The COVID-19 pandemic threatens millions of lives, and an effective response will require individuals to take costly and difficult measures to prevent infection. How should public health messaging frame these measures, which can reasonably be conceptualized as either self-interested actions or cooperative efforts? We measured the influence of three messaging treatments on coronavirus prevention intentions among Americans from Amazon Mechanical Turk. All treatments presented identical COVID-19 information, but emphasized either personal, public, or both personal and public benefits of prevention behaviors. In studies (n = 2176) conducted early in the pandemic (March 14-16, when there were under 2,000 confirmed U.S. cases), we found support for prosocial framing: the Public treatment was more effective than the Personal treatment, and no less effective than the Personal+Public treatment. In studies (n = 3985) conducted later (April 17-30, when there were over 500,000 confirmed U.S. cases), all three treatments were similarly effective. Additionally, across both sets of studies, the perceived public threat of coronavirus predicted prevention intentions more strongly than the perceived personal threat. Together, our results highlight the potential value of prosocial framing.

We thank our many volunteer translators, whose names are listed in the Appendix. We also thank Prolific for sponsoring the participants for the survey experiment and Aristeo Marras for data advice. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

COVID-19 prevention behaviors may be seen as self-interested or prosocial. Using American samples from MTurk and Prolific (total n = 6850), we investigated which framing is more effective—and motivation is stronger—for fostering prevention behavior intentions. We evaluated messaging that emphasized personal, public, or personal and public benefits of prevention. In initial studies (conducted March 14–16, 2020), the Public treatment was more effective than the Personal treatment, and no less effective than the Personal + Public treatment. In additional studies (conducted April 17–30, 2020), all three treatments were similarly effective. Across all these studies, the perceived public threat of coronavirus was also more strongly associated with prevention intentions than the perceived personal threat. Furthermore, people who behaved prosocially in incentivized economic games years before the pandemic had greater prevention intentions. Finally, in a field experiment (conducted December 21–23, 2020), we used our three messaging strategies to motivate contact-tracing app signups (n = 152,556 newsletter subscribers). The design of this experiment prevents strong causal inference; however, the results provide suggestive evidence that the Personal + Public treatment may have been more effective than the Personal or Public treatment. Together, our results highlight the importance of prosocial motives for COVID-19 prevention.

A defining aspect of human cooperation is the use of sophisticated indirect reciprocity. We observe others, talk about others, and act accordingly. We help those who help others, and we cooperate expecting that others will cooperate in return. Indirect reciprocity is based on reputation, which spreads by communication. A crucial aspect of indirect reciprocity is observability: reputation effects can support cooperation as long as peoples' actions can be observed by others. In evolutionary models of indirect reciprocity, natural selection favors cooperation when observability is sufficiently high. Complimenting this theoretical work are experiments where observability promotes cooperation among small groups playing games in the laboratory. Until now, however, there has been little evidence of observability's power to promote large-scale cooperation in real world settings. Here we provide such evidence using a field study involving 2413 subjects. We collaborated with a utility company to study participation in a program designed to prevent blackouts. We show that observability triples participation in this public goods game. The effect is over four times larger than offering a $25 monetary incentive, the company's previous policy. Furthermore, as predicted by indirect reciprocity, we provide evidence that reputational concerns are driving our observability effect. In sum, we show how indirect reciprocity can be harnessed to increase cooperation in a relevant, real-world public goods game.evolutionary game theory | experimental economics

Evolutionary game theory typically focuses on actions but ignores motives. Here, we introduce a model that takes into account the motive behind the action. A crucial question is why do we trust people more who cooperate without calculating the costs? We propose a game theory model to explain this phenomenon. One player has the option to "look" at the costs of cooperation, and the other player chooses whether to continue the interaction. If it is occasionally very costly for player 1 to cooperate, but defection is harmful for player 2, then cooperation without looking is a subgame perfect equilibrium. This behavior also emerges in population-based processes of learning or evolution. Our theory illuminates a number of key phenomena of human interactions: authentic altruism, why people cooperate intuitively, one-shot cooperation, why friends do not keep track of favors, why we admire principled people, Kant's second formulation of the Categorical Imperative, taboos, and love.game theory | evolution | emotion | motive | cooperation C ooperation occurs when we take on costs to help others. A key mechanism by which cooperation is sustained is reciprocity: Individuals cooperate with those who have cooperated in the past (1-14). However, we care about not only whether others cooperate, but, also, their decision-making process: we place more trust in cooperators who do not strategically weigh the costs and make an effort to collect them before deciding whether to cooperate. For example, we are impressed by colleagues who immediately agree to proofread a paper but view with suspicion those who ask, "how many pages does it have?" Intuitively, those who cooperate without "looking" (CWOL) can be trusted to cooperate even in times when there are large temptations to defect. However, will the added trust from CWOL be worth missing out on those large temptations? Additionally, which conditions make CWOL a winning strategy?To address these questions, we develop the envelope game ( Fig.