Social Media Addiction among Generation Z Smartphone Users: A Moderating Role for Subjective Well-being
Abstract
Purpose: This study aims to identify the factors that influence the social media behavior of Generation Z in the post-COVID era. A conceptual framework has now been constructed.
Methodology: The purpose of the standardized questionnaire was to collect primary data from Generation Z university students employing a non-probability, purposive sampling method. 841 people completed the questionnaire. The SmartPLS-SEM4.0.9.9 program was used to analyze the study model.
Results: It seems from the data that social stress, self-regulation, addictive smartphone use, and conduct related to social media use were important predictors of social media usage behavior. Furthermore, it was shown that the subjective well-being construct's moderation component lacked statistical significance.
Research limitations: The study lacks more generalizability, as it only includes data from a limited sample of Generation Z individuals from Bangladesh, specifically those residing in the Dhaka region.
Practical implications: By adding social stress and self-regulation, this study has advanced the body of current literature in addition to offering fresh perspectives and interpretations on how members of Generation Z use social media. In addition, this study aims to advance current understanding by categorizing key components that may promote the emergence of addictive behaviors associated with social media and smartphone use. Besides, by designing targeted lesson plans and interventions, the study's findings may help students become more self-reliant. Institutions that support social stress management and responsible technology use can assist students in striking a balance between their personal and academic life.
Originality: This method will help to better understand how Gen Z uses social media and how addictive smartphone use and social media usage habits affect subjective well-being.
Keywords: Generation Z; Social stress; Self-regulation; Addictive smartphone use; Social media usage behavior; Subjective well-being
Acknowledgements: The author receives the Jahangirnagar University research project aid FY 2023-2024 to complete this study. The author acknowledges the anonymous reviewers for their valuable comments and for all the support administrators provide in publishing procedures. The author also acknowledges the anonymous respondents who provided feedback on the questionnaire survey.
DOI: https://doi.org/10.58869/EJABM10(2)/07
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Abbasi, G. A., Jagaveeran, M., Goh, Y.-N., & Tariq, B. (2021). The impact of type of content use on smartphone addiction and academic performance: Physical activity as moderator. Technology in Society, 64, 101521. doi: https://doi.org/10.1016/j.techsoc.2020.101521
Andreassen, C. S., Griffiths, M. D., Hetland, J., & Pallesen, S. (2012). Development of a work addiction scale. Scandinavian journal of psychology, 53(3), 265-272.
Asmundson, G. J. G., & Taylor, S. (2020). Coronaphobia: Fear and the 2019-nCoV outbreak. J Anxiety Disord, 70, 102196. doi: 10.1016/j.janxdis.2020.102196
Bae, S.-M. (2019). The relationship between smartphone use for communication, social capital, and subjective well-being in Korean adolescents: Verification using multiple latent growth modeling. Children and Youth Services Review, 96, 93-99. doi: https://doi.org/10.1016/j.childyouth.2018.11.032
Bandura, A. (1982). The assessment and predictive generality of self-percepts of efficacy. Journal of Behavior Therapy and Experimental Psychiatry, 13(3), 195-199. doi: https://doi.org/10.1016/0005-7916(82)90004-0
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ: Prentice-Hall.
