Social distance is one of the indicators of intergroup relations. It expresses the degree of intimacy, proximity or distance in relation to the members of specific social groups, making the concept an indirect form of referring to prejudice. The present study described in this article aims to evaluate the protocol for the use of an indirect measure of social distance, implemented by computers and specialized devices. We sought to assess the potential of the technique of virtual reality as a criterion for estimating social distance by comparing the results obtained in the virtual environment with the correlated measures obtained in a computer screen. This is an experimental study, developed to evaluate the pleasantness of four photographs and the registry of two classes of indirect measures. Social distance was chosen to evaluate the photographs and the response time was used to choose the estimate, in two modalities of data collection, one in a screen environment and the other in the virtual environment, in Brazil and Mozambique. A total of 150 university students participated in the study, 87 from Brazil and 61 from Mozambique. In the study, we show that the estimate for social distance is more associated with the response time than the attractiveness of the image, regardless of the country. When we introduce in the predictive models the variables sex and skin color of the individuals portrayed in the photographs, we note that the models obtained in the virtual environment present better indicators than those obtained in the screen, except for the predictive model for the evaluation of the distance of the Black woman portrait. The response time proved to be much more central in the model than the attractiveness of the image. In the screen environment, the increase in the image size was connected to the greater amount of time spent in decision-making while in the virtual environment the distancing from the image was connected to a greater amount of time spent making a decision. The country of origin had little influence over the final models. In conclusion, we may highlight that the effects of social distance, the response time and the attractiveness of the image were greater in the virtual environment, which inspires us to highlight the importance of using more sophisticated data collection procedures through the use of information technology.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.