Expected climate change consequences and their role in explaining individual risk judgments

assumption that informing people about the seriousness of a broad range of possible impacts tends to be more promising than focusing on the level of detail. Sociodemographic variables were included in all models predicting risk judgments. Women and those further left on the political spectrum reported higher levels of worry about climate change and expectations of more negative country-specific climate change impacts. We only found differences between the youngest and older age groups for risk evaluation, not for general worry; the age group 15–24 expected more negative impacts than the age groups above 45. The models including the levels, and those including depth and width, explained about 14% and 9% of the variance in worry about climate change and about 9% and 8% of the variance in risk evaluation, respectively. Conclusions This study expands upon the existing literature addressing the content and structure of causal beliefs that members of the public keep about climate change. The findings contribute to our understanding of the type of climate change impacts people expect to be important in the country they live in, and how these expectations relate to risk judgments. Open-ended responses were categorized based on a coding scheme reflecting the theoretical model by Bo¨hm and Pfister [11]. This was done based on the assumption that people think about the national impacts of climate change in a variety of different ways, ranging from changes in pub- lic attitudes to human suffering. Future research could increase the practical impacts by focus-

ing on alternative approaches, such as categorizing the responses based on proposed communication strategies (e.g. highlighting the negative impacts on health [48] or human cul- ture [49]), or differentiating between ‘correct’ or ‘faulty’ mental models [e.g., 16, 50]. Supporting information S1 Table. Descriptive statistics and correlations among closed-ended questions included in the analyses (weighted). (DOCX) S2 Table. Coding scheme. (DOCX) S3 Table. Frequencies for each main level and sublevel within the four countries (weighted). (DOCX) S1 File. Coding instructions. (DOCX) S1 Dataset. (DTA) Acknowledgments We want to thank Keri Hartman for proofreading the manuscript. Author Contributions Conceptualization: Thea Gregersen, Rouven Doran, Gisela Bo¨hm, Hans-Ru¨diger Pfister. Formal analysis: Thea Gregersen, Hans-Ru¨diger Pfister. PLOS ONE Expected climate change consequences and individual risk judgments PLOS ONE | https://doi.org/10.1371/journal.pone.0281258 February 15, 2023 12 / 15