Barnes, S. J., Pressey, A. D., & Scornavacca, E. (2019). Mobile ubiquity: Understanding the relationship between cognitive absorption, smartphone addiction and social network services. Computers in Human Behavior, 90, 246-258. doi: https://doi.org/10.1016/j.chb.2018.09.013
Bassi, G., Lis, A., Marci, T., & Salcuni, S. (2021). The Italian Version of Smartphone Addiction Inventory (SPAI-I) for Adolescents: Confirmatory Factor Analysis and Relation with Self-Control and Internalized-Externalized Symptoms. International Journal of Mental Health and Addiction. doi: 10.1007/s11469-021-00705-w
Bassi, G., Lis, A., Marci, T., & Salcuni, S. (2023). The Italian Version of Smartphone Addiction Inventory (SPAI-I) for Adolescents: Confirmatory Factor Analysis and Relation with Self-Control and Internalized-Externalized Symptoms. International Journal of Mental Health and Addiction, 21(3), 1992-2005. doi: 10.1007/s11469-021-00705-w
Berger, S., Wyss, A. M., & Knoch, D. (2018). Low self-control capacity is associated with immediate responses to smartphone signals. Computers in Human Behavior, 86, 45-51. doi: https://doi.org/10.1016/j.chb.2018.04.031
Bianchi, A., & Phillips, J. G. (2005). Psychological Predictors of Problem Mobile Phone Use. CyberPsychology & Behavior, 8(1), 39-51. doi: 10.1089/cpb.2005.8.39
Carleton, R. N., McCreary, D. R., Norton, P. J., & Asmundson, G. J. G. (2006). Brief Fear of Negative Evaluation scale—revised. Depression and Anxiety, 23(5), 297-303. doi: https://doi.org/10.1002/da.20142
Cha, S.-S., & Seo, B.-K. (2018). Smartphone use and smartphone addiction in middle school students in Korea: Prevalence, social networking service, and game use. Health Psychology Open, 5(1), 2055102918755046. doi: 10.1177/2055102918755046
Chan, M. (2015). Mobile phones and the good life: Examining the relationships among mobile use, social capital and subjective well-being. New Media & Society, 17(1), 96-113. doi: 10.1177/1461444813516836
Chan, M. (2018). Mobile-mediated multimodal communications, relationship quality and subjective well-being: An analysis of smartphone use from a life course perspective. Computers in Human Behavior, 87, 254-262. doi: https://doi.org/10.1016/j.chb.2018.05.027
Chicca, J., & Shellenbarger, T. (2018). Connecting with Generation Z: Approaches in Nursing Education. Teaching and Learning in Nursing, 13(3), 180-184. doi: https://doi.org/10.1016/j.teln.2018.03.008
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Cho, H.-Y., Kim, D. J., & Park, J. W. (2017). Stress and adult smartphone addiction: Mediation by self-control, neuroticism, and extraversion. Stress and Health, 33(5), 624-630. doi: https://doi.org/10.1002/smi.2749
Cohen, J. (1992). A Power Premier Psychological bulletin: Hilldale NJ: Routledge.
Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17(2), 187-195. doi: https://doi.org/10.1016/S0747-5632(00)00041-8
Dayapoglu, N., Kavurmaci, M., & Karaman, S. (2016). The relationship between the problematic mobile phone use and life satisfaction, loneliness, and academic performance in nursing students. International Journal of Caring Sciences, 9(2), 647-652.
De Ridder, D., & Gillebaart, M. (2017). Lessons learned from trait self-control in well-being: making the case for routines and initiation as important components of trait self-control. Health Psychology Review, 11(1), 89-99. doi: 10.1080/17437199.2016.1266275
Deng, J., Zhou, F., Hou, W., Silver, Z., Wong, C. Y., Chang, O., . . . Huang, E. (2021). The prevalence of depressive symptoms, anxiety symptoms and sleep disturbance in higher education students during the COVID-19 pandemic: A systematic review and meta-analysis. Psychiatry Research, 301, 113863. doi: https://doi.org/10.1016/j.psychres.2021.113863
Dhir, A., Kaur, P., Chen, S., & Pallesen, S. (2019). Antecedents and consequences of social media fatigue. International Journal of Information Management, 48, 193-202. doi: https://doi.org/10.1016/j.ijinfomgt.2019.05.021
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. doi: 10.1207/s15327752jpa8603_06
Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The Satisfaction With Life Scale. Journal of Personality Assessment, 49(1), 71-75. doi: 10.1207/s15327752jpa4901_13
Dodge, N., & Chapman, R. (2018). Investigating recruitment and completion mode biases in online and door to door electronic surveys. International Journal of Social Research Methodology, 21(2), 149-163. doi: 10.1080/13645579.2017.1336596
Dodge, R., Daly, A. P., Huyton, J., & Sanders, L. D. (2012). The Challenge of Defining Wellbeing. International Journal of Wellbeing, 2, 222-235. doi: 10.5502/ijw.v2i3.4
Easterby-Smith, M., Jaspersen, L. J., Thorpe, R., & Valizade, D. (2021). Management and Business Research: Sage.
Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. SAGE Publications Sage CA: Los Angeles CA.
