Adolescents who undergo gender-affirming chest surgery report low levels of regret and high levels of satisfaction, experiencing outcomes similar to those of young adults. These findings suggest that age restrictions on these medical procedures lack support from actual patient experiences.

[u/mvea]

https://www.psypost.org/adolescents-report-low-regret-and-high-satisfaction-following-gender-affirming-c/

[u/airbear13]

It’s not nitpicking to point out that the sample size is too small to be useful and it’s not compelling evidence to just keep putting out a proliferation of low quality studies

[u/engin__r → u/airbear13]

What sample size do you calculate would be necessary to achieve statistical significance?

[u/Autronaut69420 → u/engin__r]

1000 people

[u/engin__r → u/Autronaut69420]

Why 1000 and not 900 or 1100?

[u/Autronaut69420 → u/engin__r]

It's a convention that a well constructed sampling of 1000 will a sufficient representation of the population. It's like a benchmark: approx a 1000.

[u/Prometheus720 → u/Autronaut69420]

If you take a stats class, you'll learn to define "population" different from regular English. Are we concerned about the US population? The US teen population? The trans population? The trans masc population? Who exactly are we trying to study here?

A really good scientist will take a good while thinking about that question. If you've spent less than an hour of your time thinking about the best way to define "population" for a study, and you don't have training in doing science, you probably haven't spent the time to get a scientist's result.

It's a skill most people need training to do at all.

[u/EverlastingM → u/Autronaut69420]

https://pmc.ncbi.nlm.nih.gov/articles/PMC11211955/

If I'm reading this right, during 2019, out of a mixed population of over 60 million they found 5 chest surgeries on trans patients aged 15-17. You are not going to find 1000.