Social Network Addiction: A Structural Equation Modelling

• Autores: Marqués-Molias, Luis, Villalba-Condori, Klinge Orlando, Peñaflor, Renato, Gallardo-Echenique, Eliana
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Universidad Peruana de Ciencias Aplicadas
• Repositorio: UPC-Institucional
• Lenguaje: español
• OAI Identifier: oai:repositorioacademico.upc.edu.pe:10757/675719
• Enlace del recurso: https://doi.org/10.1007/978-981-99-7210-4_2; http://hdl.handle.net/10757/675719
• Nivel de acceso: acceso embargado
• Materia: Higher education; Social media addiction; Validation study; https://purl.org/pe-repo/ocde/ford#3.00.00

One of the most common challenges for researchers is how to determine the reliability and validity of the data collection instruments used in scientific research. These instruments must be individually reliable and valid in order to ensure that a particular characteristic is estimated correctly. There is growing interest in improving the quality and use of data collection instruments for scientific research. In a recent study, confirmatory factor analysis was used in a structural equation modelling approach to validate the “Cuestionario de Adicción a Redes Sociales” (Social Network Addiction Questionnaire, ARS). As a tool for validating the ARS, structural equation modelling provided explicit estimates of error variance parameters, allowing results to be established with greater certainty.