Data Analysis

A set of 2 (culture) × 2 (sex) between-group ANOVAs (Sum of Squares Type III; default) was conducted to investigate the main and interaction effects of culture and sex on self-report empathy and other test scores. For each significant culture–sex interaction detected by the ANOVAs, further analyses were carried out to identify the source of the interaction using t-tests with Bonferroni adjustments to account for inflated Type I error. The bivariate correlations between the scores on the self-reported empathy and the empathy-related traits were examined using Pearson’s correlation coefficients (r).

Moderated mediation analyses were conducted to investigate the potential sex differences in mediating effects of each proposed empathy-related trait (i.e., SCS-ID, SCS-IT, and IRI-PD) on culture as a predictor of empathy scores (i.e., EQ, IRI-PT, and IRI-EC). The mediating effects of each trait were examined based on female and male participants separately and were compared between the two sex groups. Each of the empathy-related traits (i.e., the mediator) would formulate an indirect pathway between culture (i.e., the predictor) and the score on the empathy scale (i.e., the outcome). Thereby, the predictor could have a direct effect on the outcome and an indirect effect on the outcome through the mediator.

For the current analyses, a meaningful indirect effect was identified according to whether zero was outside the 95% CI of the indirect effect (Field, 2013). Moreover, according to Zhao et al. (2010), there are five types of mediating effects: (1) A complementary mediation exhibits a meaningful indirect effect and a significant direct effect, and both effects have the same sign (i.e., both are positive or both are negative); (2) A competitive mediation exhibits a meaningful indirect effect and a significant direct effect, but the two effects have the opposite signs (i.e., one is positive and one is negative); (3) An indirect-only mediation exhibits a meaningful indirect effect but a non-significant direct effect; (4) A direct-only non-mediation exhibits a significant direct effect but not a meaningful indirect effect; (5) A no-effect non-mediation exhibits neither a significant direct effect nor a meaningful indirect effect. The complementary mediator may reduce the magnitude of the direct impact of the predictor on the outcome variable and is considered to be able to explain part of the relationship between the two variables (MacKinnon et al., 2000). In contrast, the competitive mediator and the indirect-only mediator may change (i.e., “increase” and “in-/decrease”, respectively) the magnitude between the predictor and outcome variables and may reveal the concealed relationship between these two variables (Zhao et al., 2010). Finally, the direct-only non-mediation and the no-effect non-mediation suggest that there were no mediating effects (Zhao et al., 2010). The moderated mediating effects (bias-corrected bootstrapping with 5,000 resamples) were tested using Mplus 8.2 (Muthén and Muthén, 1998–2012), while all other analyses were conducted using SPSS (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY, United States: IBM Corp.).