Hi!! Everytime I review a paper where the results can be split in "male & female" results, I ask the researchers to explain, for example, if other categories of analysis, such as age, ethinic background etc, would be applied as well to do some more splitting in order to perceive any kind of significant results that may be hide in a dicotomic gender split.

In my opinion, you have two options:

1) You can split and report that you find an effect in males, but not in females, and add that you cannot draw a conclusion about the females YET or

2) You can add to the analysis another categories if relevant (as age, social background, etc) and than compare each intersectional categories (example: 30 years male x 30 years female; 23 years caucasian male x 23 years caucasian female, etc) in order to explain that if it is really a gender difference that justify the different results between the groups, not others factors.

I suggest you to read "Better science with sex and gender: Facilitating the use of a sex and gender-based analysis in health research", by Joy L Johnson, Lorraine Greaves and Robin Repta.

Hope it helps. :)

Yes that helps, thank you so much!

Gender differences are often seen as either biologically determined or culturally acquired or conditioned. However, in an age where gender equality is the main target, neither peer reviewers nor students show much interest in gender differences. Moreover, not only do people try to integrate their ‘ying’ and ‘yang’ in their personalities also transgender identities are publicly acknowledged, appreciated and respected.