Evaluating gender similarities and differences using metasynthesis

Despite the common lay assumption that males and females are profoundly different, Hyde (2005) used data from 46 meta-analyses to demonstrate that males and females are highly similar. Nonetheless, the gender similarities hypothesis has remained controversial. Since Hyde's provocative report, there has been an explosion of meta-analytic interest in psychological gender differences. We utilized this enormous collection of 106 meta-analyses and 386 individual meta-analytic effects to reevaluate the gender similarities hypothesis. Furthermore, we employed a novel data-analytic approach called metasynthesis (Zell & Krizan, 2014) to estimate the average difference between males and females and to explore moderators of gender differences. The average, absolute difference between males and females across domains was relatively small (d = 0.21, SD = 0.14), with the majority of effects being either small (46%) or very small (39%). Magnitude of differences fluctuated somewhat as a function of the psychological domain (e.g., cognitive variables, social and personality variables, well-being), but remained largely constant across age, culture, and generations. These findings provide compelling support for the gender similarities hypothesis, but also underscore conditions under which gender differences are most pronounced.