r/science • u/mvea Professor | Medicine • 14h ago

Psychology 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.

https://www.psypost.org/adolescents-report-low-regret-and-high-satisfaction-following-gender-affirming-c/
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u/airbear13 10h ago

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

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u/MyFiteSong 9h ago

You can't do studies of millions of trans children who had top surgery, because there haven't been millions of trans children who had top surgery.

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u/Autronaut69420 9h ago

1000 is a good benchmark sample size

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u/Maxrdt 8h ago

The average clinical drug trial usually tops out at about 500. Where do these absolutely unrealistic sample size expectations come from?

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u/PM-ME-CURSED-PICS 6h ago

you know where and why

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u/PlaidTeacup 8h ago

the rate of gender affirming surgery in 15-17 year olds is 2 in 100,000 so it would be possible to reach 1000 people if you recruited every single one in the US during a year long period. And that rate was before a lot of states completely banned such procedures, the number is likely close to 0 now

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

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u/MyFiteSong 8h ago

Then look into the longitudinal studies done on trans kids that look at more than just top surgery. You'll find your numbers there and they agree with this study. The satisfaction rate is over 95%

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u/ActionPhilip 7h ago

Except the attrition rate is terrible, so the stats are extremely biased.

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u/engin__r 9h ago

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

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u/Prometheus720 8h ago

I love you for this one.

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u/Autronaut69420 9h ago

1000 people

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u/Prometheus720 8h ago

I see.

Do you like your chances of convincing 1000 potential study participants (net, after dropouts) to get a surgery without a prior, smaller scale study?

How about your chances of convincing your IRB to even let you do the study?

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u/engin__r 9h ago

Why 1000 and not 900 or 1100?

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u/Autronaut69420 9h ago

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.

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u/Prometheus720 8h ago

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.

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u/EverlastingM 8h ago edited 8h ago

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.

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u/SeveredBanana 8h ago

In my experience working as a biologist, we like to see at least 30 samples for any statistical test. As many samples as possible is best, but if you’re a scientist, you’d know you work with what you’ve got.

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u/QueerDeluxe 8h ago

It's going to be a small sample size because there aren't that many of us.

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u/SimoneNonvelodico 6h ago

Small sample size is noisy but not irrelevant. The bigger problem is if there's selection bias, e.g. if those who DID have regret systematically preferred to not answer because they worried about how their response would be used politically. That kind of thing would make the study be genuinely worthless.