Fu, S., Chen, X., & Zheng, H. (2021). Exploring an adverse impact of smartphone overuse on academic performance via health issues: a stimulus-organism-response perspective. Behaviour & Information Technology, 40(7), 663-675. doi: 10.1080/0144929X.2020.1716848
Geng, Y., Gu, J., Wang, J., & Zhang, R. (2021). Smartphone addiction and depression, anxiety: The role of bedtime procrastination and self-control. Journal of Affective Disorders, 293, 415-421. doi: https://doi.org/10.1016/j.jad.2021.06.062
Gerson, J., Plagnol, A. C., & Corr, P. J. (2016). Subjective well-being and social media use: Do personality traits moderate the impact of social comparison on Facebook? Computers in Human Behavior, 63, 813-822. doi: https://doi.org/10.1016/j.chb.2016.06.023
Gezgin, D. M. (2018). Understanding patterns for smartphone addiction: Age, sleep duration, social network use and fear of missing out. Kıbrıslı Eğitim Bilimleri Dergisi, 13(2), 166-177.
Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185-214. doi: 10.1080/07421222.2001.11045669
Haddad, J. M., Macenski, C., Mosier-Mills, A., Hibara, A., Kester, K., Schneider, M., . . . Liu, C. H. (2021). The Impact of Social Media on College Mental Health During the COVID-19 Pandemic: a Multinational Review of the Existing Literature. Current Psychiatry Reports, 23(11), 70. doi: 10.1007/s11920-021-01288-y
Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate data analysis: A global perspective (Vol. 7): Upper Saddle River, NJ: Pearson.
Hair, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101-110. doi: https://doi.org/10.1016/j.jbusres.2019.11.069
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM): Sage publications.
Hawk, S. T., van den Eijnden, R. J. J. M., van Lissa, C. J., & ter Bogt, T. F. M. (2019). Narcissistic adolescents' attention-seeking following social rejection: Links with social media disclosure, problematic social media use, and smartphone stress. Computers in Human Behavior, 92, 65-75. doi: https://doi.org/10.1016/j.chb.2018.10.032
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
Hong, F.-Y., Chiu, S.-I., & Huang, D.-H. (2012). A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students. Computers in Human Behavior, 28(6), 2152-2159. doi: https://doi.org/10.1016/j.chb.2012.06.020
Hu, X., Kim, A., Siwek, N., & Wilder, D. (2017). The Facebook Paradox: Effects of Facebooking on Individuals’ Social Relationships and Psychological Well-Being. Frontiers in Psychology, 8. doi: 10.3389/fpsyg.2017.00087
Hussain, Z., Simonovic, B., Stupple, E. J. N., & Austin, M. (2019). Using Eye Tracking to Explore Facebook Use and Associations with Facebook Addiction, Mental Well-being, and Personality. Behavioral Sciences, 9(2). doi:10.3390/bs9020019
Islam, A. K. M. N., Laato, S., Talukder, S., & Sutinen, E. (2020). Misinformation sharing and social media fatigue during COVID-19: An affordance and cognitive load perspective. Technological Forecasting and Social Change, 159, 120201. doi: https://doi.org/10.1016/j.techfore.2020.120201
Jeong, S.-H., Kim, H., Yum, J.-Y., & Hwang, Y. (2016). What type of content are smartphone users addicted to?: SNS vs. games. Computers in Human Behavior, 54, 10-17. doi: https://doi.org/10.1016/j.chb.2015.07.035
Jha, R. K., Shah, D. K., Basnet, S., Paudel, K. R., Sah, P., Sah, A. K., & Adhikari, K. (2016). Facebook use and its effects on the life of health science students in a private medical college of Nepal. BMC Research Notes, 9(1), 378. doi: 10.1186/s13104-016-2186-0
Karoly, P. (1993). Mechanisms of Self-Regulation: A Systems View. Annual Review of Psychology, 44(1), 23-52. doi: 10.1146/annurev.ps.44.020193.000323
Khanra, S., Dhir, A., Kaur, P., & Joseph, R. P. (2021). Factors influencing the adoption postponement of mobile payment services in the hospitality sector during a pandemic. Journal of Hospitality and Tourism Management, 46, 26-39. doi: https://doi.org/10.1016/j.jhtm.2020.11.004
Kline, R. B. (2015). Principles and practice of structural equation modeling. New York: Guilford publications.
