•  
  •  
 

DOI

10.22550/REP81-2-2023-06

Abstract

Social network addiction in young people has been extensively studied and associated with multiple factors. Among the scales de­signed to measure this, the 24-item version of the Social Network Addiction Questionnaire (SNAQ) is one of the most widely used. This study analyses the psychometric properties of the Spanish version adapted to undergradu­ates. The content and construct validity of the scale was explored using the Rasch model and a confirmatory factor analysis. The data cate­gorisation structure, construct dimensionality, model fit, subject and item reliability, Wright Map structure, and differential item function­ing (DIF) were specifically analysed. 1,809 students from 24 Spanish universities partic­ipated. The results indicate that the SNAQ presents good reliability and dimensionality, and a good model fit; however, elements in need of improvement are appreciated mainly in the proposed Likert scale, in the develop­ment of new items that measure the extremes of addiction to social network sites and in the wording of one item. With respect to fac­tor analysis, three factors were obtained thatcoincide with the original construct. With the improvements that have been observed through validation, the questionnaire could confidently be used to measure the construct in the university population. The instrument fills an important gap in the identification of addictive behaviours in the use of social net­works, which could lead to a subsequent inter­vention involving undergraduates.

Please, cite this article as follows: Suárez-Perdomo, A., Garcés-Delgado, Y., García-Álvarez, E. y Ruiz-Alfonso, Z. (2023). Propiedades psicométricas del cuestionario de adicción a las redes sociales (ARS) a población universitaria | Psychometric properties of the Social Network Addiction Questionnaire (SNAQ) for undergraduates. Revista Española de Pedagogía, 81 (285), 361-379. 10.22550/REP81-2-2023-06

Referencias | References

American Psychiatric Association (2008). DSm-iv-tr - Breviario: criterios diagnósticos [DSm-iv-tr - Brief: Diagnostic criteria]. Elsevier España. https://books.google.es/books/about/DSM_IV_TR.html?hl=es&id=vA3NmKjhFAsC&redir_esc=y

Andreassen, C. S. (2015). Online social network site addiction: A comprehensive review. Cur­rent Addiction Reports, 2 (2), 175-184. 10.1007/s40429-015-0056-9

Andreassen, C. S., Torsheim, T., & Pallesen, S. (2014). Predictors of use of social network sites at work-a specific type of cyberloafing. Journal of Computer-Mediated Communication, 19 (4), 906-921. 10.1111/jcc4.12085

Andrich, D. (1988). Rasch Models for measure­ment: SAGE Publications. Sage Publications.

Arquero, J. L., & Romero-Frías, E. (2013). Using social network sites in higher education: An experience in business studies. Innovations in Education and Teaching International, 50 (3), 238-249. 10.1080/14703297.2012.760772

Austin-McCain, M. (2017). An examination of the as­sociation of social media use with the satisfaction with daily routines and healthy lifestyle habits for undergraduate and graduate students. The Open Journal of Occupational Therapy, 5 (4), 6. 10.15453/2168-6408.1327

Azizi, S. M., Soroush, A., & Khatony, A. (2019). The relationship between social networking addiction and academic performance in Iranian students of medical sciences: A cross-sectional study. BMC psychology, 7 (1), 1-8. 10.1186/s40359-019-0305-0

Azpilicueta, A. E., Cupani, M., Ghío, B., Morán, V. E., & Garrido, S. J. (2019). Adaptac­ión mediante el modelo de Rasch de tres medidas para estimar la decisión e inde­cisión de carrera y la ansiedad decisional [Adaptation using the Rasch model of three measures to estimate career decision and inde­cision and anxiety]. Perspectivas en Psicología, 16 (1), 26-37. http://rpsico.mdp.edu.ar/handle/123456789/1108

Baker, D. A., & Algorta, G. P. (2016). The relation­ship between online social networking and de­pression: A systematic review of quantitative studies. Cyberpsychology, Behavior, and So­cial Networking, 19 (11), 638-648. 10.1089/cyber.2016.0206

