A global experiment on motivating social distancing during the COVID-19 pandemic

Finding communication strategies that effectively motivate social distancing continues to be a global public health priority during the COVID-19 pandemic. This cross-country, preregistered experiment (n = 25,718 from 89 countries) tested hypotheses concerning generalizable positive and negative outcomes of social distancing messages that promoted personal agency and reflective choices (i.e., an autonomy-supportive message) or were restrictive and shaming (i.e., a controlling message) compared with no message at all. Results partially supported experimental hypotheses in that the controlling message increased controlled motivation (a poorly internalized form of motivation relying on shame, guilt, and fear of social consequences) relative to no message. On the other hand, the autonomy-supportive message lowered feelings of defiance compared with the controlling message, but the controlling message did not differ from receiving no message at all. Unexpectedly, messages did not influence autonomous motivation (a highly internalized form of motivation relying on one’s core values) or behavioral intentions. Results supported hypothesized associations between people’s existing autonomous and controlled motivations and self-reported behavioral intentions to engage in social distancing. Controlled motivation was associated with more defiance and less long-term behavioral intention to engage in social distancing, whereas autonomous motivation was associated with less defiance and more short- and long-term intentions to social distance. Overall, this work highlights the potential harm of using shaming and pressuring language in public health communication, with implications for the current and future global health challenges

The psychological science accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Paranaguá, Antonina e Curitiba, início do século XIX: reconstituindo espaços e a lógica de sua organização social

This paper is to develop a methodology to characterize the spatial distribution in the early nineteenth century, the urban residents enrolled in the Décima of Paranaguá, Antonina and Curitiba, three villages in southern province of São Paulo. Here are the problems faced and decisions made, almost always temporary and arbitrary. The result reached hypothetical plants of subdivisions and urban streets of those towns. From a database - developed mainly with the information Lista Nominativa de Habitantes - it was possible to characterize residents enrolled in the books of property tax Décima. Spatialising thematic data in plants, where they lived was possible to perceive the social group, your choices (or lack thereof), or realize their preferred sites, but not exclusive housing.O objetivo desse artigo é desenvolver uma metodologia para caracterizar a espacialização, no início do século XIX, dos moradores arrolados nas décimas urbanas de Paranaguá, Antonina e Curitiba, três vilas do sul da capitania de São Paulo. Apresentamos aqui os problemas enfrentados e decisões tomadas, quase sempre provisórias e arbitrárias. O resultado chegou a plantas hipotéticas dos loteamentos e arruamentos urbanos daquelas vilas. A partir de um banco de dados - elaborado principalmente com informações das Listas Nominativas de Habitantes -, foi possível caracterizar os moradores arrolados nos livros de imposto predial de Décima. Espacializando esses dados em plantas temáticas, foi possível perceber onde moravam os grupo sociais, suas escolhas (ou a falta delas), ou seja, perceber seus locais preferenciais, mas não exclusivos, de habitação