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Abstract People believe they should consider how their behavior might negatively impact other people, Yet their behavior often increases others’ health risks. This creates challenges for managing public health crises like the COVID-19 pandemic. We examined a procedure wherein people reflect on their personal criteria regarding how their behavior impacts others’ health risks. We expected structured reflection to increase people's intentions and decisions to reduce others’ health risks. Structured reflection increases attention to others’ health risks and the correspondence between people's personal criteria and behavioral intentions. In four experiments during COVID-19, people (N  = 12,995) reported their personal criteria about how much specific attributes, including the impact on others’ health risks, should influence their behavior. Compared with control conditions, people who engaged in structured reflection reported greater intentions to reduce business capacity (experiment 1) and avoid large social gatherings (experiments 2 and 3). They also donated more to provide vaccines to refugees (experiment 4). These effects emerged across seven countries that varied in collectivism and COVID-19 case rates (experiments 1 and 2). Structured reflection was distinct from instructions to carefully deliberate (experiment 3). Structured reflection increased the correlation between personal criteria and behavioral intentions (experiments 1 and 3). And structured reflection increased donations more among people who scored lower in cognitive reflection compared with those who scored higher in cognitive reflection (experiment 4). These findings suggest that structured reflection can effectively increase behaviors to reduce public health risks. 

Can deliberation increase charitable giving when giving is impulsive (i.e., a one-time small gift in response to an immediate appeal)? We conduct two studies in Israel and Sweden to compare two forms of deliberation, unguided and guided, in their ability to decrease the singularity effect (i.e., giving more to one than many victims), often evident in impulsive giving. Under unguided deliberation, participants were instructed to simply think hard before making a donation decision whereas participants in the guided deliberation condition were asked to think how much different prespecified decision attributes should influence their decision. We find that both types of deliberation reduce the singularity effect, as people no longer value the single victim higher than the group of victims. Importantly, this is driven by donations being decreased under deliberation only to the single victim, but not the group of victims. Thus, deliberation affects donations negatively by overshadowing the affective response, especially in situations in which affect is greatest (i.e., to a single victim). Last, the results show that neither type of deliberation significantly reversed the singularity effect, as people did not help the group significantly more than the single victim. This means that deliberate thinking decreased the overall willingness to help, leading to a lower overall valuation of people in need. 

Knowing the descriptive norm concerning others' prosociality could affect your behavior, but would you seek out or avoid such knowledge? This high‐powered preregistered experiment explores the effect of both forced and optionally revealed descriptive norms on real monetary donations. These norms were established by learning the proportion of previous participants who had donated to a charitable organization that the respondent now was asked to donate to. For those learning about a norm, participants were more likely to donate if they were shown that a majority donates, compared with if they were shown that a minority donates. For the participants who were asked if they wanted to reveal the norm or not, we found that about half choose to reveal the norm. Those who avoided revealing the norm donated less frequently; both compared with revealers and with those who were forced to view the norm. However, these norm avoiders also donate a higher mean amount. Taken together, this hints at norm avoiders being composed of both altruistic and non‐altruistic people, with fewer of those who are undecided. This type of norm avoidance may be more related to information avoidance motives rather than mere curiosity or reactance. The present findings can inspire further research into the motives of norm avoidance. 

Citizen activists play a role in translating public concern about the climate crisis to policymakers and elevating it on the political agenda. We consider the dynamic between citizen activists and the decision-makers they seek to influence and we review psychological research relevant to advocating for climate legislation. We conducted a study with citizen activists who lobby the US Congress for a carbon pricing policy to address climate change. The study assessed how activists think about four social psychological approaches: affirmation, social norms, legacy and immediacy. The findings provide a window into activists’ intuitions about which strategies to use, whom to use them with and their perceived effectiveness. A strategy of establishing shared values and common ground (affirmation) was used most frequently overall. A strategy emphasizing the long-term costs and benefits of addressing climate change (legacy) was employed less frequently than affirmation and seen as less effective by activists but it was the only strategy that was associated with perceived increases in Congressional Representatives’ support of the policy. Citizen activists and their interactions with elected officials provide an opportunity for social-behavioral scientists to understand and potentially overcome barriers to enacting climate policy. 

This paper asks whether moral preferences in eight medical dilemmas change as a function of how preferences are expressed, and how people choose when they are faced with two equally attractive help projects. In two large-scale studies, participants first read dilemmas where they “matched” two suggested helping projects (which varied on a single attribute) so that they became equally attractive. They did this by filling in a missing number (e.g., how many male patients must Project M save in order to be equally attractive as Project F which can save 100 female patients). Later, the same participants were asked to choose between the two equally attractive projects. We found robust evidence that people do not choose randomly, but instead tend to choose projects that help female (vs. male), children (vs. adult), innocent (vs. non-innocent), ingroup (vs. outgroup) and existing (vs. future) patients, and imply no (vs. some) risk of a harmful side-effect, even when these projects have been matched as equally attractive as, and save fewer patients than the contrasting project. We also found that some moral preferences are hidden when expressed with matching but apparent when expressed with forced choice. For example, 88–95% of the participants expressed that female and male patients are equally valuable when doing the matching task, but over 80% of them helped female patients in the choice task. 

We replicate and extend unit asking – a method to increase donations by first asking donors for their willingness to donate for one unit and then asking for donations for multiple units (Hsee, Zhang & Xu, 2013) We conducted a large scale replication and extension using a 2 (unit asking, control) x 3 (domains; children (original), animals, environment) between-subjects design. Across three domains, we find that unit asking increased donations, suggesting that this method can be used to increase giving to different charitable causes.