This study estimates empirically derived guidelines for effect size interpretation for research in social psychology overall and subdisciplines within social psychology, based on analysis of the true distributions of the two types of effect size measures widely used in social psychology (correlation coefficient and standardized mean differences). Analysis of empirically derived distributions of 12,170 correlation coefficients and 6,447 Cohen's d statistics extracted from studies included in 134 published meta-analyses revealed that the 25th, 50th, and 75th percentiles corresponded to correlation coefficient values of 0.12, 0.24, and 0.41 and to Cohen's d values of 0.15, 0.36, and 0.65 respectively. The analysis suggests that the widely used Cohen's guidelines tend to overestimate medium and large effect sizes. Empirically derived effect size distributions in social psychology overall and subdisciplines can be used both for effect size interpretation and for sample size planning when other information about effect size is not available.

A number of recent research publications have shown that commonly used guidelines for interpreting effect sizes suggested by Cohen (1988) do not fit well with the empirical distribution of those effect sizes, and tend to overestimate them in many research areas. This study proposes empirically derived guidelines for interpreting effect sizes for research in social psychology, based on analysis of the true distributions of the two types of effect size measures widely used in social psychology (correlation coefficient and standardized mean differences). Analysis was carried out on the empirical distribution of 9884 correlation coefficients and 3580 Hedges’ g statistics extracted from studies included in 98 published meta-analyses. The analysis reveals that the 25th, 50th, and 75th percentiles corresponded to correlation coefficients values of 0.12, 0.25, and 0.42 and to Hedges’ g values of 0.15, 0.38, and 0.69, respectively. This suggests that Cohen’s guidelines tend to overestimate medium and large effect sizes. It is recommended that correlation coefficients of 0.10, 0.25, and 0.40 and Hedges’ g of 0.15, 0.40, and 0.70 should be interpreted as small, medium, and large effects for studies in social psychology. The analysis also shows that more than half of all studies lack sufficient sample size to detect a medium effect. This paper reports the sample sizes required to achieve appropriate statistical power for the identification of small, medium, and large effects. This can be used for performing appropriately powered future studies when information about exact effect size is not available.

A meta-analysis was conducted to examine the relationship between out-group entitativity and prejudice. A quantitative analysis of 85 effect sizes from 33 independent samples showed a significant positive relationship between entitativity and prejudice (Fisher's z = .414, 95% CI [0.272, 0.557], p < .0001). Three possible moderators of the relationship between entitativity and prejudice were tested: conceptualization of the entitativity (essence-based entitativity scale, agency-based entitativity scale, common entitativity scale), the target of the prejudice, and the measures of prejudice (attitudes, emotions, behaviour towards out-group). Results demonstrated that out-group entitativity correlated with prejudice only when entitativity was conceptualized as an essence-based or common-based scale, and prejudice was measured as the attitude to the out-group. The target of prejudice does not moderate the relationship between entitativity and prejudice.

The Ambivalent Sexism Theory suggests that there are two complementary types of sexism: hostile (subjectively negative attitude towards gender groups) and benevolent (subjectively positive attitude towards gender groups). In this meta-analysis we analyzed the relationship between ambivalent sexism and attitudes toward male-to-female violence or violent behavior. Violence type, the context of violence, respondents' gender, the countries' level of gender inequality, and sample type were tested as moderators. The results showed that both hostile and benevolent sexism independently impact on attitudes toward violence and violent behavior albeit to a different degree. Specifically, the relationship between hostile sexism and attitudes and behavior is stronger than for the benevolent sexism. The type and context of violence moderate the relationship between hostile sexism and attitudes toward violence and violent behavior. Only the country's gender inequality levels showed a moderation effect for benevolent sexism. Theoretical and practical implications of the results are discussed.

The COVID-19 pandemic is increasing negative emotions and decreasing positive emotions globally. Left unchecked, these emotional changes may have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we will examine the impact of reappraisal, a widely studied and highly effective form of emotion regulation. Participants from 55 countries (expected N = 25,448) will be randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing), an active control condition, or a passive control condition. We predict that both reappraisal interventions will reduce negative emotions and increase positive emotions relative to the control conditions. We further predict that reconstrual will decrease negative emotions more than repurposing, and that repurposing will increase positive emotions more than reconstrual. We hope to inform efforts to create a scalable intervention for use around the world to build resilience during the pandemic and beyond.