the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Psychometric and cultural characterization of relative volcanic risk perception levels of individuals highly exposed to proximal activity from Villarrica volcano, Chile
Abstract. This study combines the Psychometric Paradigm and the Cultural Theory to analyze volcanic risk perception (VRP) of more than two hundred residents and a similar number of non-residents in the high-hazard zone of Villarrica volcano. While the psychometric approach captures statistical variations in VRP, Cultural Theory helps characterize cultural patterns influencing risk perception. Together, they provide a more comprehensive framework for emergency management. A key distinction is observed between residents and non-residents. Residents show lower knowledge scores but higher internal trust, suggesting strong community ties yet a limited understanding of volcanic hazards. Non-residents, in contrast, have higher knowledge but lower internal trust, which may lead to overconfidence in their ability to respond to eruptions. However, both groups share similar external trust, indicating confidence in authorities and experts, which is vital for adherence to safety measures. Demographic factors also influence VRP. Elderly individuals and those outside the workforce tend to have lower VRP, highlighting the need for targeted risk communication. Higher education levels correlate with higher VRP, while economic activity (e.g., tourism, agriculture) influences risk perception, with some groups exhibiting extreme variations. Further effort is needed on indigenous populations, as they show lower VRP, warranting better integration of indigenous knowledge into risk assessments. Similarly, gender and religion show no clear patterns, although they may still shape risk perception in a more complex way. Ultimately, understanding the cultural and social dimensions of VRP is essential for designing effective, group-specific risk communication strategies to strengthen community resilience.
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RC1: 'Comment on egusphere-2025-2535', Francisca Vergara-Pinto, 14 Aug 2025
The manuscript presents an interesting contribution to understanding the perception of volcanic risk in the southern Andes of Chile through a psychometric approach combined with cultural risk theory. It explores the variability and diversity of risk perceptions among populations living near the Villarrica volcano, which is one of the most hazardous volcanoes in the country. Using survey analysis, the work examines the various factors that influence how people perceive risk, emphasizing the significance of psychometric-cultural analysis in comprehending the complex sociocultural, environmental, and economic contexts surrounding a volcanic eruption emergency. This topic deserves the attention of those in the fields of volcanology and disaster risk studies.
However, the manuscript has some shortcomings in both form and content that could be improved. I recommend its publication after major revision. For instance, the results and discussions could be presented more clearly and effectively. Additionally, the conclusion should focus on the most important findings without reiterating the results, instead building upon them for a more insightful end to the study. To further enhance this work, I suggest some moderate/major changes that could be considered. The suggestions and comments (see PDF) are organised according to the structure of the paper to make the audience more familiar with the topic:
1 Introduction: The authors begin the introduction by stating that “in the context of natural hazards, significant scientific attention on risk perception has focused on earthquakes and tsunami related disasters, while comparatively less attention has been given to volcanology”. The literature offers a different perspective, both internationally and in Chile and Latin America. I recommend reviewing and citing some works that oppose this notion, perhaps noting that “while comparatively minor, volcanology is gaining increased attention.” For example: Iceland (Bird, Gísladóttir and Dominey-Howes 2011; Kokorsh and Gisladottir 2023); Mexico (López-Vázquez 2009); Chile (Vergara-Pinto and Marín 2023; Alegría and Vergara-Pinto 2024); Colombia (Peña et al. 2020). Including this type of background would reinforce the idea of the potential for studying the perception of volcanic risk.
When referring to levels of risk perception: In the background information, it is clear that VRP is eminently cultural, contextual, and multifactorial. Before this sentence, I suggest pointing out that there are qualitative, quantitative, or mixed ways of approaching VRP and that you consider it optimal to measure “levels” of risk perception (quantifying a factor) and eventually point out difficulties in quantifying certain cultural aspects (for example, quantifying religion or belief variables).
When referring to knowledge: Is this factor more related to “Appropiation of scientific information”? I wonder if this factor could distinguish that people's knowledge is the result of a combination of information and experience (other sources, disaster memory, oral tradition, etc.). Or if it only measures access to scientific information.
