I don’t have a great sense of this issue specifically, but the first place I go looking to find the outside view on something like this is often the Global Burden of Disease study, which has been estimating disease prevalence since the 90s.
This chart displays the prevalence per 100,000 people of depressive disorders and self-harm injuries/deaths since 1900, among 10–24 year-olds, split by SDI groups. I think there are a lot of good reasons to be skeptical of GBD depression estimates, but data from high-income countries has been historically measured reliably since the 2010s, from which a meaningful increase due to the internet or smartphones would present itself.
I would see the variation here as relatively random. Overall, I highly trust the GBD and its component data sources. So for me to update my beliefs, I would first want to understand why these high-level indicators are wrong or otherwise obscuring the real problem.
P.S. I’ll say one thing that I’ve found is a useful litmus test for whenever you see charts like this—keep an eye on the axes. A lot of ‘public intellectual’ types tend to post charts that cut the y-axis off above zero (inflating the relative size of changes), or the x-axis after the 90s (rates of depression and suicide appear to have changed more significantly over 1990–2010 than from 2010–2020, in ways that would drown out any proposed increase if included), or before 2020 (COVID-19 bumps tend to put modest increases over the 2010s in perspective).
I don’t have a great sense of this issue specifically, but the first place I go looking to find the outside view on something like this is often the Global Burden of Disease study, which has been estimating disease prevalence since the 90s.
This chart displays the prevalence per 100,000 people of depressive disorders and self-harm injuries/deaths since 1900, among 10–24 year-olds, split by SDI groups. I think there are a lot of good reasons to be skeptical of GBD depression estimates, but data from high-income countries has been historically measured reliably since the 2010s, from which a meaningful increase due to the internet or smartphones would present itself.
Here’s a link to the data.
My country, Australia, also keeps good track of suicide rates. They look like this over the internet era:
I would see the variation here as relatively random. Overall, I highly trust the GBD and its component data sources. So for me to update my beliefs, I would first want to understand why these high-level indicators are wrong or otherwise obscuring the real problem.
P.S. I’ll say one thing that I’ve found is a useful litmus test for whenever you see charts like this—keep an eye on the axes. A lot of ‘public intellectual’ types tend to post charts that cut the y-axis off above zero (inflating the relative size of changes), or the x-axis after the 90s (rates of depression and suicide appear to have changed more significantly over 1990–2010 than from 2010–2020, in ways that would drown out any proposed increase if included), or before 2020 (COVID-19 bumps tend to put modest increases over the 2010s in perspective).