Research Article
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Year 2021, Volume: 8 Issue: 1, 409 - 422, 01.01.2021
https://doi.org/10.17275/per.21.24.8.1

Abstract

References

  • Boffi, M., Riva, E., Rainisio, N., & Inghilleri, P. (2016). Social psychology of flow: A situated framework for optimal experience. In L. Harmat et al. (Eds.) Flow experience: Empirical research and applications (pp. 215-231). Springer. doi:10.1007/978-3-319-28634-1
  • Brailovskaia, J., Margraf, J., & Köllner, V. (2019). Addicted to Facebook? Relationship between Facebook Addiction Disorder, duration of Facebook use and narcissism in an inpatient sample. Psychiatry Research, 273, 52-57. doi:10.1016/j.psychres.2019.01.016
  • Brailovskaia, J., Rohmann, E., Bierhoff, H. W., & Margraf, J. (2018). The brave blue world: Facebook flow and Facebook Addiction Disorder (FAD). PloS One, 13(7), 1-12. doi:10.1371/journal.pone.0201484
  • Chen, H. (2006). Flow on the net–detecting Web users’ positive affects and their flow states. Computers in Human Behavior, 22(2), 221-233. doi:10.1016/j.chb.2004.07.001
  • Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York, NY:Harper & Row.
  • Csikszentmihalyi, M. (2014). Applications of flow in human development and education. New York, NY:Springer.
  • Delle Fave, A. & Bassi, M. (2016). Flow and psychological selection. In L. Harmat et al. (Eds.) Flow experience: Empirical research and applications (pp. 3-19). Springer. doi:10.1007/978-3-319-28634-1
  • Deng, T., Kanthawala, S., Meng, J., Peng, W., Kononova, A., Hao, Q., ... & David, P. (2019). Measuring smartphone usage and task switching with log tracking and self-reports. Mobile Media & Communication, 7(1), 3-23. doi:10.1177/2050157918761491
  • Enez Darcin, A., Kose, S., Noyan, C. O., Nurmedov, S., Yılmaz, O., & Dilbaz, N. (2016). Smartphone addiction and its relationship with social anxiety and loneliness. Behaviour & Information Technology, 35(7), 520-525. doi: 10.1080/0144929X.2016.1158319
  • Esteban-Millat, I., Martínez-López, F. J., Huertas-García, R., Meseguer, A., & Rodríguez-Ardura, I. (2014). Modelling students' flow experiences in an online learning environment. Computers & Education, 71, 111-123. doi:10.1016/j.compedu.2013.09.012
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics. London: Sage.
  • Gezgin, D. M., Cakir, O., & Yildirim, S. (2018). The relationship between levels of nomophobia prevalence and internet addiction among high school students: The factors influencing Nomophobia. International Journal of Research in Education and Science, 4(1), 215-225. doi:10.21890/ijres.383153.
  • Gezgin, D. M., & Çakır, Ö. (2016). Analysis of nomofobic behaviors of adolescents regarding various factors. Journal of Human Sciences, 13(2), 2504-2519. doi:10.14687/jhs.v13i2.3797
  • 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. doi:10.1016/j.chb.2016.05.091
  • Han, S., Kim, K. J., & Kim, J. H. (2017). Understanding nomophobia: Structural equation modeling and semantic network analysis of smartphone separation anxiety. Cyberpsychology, Behavior, and Social Networking, 20(7), 419-427. doi:10.1089/cyber.2017.0113
  • Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling. Retrieved from http://processmacro.org/download.html
  • Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press.
  • Hayes, A. F., Montoya, A. K., & Rockwood, N. J. (2017). The analysis of mechanisms and their contingencies: PROCESS versus structural equation modeling. Australasian Marketing Journal, 25(1), 76-81. doi:10.1016/j.ausmj.2017.02.001
  • Hoffman, D. L. & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60(3), 50-68. doi:10.1177/002224299606000304
  • Hoffman, D. L., & Novak, T. P. (2009). Flow online: Lessons learned and future prospects. Journal of Interactive Marketing, 23(1), 23-34. doi:10.1016/j.intmar.2008.10.003
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.doi:10.1080/10705519909540118
  • Huang, L. Y., Hsieh, Y. J., & Wu, Y. C. J. (2014). Gratifications and social network service usage: The mediating role of online experience. Information & Management, 51(6), 774-782. doi:10.1016/j.im.2014.05.004
  • Guo, Y. M., & Poole, M. S. (2009). Antecedents of flow in online shopping: A test of alternative models. Information Systems Journal, 19(4), 369-390. doi:10.1111/j.1365-2575.2007.00292.x
  • Kara, M., Baytemir, K., & Inceman-Kara, F. (2019). Duration of daily smartphone usage as an antecedent of nomophobia: Exploring multiple mediation of loneliness and anxiety. Behaviour & Information Technology, 1-14. doi:10.1080/0144929X.2019.1673485
  • Kaur, P., Dhir, A., Chen, S., & Rajala, R. (2016a). Flow in context: Development and validation of the flow experience instrument for social networking. Computers in Human Behavior, 59, 358-367. doi:10.1016/j.chb.2016.02.039
