So what is, in a broad sense, the way we're going to do a fair comparison?

Understanding which states legalized and which didn't and trends in those states is central to the quasi-experimental methods we're using here.

I'll say briefly that like a lot of times when you're doing health policy research, the map of your treated states versus your control states looks a lot like an ACA Medicaid expansion map.

This is not one of those cases.

You know, it tends to be that states do a lot of overlapping health policy, but this is – a policy where states like Texas and California are both in our control group, but states like New York have legalized.

So this isn't as clearly correlated with all these other health policies as some other papers I've worked on.

But the central method we use is called a difference-in-differences method, and specifically we're using— Difference-in-differences.

We know this is this drama psychiatry podcast, but it's interesting to speculate.

Why, and what are we kind of expecting or what are we planning for in considering them differently?

There's a few reasons we consider them separately.

The first is that men and women use sports betting apps at different rates.

So survey findings kind of differ in, in how prevalent these apps are, but by any measure, men are usually about two times more likely than women to use sports betting apps.

Also, women tend to have greater underlying rates of mental health treatment.

So when you're thinking about changes, the effect sizes we estimate in percentage points, so, you know, let's say we see a one percentage point increase in mental health care use.

Well, that's extrapolated on a higher number of bettors that are men, for example, but is also over a lower baseline mental health treatment rate.

We, we know this is a JAMA Psychiatry podcast, but it's interesting to, to speculate.