Koç, T., & Turan, A. H. (2021). The Relationships Among Social Media Intensity, Smartphone Addiction, and Subjective Wellbeing of Turkish College Students. Applied Research in Quality of Life, 16(5), 1999-2021. doi: 10.1007/s11482-020-09857-8
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration (ijec), 11(4), 1-10. doi: 10.4018/ijec.2015100101
Kopp, C. B. (1982). Antecedents of self-regulation: A developmental perspective. Developmental Psychology, 18(2), 199-214. doi: 10.1037/0012-1649.18.2.199
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.
Lee, H., Min, H., Oh, S.-m., & Shim, K. (2018). Mobile Technology in Undergraduate Nursing Education: A Systematic Review. hir, 24(2), 97-108. doi: 10.4258/hir.2018.24.2.97
Liu, H., Liu, W., Yoganathan, V., & Osburg, V.-S. (2021). COVID-19 information overload and generation Z's social media discontinuance intention during the pandemic lockdown. Technological Forecasting and Social Change, 166, 120600. doi: https://doi.org/10.1016/j.techfore.2021.120600
Long, J., Liu, T.-Q., Liao, Y.-H., Qi, C., He, H.-Y., Chen, S.-B., & Billieux, J. (2016). Prevalence and correlates of problematic smartphone use in a large random sample of Chinese undergraduates. BMC Psychiatry, 16(1), 408. doi: 10.1186/s12888-016-1083-3
Mahapatra, S. (2019). Smartphone addiction and associated consequences: role of loneliness and self-regulation. Behaviour & Information Technology, 38(8), 833-844. doi: 10.1080/0144929X.2018.1560499
Manwell, L. A., Tadros, M., Ciccarelli, T. M., & Eikelboom, R. (2022). Digital dementia in the internet generation: excessive screen time during brain development will increase the risk of Alzheimer's disease and related dementias in adulthood. JIN, 21(1). doi: 10.31083/j.jin2101028
Marciano, L., Ostroumova, M., Schulz, P. J., & Camerini, A.-L. (2022). Digital Media Use and Adolescents' Mental Health During the Covid-19 Pandemic: A Systematic Review and Meta-Analysis. Frontiers in Public Health, 9. doi: 10.3389/fpubh.2021.793868
Meier, A., Reinecke, L., & Meltzer, C. E. (2016). “Facebocrastination”? Predictors of using Facebook for procrastination and its effects on students’ well-being. Computers in Human Behavior, 64, 65-76. doi: https://doi.org/10.1016/j.chb.2016.06.011
Munzel, A., Meyer-Waarden, L., & Galan, J.-P. (2018). The social side of sustainability: Well-being as a driver and an outcome of social relationships and interactions on social networking sites. Technological Forecasting and Social Change, 130, 14-27. doi: https://doi.org/10.1016/j.techfore.2017.06.031
Nochaiwong, S., Ruengorn, C., Thavorn, K., Hutton, B., Awiphan, R., Phosuya, C., . . . Wongpakaran, T. (2021). Global prevalence of mental health issues among the general population during the coronavirus disease-2019 pandemic: a systematic review and meta-analysis. Scientific Reports, 11(1), 10173. doi: 10.1038/s41598-021-89700-8
Osgerby, B. (2020). Youth culture and the media: Global perspectives (2nd ed.): Routledge.
Parasuraman, S., Sam, A. T., Yee, S. W. K., Chuon, B. L. C., & Ren, L. Y. (2017). Smartphone usage and increased risk of mobile phone addiction: A concurrent study. Int J Pharm Investig, 7(3), 125-131. doi: 10.4103/jphi.JPHI_56_17
Parent, N., Bond, T., Wu, A., & Shapka, J. (2022). Predicting Patterns of Problematic Smartphone Use among University Students: A Latent Class Analysis. Human Behavior and Emerging Technologies, 2022, 4287600. doi: 10.1155/2022/4287600
Pera, A. (2020). The Psychology of Addictive Smartphone Behavior in Young Adults: Problematic Use, Social Anxiety, and Depressive Stress. Frontiers in Psychiatry, 11. doi: 10.3389/fpsyt.2020.573473
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903. doi: 10.1037/0021-9010.88.5.879
Poláková, P., & Klímová, B. (2019). Mobile Technology and Generation Z in the English Language Classroom—A Preliminary Study. Education Sciences, 9(3). doi:10.3390/educsci9030203
Prakash, J., Ghosh, P., Chaudhury, S., & Srivastava, K. (2024). Nurturing mental health in the postpandemic era. Industrial Psychiatry Journal, 33(Suppl 1).