  • Kaur, P., Dhir, A., Chen, S., & Rajala, R. (2016b). Understanding online regret experience using the theoretical lens of flow experience. Computers in Human Behavior, 57, 230-239. doi:10.1016/j.chb.2015.12.041
  • Khang, H., Kim, J. K., & Kim, Y. (2013). Self-traits and motivations as antecedents of digital media flow and addiction: The Internet, mobile phones, and video games. Computers in Human Behavior, 29(6), 2416-2424. doi:10.1016/j.chb.2013.05.027
  • Kim, H. K., & Davis, K. E. (2009). Toward a comprehensive theory of problematic Internet use: Evaluating the role of self-esteem, anxiety, flow, and the self-rated importance of Internet activities. Computers in Human Behavior, 25(2), 490-500. doi:10.1016/j.chb.2008.11.001
  • King, A. L. S., Valença, A. M., & Nardi, A. E. (2010). Nomophobia: the mobile phone in panic disorder with agoraphobia: reducing phobias or worsening of dependence?. Cognitive and Behavioral Neurology, 23(1), 52-54. doi:10.1097/WNN.0b013e3181b7eabc
  • King, A. L. S., Valença, A. M., Silva, A. C. O., Baczynski, T., Carvalho, M. R., & Nardi, A. E. (2013). Nomophobia: Dependency on virtual environments or social phobia?. Computers in Human Behavior, 29(1), 140-144. doi:10.1016/j.chb.2012.07.025
  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205-223. doi:10.1287/isre.13.2.205.83
  • Lauricella, A. R., Cingel, D. P., Blackwell, C., Wartella, E., & Conway, A. (2014). The mobile generation: Youth and adolescent ownership and use of new media. Communication Research Reports, 31(4), 357-364. doi:10.1080/08824096.2014.963221
  • Liu, H., Chu, H., Huang, Q., & Chen, X. (2016). Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce. Computers in Human Behavior, 58, 306-314. doi:10.1016/j.chb.2016.01.012
  • Mendoza, J. S., Pody, B. C., Lee, S., Kim, M., & McDonough, I. M. (2018). The effect of cellphones on attention and learning: The influences of time, distraction, and nomophobia. Computers in Human Behavior, 86, 52-60. doi:10.1016/j.chb.2018.04.027
  • Novak, T. P., Hoffman, D. L., & Yung, Y. F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22-42. doi:10.1287/mksc.19.1.22.15184
  • Rains, S. A., & Brunner, S. R. (2015). What can we learn about social network sites by studying Facebook? A call and recommendations for research on social network sites. New Media & Society, 17(1), 114-131. doi:10.1177/1461444814546481
  • Seo, D. G., Park, Y., Kim, M. K., & Park, J. (2016). Mobile phone dependency and its impacts on adolescents’ social and academic behaviors. Computers in Human Behavior, 63, 282-292. doi:10.1016/j.chb.2016.05.026
  • Sırakaya, M. (2018). Examination of associate students' nomophobia levels according to smartphone use. Mersin University Journal of the Faculty of Education, 14(2), 714-727. doi:10.17860/mersinefd.359458
  • Škařupová, K., Ólafsson, K., & Blinka, L. (2016). The effect of smartphone use on trends in European adolescents’ excessive Internet use. Behaviour & Information Technology, 35(1), 68-74. doi:10.1080/0144929X.2015.1114144
  • Stavropoulos, V., Griffiths, M. D., Burleigh, T. L., Kuss, D. J., Doh, Y. Y., & Gomez, R. (2018). Flow on the Internet: a longitudinal study of Internet addiction symptoms during adolescence. Behaviour & Information Technology, 37(2), 159-172. doi:10.1080/0144929X.2018.1424937
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston, MA:Pearson.
  • Tams, S., Legoux, R., & Léger, P. M. (2018). Smartphone withdrawal creates stress: A moderated mediation model of nomophobia, social threat, and phone withdrawal context. Computers in Human Behavior, 81, 1-9. doi:10.1016/j.chb.2017.11.026
  • Yang, S., Lu, Y., Wang, B., & Zhao, L. (2014). The benefits and dangers of flow experience in high school students’ internet usage: The role of parental support. Computers in Human Behavior, 41, 504-513.doi:10.1016/j.chb.2014.09.039
  • Yang, X., Zhou, Z., Liu, Q., & Fan, C. (2019). Mobile phone addiction and adolescents’ anxiety and depression: The moderating role of mindfulness. Journal of child and family studies, 28(3), 822-830. doi:10.1007/s10826-018-01323-2
  • Yildirim, C., & Correia, A. P. (2015). Exploring the dimensions of nomophobia: Development and validation of a self-reported questionnaire. Computers in Human Behavior, 49, 130-137. doi:10.1016/j.chb.2015.02.059
  • Yildirim, C., Sumuer, E., Adnan, M., & Yildirim, S. (2016). A growing fear: Prevalence of nomophobia among Turkish college students. Information Development, 32(5), 1322-1331. doi:10.1177/0266666915599025
  • Yıldız Durak, H. (2018). What would you do without your smartphone? Adolescents’ social media usage, locus of control, and loneliness as a predictor of nomophobia. Addicta: The Turkish Journal on Addictions, 5(3), 543-557. doi:10.15805/addicta.2018.5.3.0025
  • Yildiz Durak, H. (2019). Investigation of nomophobia and smartphone addiction predictors among adolescents in Turkey: Demographic variables and academic performance. The Social Science Journal, 56(4), 492-517. doi:10.1016/j.soscij.2018.09.003

