Evaluating Gender Similarities and Differences Using Metasynthesis

doi:10.1037/a0038208

Evaluating Gender Similarities and Differences Using Metasynthesis

2015-01-01

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DOI：10.1037/a0038208

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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.

Keyword:

gender

gender differences

gender similarities

meta-analysis

Evaluating Gender Similarities and Differences Using Metasynthesis

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