English-speakers sometimes say that they feel "moved to tears," "emotionally touched," "stirred," or that something "warmed their heart;" other languages use similar passive contact metaphors to refer to an affective state. The authors propose and measure the concept of kama muta to understand experiences often given these and other labels. Do the same experiences evoke the same kama muta emotion across nations and languages? They conducted studies in 19 different countries, 5 continents, 15 languages, with a total of 3,542 participants. They tested the construct while validating a comprehensive scale to measure the appraisals, valence, bodily sensations, motivation, and lexical labels posited to characterize kama muta. The results are congruent with theory and previous findings showing that kama muta is a distinct positive social relational emotion that is evoked by experiencing or observing a sudden intensification of communal sharing. It is commonly accompanied by a warm feeling in the chest, moist eyes or tears, chills or piloerection, feeling choked up or having a lump in the throat, buoyancy, and exhilaration. It motivates affective devotion and moral commitment to communal sharing. Although the authors observed some variations across cultures, these 5 facets of kama muta are highly correlated in every sample, supporting the validity of the construct and the measure. (PsycINFO Database Record

English-speakers sometimes say that they feel moved to tears, emotionally touched, stirred, or that something warmed their heart; other languages use similar passive contact metaphors to refer to an affective state. We propose and measure the concept of kama muta to understand experiences often given these and other labels. Do the same experiences evoke the same kama muta emotion across nations and languages? We conducted studies in 19 different countries, five continents, 15 languages, with a total of 3542 participants. We tested the construct while validating a comprehensive scale to measure the appraisals, valence, bodily sensations, motivation, and lexical labels posited to characterize kama muta. Our results are congruent with theory and previous findings showing that kama muta is a distinct positive social relational emotion that is evoked by experiencing or observing a sudden intensification of communal sharing. It is commonly accompanied by a warm feeling in the chest, moist eyes or tears, chills or piloerection, feeling choked up or having a lump in the throat, buoyancy and exhilaration. It motivates affective devotion and moral commitment to communal sharing. While we observed some variations across cultures, these five facets of kama muta are highly correlated in every sample, supporting the validity of the construct and the measure.

Social thermoregulation theory posits that modern human relationships are pleisiomorphically organized around body temperature regulation. In two studies (N = 1755) designed to test the principles from this theory, we used supervised machine learning to identify social and non-social factors that relate to core body temperature. This data-driven analysis found that complex social integration (CSI), defined as the number of high-contact roles one engages in, is a critical predictor of core body temperature. We further used a cross-validation approach to show that colder climates relate to higher levels of CSI, which in turn relates to higher CBT (when climates get colder). These results suggest that despite modern affordances for regulating body temperature, people still rely on social warmth to buffer their bodies against the cold.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world.

People display systematic priorities to self-related stimuli. As the self is not a unified entity, however, it remains unclear which aspects of the self are crucial to producing this stimulus prioritization. To explore this issue, we manipulated the valence of the self-concept (good me vs. bad me) -a core identity-based facet of the self -using a standard shape-label association task in which participants initially learned the associations (e.g., circle/good-self, triangle/good-other, diamond/bad-self, square/bad-other), after which they completed shape-label matching and shape-categorization tasks, such that attention was directed to different aspects of the stimuli (i.e., self-relevance and valence). The results revealed that responses were more efficient to the good-self shape (vs. other shapes), regardless of the task that was undertaken. A hierarchical drift diffusion model (HDDM) analysis indicated that this good-self prioritization effect was underpinned by differences in the rate of information uptake. These findings demonstrate that activation of the good-self representation exclusively facilitates perceptual decision-making, thereby furthering understanding of the self-prioritization effect.

Social thermoregulation theory posits that modern human relationships are pleisiomorphically organized around body temperature regulation. In two studies (N=1755) designed to test the principles from this theory, we used supervised machine learning to identify social and non-social factors that relate to core body temperature. This data-driven analysis found that complex social integration (CSI), defined as the number of high contact roles one engages in, is a critical predictor of core body temperature. We further used a cross-validation approach to show that colder climates relate to higher levels of CSI, which in turn relates to higher CBT (when climates get colder). These results suggest that despite modern affordances for regulating body temperature, people still rely on social warmth to buffer their bodies against the cold.

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.

Over the last ten years, Oosterhof and Todorov’s valence-dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgments of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov’s methodology across 11 world regions, 41 countries, and 11,570 participants. When we used Oosterhof and Todorov’s original analysis strategy, the valence-dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions we observed much less generalization. Collectively, these results suggest that, while the valence-dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods, correlate and rotate the dimension reduction solution.