Minding the gap: The moderating role of education between subjective health and social life perception and Internet use time

Lidando com a lacuna: O papel moderador da educação na relação entre a perceção subjetiva da saúde e da vida social e o tempo de utilização da Internet

Ângela Leite , João Alves , Hélder Fernando Pedrosa e Sousa , Maria Alzira Pimenta Dinis

Suma Psicológica, (2023), 30(1), pp. 1-11.

Received 21 May 2022
Accept 26 October 2022

https://doi.org/10.14349/sumapsi.2023.v30.n1.1

Resumen

Introdução: O vício da Internet traduz-se numa utilização intensa e frequente. Existe uma lacuna na literatura sobre o desconhecimento dos preditores do uso problemático da Internet (PIU) do tempo de utilização da Internet (IUT). Objetivo: Identificar as variáveis sociodemográficas/psicológicas que contribuem e moderam o IUT. Participantes: 1270 participantes da European Social Survey (EES), Round 8. Instrumentos: Variáveis ESS ​​que avaliam a utilização da Internet (IU), perceção de saúde, bem-estar, vida social e variáveis sociodemográficas, subjacentes ao construto. Resultados: Idade, escolaridade, fontes de renda familiar, atividades sociais em comparação com outras da mesma idade e saúde geral subjetiva explicam IU por dia e idade, anos de escolaridade, domicílio, convívio social com outras pessoas e quem para discutir assuntos íntimos explicam IU por semana. A escolaridade mostrou-se um moderador significativo na relação entre saúde geral subjetiva e IU por semana; e na relação entre encontro social com outras pessoas e IU por dia. Discussão: IU desadaptativa, quando a perceção de saúde é pior, e IU adaptativa, quando a perceção de vida social é melhor, dependem da escolaridade. Conclusões: Os resultados sugerem o estudo do IUT de acordo com o nível educacional, pois o que pode ser um PIU num nível educacional pode não ser noutro.


Palavras chave:
Utilização da Internet (IU), bem-estar, percepção subjectiva de saúde

Abstract

Introduction: Internet addiction results in intense and frequent use. There is a gap in the literature in relation to the unawareness of problematic Internet use (PIU) in predicting Internet use time (IUT). Objective: To identify sociodemographic/psychological variables contributing and moderating IUT. Participants: 1,270 participants of the European Social Survey (EES), Round 8. Instruments: EES variables assessing Internet use (IU), health perception, well-being, social life, and sociodemographic variables, underlying the construct. Results: Age, education, sources of household income, social activities compared to others of the same age and subjective general health explain IU per day; and age, years of education, domicile and socially meeting with other people with whom to discuss intimate matters explain IU per week. Education was found to be a significant moderator in the relationship between subjective general health and IU per week; and in the relationship between socially meeting with other people and IU per day. Discussion: Maladaptive IU, when the perception of health is worse, and adaptive IU, when the perception of social life is better, are both suggested, depending on education. Conclusions: These findings point to the need to study IUT involving educational level, keeping in mind that what may be PIU at one educational level may not be the case at another.


Keywords:
Internet use (IU), well-being, subjective general health

Artículo Completo
Bibliografía

Aboujaoude, E. (2010). Problematic Internet use: An overview. World Psychiatry: Official Journal of the World Psychiatric Association (WPA), 9(2), 85-90. https://doi.org/10.1002/j.2051-5545.2010.tb00278.x

Amichai-Hamburger, Y., & Hayat, Z. (2011). The impact of the Internet on the social lives of users: A representative sample from 13 countries. Computers in Human Behavior, 27(1), 585-589. https://doi.org/10.1016/j.chb.2010.10.009

Bach, R. L., & Wenz, A. (2020). Studying health-related Internet and mobile device use using web logs and smartphone records. PLOS ONE, 15(6), e0234663-e0234663. https://doi.org/10.1371/journal.pone.0234663

