Intergroup helping during the coronavirus crisis: Effects of group identification, ingroup blame and third party outgroup blame

Abstract

Two studies tested predictors of helping across national boundaries. British participants reported blame attributions for the coronavirus crisis, either to the British government (ingroup blame), or to the Chinese government (third party outgroup blame), and it was tested whether this was associated with intentions to donate money to help outgroup members suffering from effects of the coronavirus crisis in the world's poorer countries. It was hypothesized that strength of identification with the national ingroup would be negatively associated with blame attributions to the ingroup, and that it would be positively associated with blame attributions to a third party outgroup. Blame attributions were predicted in turn to be related to outgroup helping, with ingroup blame being positively associated with helping intentions, and third party outgroup blame being negatively associated with helping intentions. Support for these predictions were found in one exploratory (N = 100) and one confirmatory (N = 250) study.

Intergroup helping during the COVID-19 crisis: A moderated mediation with effects of ingroup identification, ingroup blame, and perceived global common fate

“…In other words, in the face of adversity or challenges ingroup identification will be positively related to a desire to blame outgroups for the issues at hand, and negatively related to a willingness to acknowledge ingroup culpability. This is indeed what Zagefka (2021a) found for British nationals and their attributions for problems caused by the coronavirus crisis. Strongly identified Brits were more likely to emphasise things the Chinese had done to exaccerbate the crisis, and less likely to think that the British themselves were to blame for the problems because they had mishandled the crisis (see also Zagefka & Sun, 2021 ).…”

“…Sample size was determined with G*Power, computing the required sample size given an alpha of .05 and a power of .80. Estimates were based on moderate correlations of blame and outgroup helping found in previous work in the context of the coronavirus crisis ( Zagefka, 2021a ).…”

The Impact of COVID-19 on the Majority Population, Ethno-Racial Minorities, and Immigrants

“…Yet, outgroup derogation and ethnic prejudice may also spread from seemingly unconnected events, such as natural disasters and pandemics (Kim & Chang, 2014). Negative inter-group consequences of natural disasters and pandemics stem from several possible underlying processes, such as outgroup blaming for spreading the disease (Zagefka, 2021), protection of ideological belief systems (Fairlamb & Cinnirella, 2021), or perceived competition for restricted resources (Vezzali et al, 2018).…”

“…In the context of the COVID-19 outbreak, “bonding” types of prosociality within one’s own community (e.g., when you help your neighbor with groceries), and “bridging” variants of prosociality, including vulnerable populations beyond one’s immediate ingroup (e.g., when you volunteer at a homeless shelter) were both connected with dispositional factors, such as fulfilment of self-transcendence goals (Politi et al, 2020). Moreover, outgroup helping was positively connected with contextual clues about the global emergency, such as ingroup (instead of outgroup) blaming for spreading the virus (Zagefka, 2021).…”

Prosociality during COVID‐19: Globally focussed solidarity brings greater benefits than nationally focussed solidarity

“…All participants were required to have British nationality. The sample size was determined by the fact that effects stabilize around N = 250 (Schönbrodt & Perugini, 2013 ), and that this sample size generated sufficient power to similar effects in previous work on intergroup helping in the context of COVID‐19 (James & Zagefka, 2017 ; Zagefka, 2021 ). Moreover, an a priori power analysis with G*Power (Faul, Erdfelder, Lang, & Buchner, 2007 ) was conducted, assuming a slope of .16 and α = .05 and aiming for a power of 0.80.…”