Regarding external trust: Perceiving more risk could sound ambiguous. I suggest clarifying whether you mean that a person may perceive risk more (be more aware of the risks) or perceive that there is more risk (more likelihood of suffering a consequence).
When referring to the psychometric paradigm and cultural theory of risk: I suggest including examples or results from these applications to help readers understand how this approach aids in interpreting perceptions of risk. For instance, beyond providing statistical data (%), what other insights can psychometric analyses reveal. The criticisms about the cultural theory of risk have been addressed by other authors who have sought to move beyond the general categorization of four archetypes. They suggest that culture is dynamic and, consequently, so are perceptions of risk. Additionally, these works may reference cultural constructs that influence people's understanding of disasters, such as myths, beliefs, or traditions that shape representations of risk (Douglas 1996; Oliver-Smith 1999; García Acosta 2005; Hoffman 2015).
While there is a substantial body of literature on risk perception and volcanism in the Global North, important references from Chile should also be included. This would demonstrate that your work contributes to an existing line of research on volcanic risk perception in Chile, particularly by introducing new insights from psychometric approaches. Some key references to include: Elderly individuals and place attachment (Díaz, Peña, Valles et al. 2022); Volcanic rurality in transformation (Vergara-Pinto, O’Grady, Fredriksen et al. 2024); Perception and local knowledge of risk at Villarrica volcano (Muena Briones 2023).
The section on the study area and historical eruptions offers a detailed description of the volcano and surrounding communities. I suggest concluding by highlighting the effects of population growth, especially regarding land use changes and risks (e.g., Ruiz, Morales, Contreras et al. 2025); and include some insights on volcanic activity after the 2015 event, particularly the yellow alert 2022-2024, and significant changes in the volcano's behaviour since then. (e.g., Romero et al. 2025)
2 Methodology: It is important to specify who designed the questionnaire administered in 2016 and 2017. If the authors were responsible for its design, this should be clearly stated. Conversely, if the questionnaire was administered by SERNAGEOMIN staff, evidence of permission to publish the survey data should be provided.
When referring to the ‘Occupation’ variable: It is not recommendable to assume that greater access to information equates to greater knowledge. For instance, retired older adults may have accumulated knowledge over their lifetimes, or they may possess local knowledge and disaster memories that aid them in making decisions. This is a point that could be presented as a complementary perspective on the issue of Occupation. Here are some examples: Mt Merapi (Septiana et al. 2019); Nevados de Chillan (Sandoval et al. 2023).
3 Results: It would be good for the authors to rethink the structure and order of the Results and Discussion sections, ideally merging them into a single section to avoid repetitions. This restructuring would enhance readers' comprehension and improve the overall coherence of the paper.
4 Discussion: Regarding cultural patterns of VRP levels, the Results section discusses variations on the theme of religion, but here, you could expand on the implications or interpretations. What does this reveal about the population living near the Villarrica volcano? What influence does religion appear to have on the perception of risk? (especially in this area, where people may believe in the Christian God, Chao Ngünechen, or sometimes both).
5 Conclusion: This section summarizes the article, but it could be enhanced with reflections and recommendations on the study topic. I suggest specifying the types of vulnerabilities that may affect specific groups and how tailored risk communication should be in practice. Finally, it is important to reflect on how representative the findings from the 2016-2017 survey are of the current situation at Villarrica volcano. Significant changes - whether positive or negative - in the composition of the population may have occurred, particularly in the aftermath of COVID-19 (e.g., lifestyle migration).
The figures and maps are well-done, and the references appear to be accurate. If possible, the questionnaire could be included as supplementary material, or the main themes of the questions could be summarized to provide a clearer overview of what was asked concerning the variables and factors involved.
Overall, the manuscript could be strengthened by addressing more clearly the role of cultural factors in the diverse perceptions held by residents and non-residents of the Villarrica volcano.
