To be clear, the “/s” means the statement is sarcasm.

Obviously Biden can’t prevent Republicans from stopping legislation. Recently their main tactic is to filibuster any Senate bill. The rules of the Senate are weird, they decide during each session, and none of their rules are specifically described in the Constitution. So it’s odd that some bills can pass with simple majority, others require 60 or more votes in favor, and some only require a minority to filibuster. I don’t really get it.

But seriously, we’re none of those issues important to you? They covered a pretty wide range of topics.

Yeah I hear you, and hear the sarcasm.

Just to add to your thought, I originally didn’t think employers really wanted to hold their employees health hostage.

That’s clearly untrue in plenty of cases (due respect to people who have this lived experience). If people could retain quality healthcare even moving to a new position, employers would have to do other things to influence them to stay. It doesn’t affect all companies, but a fair percentage.

I guess I didn’t understand why state legislators would care enough. I thought more people were employees than employers, and maybe that’s just not true in the majority of highly rural counties in NC. Lots of small businesses, where even the employees want low employer costs so their positions (underpaid as they are) still exist. Low pay is still better than no pay.

All that said, this is why it’s a decision to be made at a high level and not low level. High level sees value overall, and can (and tries to) provide extra funding where it is most needed.

Biden should just not let the GOP stop every piece of legislation they want to stop. /s

Where have you been? In NC our state still hasn’t expanded Medicare, even though it would clearly save the state and its citizens much money. There is no logic to it.

I get what you’re saying, and to be frank I appreciate the skepticism, and the drive to reality-check the numbers. Sometimes the numbers are over- or under-stated, or not reasonable effects.

In this case the abstract actually says it’s a significant change:

> “was significantly reduced in the HC group (1.04±0.31 vs 0.87±0.24 , p < 0.001)”

They include the P-value. You’re right it’s hard to know what the +/- means, typically that’s standard deviation, and not reflective of confidence intervals. Literally the confidence interval at 95% by definition would be smaller than the difference, that is if it used the same model used by the test.

It’s a whole thing about reporting and displaying confidence intervals, versus standard deviations, etc. Sometimes it’s straightforward to report standard deviation, but is not reflective of whatever statistical model was actually used. Frustrating, but not usually an author issue, also a journal guidance issue.

Oh, and the reason standard deviation does not indicate whether effect size is significant is in part that it doesn’t account for the number of individuals, nor the actual statistical model. Standard deviation is a simple university summary.

These articles are valuable components of the overall research still ongoing to understand mental health and related pharmacotherapies. They have value. They are not showing serotonin is unrelated to depression.

First “major depressive disorder” is substantially stronger diagnosis than more commonly diagnosed depression.

Second, even among this subset of patients, “SSRIs significantly reduced the Hamilton Depression Rating Scale.” Their initial overall finding was significant decrease in depression (on multiple measurement scales).

They also found increase in adverse episodes (30/1000 in treated versus 22/1000 placebo), which is a known risk with serotonin-related treatments. This risk should not be ignored, for sure. However that risk doesn’t erase the benefit of treatment in some patients, it adds a secondary factor. It is certainly valid for the authors (and other scientists and physicians) to have the opinion that the risks do not outweigh the benefits, however that isn’t the subject of the study, nor is that type of opinion factual. The risks of adverse events is higher in “major depressive disorder”, and so their opinion is based upon a very focused study that only includes the stronger depressive disorder.

The serotonin model is not dead, nor is new data showing it to be dead. The serotonin model is as yet incomplete. The benefits of treatment is not fully understood in concert with risks to each patient.

Edit: fixed typo “sowing” to “showing”. Oops.

Can you describe “error bars” and why they are more important to you than the P-value? What metric would you want to see?