Balakrishnan, V., & Shamim, A. (2013). Malaysian Facebookers: Motives and addictive behaviours unraveled. Computers in Human Behavior, 29 (4), 1342-1349. 10.1016/j.chb.2013.01.010

Banjanin, N., Banjanin, N., Dimitrijevic, I., & Pantic, I. (2015). Relationship between inter­net use and depression: Focus on physiological mood oscillations, social networking and online addictive behavior. Computers in Human Be­havior, 43, 308-312. 10.1016/j.chb.2014.11.013

Bond, T. G., & Fox, C. M. (2012). Why measure­ment is fundamental. Applying the Rasch Mod­el: Fundamental Measurement in the Human Sciences. Routledge.

Buglass, S. L., Binder, J. F., Betts, L. R., & Underwood, J. D. (2017). Motivators of online vulnera­bility: The impact of social network site use and FOMO. Computers in Human Behav­ior, 66, 248-255. 10.1016/j.chb.2016.09.055

Busalim, A. H., Masrom, M., & Zakaria, W. N. B. W. (2019). The impact of Facebook addiction and self-esteem on students’ academic per­formance: A multi-group analysis. Comput­ers & Education, 142, 103651. 10.1016/j.compedu.2019.103651

Çam, E., & Isbulan, O. (2012). A new addiction for teacher candidates: Social networks. Turkish Online Journal of Educational Technology-TO­JET, 11 (3), 14-19. https://www.learntechlib.org/p/55773/

Cao, X., Masood, A., Luqman, A., & Ali, A. (2018). Ex­cessive use of mobile social networking sites and poor academic performance: Antecedents and consequences from stressor-strain-outcome per­spective. Computers in Human Behavior, 85, 163- 174. 10.1016/j.chb.2018.03.023

Charlton, J. P., & Danforth, I. D. (2007). Distin­guishing addiction and high engagement in the context of online game playing. Computers in human behavior, 23 (3), 1531-1548. 10.1016/j.chb.2005.07.002

Escurra, M., & Salas, E. (2014). Construcción y vali­dación del cuestionario de adicción a redes sociales (ARS) [Construction and validation of the ques­tionnairy of Social Networking Addiction (SNA)]. Liberabit. Revista de Psicología, 20 (1), 73-91. http://www.scielo.org.pe/pdf/liber/v20n1/a07v20n1.pdf

Fioravanti, G., Dèttore, D., & Casale, S. (2012). Ado-lescent Internet addiction: Testing the asso­ciation between self-esteem, the perception of Internet attributes, and preference for online social interactions. Cyberpsychology, Behavior, and Social Networking, 15 (6), 318-323. 10.1089/cyber.2011.0358

Fossum, I. N., Nordnes, L. T., Storemark, S. S., Bjorvatn, B., & Pallesen, S. (2014). The asso­ciation between use of electronic media in bed before going to sleep and insomnia symptoms, daytime sleepiness, morningness, and chrono­type. Behavioral Sleep Medicine, 12 (5), 343-357. 10.1080/15402002.2013.819468

García-Álvarez, E. (2015). Relaciones y capaci­dades interorganizativas: un enfoque de Supply Chain Management (SCM) en red [Interorga-nizational relationships and capabilities: a net­worked approach to Supply Chain Management (SCM)] [Doctoral dissertation, Universidad de La Laguna]. RIULL Repositorio Institucional. http://riull.ull.es/xmlui/handle/915/2398

Gómez, M., Roses, S., & Farias, P. (2012). El uso académico de las redes sociales en universitarios [The academic use of social networks among university students]. Comunicar, 38 (19), 131- 138. 10.3916/C38-2012-03-04

Jacobsen, W. C., & Forste, R. (2011). The wired generation: Academic and social outcomes of electronic media use among university stu­dents. Cyberpsychology, Behavior, and So­cial Networking, 14 (5), 275-280. 10.1089/cyber.2010.0135

