Causal factors affecting the smartphone addiction of generation Z in Bangkok during the COVID-19 pandemic
Article Sidebar
Main Article Content
Abstract
The objectives of this research were to understand the smartphone addiction of Generation Z (Gen Z) in Bangkok, Thailand and investigate the causal factors in smartphone addiction among this sample group during the 2019 Coronavirus (COVID-19) pandemic. A sequential exploratory design was adopted in this study. In the qualitative phase, five Gen Z informants living in Bangkok and addicted to smartphones participated in interviews. In the quantitative phase, multistage sampling was employed for the sample selection, which consisted of 400 respondents who exhibited smartphone addiction and lived in Bangkok. The following instruments were used: 1) smartphone addiction scale: Thai short version, 2) the Thai version of the self-regulation scale, 3) the Thai multi-dimensional scale of perceived social support, 4) the new media literacy scale: Thai version, and 5) the Thai version of the Alabama parenting questionnaire short form. The Cronbach’s alpha coefficients equaled 0.87, 0.84, 0.89, 0.75, and 0.79, respectively. Structural equation modeling was used to analyze the data. The results revealed that the factors associated with smartphone addiction were personal factors, such as new media literacy and self-regulation, and environmental factors, such as social support and parenting style. Moreover, the hypothesized model was considered to be suitable for predicting smartphone addiction among Gen Z respondents based on the following statistics: Chi-square = 36.31, p = 0.07, df = 25, Chi-square/df = 1.45, SRMR = 0.03, RMSEA = 0.03, CFI = 1.00, and GFI = 1.00. New media literacy, perceived social support, and parenting significantly influenced self-regulation, which in turn influenced smartphone addiction. After considering R2, the prediction of smartphone addiction by causal factors and self-regulation were 94% and 46%, respectively. This study proposes the implementation of additional educational programs that focus on enhancing media literacy, fostering self-regulation, and encouraging social support. Moreover, these results may provide valuable information to support the creation of effective intervention approaches to facilitate clinical programs for addiction rehabilitation which promote healthier lifestyles as a means of regulating smartphone usage.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All rights reserved. Apart from citations for the purposes of research, private study, or criticism and review,no part of this publication may be reproduced, stored or transmitted in any other form without prior written permission by the publisher.
References
Administrative Strategy Division. (2021). Sathiti Krung Thep Maha Nakhon 2563 [Statistical profile of BMA 2020]. https://webportal.bangkok.go.th/public/user_files_editor/130/BMA%20STATISTIC/BMA_STAT_63.pdf [in Thai]
Ahmed, N. (2019). Generation Z’s smartphone and social media usage: A survey. Journalism and Mass Communication, 9(3), 101–122.
Akturk, U., & Budak, F. (2019). The correlation between the perceived social support of nursing students and smartphone addiction. International Journal of Caring Sciences, 12(3), 1825–1835.
Bae, S. M. (2015). The relationships between perceived parenting style, learning motivation, friendship satisfaction, and the addictive use of smartphones with elementary school students of South Korea: Using multivariate latent growth modeling. School Psychology International, 36(5), 513–531.
Bakar, M. F. A., Yusoff, S. H. M., Rahman, R. A., & Idris, N. S. (2021). The prevalence of smartphone addiction and its association with parenting styles among secondary school students in Kota Bharu, Kelantan. International Medical Journal, 28(5), 542–546.
Bentler, P. M. (1990). Comparative fit indexes in structural equation models. Psychological Bulletin, 107(2), 238–246.
Billieux, J. (2012). Problematic use of the mobile phone: A literature review and a pathways model. Current Psychiatry Reviews, 8(4), 299–307. https://doi.org/10.2174/157340012803520522
Budiarti, A., Sustrami, D., & Febriani, V. (2022). The correlation between parenting styles and smartphone addiction among primary school students in Indonesia. International Journal of Nursing and Midwifery Science, 6(1), 96–102.
