To be (or not to be) elevated? Group membership, moral models, and prosocial behavior

ABSTRACT

Recent findings suggest that people can experience feelings of moral elevation when witnessing uncommon moral virtue, and consequently being more prone to engage in prosocial behaviors. However, people can potentially perceive outstanding moral exemplars as a threat to their self-concept due to negative social comparison and consequently derogate them. This research aims to investigate the role of group membership in predicting moral elevation and prosocial intentions when witnessing outstanding moral exemplars. In three online studies, we showed participants a situation where a person from their ingroup (vs. outgroup) (i.e. same gender; same university; same nationality) helped a stranger and then measured their elevation feelings, negative emotions, and prosocial intentions. We predicted that when moral models are ingroup members, people will show higher elevation, lower negative emotions, and will be more prone to engage in prosocial behaviors as opposed to when moral models are outgroup members. Results partially supported our hypotheses.

KEYWORDS:

• Group membership
• morality
• moral elevation
• moral model
• prosociality
• prosocial intentions

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings and the material used for this study are openly available on the OSF page dedicated to the project at https://doi.org/10.17605/OSF.IO/42PMG

Open scholarship

This article has earned the Center for Open Science badges for Open Data and Open Materials through Open Practices Disclosure. The data and materials are openly accessible at https://doi.org/10.1080/17439760.2024.2322446

Notes

1. For the first two studies we used convenience samples, we subsequently performed a sensitivity analysis using G*Power 3.1 (Faul et al., 2007) and determined that, in Study 1, a sample size of N = 176 with 80% power across three condition was enough to detect a small-to-medium effect size (f = 0.25); while, in Study 2, a sample size of N = 189 was enough to detect a small-to-medium effect size (f = 0.24). Finally, for Study 3 we conducted a power analysis using G*Power 3.1 (Faul et al., 2007) and determined that a sample size of N = 159 would be enough to detect a small-to-medium interaction effect across the three conditions with 80% power. Nevertheless, we recruited a larger sample to deal with potential missing data and with participants failing the control check.