Kong, Q., Lai-Ku, K. Y., Deng, L., & Yan-Au, A. C. (2021). Motivation and perception of Hong Kong university students about social me­dia news. Comunicar, 29 (67). 10.3916/C67-2021-03

Kuss, D. J., & Griffiths, M. D. (2017). Social net­working sites and addiction: Ten lessons learned. International journal of environmen­tal research and public health, 14 (3), 311. 10.3390/ijerph14030311

Linacre, J. M. (2002). Optimizing rating scale cate-gory effectiveness. Journal of Applied Mea-surement, 3 (1), 85-106. https://pubmed.ncbi.nlm.nih.gov/11997586/

Linacre, J. M. (2009). A user’s guide to Winsteps-min­istep: Rasch-model computer programs. Pro­gram manual 3.68. 0. IL. https://ia800607.us.archive.org/23/items/B-001-003-730/winsteps.pdf

Linacre, J. M. (2015). A user’s guide to winsteps min­istep: Rasch-model computer programs. https://www.scienceopen.com/document?vid=9923a1a4-3164-4056-b230-bada789f854e

Linacre, J. M. (2018). A user’s guide to Winsteps 3.70. 0: Rasch-model computer programs. Winsteps. https://www.researchgate.net/publication/238169941_A_User''s_Guide_to_Winsteps_Rasch-Model_Computer_Program

Liu, C., & Ma, J. (2020). Social media addiction and burnout: The mediating roles of envy and social media use anxiety. Current Psychology, 39 (6), 1883- 1891. 10.1007/s12144-018-9998-0

Mushtaq, A. J., & Benraghda, A. (2018). The effects of social media on the undergraduate students’ academic performances. Library Philosophy and Practice, 4 (1). https://digitalcommons.unl.edu/libphilprac/1779/

O’Keeffe, G. S., & Clarke-Pearson, K. (2011). The impact of social media on children, adolescents, and families. Pediatrics, 127 (4), 800-804. 10.1542/peds.2011-0054

Oreja-Rodríguez, J. R. (2015). Mediciones, posicio­namientos y diagnósticos competitivos [Mea-surements, positioning and competitive diag­nostics]. Fundación FYDE-CajaCanarias.

Organic Law 3/2018, of December 5, on Person­al Data Protection and guarantee of digital rights. Spanish Official State Gazette, 294. https://www.boe.es/eli/es/lo/2018/12/05/3/con

Pertegal-Vega, M. Á., Oliva-Delgado, A., & Rodríguez-Meirinhos, A. (2019). Systematic re­view of the current state of research on Online Social Networks: Taxonomy on experience of use. Comunicar, 27 (60), 81-91. 10.3916/C60-2019-08

Rasch, G. (1980). Probabilistic models for intelli­gence and attainment tests (expanded edition). University of Chicago Press.

Seabrook, E. M., Kern, M. L., & Rickard, N. S. (2016). Social networking sites, depression, and anxiety: A systematic review. JMIR mental health, 3 (4), e5842. 10.2196/mental.5842

Sekaran, U. (2000). Research Methods for Business: A Skill-building Approach. John Wiley & Sons.

Suárez-Perdomo, A., Ruiz-Alfonso, Z., & Garcés-Delgado, Y. (2022). Profiles of under­graduates’ networks addiction: Difference in academic procrastination and performance. Computers & Education, 181, 104459. 10.1016/j.compedu.2022.104459

Turel, O., & Serenko, A. (2012). The benefits and dangers of enjoyment with social network­ing websites. European Journal of Informa­tion Systems, 21 (5), 512-528. 10.1057/ejis.2012.1

Wilson, K., Fornasier, S., & White, K. M. (2010). Psychological predictors of young adults’ use of social networking sites. Cyberpsychology, Be­havior, and Social Networking, 13 (2), 173-177. 10.1089/cyber.2009.0094