Charoenwanit, S., & Soonthornchaiya, R. (2019). Development of smartphone addiction scale: Thai short version (SAA-SV-TH). Journal of Mental Health of Thailand, 27(1), 25–36. [in Thai]
Chen, D.-T., Wu, J., & Wang, Y.-M. (2011). Unpacking new media literacy. Journal on Systemics, Cybernetics and Informatics, 9(2), 84–88.
Ching, K. H., & Tak, L. M. (2017). The structural model in parenting style, attachment style, self-regulation, and self-esteem for smartphone addiction. IAFOR Journal of Psychology & the Behavioral Science, 3(1), 85–103.
Creswell, J. W., & Plano Clark, V. (2018). Designing and conducting mixed methods research (3rd ed.). Sage Publications.
Deonisius, R. F., Lestari, I., & Sarkadi, I. L. (2019). The effect of digital literacy to internet addiction. Jurnal EDUCATIO: Jurnal Pendidikan Indonesia, 5(2), 71–75.
Diehl, M., Semegon, A. B., & Schwarzer, R. (2006). Assessing attention control in goal pursuit: a component of dispositional self-regulation. Journal of Personality Assessment, 86(3), 306–317. http://dx.doi.org/10.1207/s15327752jpa8603_06
Elgar, F. J., Waschbusch, D. A., Dadds, M. R., & Sigvaldason, N. (2007). Development and validation of a short form of the Alabama parenting questionnaire. Journal of Child and Family Studies, 16, 243–259. https://doi.org/10.1007/s10826-006-9082-5
Fatkuriyah, L., & Sun-Mi, C. (2021). The relationship among parenting style, self-regulation, and smartphone addiction proneness in Indonesian junior high school students. Indonesian Journal of Nursing Practices, 5(1), 51–59.
Gentina, E. (2020). Generation Z in Asia: A research agenda. In E. Gentina & E. Parry (Eds.), The new generation Z in Asia: Dynamics, differences, digitalisation (pp. 3–19). Emerald Publishing Limited.
Gestsdottir, S., Bowers, E., von Eye, A., Napolitano, C. M., & Lerner, R. M. (2010). Intentional self regulation in middle adolescence: The emerging role of loss-based selection in positive youth development. Journal of Youth and Adolescence, 39, 764–782. https://doi.org/10.1007/s10964-010-9537-2
Ghosh, P. (2020). Smartphone addiction—A new disorder or just a hype. Clinical Psychiatry, 6(1), 66.
Gökçearslan, Ş., Mumcu, F. K., Haşlaman, T., & Çevik, Y. D. (2016). Modelling smartphone addiction: The role of smartphone usage, self-regulation, general self-efficacy and cyberloafing in university students. Computers in Human Behavior, 63, 639–649. https://doi.org/10.1016/j.chb.2016.05.091
Herrero, J., Torres, A., Vivas, P., & Urueña, A. (2019). Smartphone addiction and social support: A three-year longitudinal study. Psychosocial Intervention, 29(3), 111–118.
Hosen, I., al Mamun, F., Sikder, M. T., Abbasi, A. Z., Zou, L., Guo, T., & Mamun, M. A. (2021). Prevalence and associated factors of problematic smartphone use during the COVID-19 pandemic: A Bangladeshi study. Risk Management and Healthcare Policy, 14, 3797–3805. https://doi.org/10.2147/RMHP.S325126
Jessor, R. (2014). Problem behavior theory: A half-century of research on adolescent behavior and development. In R. M. Lerner, A. C. Petersen, R. K. Silbereisen, & J. Brooks-Gunn (Eds.), The developmental science of adolescence: History through autobiography (pp. 239–256). Psychology Press.
Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). The Guilford Press.
Koc, M., & Barut, E. (2016). Development and validation of new media literacy scale (NMLS) for university students. Computers in Human Behavior, 63, 834–843.
Konan, N., Durmuş, E., Ağıroğlu Bakır, A., & Türkoğlu, D. (2018). The relationship between smartphone addiction and perceived social support of university students’. International Online Journal of Educational Sciences, 10(5), 244–259.
