From significant to meaningful: ATOMizing the study of sex differences and similarities

Abstract

The sex differences field often relies on an implicit and flawed heuristic: defining a “difference” by any statistically significant gap between group averages. This practice yields findings that are often not useful, even counterproductive, for understanding sex-related variation and for advancing personalized healthcare.

Following current statistical consensus, we argue that sex differences should be defined not by significance alone but by context-dependent criteria prioritizing informativeness. Drawing on the American Statistical Association’s ATOM principles (Accept uncertainty, be Thoughtful, be Open, be Modest), we call for explicit, justified definitions and for a shift from group averages to meaningful individual variation.

To illustrate this methodological and philosophical shift, we introduce Thresholded Probability of Superiority (TPS), a method that treats sex differences as probability distributions rather than overgeneralized, fixed abstractions. Thus, TPS allows for a more nuanced, relevant, and actionable understanding of sex-related variation, with greater potential to inform precision medicine.