Relational Mobility Predicts Faster Spread of COVID-19: A 39-Country Study
Cristina E. Salvador, Martha K. Berg, Qinggang Yu, Alvaro San Martin, and Shinobu Kitayama
A country’s relational mobility (i.e., the community-level tendency to engage with strangers and freely choose friends) appears to influence the initial spread rate of COVID-19. Salvador and colleagues analyzed the growth curves of confirmed cases and deaths due to COVID-19 in 39 countries. They found that growth was accelerated in countries with higher relational mobility scores, measured in a previous study by the extent to which people perceive others in their communities as socially open and seeking new friendships. These findings underscore the need for social distancing to “flatten the curve,” especially in countries that value social openness.
Preverbal Infants Discover Statistical Word Patterns at Similar Rates as Adults: Evidence From Neural Entrainment
Dawoon Choi, Laura J. Batterink, Alexis K. Black, Ken A. Paller, and Janet F. Werker
Preverbal children (6-months-old) appear to already have the ability to segment words from continuous speech, a process facilitated by learning the statistical patterns of language. Choi and colleagues used electroencephalogram measures to track the ability of infants to segment words. Infants’ neural processing increasingly synchronized with the embedded words over the learning period. This increase in neural synchronization to words during segmentation learning was comparable to that of adults. Thus, infants were likely tracking probabilities among speech and using them to segment words, like adults do. This indicates that speech segmentation may use neural mechanisms that emerge early in life and are maintained throughout adulthood.
Universal Patterns in Color-Emotion Associations Are Further Shaped by Linguistic and Geographic Proximity
Domicele Jonauskaite, Ahmad Abu-Akel, Nele Dael, et al.
“Feeling blue” or “turning green with envy” are associations that may be shaped by linguistic and geographic proximity. The researchers tested the emotional associations of colors in 30 nations and found universal associations along with local differences. Nations sharing close languages or geographic proximity had greater associations. Thus, the universal associations between color and emotions appear to be affected by linguistic and geographic factors. These findings may inform practice in applied domains, such as design.
Moral Choice When Harming Is Unavoidable
Jonathan Z. Berman and Daniella Kupor
Berman and Kupor distinguish between harm avoidance (desire to avoid causing any harm) and harm aversion (desire to minimize the negative impact caused by one’s actions). Across six studies, they show that participants prefer to completely avoid committing a harmful act when they have the opportunity to do so. However, when participants must choose between less harm for less benefit and more harm for more benefit, they become increasingly willing to commit harm for greater benefits. Thus, the benefits individuals refuse to accept when harm is avoidable can become desirable when some harm is bound to occur.
The Well-Being Benefits of Person-Culture Match Are Contingent on Basic Personality Traits
Jochen E. Gebauer, Jennifer Eck, Theresa M. Entringer, et al.
The benefits of one’s characteristics matching those of their culture may depend on one’s personality. Gebauer and colleagues analyzed data from a larger project that included measures of religiosity, self-esteem, and personality traits among people across 102 countries. To assess the person-culture match, the authors calculated each country’s average religiosity and compared it to each individual’s religiosity. People with high levels of communion, agreeableness, and neuroticism were more likely to benefit from person-culture match, whereas people with high levels of agency, openness, extraversion, and conscientiousness were less likely to benefit. People with low levels of agreeableness and neuroticism and high levels of openness, extraversion, and conscientiousness even experienced a detrimental impact on their well-being when there was person-culture match.
People Reject Algorithms in Uncertain Decision Domains Because They Have Diminishing Sensitivity to Forecasting Error
Berkeley J. Dietvorst and Soaham Bharti
People may be unwilling to use algorithmic decision-makers (e.g., virtual doctors, self-driving cars) in inherently uncertain domains, such as financial investing or medical decision-making. In nine studies, Dietvorst and Bharti showed that people have diminishing sensitivity to forecasting errors—they perceive “relatively large subjective differences between different magnitudes of near-perfect forecasts (the best possible forecasts that produce little to no error) and relatively small subjective differences between forecasts with greater amounts of error.” As a result, they are less likely to choose the best decision-makers in domains that are more unpredictable (e.g., with random outcomes vs. with outcomes determined by an equation) and instead tend to prefer decision-makers based on their perceived likelihood of producing a near-perfect choice and with high variance in performance. This leads people to favor riskier and often worse-performing decision-makers, such as human judgment, in uncertain domains.
Using Machine Learning to Generate Novel Hypotheses: Increasing Optimism About COVID-19 Makes People Less Willing to Justify Unethical Behaviors
Abhishek Sheetal, Zhiyu Feng, and Krishna Savani
Optimism may nudge people to avoid unethical behaviors, such as hoarding potentially scarce resources and violating social distancing during the pandemic. Sheetal and colleagues used machine learning to predict whether individuals perceived unethical behaviors as justifiable, on the basis of their answers to a survey about values. This model identified low optimism about the future of humanity as a top predictor of unethical behavior. This finding was supported by another experiment in which participants who read an optimistic scenario about COVID-19 were less willing to justify hoarding and violating social distancing than participants who read a pessimistic scenario.