives has yet to truly emerge in behavioral health care. Complementing therapy, AI and machine learning now appear to have the potential to revolutionize the way we diagnose and treat mental health issues. Soon, algorithms could become our first line of defense against mental health issues that can be debilitating for many.

How can AI help?

Researchers are now pioneering a new approach to mental health care in which an AI analyzes the language used during therapy sessions. An automated form of quality control is becoming increasingly essential to help therapists meet demand. Natural language processing, also known as NLP, identifies which parts of a conversation between therapist and client and what types of utterances and exchanges seem to be most effective in treating different disorders. Understanding the therapy’s most essential ingredients could help open the door to more personalized mental health care, allowing physicians to tailor psychiatric treatments to specific clients that are essential when prescribing drugs.

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Machine learning techniques that perform machine translation from sessions allow large amounts of the language to be analyzed quickly. This gives researchers access to an endless and untapped source of data: language therapists. The researchers also believe that they can use the information from the processed data to improve the treatment and its results. It can make more people get better and heal quickly.

Work

At the start, a few hundred transcripts are hand annotated to form the NLP patterns, emphasizing the role therapists and clients’ words play at this point in the session. The technology works similar to a sentiment analysis algorithm that can distinguish and tell whether movie reviews are positive or negative. Then, the AI ​​translates the natural language into a sort of barcode or fingerprint of a therapy session that reveals the full role played by different utterances. For example, a fingerprint for a session can show how much time was spent in constructive therapy versus general conversations. Such reading can help therapists focus more on the former in building future sessions. AI techniques could also help potential clients connect with therapists and determine what types of therapy will work best for them.

What else?

A virtual therapist named Ellie has also been launched and tested by the Institute for Creative Technologies (ICT) at the University of Southern California. Ellie was originally designed to treat veterans suffering from depression and post-traumatic stress disorder. It can detect words and non-verbal cues like facial expressions, gestures and different postures. Nonverbal cues are an important aspect of therapy, but they can be subtle and difficult to perceive. Ellie’s creators argued that this virtual human can advance mental health and improve diagnostic accuracy.

See also

A few psychologists argue that humans might find it easier to share potentially embarrassing information with a virtual therapist, while in human-to-human interactions there often seems to be some degree of restraint. It has been observed that when patients talk to a therapy robot, they report not feeling judged. Therapists, on the other hand, can discuss AI-generated feedback for further improvements. The idea is to help therapists take control of their professional development, showing them what they are good at, things other therapists can learn from, and a few of them are not very good. in areas they might want to work on.

In summary

While AI for mental health still faces many complexities, research shows that behavioral health interventions benefit from continuity, and technology appears to provide an improved user experience. Additionally, as the human brain is complex with its own set of challenges, collecting data from behavioral health sessions in a consistent, measurable, and accessible manner will be essential for better care and better outcomes in the future. close.

Victor Dey

Victor is an aspiring Data Scientist and holds a Master of Science in Data Science & Big Data Analytics. He is a researcher, data science influencer and also a former college football player. A great connoisseur of new developments in data science and artificial intelligence, he is committed to developing the data science community.


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