Winsteps (n. d.). Winsteps. https://www.winsteps.com/winsteps.htm

Wolniczak, I., Cáceres-DelAguila, J. A., Palma- Ardiles, G., Arroyo, K. J., Solís-Visscher, R., Paredes-Yauri, S., Mego-Aquije, K., & Bernabe- Ortiz, A. (2013). Association between Face­book dependence and poor sleep quality: a study in a sample of undergraduate students in Peru. PloS One, 8 (3), e59087. 10.1371/journal.pone.0059087

Wright, B. D. (2002). Number of person or item strata: (4*Separation + 1)/3. Rasch Measure­ment Transactions, 16, 888. https://www.rasch.org/rmt/rmt163f.htm

Wright, B. D., & Stone, M. H. (2003). Five steps to science: Observing, scoring, measuring, analyzing, and applying. Rasch Measurement Transactions, 17 (1), 912-913. https://www.rasch.org/rmt/rmt171j.htm

Xanidis, N., & Brignell, C. M. (2016). The associ­ation between the use of social network sites, sleep quality and cognitive function during the day. Computers in Human Behavior, 55, 121- 126. 10.1016/j.chb.2015.09.004

Zamora Araya, J. A., Smith Castro, V., Montero Rojas, E., & Moreira Mora, T. E. (2018). Ad­vantages of the Rasch model for analysis and interpretation of attitudes: The case of the benevolent sexism subscale. Revista Evaluar, 18 (3). 10.35670/1667-4545.v18.n3.22201

Author Biography

Arminda Suárez-Perdomo holds a doctorate in Developmental Psychology and is a Assistant Professor at the De­partment of Didactics and Educational Research at the Universidad de La La­guna. Her lines of research focus on the evaluation of programmes to promote positive parenting in virtual environ­ments for experiential learning, analy­sis of digital parenting skills, as well as problematic internet use among under­graduates and its possible influence on the behaviour of procrastination and ed­ucational goals.

https://orcid.org/0000-0002-6755-5284

Yaritza Garcés-Delgado holds a doctorate in Education which received the qualification of international doctor­ate and is an Assistant Professor in the Area for Research and Diagnosis Methods in Education at the Department of Di­dactics and Educational Research at the Universidad de La Laguna (Spain). She is a research associate in the Grupo Uni­versitario de Formación y Orientación In­tegrada (GUFOI) (University Group for Integrated Training and Guidance) and the research and innovation group EDUL­LAB (Laboratorio de Educación y Nuevas Tecnologías) (Education and New Tech­nologies Laboratory), both officially recog­nised research groups at the Universidad de La Laguna. She is a member of and the regional representative for the Asociación Interuniversitaria de Investigación Ped­agógica (AIDIPE) (Interuniversity Associ­ation for Pedagogical Research) in the Ca­nary Islands. Her lines of research focus on the development of methods and lines of research applied to education, academic and career guidance for students and the application of technologies to education.

https://orcid.org/0000-0003-3471-1014

Edgar García-Álvarez holds a doctor­ate in Business Structure. He specialises in university management, knowledge transfer and business innovation. His areas of aca­demic knowledge are (1) business structure and administration, (2) statistical methodol­ogy based on the Rasch Model Measurement Theory (TMR) and (3) the agri-food sector. He is currently administrator of the Escue­la Politécnica Superior de Ingeniería (EPSI) at the Universidad de La Laguna and a lec­turer-tutor at the Universidad Nacional de Educación a Distancia (UNED).

https://orcid.org/0000-0003-3008-9571

Zuleica Ruiz-Alfonso holds a doc­torate from the Facultad de Ciencias de la Educación at the Universidad de Las Pal­mas de Gran Canaria. She is currently working as a postdoctoral researcher as part of the Juan de la Cierva-Incorpora­tion Programme at the Departamento de Didáctica e Investigación Educativa de la Universidad de La Laguna, funded by the Spanish Ministry of Science and Innova­tion. Her main line of research focuses on analysing how to improve student in­volvement and performance through var­iables capable of being modified, such as the effectiveness of teaching and passion for learning.

https://orcid.org/0000-0001-7090-0096

Licencia Creative Commons | Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Share

COinS

Palabras clave | Keywords

addiction, Rasch model, social networks, undergraduates