Adaptation and psychometric evaluation of the Natural Disasters Picture System (NDPS) to the Spanish population.

Introduction: Climate change is causing an increase in natural disasters and extreme weather events. This threat is impacting the mental health of those who experience it. However, empirical research in the Spanish context is limited by the lack of culturally adapted tools. Methods: In this study, we have adapted and validated with a Spanish sample composed by 73 participants the Natural Disasters Picture System (NDPS). The methodology incorporated Exploratory Factor Analysis (EFA), Mixed Linear Models (MLM) with intercepts for subjects and stimuli, and predictive classification using Machine Learning (Random Forest). Results: The results demonstrated the cross-cultural robustness of the original four clusters ("Frightening," "Desolation," "Neutral" and "Pleasant/Aesthetic"). Additionally, we identified a unidimensional latent factor and a significant perceptual overlap between "Frightening" (fear) and "Desolation" (sadness) in the Machine Learning Model. Discussion: The NDPS provides a set of visual stimuli that can be used to investigate risk perception and the elicitation of emotions. Despite the appropriate distribution of commonalities and the accuracy of MLMs, that support the instrument's properties, we acknowledge the possible limitation sample.