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879-891. doi: 10.3758/BRM.40.3.879
Prensky, M. (2001). Digital Natives, Digital Immigrants Part 2: Do They Really Think Differently? On the Horizon, 9(6), 1-6. doi: 10.1108/10748120110424843
Priporas, C.-V., Stylos, N., & Fotiadis, A. K. (2017). Generation Z consumers' expectations of interactions in smart retailing: A future agenda. Computers in Human Behavior, 77, 374-381. doi: https://doi.org/10.1016/j.chb.2017.01.058
Ransing, R., Adiukwu, F., Pereira-Sanchez, V., Ramalho, R., Orsolini, L., Teixeira, A. L. S., . . . Kundadak, G. K. (2020). Mental Health Interventions during the COVID-19 Pandemic: A Conceptual Framework by Early Career Psychiatrists. Asian Journal of Psychiatry, 51, 102085. doi: https://doi.org/10.1016/j.ajp.2020.102085
Roberts, J. A., & David, M. E. (2020). The Social Media Party: Fear of Missing Out (FoMO), Social Media Intensity, Connection, and Well-Being. International Journal of Human–Computer Interaction, 36(4), 386-392. doi: 10.1080/10447318.2019.1646517
Rothbart, M. K., & Bates, J. E. (1998). Temperament Handbook of child psychology: Social, emotional, and personality development, Vol. 3, 5th ed. (pp. 105-176). Hoboken, NJ, US: John Wiley & Sons, Inc.
Roy, A., Singh, A. K., Mishra, S., Chinnadurai, A., Mitra, A., & Bakshi, O. (2020). Mental health implications of COVID-19 pandemic and its response in India. International Journal of Social Psychiatry, 67(5), 587-600. doi: 10.1177/0020764020950769
Samaha, M., & Hawi, N. S. (2016). Relationships among smartphone addiction, stress, academic performance, and satisfaction with life. Computers in Human Behavior, 57, 321-325. doi: https://doi.org/10.1016/j.chb.2015.12.045
Sarangi, A., Amor, W., Co, E. L. F., Javed, S., Usmani, S., & Rashid, A. (2022). Social Media Reinvented: Can Social Media Help Tackle the Post-Pandemic Mental Health Onslaught? Cureus, 14(1), e21070. doi: 10.7759/cureus.21070
Satici, S. A. (2019). Facebook Addiction and Subjective Well-Being: a Study of the Mediating Role of Shyness and Loneliness. International Journal of Mental Health and Addiction, 17(1), 41-55. doi: 10.1007/s11469-017-9862-8
Satici, S. A., & Uysal, R. (2015). Well-being and problematic Facebook use. Computers in Human Behavior, 49, 185-190. doi: https://doi.org/10.1016/j.chb.2015.03.005
Servidio, R. (2021). Self-control and problematic smartphone use among Italian University students: The mediating role of the fear of missing out and of smartphone use patterns. Current Psychology, 40(8), 4101-4111. doi: 10.1007/s12144-019-00373-z
Sheth, J. (2020). Impact of Covid-19 on consumer behavior: Will the old habits return or die? Journal of Business Research, 117, 280-283. doi: https://doi.org/10.1016/j.jbusres.2020.05.059
Shiraev, E. B., & Levy, D. A. (2020). Cross-cultural psychology: Critical thinking and contemporary applications (7th ed.). New York: Routledge.
Snyder, M. (2022). Seek, and ye shall find: Testing hypotheses about other people Social cognition (pp. 277-304): Routledge.
