Beyond the individual: testing and applying a collective protection motivation model for pro-environmental behaviors
摘要
In the face of complex and urgent environmental crises, researchers increasingly advocate for transformation-oriented approaches that consider the scale of changes required. This paper introduces a Collective Protection Motivation (CPM) model, which builds upon Protection Motivation Theory’s (PMT) robust analysis of personal decision-making and integrates recent findings from collective environmental action research. Specifically, the CPM model adapts PMT’s appraisal processes to account for the collective and large-scale dimensions of climate change in terms of both impact and required responses. Two correlational studies tested the CPM model’s structure and predictive power in multi-level pro-environmental behavioral intentions through structural equation modeling analyses. Study 1 (N = 928) focused on general pro-environmental behavioral intentions, while Study 2 (N = 402) examined initiatives for reducing meat consumption-production. The results supported the overall structure of the CPM model, validating the collective conceptualizations of threat, coping, and costs-rewards appraisals. The model also successfully predicted a significant proportion of behavioral intentions. Notably, the model’s most innovative construct - collective coping, which incorporates the ability to envision sustainable futures (cognitive alternatives) - demonstrated systematic predictive power in individuals’ intentions to adopt general and specific pro-environmental behaviors. While further research is needed to confirm its generalizability, the CPM model offers a promising framework for understanding the decision-making processes behind both individual and collective pro-environmental actions. It emphasizes the contribution of cognitive alternatives to the subjective sense of collective agency and highlights the importance of merging individual and collective approaches to better understand the psychological drivers behind support for large-scale ecological transformations.