Bargh, J. A., & McKenna, K. Y. A. (2004). The Internet and social life. Annual Review of Psychology, 55(1), 573-590. https://doi.org/10.1146/annurev.psych.55.090902.141922

Bessière, K., Pressman, S., Kiesler, S., & Kraut, R. (2010). Effects of Internet use on health and depression: A longitudinal study. Journal of Medical Internet Research, 12(1), e6. https://doi.org/10.2196/jmir.1149

Bozoglan, B., Demirer, V., & Sahin, I. (2013). Loneliness, self-esteem, and life satisfaction as predictors of Internet addiction: A cross-sectional study among Turkish university students. Scandinavian Journal of Psychology, 54(4), 313-319. https://doi.org/10.1111/sjop.12049

Büchi, M., Festic, N., & Latzer, M. (2018). How social well-being is affected by digital inequalities. International Journal of Communication, 12, 3686-3706. https://ijoc.org/index.php/ijoc/article/view/8780/2450

Castellacci, F., & Tveito, V. (2018). Internet use and well-being: A survey and a theoretical framework. Research Policy, 47(1), 308-325. https://doi.org/10.1016/j.respol.2017.11.007

Chak, K., & Leung, L. (2004). Shyness and locus of control as predictors of Internet addiction and Internet use. Cyberpsychology & Behavior, 7(5), 559-570. https://doi.org/10.1089/cpb.2004.7.559

Chang, F.-C., Chiu, C.-H., Lee, C.-M., Chen, P.-H., & Miao, N.-F. (2014). Predictors of the initiation and persistence of Internet addiction among adolescents in Taiwan. Addictive Behaviors, 39(10), 1434-1440. https://doi.org/10.1016/j.addbeh.2014.05.010

Cheung, J. C.-S., Chan, K. H.-W., Lui, Y.-W., Tsui, M.-S., & Chan, C. (2018). Psychological Well-Being and Adolescents’ Internet Addiction: A School-Based Cross-Sectional Study in Hong Kong. Child and Adolescent Social Work Journal, 35(5), 477-487. https://doi.org/10.1007/s10560-018-0543-7

Chopik, W. J. (2016). The benefits of social technology use among older adults are mediated by reduced loneliness. Cyberpsychology, Behavior and Social Networking, 19(9), 551-556. https://doi.org/10.1089/cyber.2016.0151

de-Mateo-Silleras, B., Camina-Martín, M. A., Cartujo-Redondo, A., Carreño-Enciso, L., de-la-Cruz-Marcos, S., & Redondo-del-Río, P. (2019). Health perception according to the lifestyle of university students. Journal of Community Health, 44(1), 74-80. https://doi.org/10.1007/s10900-018-0555-4

Demirci, Ş., Uğurluoğlu, Ö., Konca, M., & Çakmak, C. (2021). Socio-demographic characteristics affect health information seeking on the Internet in Turkey. Health Information & Libraries Journal, 38(4), 304-312. https://doi.org/10.1111/hir.12358

European Social Survey. (2016). ESS Round 8 Source Questionnaire. https://www.europeansocialsurvey.org/data/download.html?r=8

Fernandes, B., Maia, B. R., & Pontes, H. M. (2019). Internet addiction or problematic Internet use? Which term should be used? Psicologia USP, 30, 1-8. https://doi.org/10.1590/0103-6564E190020

Gleave, E., Welser, H. T., Lento, T. M., & Smith, M. A. (2009). A conceptual and operational definition of ‘social role’ in online community. 2009 42nd Hawaii International Conference on System Sciences, 1-11. https://doi.org/10.1109/HICSS.2009.6

Gmel, G., Notari, L., & Schneider, E. (2017). Is there an Internet addiction and what distinguishes it from problematic Internet use – An attempt to provide working definitions. Addiction Switzerland. https://bit.ly/413HydL