Kwak, J. Y., Kim, J. Y., & Yoon, Y. W. (2018). Effect of parental neglect on smartphone addiction in adolescents in South Korea. Child Abuse & Neglect, 77, 75–84. https://doi.org/10.1016/j.chiabu.2017.12.008
Kwan, H. C., & Leung, M. T. (2015). The path model of parenting style, attachment style, self-regulation and smartphone addiction. Applied Psychology, 196–214. https://doi.org/10.1142/9789814723398_0011
Kwon, M., Kim, D. J., Cho, H., & Yang, S. (2013). The smartphone addiction scale: development and validation of a short version for adolescents. PLoS ONE, 8(2), e83558.
Lee, J., Moon, J., & Cho, B. (2015). The mediating role of self-regulation between digital literacy and learning outcomes in the digital textbook for middle school English. Educational Technology International, 16(1), 58–83.
Lin, T.-B., Li, J.-Y., Deng, F., & Lee, L. (2013). Understanding new media literacy: An explorative theoretical framework. Educational Technology & Society, 16(4), 160–170.
Miles, M., & Huberman, M. (1994). Qualitative data analysis: An expanded sourcebook. Sage.
Mo, P. K. H., Chan, V. W. Y., Chan, S. W., & Lau, J. T. F. (2018). The role of social support on emotion dysregulation and Internet addiction among Chinese adolescents: A structural equation model. Addictive Behaviors, 82, 86–93. https://doi.org/10.1016/j.addbeh.2018.01.027
Panova, T., & Carbonell, X. (2018). Is smartphone addiction really an addiction? Journal of Behavioral Addiction, 7(2), 252–259.
Perera, M. U., Gardner, L., & Peiris, A. (2016). Investigating the interrelationship between undergraduates’ digital literacy and self-regulated learning skills. Proceedings of the Thirty-Seventh International Conference on Information Systems, 11.
Radzi, C. W. J. B. W. M., Jenatabadi, H. S., & Hasbullah, M. B. (2015). Firm sustainability performance index modeling. Sustainability, 7(12), 16196–16212.
Shirzad, M., Dilmaghani, N. T. K., & Lafte, A. (2019). The role of media literacy in health literacy and internet addiction among female postgraduate students. Journal of Research and Health, 9(3), 254–260.
Statista Research Department. (2023, April 4). Share of smartphone users in Thailand in the 4th quarter of 2022, by age group. Statista. https://www.statista.com/statistics/1253908/thailand-share-of-smartphone-users-by-age/
Ting, C. H., & Chen, Y. Y. (2020). Chapter 8—Smartphone addiction. In C. A. Essau & P. H. Delfabbro (Eds.), Adolescent Addiction (2nd ed.) (pp. 215–240). Academic Press.
Tripathi, S. (2013). Do large agglomerations lead to economic growth? Evidence from urban India. Review of Urban and Regional Development Studies, 25(3), 176–200.
Van Deursen, A. J. A. M., Bolle, C. L., Hegner, S. M., & Kommers, P. A. M. (2015). Modeling habitual and addictive smartphone behavior: The role of smartphone usage types, emotional intelligence, social stress, self-regulation, age, and gender. Computers in Human Behavior, 45, 411-420.
Wacks, Y., & Weinstein, A. M. (2021). Excessive smartphone use is associated with health problems in adolescents and young adults. Frontiers in Psychiatry, 12, 669042. https://doi.org/10.3389/fpsyt.2021.669042
Wongpakaran, N., & Wongpakaran, T. (2012). A revised Thai multidimensional scale of perceived social support. The Spanish Journal of Psychology, 15(3), 1503–1509.
Yildiz, M. A. (2017). Emotion regulation strategies as predictors of internet addiction and smartphone addiction in adolescents. Journal of Educational Science & Psychology, 7(1), 66–78.
Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The multidimensional scale of perceived social support. Journal of Personality Assessment, 52(1), 30–41.
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2
Zimmerman, B. J. (2013). From cognitive modeling to self-regulation: A social cognitive career path. Educational Psychologist, 48(3), 135–147. http://dx.doi.org/10.1080/00461520.2013.794676