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RC2: 'Comment on egusphere-2025-2535', Letícia Guimarães, 22 Aug 2025
The manuscript represents an important contribution to risk-perception studies and to risk management at the Villarrica volcano, one of the highest risk volcanic systems in Latin America. Through a combination of psychometric approach and socio-cultural characterization the study assesses how social, cultural and economic aspects influence volcanic risk perception and provides valuable information on the current state of knowledge and awareness of the exposed population (here, including residents and non-residents, a key asset of this study), a fundamental piece of information for effective preparedness strategies.
In addition to considering two distinct exposed groups, the work considers a wide variety of social, cultural, and economic aspects in the construction of risk perception, generating relevant data for disaster risk science and risk reduction policies. However, to be worthy of the quality and relevance of the data, some improvements – especially in the methods and data presentation – are needed, with publication of the manuscript after major revision.
The INTRODUCTION brings a summary of volcanic risk perception (VRP) studies, the concepts of psychometric paradigm and the cultural theory, and the geological setting of the target volcanic system. The text is well written, but the state-of-the-art of VRP studies could be better developed; even considering that VRP has, proportionally, less studies than other geological hazards, there is a set of good published works (especially from the 2000's on) whose findings could be better and briefly presented here (also for supporting the discussion section). Also, shouldn’t tephra fall out be included as a potential volcanic hazard for this region (at lines 106-107)? In figure 01, only historical lahar deposits are shown; considering the whole set of volcanic hazards, it would be interesting to include a multiple hazard map.
In the METHODOLOGY section the application of the questionnaires and the analyzed social, cultural and economic parameters are well explained, but some additional information on the survey procedure and the statistical approach would greatly improve the manuscript.
Considering a greater reliability of the study and its eventual future replicability, I suggest presenting the 28 questions that constitute the survey (not only the "desirable answers" as presented in table 1) and the used score criteria. In section 1.1 (lines 74-76) the authors mentioned that psychometric and cultural theory analysis are usually based on "point-scale systems such as Likert scales or 5-point questions" but it's not clear which is the scoring method applied here (is it a Likert scale?). In section 2.2 (line 172) it is mentioned that "Each survey question is assigned a value of one (1) when the response aligns with theoretically optimal VRP", but how are the answers that diverge from those considered the "desirable answers" in table 1 scored? Presenting the applied questionary and the score method is crucial.
In figure 3 legend, a better explanation of the "rural sample (ppl)" meaning would be appreciated (what do those numbers mean? the exact number of people interviewed in each area?).
In table 2, the data on “rural” areas refers to all the three municipalities (Pucón, Coñaripe and Villarrica)? Why data from Villarrica region is not presented individualized as the Pucón and Coñaripe data?
In section 2.2 the statistical approach should be better detailed, considering readers and stakeholders that could not be fully familiar with the topic. After a better explanation of the scoring method in the previous section, a clearer step-by-step method description would be appreciated. Example: (1) the sum of the scores of each response defines the VRP score of each interviewee: (2) the set of samples (VRP scores of all interviewees) are grouped in clusters considering the k-means analysis; (3) the clusters are defined based on the definition of the best clusters centroids based on standard variation; (4) the standard variation is defined as... (and so on). Here, terminology standardization is important to enhance the understanding of the method and the results obtained. For instance:
- k-means clustering usually considers within-cluster sum of squared distances (WCSS), also called variation or standard variation, which is slightly different from the standard deviation. Both terms are used in the manuscript: standard variation (in the methods), and standard deviation (in figures 7 and 8, in section 3.3.2.). If they're not referring to the same thing, and both calculations are applied in the study, I would suggest prioritizing the term "WCSS" in the methods to avoid misunderstandings and make it clearer where each calculation is applied.
- If the "J" term in equation 1 (lines 181 and 183) represents the WCSS, I'd suggest using "WCSS" instead of a new term/definition ("objective function").
