How can ai and mental health combined help prevent or improve psychological illnesses? Is it possible that something as new and disruptive as technology and artificial intelligence can influence something as serious and important as mental health?
There are many studies being carried out today on the application of technology to medicine and there are many different use cases. In this post we will talk about two of the most recent studies and projects.
Youper: The combination of AI and mental health that reduces stress and depression
A Stanford study focused on a new medical therapy that relies on technology and AI has shown that technology helps reduce stress and depression.
This study is based on Youper – a health app that uses AI to improve symptoms of depression and stress.
“The mental health care system is failing us: studies show that it can take ten years for a patient to receive adequate treatment. Telemedicine alone cannot solve this problem: there are not enough health professionals and they are also overwhelmed,” said Dr. Jose Hamilton, founder and CEO of Youper, in a press release.
And that’s how the idea for Youper originated.
The app connects the user with an AI therapist called Youper, who assesses the patient’s mental health needs and recommends a series of solutions to resolve their symptoms and improve their mood.
And how do they do that?
- By improving the patient’s day-to-day life with quick conversations
- Helping them fall asleep through relaxation and calming exercises
- Using mindfulness to increase concentration, balance and well-being
- Helping the user to understand themselves by monitoring their mood and managing their symptoms
The Stanford study observed that the app’s users reduced their anxiety and depression by 24% and 19% respectively.
STOP: Is it possible to prevent suicides with AI?
Another project that also combines ai and mental health – in this case to prevent suicides – is STOP. This project is led by Ana Freire, a researcher in the Department of Information and Communication Technologies at the Universitat Pompeu Fabra. This project looks for, studies and analyses patterns of suicidal behavior in social media.
According to data from the National Statistics Institute (INE), suicide is the leading cause of unnatural death in Spain with an average of more than 10 deaths per day.
One of the most worrying data is that more and more young people are engaging in suicidal behavior, especially after the pandemic crisis we are still experiencing.
“The Spanish Association of Pediatrics, in fact, recently warned of the consequences of the pandemic in teenagers and pointed out how psychiatric hospital admissions in this population group have multiplied by four, compared to the same dates in 2020”.
We can read in El Español, which interviewed Ana Freire.
Ana Freire began to investigate when she read Facebook post by a woman announcing her imminent suicide.
The researcher also saw that her previous posts revealed that the woman was suffering from severe depression and wondered why a system that could automatically detect these suicidal behaviors didn’t exist.
This is how she launched STOP – an AI and mental health project for studying suicidal tendencies in social media
AI is used by researchers in this study to recognize patterns of high and low suicide risk based on anonymous tweets.
The study is based on Twitter because it’s one of the social networks that provides the most data and information needed by researchers. However, the results obtained can be applied to any other social media.
As we can read in the interview in El Español: “From these tweets we extract different characteristics that our algorithms analyse, such as the frequency of certain words, the time of publication (to detect insomnia), the number of likes or retweets received by that publication (to measure social support), and we even analyze the images that sometimes come with the text”.
Also, she affirms: “The use of AI in these tweets has allowed us to establish differences between “high risk” and “risk-free” groups: the first group tends to speak more in first person and to use terms related to feelings, among which anxiety stands out”. The system is able to detect patterns at 85% accuracy.
This is definitely an important improvement in the mental health sector thanks to artificial intelligence and technology.
Let’s hope that this type of initiatives and projects continue to help to prevent depression, anxiety and suicide and help all the people who need it to improve their personal situation.