Heo, J., Chun, S., Lee, S., Lee, K. H., & Kim, J. (2015). Internet use and well-being in older adults. Cyberpsychology, Behavior, and Social Networking, 18(5), 268-272. https://doi.org/10.1089/cyber.2014.0549

Hunsaker, A., Hargittai, E., & Micheli, M. (2021). Relationship between Internet use and change in health status: Panel study of young adults. Journal of Medical Internet Research, 23(1), e22051. https://doi.org/10.2196/22051

Idler, E. L., & Benyamini, Y. (1997). Self-rated health and mortality: A review of twenty-seven community studies. Journal of Health and Social Behavior, 38(1), 21-37.

Ingold, T. (2016). Evolution and social life (1 ed.). Routledge.

Johnson, P. O., & Fay, L. C. (1950). The Johnson-Neyman technique, its theory and application. Psychometrika, 15(4), 349-367. https://doi.org/10.1007/BF02288864

Kearns, A., & Whitley, E. (2019). Associations of Internet access with social integration, wellbeing and physical activity among adults in deprived communities: Evidence from a household survey. BMC Public Health, 19(1), 860-860. https://doi.org/10.1186/s12889-019-7199-x

Kurniasanti, K. S., Assandi, P., Ismail, R. I., Nasrun, M. W. S., & Wiguna, T. (2019). Internet addiction: A new addiction? Medical Journal of Indonesia, 28(1), 82-91. https://doi.org/10.13181/mji.v28i1.2752

Lam, S. S. M., Jivraj, S., & Scholes, S. (2020). Exploring the relationship between Internet use and mental health among older adults in england: Longitudinal observational study. Journal of Medical Internet Research, 22(7), e15683. https://doi.org/10.2196/15683

Langarizadeh, M., Naghipour, M., Tabatabaei, S. M., Mirzaei, A., & Vaghar, M. E. (2018). Prediction of Internet addiction based on information literacy among students of Iran University of Medical Sciences. Electronic Physician, 10(2), 6333-6340. https://doi.org/10.19082/6333

Leung, H., Pakpour, A. H., Strong, C., Lin, Y.-C., Tsai, M.-C., Griffiths, M. D., Lin, C.-Y., & Chen, I. H. (2020). Measurement invariance across young adults from Hong Kong and Taiwan among three Internet-related addiction scales: Bergen Social Media Addiction Scale (BSMAS), Smartphone Application-Based Addiction Scale (SABAS), and Internet Gaming Disorder Scale-Short Form (IGDS-SF9) (Study Part A). Addictive Behaviors, 101, 105969. https://doi.org/10.1016/j.addbeh.2019.04.027

Ojo, A. O., Arasanmi, C. N., Raman, M., & Tan, C. N.-L. (2019). Ability, motivation, opportunity and sociodemographic determinants of Internet usage in Malaysia. Information Development, 35(5), 819-830. https://doi.org/10.1177/0266666918804859

Papacharissi, Z., & Rubin, A. M. (2000). Predictors of internet use. Journal of Broadcasting & Electronic Media, 44(2), 175-196. https://doi.org/10.1207/s15506878jobem4402_2

Perrig-Chiello, P., & Darbellay, F. (2004). La santé et le bien-être: Aspects différentiels et développementaux. In P. Perrig-Chiello & H. B. Stähelin (Eds.), Réalités Sociales (pp. 1-15).

Pestana, M. H., & Gageiro, J. N. (2014). Análise de dados para ciências sociais – A complementaridade do SPSS [Data Analysis for Social Sciences – The Complementarity of SPSS]. Edições Sílabo.

