[Proposal] Overcoming Self-Focus in the Presence of Contagious Diseases: Performance-Diagnostic Information Increases Donations to Causes Highlighting Benefits for Others

Overcoming Self-Focus in the Presence of Contagious Diseases: Performance-Diagnostic Information Increases Donations to Causes Highlighting Benefits for Others

Donations to charitable health organizations (e.g., causes associated with health care, diseases, disorders, and medical research) have become increasingly important, especially in the context of the COVID-19 pandemic. Our key goal is to understand how organizations can create effective donation appeals for causes related to disease prevention and treatment, especially contagious diseases.

A relevant question when creating a donation appeal is whether to focus on the donor’s personal benefits of donating or the benefits for others (White and Peloza 2009). This question lies at the heart of a broader question in prosocial behavior, which is whether people donate to benefit others (“It is important to give back to society,”) or themselves (“I donate if the cause helps me,”). We propose that the effectiveness of highlighting personal benefits or benefits for others depends on people’s perceived likelihood that they will get the disease or class of diseases mentioned in the appeal.

When the likelihood of getting the disease is low, people do not feel threatened by the possibility of getting it (Weinstein and Klein 1996). If a person believes it is unlikely that they will get a disease, they should infer that others will need, and benefit more, from the work of the health organization (Batson and Shaw 1991). In this case, appeals that focus on the benefits to other people (vs. personal benefits) are more effective because the donor will perceive that others are the right target for the benefits a donation could bring (H1). As the likelihood of getting the disease increases, people feel threatened by, or at least consider, the prospect of getting sick (Sheeran, Harris, and Epton 2014). The perception of a threat should make them more focused on their personal interests, which will make donation appeals with self-benefits more effective. In this case, appeals that focus on personal benefits (vs. other people) are more effective because the donor will perceive that him or herself is the right target for the benefits a donation could bring (H2).

If these hypotheses (H1 and H2) are true, they reveal a potential issue. Many organizations use other-benefit appeals due to the nature of charitable giving, which means their appeals may not be effective when people believe they can get a disease. In addition, appealing to self-benefits when society needs help may harm the organization’s image. Moreover, as the spread of a disease in a community increases, people may derive real benefit from donating to a cause focused on benefitting others, as the fewer people in a donor’s community get the disease, the less likely it is that a donor will get the disease themselves. The fewer people get infected in a community, the less the disease circulates, which ultimately benefits everyone (Fauci et al. 2020).

Given its importance, we investigate a solution to this issue. We propose that the increase in donations resulting from self-benefit appeals is associated with the belief that a health organization’s work is not enough to stop a disease from spreading around a community and ultimately benefit the donor. If that is the case, providing information that is diagnostic of the successful performance of the organization should attenuate this belief. When such information is provided, appeals with benefits for others will be more effective than those with personal benefits (H3). If our hypotheses hold true, it means the current discussion on helping oneself versus helping others is limited, and should be broadened to consider what type of evidence potential donors are being presented to support the effectiveness of donating to benefit others.

This research contributes to the area of prosocial behavior by demonstrating that, despite the fact that donating necessarily involves helping others, the likelihood that the cause can affect a potential donor can determine whether highlighting benefits for others increases or decreases donations. It also contributes by demonstrating that it is possible for potential donors to donate more when benefits for others (vs. personal benefits) are highlighted, but that a health organization needs to provide additional evidence of its successful performance in the past for that to happen. Further, previous research has not provided much insight into how characteristics of the cause itself, or the disease in the case of health organizations, influence donations under different benefit targets (personal, others). This research will help health organizations by demonstrating strategies these organizations can use to design donation appeals with the correct combination of information types (likelihood of getting a disease, benefit target) to maximize donations.

Thus far, we have data for four preregistered experiments providing support for our hypotheses (Study 1, H1 and H2: AsPredicted: Captcha Study 2, H1 and H2: AsPredicted: Captcha Studies 3 and 4, H2 and H3: AsPredicted: Captcha and AsPredicted: Captcha). We are applying for the Prolific Research Grant competition because we can improve the robustness and generalizability of our findings even further.

First, all our studies were run before the COVID-19 vaccines were wildly available. We believe it would be important to run exact replications of Studies 2 and 3 (which encompass all of our hypotheses) with vaccinated participants (screening). Details (e.g., sample size) are in the linked preregistrations, and 1400 P’s with an 11.22 hourly rate would cost $2,445.33.

Second, none of our studies test different categories of personal and other benefits. Because different benefits could affect our results differently, we intend to test whether benefit type moderates our results. To do so, we intend to replicate Study 1 by adding a factor (benefit type: disease-related vs. tax benefits vs. emotional benefits vs. abstract benefits) into the design. This results in a study with 3200 P’s, costing $5,589.33. Preregistration: AsPredicted: Captcha.

Upon publication, we will report all stimuli, materials, additional methodological details, additional analysis (if any), and data exclusions (if any) in a Web Appendix. The exact stimuli (Qualtrics .qsf files), raw data, and code to reproduce all analyses will be available at an Open Science Framework repository.