Clinical evidence suggests that mindfulness meditation reduces anxiety, depression, and stress, and improves emotion regulation due to modulation of activity in neural substrates linked to the regulation of emotions and social preferences. However, less was known about whether mindfulness meditation might alter pro-social behavior. Here we examined whether mindfulness meditation activates human altruism, a component of social cooperation. Using a simple donation game, which is a real-world version of the Dictator's Game, we randomly assigned 326 subjects to a mindfulness meditation online session or control and measured their willingness to donate a portion of their payment for participation as a charitable donation. Subjects who underwent the meditation treatment donated at a 2.61 times higher rate than the control (p = 0.005), after controlling for socio-demographics. We also found a larger treatment effect of meditation among those who did not go to college (p < 0.001) and those who were under 25 years of age (p < 0.001), with both subject groups contributing virtually nothing in the control condition. Our results imply high context modularity of human altruism and the development of intervention approaches including mindfulness meditation to increase social cooperation, especially among subjects with low baseline willingness to contribute.

Thailand has the highest road traffic fatality rate in Southeast Asia, making road safety a critical public health concern. A 2015 World Health Organization (WHO) Report showed that speeding behavior was the most important determinant for road traffic crashes in Thailand. Here, we aimed to examine associations of socio-demographic factors (gender, age, socioeconomic status) with self-reported motorcycle speeding behavior. Additionally, we examined a potential role of time discounting and risk preference as mediators in the association of socio-demographic factors with speeding. We used data obtained from the Mahasarakham University Social Network Survey 2018 (MSUSSS) (N = 150). We ran linear network autocorrelation models (lnam) to account for the data's social network structure. We found that males are more likely than females to engage in speeding behavior (β = 0.140, p = 0.001) and to discount the future (β = 5.175, p = 0.017). However, further causal mediation analysis showed that time discounting does not mediate the gender-speeding association (p for mediation = 0.540). Although socioeconomic status (subjective social class) was not associated with speeding (β = 0.039, p = 0.177), age was marginally associated with speeding (β = 0.005, p = 0.093). Future studies may consider using a larger sample.

Sustaining economic activities while curbing the number of new coronavirus disease 2019 (COVID-19) cases until effective vaccines or treatments become available is a major public health and policy challenge. In this paper, we use agent-based simulations of a network-based susceptible-exposed-infectious-recovered (SEIR) model to investigate two network intervention strategies for mitigating the spread of transmission while maintaining economic activities. In the simulations, we assume that people engage in group activities in multiple sectors (e.g., going to work, going to a local grocery store), where they interact with others in the same group and potentially become infected. In the first strategy, each group is divided into two subgroups (e.g., a group of customers can only go to the grocery store in the morning, while another separate group of customers can only go in the afternoon). In the second strategy, we balance the number of group members across different groups within the same sector (e.g., every grocery store has the same number of customers). The simulation results show that the dividing groups strategy substantially reduces transmission, and the joint implementation of the two strategies could effectively bring the spread of transmission under control (i.e., effective reproduction number ≈ 1.0).