Pordata (2020). Private households with a computer, with Internet access and with broadband Internet access (%). https://bit.ly/3Z1iuSL

Reading, R. (2009). Closing the gap in a generation: Health equity through action on the social determinants of health. Child: Care, Health and Development, 35(2), 285-286. https://doi.org/10.1111/j.1365-2214.2008.00935_10.x

Ryan, C., & Lewis, J. M. (2017). Computer and Internet use in the United States: 2015. American Community Survey Reports, ACS-37, U.S. Census Bureau. https://www.census.gov/content/dam/Census/library/publications/2017/acs/acs-37.pdf

Ryff, C. D. (1995). Psychological well-being in adult life. Current Directions in Psychological Science, 4(4), 99-104. https://doi.org/10.1111/1467-8721.ep10772395

Schehl, B., Leukel, J., & Sugumaran, V. (2019). Understanding differentiated Internet use in older adults: A study of informational, social, and instrumental online activities. Computers in Human Behavior, 97, 222-230. https://doi.org/10.1016/j.chb.2019.03.031

Shek, D. T. L., Sun, R. C. F., & Yu, L. (2013). Internet addiction. In D. W. Pfaff (Ed.), Neuroscience in the 21st Century. (pp. 2775-2811). Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1997-6_108

Shen, W., Hua, M., Wang, M., Yuan, Y., Shao, M., & Zhao, Y. (2023). Anhedonia mediates the link between problematic Internet use and psychological well-being. Current Psychology. https://doi.org/10.1007/s12144-021-01575-0

Spada, M. M. (2014). An overview of problematic Internet use. Addictive Behaviors, 39(1), 3-6. https://doi.org/10.1016/j.addbeh.2013.09.007

Tirado-Morueta, R., Aguaded-Gómez, J. I., Ortíz-Sobrino, M. Á., Rodríguez-Martín, A., & Álvarez-Arregui, E. (2020). Determinants of social gratifications obtained by older adults moderated by public supports for Internet access in Spain. Telematics and Informatics, 49, 101363-101363. https://doi.org/10.1016/j.tele.2020.101363

Tokunaga, R. S. (2015). Perspectives on Internet addiction, problematic Internet use, and deficient self-regulation: Contributions of communication research. Annals of the International Communication Association, 39(1), 131-161. https://doi.org/10.1080/23808985.2015.11679174

Tyler, M., De George-Walker, L., & Simic, V. (2020). Motivation matters: Older adults and information communication technologies. Studies in the Education of Adults, 52(2), 175-194. https://doi.org/10.1080/02660830.2020.1731058

Valarezo, Á., Pérez-Amaral, T., Garín-Muñoz, T., Herguera García, I., & López, R. (2018). Drivers and barriers to cross-border e-commerce: Evidence from Spanish individual behavior. Telecommunications Policy, 42(6), 464-473. https://doi.org/10.1016/j.telpol.2018.03.006

Wang, L., Luo, J., Bai, Y., Kong, J., Luo, J., Gao, W., & Sun, X. (2013). Internet addiction of adolescents in China: Prevalence, predictors, and association with well-being. Addiction Research & Theory, 21(1), 62-69. https://doi.org/10.3109/16066359.2012.690053

Wangberg, S. C., Andreassen, H. K., Prokosch, H.-U., Santana, S. M. V., Sørensen, T., & Chronaki, C. E. (2008). Relations between Internet use, socio-economic status (SES), social support and subjective health. Health Promotion International, 23(1), 70-77. https://doi.org/10.1093/heapro/dam039

Worsley, J. D., Mansfield, R., & Corcoran, R. (2018). Attachment anxiety and problematic social media use: The mediating role of well-being. Cyberpsychology, Behavior, and Social Networking, 21(9), 563-568. https://doi.org/10.1089/cyber.2017.0555

Zhou, N., Cao, H., Li, X., Zhang, J., Yao, Y., Geng, X., Lin, X., Hou, S., Liu, F., Chen, X., & Fang, X. (2018). Internet addiction, problematic Internet use, nonproblematic Internet use among Chinese adolescents: Individual, parental, peer, and sociodemographic correlates. Psychology of Addictive Behaviors, 32(3), 365-372. https://doi.org/10.1037/adb0000358

PDF