Building bridges for anti-racism activism: Testing situational theory of problem solving and problem chain recognition effect

Abstract

This study investigates how people participate in activism against Asian hate crimes (i.e., Asian Lives Matter (ALM)). In contrast to numerous studies that use Situational Theory of Problem Solving (STOPS) to predict information behaviors, this study introduced and examined a streamlined model focused on predicting activism behaviors. Moreover, this study tests the Problem Chain Recognition (PCR) effect by exploring how situational motivation in problem solving related to the Black Lives Matter (BLM) movement affects individuals’ perceptions and communicative acquisition about the issue of anti-Asian hate crimes. Further, this study examines the differences among three American socialized racial groups in terms of problem recognition, constraint recognition, involvement recognition of activism against Asian hate crimes, and activism behaviors. The results of this study revealed that situational motivation in problem solving and referent criterion lead to activism against anti-Asian hate crime. In addition, this study found positive PCR effects between BLM and ALM. This represents a pioneering utilization of the PCR effect to the field of racial activism. Importantly, there were significant differences to perceive activism for anti-Asian hate crimes among three racial group (Blacks, Whites, and Asians). Therefore, the results of this study contribute to the theoretical building of STOPS and practical implications for understanding the complexity of the American socialized racial discourse and predicting racial activism in relation to BLM and ALM.