We conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings. Each protocol was administered to approximately half of 125 samples that comprised 15,305 participants from 36 countries and territories. Using the conventional criterion of statistical significance ( p < .05), we found that 15 (54%) of the replications provided evidence of a statistically significant effect in the same direction as the original finding. With a strict significance criterion ( p < .0001), 14 (50%) of the replications still provided such evidence, a reflection of the extremely high-powered design. Seven (25%) of the replications yielded effect sizes larger than the original ones, and 21 (75%) yielded effect sizes smaller than the original ones. The median comparable Cohen’s ds were 0.60 for the original findings and 0.15 for the replications. The effect sizes were small (< 0.20) in 16 of the replications (57%), and 9 effects (32%) were in the direction opposite the direction of the original effect. Across settings, the Q statistic indicated significant heterogeneity in 11 (39%) of the replication effects, and most of those were among the findings with the largest overall effect sizes; only 1 effect that was near zero in the aggregate showed significant heterogeneity according to this measure. Only 1 effect had a tau value greater than .20, an indication of moderate heterogeneity. Eight others had tau values near or slightly above .10, an indication of slight heterogeneity. Moderation tests indicated that very little heterogeneity was attributable to the order in which the tasks were performed or whether the tasks were administered in lab versus online. Exploratory comparisons revealed little heterogeneity between Western, educated, industrialized, rich, and democratic (WEIRD) cultures and less WEIRD cultures (i.e., cultures with relatively high and low WEIRDness scores, respectively). Cumulatively, variability in the observed effect sizes was attributable more to the effect being studied than to the sample or setting in which it was studied.

Since its outbreak, COVID-19 has impacted world regions differentially. Whereas some regions still record tens of thousands of new infections daily, other regions have contained the virus. What explains these striking regional differences? We advance a cultural psychological perspective on mask usage, a precautionary measure vital for curbing the pandemic. Four large-scale studies provide evidence that collectivism (versus individualism) positively predicts mask usage—both within the United States and across the world. Analyzing a dataset of all 3,141 counties of the 50 US states (based on 248,941 individuals), Study 1a revealed that mask usage was higher in more collectivistic US states. Study 1b replicated this finding in another dataset of 16,737 individuals in the 50 US states. Analyzing a dataset of 367,109 individuals in 29 countries, Study 2 revealed that mask usage was higher in more collectivistic countries. Study 3 replicated this finding in a dataset of 277,219 Facebook users in 67 countries. The link between collectivism and mask usage was robust to a host of control variables, including cultural tightness–looseness, political affiliation, demographics, population density, socioeconomic indicators, universal health coverage, government response stringency, and time. Our research suggests that culture fundamentally shapes how people respond to crises like the COVID-19 pandemic. Understanding cultural differences not only provides insight into the current pandemic, but also helps the world prepare for future crises.

We conducted preregistered replications of 28 classic and contemporary published findings with protocols that were peer reviewed in advance to examine variation in effect magnitudes across sample and setting. Each protocol was administered to approximately half of 125 samples and 15,305 total participants from 36 countries and territories. Using conventional statistical significance (p &lt; .05), fifteen (54%) of the replications provided evidence in the same direction and statistically significant as the original finding. With a strict significance criterion (p &lt; .0001), fourteen (50%) provide such evidence reflecting the extremely high powered design. Seven (25%) of the replications had effect sizes larger than the original finding and 21 (75%) had effect sizes smaller than the original finding. The median comparable Cohen’s d effect sizes for original findings was 0.60 and for replications was 0.15. Sixteen replications (57%) had small effect sizes (&lt; .20) and 9 (32%) were in the opposite direction from the original finding. Across settings, 11 (39%) showed significant heterogeneity using the Q statistic and most of those were among the findings eliciting the largest overall effect sizes; only one effect that was near zero in the aggregate showed significant heterogeneity. Only one effect showed a Tau &gt; 0.20 indicating moderate heterogeneity. Nine others had a Tau near or slightly above 0.10 indicating slight heterogeneity. In moderation tests, very little heterogeneity was attributable to task order, administration in lab versus online, and exploratory WEIRD versus less WEIRD culture comparisons. Cumulatively, variability in observed effect sizes was more attributable to the effect being studied than the sample or setting in which it was studied.

Data recently published in PNAS mapped out regional differences in the tightness of social norms across China [R. Y. J. Chua, K. G. Huang, M. Jin, Proc. Natl. Acad. Sci. U.S.A. 116, 6720–6725 (2019)]. Norms were tighter in developed, urbanized areas and weaker in rural areas. We tested whether historical paddy rice farming has left a legacy on social norms in modern China. Premodern rice farming could plausibly create strong social norms because paddy rice relied on irrigation networks. Rice farmers coordinated their water use and kept track of each person’s labor contributions. Rice villages also established strong norms of reciprocity to cope with labor demands that were twice as high as dryland crops like wheat. In line with this theory, China’s historically rice-farming areas had tighter social norms than wheat-farming areas, even beyond differences in development and urbanization. Rice–wheat differences were just as large among people in 10 neighboring provinces (n = 3,835) along the rice–wheat border. These neighboring provinces differ sharply in rice and wheat, but little in latitude, temperature, and other potential confounding variables. Outside of China, rice farming predicted norm tightness in 32 countries around the world. Finally, people in rice-farming areas scored lower on innovative thinking, which tends to be lower in societies with tight norms. This natural test case within China might explain why East Asia—historically reliant on rice farming—has tighter social norms than the wheat-farming West.