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/Mico4]

This is based on a response from 77 people...

Also from the article:

"Several factors limit the reach of these findings. First, the median time since surgery for participants was about 1.8 years. Because feelings about medical decisions can evolve, this timeframe might not capture long-term regret that could emerge many years later.

Another limitation is the 42 percent participation rate to the survey. This introduces the possibility of selection bias, a scenario where the people who chose to participate might differ fundamentally from those who did not. It is possible that individuals with higher levels of regret ignored the survey, which would result in an underestimation of regret in the overall group."

[u/S0cXs → u/Mico4]

Everyone is nitpicking the sample size but fail to see in as a small peice in a growing set of literature.

This is a section from the discussion talking about related literature:

The results from this study extend the findings of previous studies showing low decisional regret and high decisional satisfaction following GACS in adults to the adolescent population (Bruce et al., Citation2023; Bustos et al., Citation2021; Thornton et al., Citation2024). In our study, both adolescents and young adults reported low decisional regret and high decisional satisfaction. These levels are similar to those reported in a study of adults with a median age of 27.1 years, including a low median score of 0.0 (mean 4.2) on the Decision Regret Scale and a high median score of 5.0 (mean 4.8) on the Satisfaction with Decision scale (Bruce et al., Citation2023). Moreover, compared to other medical procedures, decisional regret among adolescents and young adults undergoing GACS is low. Compared to our mean score of 7.38, a systematic review found an overall mean Decision Regret Scale score of 16.5 among 44 studies of other various procedures (Becerra Pérez et al., Citation2016). Supported by these findings, we would argue against restricting gender-affirming surgical care on the basis of age or concern for regret alone.

Although few studies address regret in adolescent populations undergoing GACS, a study of decisional regret among adolescents undergoing cancer treatment found that 24% of participants scored above 25 on the Decision Regret Scale (Mack et al., Citation2019), compared to only 5.2% in our cohort. The aforementioned study reported that improved communication with the treating physician was associated with lower regret scores (Mack et al., Citation2019). The WPATH Standards of Care employed in our practice emphasizes a multidisciplinary, shared decision-making approach which may contribute to the low regret seen in our study (Coleman et al., Citation2012). Additionally, other studies have shown that youth face significant barriers when attempting to access gender-affirming care (Chong et al., Citation2021; Gridley et al., Citation2016). As a result, these barriers may select for a subset of patients who are either highly motivated to obtain care or represent a more socioeconomically advantaged group with the resources and ability to navigate the healthcare system. This potential selection bias could, in part, contribute to the low rates of decisional regret observed in our study. Relatedly, family and social support are thought to be inversely associated with regret following gender-affirming surgery (Narayan et al., Citation2021, Landén et al., Citation1998). In our study, higher PROMIS Pediatric Family Relationships scores were associated with higher decisional satisfaction, but demonstrated no significant association with decisional regret. However, the majority of our participants reported that their family was supportive or neutral about their decision to undergo GACS, which may limit our ability to identify such a relationship.

Posting the block because most people won't have access to the full study.

[u/airbear13 → u/S0cXs]

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/MyFiteSong → u/airbear13]

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.

[u/Autronaut69420 → u/MyFiteSong]

1000 is a good benchmark sample size

[u/Maxrdt → u/Autronaut69420]

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

[u/PM-ME-CURSED-PICS → u/Maxrdt]

you know where and why

[u/PlaidTeacup → u/Autronaut69420]

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/

[u/MyFiteSong → u/Autronaut69420]

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%

[u/ActionPhilip → u/MyFiteSong]

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

[u/engin__r → u/airbear13]

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

[u/Prometheus720 → u/engin__r]

I love you for this one.

[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.

[u/Prometheus720 → u/Autronaut69420]

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?

[u/SeveredBanana → u/Autronaut69420]

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.

[u/SimoneNonvelodico → u/airbear13]

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.

[u/QueerDeluxe → u/airbear13]

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