Depression level estimation during covid 19
Description
This Dataset presents data for the estimation of depression level estimation based in factor psychological and life experiences during and after pandemic Covid-19. The data contains 31 attributes and 2953 records, the records are labelled with the class variable Normal and Anormal that indicate the respective level of depression. 33% of the data was generated synthetically using the Weka tool and the SMOTE filter, 66% of the data was collected directly from users through a web platform. This data can be used to generate intelligent computational tools to identify the depression level of an individual and to build recommender systems that monitor depression levels.
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This paper presents data for the estimation of depression level estimation based in psychological factors and life experiences both during and after pandemic Covid-19. The data contains 31 attributes and 2953 records, the records are labelled with the class variable Normal and Anormal that indicate the correspondent level of depression. 33% of the data was generated synthetically using the Weka tool and the SMOTE filter, 66% of the data was collected directly from users through a web platform. This data can be used to create intelligent computational tools to identify the depression level of an individual and to build recommendation systems that monitor depression levels.