Young adult suicide is down, as demonstrated by regression.

This is an article about a very sensitive topic, but it is also a hopeful article (young adult suicide seems to be on the decline in the US, and there is reason to believe that it is due to the introduction of the 988 hotline.)

Here is a link to the original research study published in JAMA Network, and here is a link to Scientific American's write-up on the research.

In my class, I emphasize that regression has a lot in common with correlation, but adds prediction. I emphasize it so much that I used it in the name of my regression chapter in my textbook.

As such, I was delighted to find this  excellent, psychology-related example of how past data was used to predict the future. But the future is the present? And the predicted data lives in an alternative timeline where the 988 mental health crisis hotline never existed in America. Anyway, TL;DR: Young adult suicide is on the decline (hooray!!) in America, and this research a) uses fancy regression to demonstrate this and then 2) uses available data to argue for a causal relationship between the introduction of 988 and the decline in suicide. 

1. The researchers used regression to show what suicide rates would look like if they followed the pre-2022 trend, versus what the data actually looks like, post 2022 (and introduction of 988).

It might use fancy regression, but it is still using regression to infer the present from past data. AND it is a mental health example, and I teach Psych Stats.

I used this in class today to review regression. Specifically, is shows how the decline we are seeing is not predicted by previous trends. When I teach regression, it is easy to get in the weeds with all the betas and R-squareds, so it is nice to bring the focus back to regression being used in real life to make an argument. I also like using this example at the end of the semester because it is a reminder that this resource exists. 

So, young adult suicide is down, but was it 988? Well, the paper addresses that as well and shows how to use stats and the data you have to argue for causality. 

Here, the scientists examined each state and its use of the hotline. They grouped the "high-uptake states", or the ten states that used the hotline the most, versus the "low-uptake states", ten states that used the hotline the least, and they found this:

You can see the difference, with the high-uptake states experiencing an 18% decrease in suicide versus an 11% decrease in the low-uptake states. Additionally, the researchers compared this data to English data and didn't find this decrease.