I've been thinking about this reply of yours and I know the study you have there has very little scientific merits. It's too small of a sample size to say anything. The rule for a scientific study is
"As a general rule, any correlation that has a p-value of greater than 0.05 (p>0.05) should not be taken as evidence for anything."
The p value for your study is ten times what is required for your study to be declared anything but trash.
And if I study your thing on twins I think I'll find the same thing. In short, you haven't proven anything.
I'm not a social scientist so anyone with more experience in this field please correct me, but my understanding of the study in question is that the null hypothesis in this case was that socially youth and nontransgender youth have similar levels of anxiety. In this case a higher p value means that the two groups did not show significant differences in their depression which is the conclusion being made.
A quote from the study that this one was following up on:
"In terms of depression, transgender children’s symptoms (M = 50.1) did not differ from the population average, P = .883. In contrast, transgender children had elevated rates of anxiety compared with the population average (M = 54.2), t(72) = 4.05, P < .001"
So the children did not have differing levels of depression, but had statistically significant differences in their levels of anxiety. Basically, this study having high p-values is the reason they conclude that socially accepted transgender youth do not have differing levels of depression from cisgender youth. To throw out the study because of high p-values is to misunderstand the study itself.