[kazagistar]

That seems like it's likely mostly just conflated with one of the well known causes of suicide, financial instability and generally being poor. The better data would be studies that try to compare similar socioeconomic classes, age ranges, etc.

I wish it took only a second to find out what is true, but data is complicated and has lots of confounding variables, and it's too easy to not account for them and get totally untrue information out of the data.

[icandoit]

Why insist on causality depending on a single variable? This is very strange to me. Of course the trust is confounded, the truth is multi-variable.

The algorithm to pursue truth:

    1. Find out how you personally differ from happy and healthy people.
    2. Reduce those differences however you can.
    3. Watch yourself become happier and healthier.
    4. That's the whole thing.

Does being poor suck? Yes. Reduce it's likelihood and it's impact.

Don't demand that information conform to your assumption before you can take action. Take action and document your assumptions and challenge them along your journey to improvement.

A neural network does not make demands of its data set. It changes itself to better match the limited truth that it does see.

Uncertainty and doubt are your enemies. Challenge them with data don't reduce yourself to paralysis. Look up "Epistemic learned helplessness".

An example: Will flossing improve my health? Be the kind of person that wants to improve their health and tries to improve their health. Try flossing as matter of character, not based on whether it does independent of the social class of other flossers. If successful people think that other successful people floss, then they will too. There is no isolation among the variables. Don't demand that of reality.