Sobolewski, J., Rothschild, A., & Freeman, A. (2024). The Impact of Incentives on Data Collection for Online Surveys: Social Media Recruitment Study. JMIR Form Res, 8, e50240. doi: 10.2196/50240
Sohu, A., & Chaudhary, J. (2024). The Impact of Smartphone Usage Patterns on Health and Other Aspects of Life Post-Covid Pandemic. Journal of Humanities and Social Sciences Studies, 6(8), 01-08. doi: https://doi.org/10.32996/jhsss.2024.6.8.1
Su, P., & He, M. (2024). The mediating role of loneliness in the relationship between smartphone addiction and subjective well-being. Scientific Reports, 14(1), 4460. doi: 10.1038/s41598-024-54546-3
Sundarasen, S., Chinna, K., Kamaludin, K., Nurunnabi, M., Baloch, G. M., Khoshaim, H. B., . . . Sukayt, A. (2020). Psychological Impact of COVID-19 and Lockdown among University Students in Malaysia: Implications and Policy Recommendations. International Journal of Environmental Research and Public Health, 17(17), 6206.
Szymkowiak, A., Melović, B., Dabić, M., Jeganathan, K., & Kundi, G. S. (2021). Information technology and Gen Z: The role of teachers, the internet, and technology in the education of young people. Technology in Society, 65, 101565. doi: https://doi.org/10.1016/j.techsoc.2021.101565
Talwar, S., Dhir, A., Singh, D., Virk, G. S., & Salo, J. (2020). Sharing of fake news on social media: Application of the honeycomb framework and the third-person effect hypothesis. Journal of Retailing and Consumer Services, 57, 102197. doi: https://doi.org/10.1016/j.jretconser.2020.102197
Tangney, J. P., Boone, A. L., & Baumeister, R. F. (2018). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success Self-regulation and self-control (pp. 173-212): Routledge.
Valenzuela, S., Park, N., & Kee, K. F. (2009). Is There Social Capital in a Social Network Site?: Facebook Use and College Students' Life Satisfaction, Trust, and Participation1. Journal of Computer-Mediated Communication, 14(4), 875-901. doi: 10.1111/j.1083-6101.2009.01474.x
Valkenburg, P. M., & Peter, J. (2007). Online Communication and Adolescent Well-Being: Testing the Stimulation versus the Displacement Hypothesis. Journal of Computer-Mediated Communication, 12(4), 1169-1182. doi: 10.1111/j.1083-6101.2007.00368.x
Van Den Beemt, A., Thurlings, M., & Willems, M. (2020). Towards an understanding of social media use in the classroom: a literature review. Technology, Pedagogy and Education, 29(1), 35-55. doi: 10.1080/1475939X.2019.1695657
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. doi: https://doi.org/10.1016/j.chb.2014.12.039
Van Rooij, A. J., Ferguson, C. J., Van de Mheen, D., & Schoenmakers, T. M. (2017). Time to abandon internet addiction? Predicting problematic internet, game, and social media use from psychosocial well-being and application use. Clinical Neuropsychiatry, 14(1), 113-121.
Vizcaya-Moreno, M. F., & Pérez-Cañaveras, R. M. (2020). Social Media Used and Teaching Methods Preferred by Generation Z Students in the Nursing Clinical Learning Environment: A Cross-Sectional Research Study. International Journal of Environmental Research and Public Health, 17(21). doi:10.3390/ijerph17218267
Wind, T. R., Rijkeboer, M., Andersson, G., & Riper, H. (2020). The COVID-19 pandemic: The 'black swan' for mental health care and a turning point for e-health. Internet Interv, 20, 100317. doi: 10.1016/j.invent.2020.100317
Yang, Z., & Peterson, R. T. (2004). Customer perceived value, satisfaction, and loyalty: The role of switching costs. Psychology & Marketing, 21(10), 799-822. doi: https://doi.org/10.1002/mar.20030
Zhang, A., Xiong, S., Peng, Y., Zeng, Y., Zeng, C., Yang, Y., & Zhang, B. (2022). Perceived stress and mobile phone addiction among college students: The roles of self-control and security. Frontiers in Psychiatry, 13. doi: 10.3389/fpsyt.2022.1005062
Zhang, C. a., Tang, L., & Liu, Z. (2023). How social media usage affects psychological and subjective well-being: testing a moderated mediation model. BMC Psychology, 11(1), 286. doi: 10.1186/s40359-023-01311-2
Zhou, J., Zuo, M., Yu, Y., & Chai, W. (2014). How fundamental and supplemental interactions affect users’ knowledge sharing in virtual communities? A social cognitive perspective. Internet Research, 24(5), 566-586. doi: 10.1108/IntR-07-2013-0143
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