Mental health disorders are among the leading causes of morbidity and mortality, expected to cost the world’s economy some $16 trillion by 2030.
They affect at least 10% of the population, with up to 20% of children and adolescents
suffering from some type of mental disorder and women more likely than men
to be diagnosed with depression.
In the US, around 19% of people
experienced a mental illness in 2017-18, which was a year-on-year increase of 1.5 million people. The number of the young reporting mental distress is rising more significantly.
No one seems to know exactly why depression and anxiety are so common nowadays. Many experts even dismiss any upswing, arguing that what we see is a surge of people actively seeking treatment.
Indeed, the number of people applying for help with depression or anxiety in the US has soared, according to the 2021 State of Mental Health in America report. As many as 315,220 people took anxiety tests in January to September 2020, 93% up from the entire 2019. The number of people taking depression screens increased by 62% to 534,784 people.
At the same time, only around 40% of US adults
with mental illness received treatment in 2019. One of the reasons is a shortage of mental health providers, which the US National Council for Behavioral Health predicts can reach over 15,000 clinicians in the next couple of years.
The need for solutions that can scale access to mental health treatment is desperate, while such solutions are already here, thanks to AI.