The p-values relevant for testosterone are on the lower side, with one them 0.049 (which screams p-hacking) and another at 0.02 (also really shitty). A reasonable back-of-the-envelope method to correct for p-hacking and publication bias involves multiplying the p-values with 20 (the reasoning is not super-involved. think about what happens to the truncated normal distribution in the case of complete publication bias); in that case, none of the testosterone-related p-values in said paper are significant. I feel comfortable ignoring it.
About that paper.
The p-values relevant for testosterone are on the lower side, with one them 0.049 (which screams p-hacking) and another at 0.02 (also really shitty). A reasonable back-of-the-envelope method to correct for p-hacking and publication bias involves multiplying the p-values with 20 (the reasoning is not super-involved. think about what happens to the truncated normal distribution in the case of complete publication bias); in that case, none of the testosterone-related p-values in said paper are significant. I feel comfortable ignoring it.