Social Network Addiction: A Structural Equation Modelling

Luis Marqués-Molias, Klinge Orlando Villalba-Condori, Renato Peñaflor, Eliana Gallardo-Echenique

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationCommunication and Applied Technologies - Proceedings of ICOMTA 2023
EditorsDaniel Barredo Ibáñez, Laura M. Castro, Araceli Espinosa, Iván Puentes-Rivera, Paulo Carlos López-López
PublisherSpringer Science and Business Media Deutschland GmbH
Pages13-23
Number of pages11
ISBN (Print)9789819977536
DOIs
StatePublished - 2024
EventInternational Conference on Communication and Applied Technologies, ICOMTA 2023 - Puebla, Mexico
Duration: 6 Sep 20238 Sep 2023

Publication series

NameSmart Innovation, Systems and Technologies
Volume375
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

ConferenceInternational Conference on Communication and Applied Technologies, ICOMTA 2023
Country/TerritoryMexico
CityPuebla
Period6/09/238/09/23

Keywords

  • Higher education
  • Social media addiction
  • Validation study

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