Mental Models Matter: Conceptualizations of the Human–Nature Relationship Predict Pro-Environmental Attitudes and Behavioral Intentions
Year: 2025
Type: article
Study design: Observational Study
Abstract: Mental models—internal, dynamic, incomplete representations of the external world that people use to guide cognitive processes such as reasoning, decision making, and language comprehension—have practical implications for predicting attitudes and behaviors across various domains. This study examines how mental models of the human–nature relationship predict pro-environmental behavioral intentions directly and indirectly as mediated through anthropocentric and biocentric environmental attitudes. To address these aims, participants were asked about mental model components of the human–nature relationship (human exceptionalism, beliefs about human impact on nature, and beliefs about nature’s impact on humans), pro-environmental attitudes (biocentric and anthropocentric), and their pro-environmental behavioral intentions (protection and investment). We found that protection intentions were (1) directly predicted by human exceptionalism beliefs (negatively) and perceived human impact on nature (positively) and (2) indirectly predicted by mental model components via biocentric attitudes. Investment intentions were directly predicted by nature’s perceived impact on humans, and were similarly indirectly predicted by mental model components via biocentric attitudes. The results suggest that mental models of the human–nature relationship provide a cognitive foundation for environmental behavioral intentions both directly and through their association with environmental attitudes. These findings have implications for pro-environmental interventions that deal with conceptual and attitudinal change.
Source: Sustainability
DOI: 10.3390/su17094242
Authors: Joan J. H. Kim, John D. Coley
Institution: Northeastern University
Language: English
Subfield: Management, Monitoring, Policy and Law
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: National Science Foundation
OpenAlex ID: W4410157339