The RESULTS starts with a paragraph whose final sentences (lines 252-254) seem to be outplaced; they would fit better in the introduction, when describing the whole content of the manuscript. Another necessary textual review is the standardization of terms; for example, in the previous section and in the figures 3 and 6, the authors refer to the localities as Pucón, Coñaripe and Villarrica but in this section (3.2 and figure 5) the authors refer to the localities as Pucón, Panguipulli and Villarica.
Considering that the results are the core of a study, the raw data, the scores for each factor and the final VRP score should be presented (it could be done as supplementary table, considering it is an extensive dataset). From this, some improvements can be made to the graphical presentation of the data, to facilitate visualization and enhance the understanding of eventual patterns and correlations:
- Figures 5 and 6 written legend: please indicate that the results are for residents.
- Figure 6 graphic legend: please clarify the meaning of the sample size symbol - what do those numbers mean (the number of interviewees)?
- Figures 7 and 8: Y axis titled as "standard deviation" - is this right? Or is it WCSS? If this is the standard deviation, the methods section should include some info regarding this calculation. In any case, neither the WCSS nor the standard deviation provide negative values. Or are these values the clusters’ centroids? In this case, how negative scores could be obtained from the survey? So… what is the meaning of these diagrams? What do the authors want to present? With these diagrams, if they represent standard deviation values, we are simply visualizing the dispersion of scores, so I would suggest a different type of diagram: boxplots could be an interesting and more meaningful way to present the factors' scores. Through boxplots the reader could know the whole range of scores, their dispersion, minimum and maximum scores... and it could include a label with each cluster’s centroids values. With all this information in one diagram, it would be easier to comprehend how each factor is contributing to the final VRP.
- Figure 9: this is the high point of the study and the most important information for stakeholders, especially those responsible for risk management. Why did you choose presenting the pie charts as “distribution of cultural groups by VRP levels” and not the opposite way (“distribution of VRP levels by cultural groups”)? Could this change highlight different patterns? The pie charts focused on the VRP levels (the way it is presented) could be hindering a precise characterization of a given social group? For instance: a given group (e.g. 18 to 40 years old residents) have a few people in the high VRP, but them represent the majority of those in this level; the same group (18 to 40 years old residents) have a lot of people in the low VRP (more people than in the high level) but corresponding to the minority in the low VRP. Considering that pie charts display relative proportion of data, the resulting charts would show a bigger area for this group in the High VRP chart and a smaller area in the Low VRP chart, given the idea of more people with higher VRP. But, considering the absolute number of 18 to 40 years old residents, the group has more people with low VRP, so it would also deserve attention. In any case, it is fundamental to present the raw data as supplementary material to support the diagrams and the related discussion.
If the authors agree with the proposed review, the text might also need some revision.
The DISCUSSION section is well written, but in the first part of it the authors are, again, focusing on critics to/problems with the applied approach. To avoid disqualifying the work, such criticisms/problems could be presented only in the introduction, where the pros of the method and the reason why the authors chose to use it should be better detailed, leaving this section exclusively for the discussion of the results and patterns described in the previous item.
At line 375 it is not very clear what the authors mean by “positive behavior”, so this could be better explained.
Providing the score method and the raw data, as requested before, would also be useful in this section, for example, to better understand how negative VRP scores are obtained (as mentioned at line 381).
The authors discuss the relation between age and education level of non-residents and their VRP score - would their economic characteristics (occupation and economic activity) also influence this result?
Lastly, the CONCLUSIONS are well written, concise and straightforward, but may need some revision after the above-mentioned changes.
In summary, the manuscript represents an important contribution to the volcanic risk perception science and to the assessment and management of one of the riskiest volcanic systems in Latin America. A better understanding of exposed population characteristics, their knowledge and risk perception may help delineate educational and communication policies, key parameters for disaster risk reduction. However, some drawbacks need attention to improve the paper and major reviews are required before publication. The main points in this review are: (i) more detailed method explanation; (ii) providing of the applied questionnaires, the score system, and the raw data; and (iii) reviewing of figures, especially those from results section.
Citation: https://doi.org/10.5194/egusphere-2025-2535-RC2
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