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The COVID-19 pandemic has produced unprecedented changes in the lives of many people. Although research has documented associations between concerns related to COVID-19 and poor mental health indicators, fewer studies have focused on positive factors that could help people better cope with this stressful social context. To fill this gap, the present research investigated the trajectories of self-compassion facets in times of dramatic social change. Using a longitudinal research design, we described the trajectories of self-kindness, common humanity, and mindfulness during the first eight months of the COVID-19 pandemic, in a representative sample of Canadian adults (N = 3617). Relying on a multi-trajectory group-based approach, we identified clusters of individuals following persistently low (4.0%), moderate-low (39.3%), moderate-high (46.7%), and high (10.0%) levels of self-kindness, common humanity, and mindfulness. Interestingly, we found that compassionate self-responding trajectories were mainly stable over time with minor fluctuations for some groups of individuals, in line with the epidemiological situation. In terms of covariates, we observed that older women were more likely to follow trajectories of high compassionate self-responding, as compared to the other age and gender groups. In terms of mental health indicators, we demonstrated that trajectory groups with high levels of compassionate self-responding were associated with greater life satisfaction, more happiness, better sleep quality, higher sleep quantity, and fewer negative emotions, as compared to lower trajectory groups. The results supported the idea that self-compassion during the COVID-19 pandemic could have favored better mental health indicators and could possibly be promoted as a psychological intervention in the general population.

In the context of public health crises such as the COVID-19 pandemic, it is essential that individuals cooperate by complying with preventive measures (e.g., wearing a mask). The current research examines how high trust in close others is linked to less cooperation—that is, less compliance with measures—and thus, undermines collective interests. Specifically, we test whether individuals are less willing to comply with preventive measures when interacting with close others they trust. We conducted two experiments in which participants read a vignette depicting a social interaction with either close others (e.g., family) or strangers. Participants had to report the extent to which they would (1) trust the other people in the situation and (2) comply with the mask wearing and physical distancing measures during this interaction. In both experiments, we find that when individuals are considering an interaction with close others, they report experiencing higher trust which is then linked to lower compliance with preventive measures. In Experiment 2, we further demonstrate that participants report less compliance with preventive measures around close others, even when they perceive non-compliance with the measures as morally “wrong”. Our findings shed light on the challenges that compliance with preventive measures poses during social interactions in a context of high trust

Dramatic social change (DSC) is the new normal, affecting millions of people around the world. However, not all events plunge societies into DSC. According to de la Sablonnière (2017, Front. Psychol., 8, 1), events that have a rapid pace of change, that rupture an entire group's social and normative structures, and that threaten the group's cultural identity will result in DSC. This perspective provokes important unanswered questions: What is the chance that a DSC will occur if an event takes place? And, when will other societal states arise from such events? Addressing these questions is pivotal for a genuine psychology of social change to emerge. The goal of this article was to describe a methodology that attempts to answer these questions via a probabilistic decision tree within a Bayesian framework. According to our analysis, a DSC should occur 6.25% of the time that an event takes place in a stable society (68.75% of the time for incremental social change, 12.5% for inertia, and 12.5% for stability). The Bayesian probabilistic decision tree could be applied to specific event and thus serve as a guide for a programmatic study of social change and ultimately inform policymakers who need to plan and prepare for events that lead to DSC.

Globalization impacts the identities of millions. This research first investigates whether participating in a new cultural group predicts higher identification with it while remaining in one’s group of origin. Second, it tests whether the association between identification with the new group (following participation) and with the group of origin depends on the perceived similarity between groups. Studies 1 and 2 (in Kyrgyzstan) showed that participating in the American group predicted greater identification with Americans. This, in turn, positively predicted identification with Kyrgyz in contexts promoting similarities; a negative association between identities emerged when similarities were not promoted (Study 2). Studies 3 (in Kyrgyzstan) and 4 (in Canada) replicated these findings measuring similarity and with a repeated measures methodology (Study 4).