High Schoolers’ Usage Intensity of Mobile Social Media and Nomophobia: Investigating the Mediating Role of Flow Experience

Year 2021, Volume: 8 Issue: 1, 409 - 422, 01.01.2021
https://doi.org/10.17275/per.21.24.8.1

Abstract

This study aimed to investigate the relationship between high schoolers’ usage intensity of mobile social media and nomophobia through the mediation of flow experience. By adopting flow as a multidimensional construct; skill, machine interaction, and social interaction were included in the analysis as the conditions while concentration, enjoyment, and playfulness were included as the dimensions. A total of 584 adolescent mobile social media users participated in the study. The proposed model was tested through ordinary least-squares regression analysis and bootstrap methods. The findings showed that the usage intensity of the favorite mobile social media significantly predicts both conditions and dimensions of flow experience and nomophobia. In addition, the dimensions of flow experience together with skill significantly mediate the relationship between the usage intensity and nomophobia while the other conditions do not. These findings imply that as students spend more time on their favorite mobile social media, their nomophobic behaviors increase with the mediation of the dimensions and skill; but not the other conditions. The current study contributes to the relevant literature by associating nomophobia with flow experience on multiple mobile social media platforms. It also has implications for parents, school counselors, and educators of high school students.

References

  • Boffi, M., Riva, E., Rainisio, N., & Inghilleri, P. (2016). Social psychology of flow: A situated framework for optimal experience. In L. Harmat et al. (Eds.) Flow experience: Empirical research and applications (pp. 215-231). Springer. doi:10.1007/978-3-319-28634-1
  • Brailovskaia, J., Margraf, J., & Köllner, V. (2019). Addicted to Facebook? Relationship between Facebook Addiction Disorder, duration of Facebook use and narcissism in an inpatient sample. Psychiatry Research, 273, 52-57. doi:10.1016/j.psychres.2019.01.016
  • Brailovskaia, J., Rohmann, E., Bierhoff, H. W., & Margraf, J. (2018). The brave blue world: Facebook flow and Facebook Addiction Disorder (FAD). PloS One, 13(7), 1-12. doi:10.1371/journal.pone.0201484
  • Chen, H. (2006). Flow on the net–detecting Web users’ positive affects and their flow states. Computers in Human Behavior, 22(2), 221-233. doi:10.1016/j.chb.2004.07.001
  • Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York, NY:Harper & Row.
  • Csikszentmihalyi, M. (2014). Applications of flow in human development and education. New York, NY:Springer.
  • Delle Fave, A. & Bassi, M. (2016). Flow and psychological selection. In L. Harmat et al. (Eds.) Flow experience: Empirical research and applications (pp. 3-19). Springer. doi:10.1007/978-3-319-28634-1
  • Deng, T., Kanthawala, S., Meng, J., Peng, W., Kononova, A., Hao, Q., ... & David, P. (2019). Measuring smartphone usage and task switching with log tracking and self-reports. Mobile Media & Communication, 7(1), 3-23. doi:10.1177/2050157918761491
  • Enez Darcin, A., Kose, S., Noyan, C. O., Nurmedov, S., Yılmaz, O., & Dilbaz, N. (2016). Smartphone addiction and its relationship with social anxiety and loneliness. Behaviour & Information Technology, 35(7), 520-525. doi: 10.1080/0144929X.2016.1158319
  • Esteban-Millat, I., Martínez-López, F. J., Huertas-García, R., Meseguer, A., & Rodríguez-Ardura, I. (2014). Modelling students' flow experiences in an online learning environment. Computers & Education, 71, 111-123. doi:10.1016/j.compedu.2013.09.012
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics. London: Sage.
  • Gezgin, D. M., Cakir, O., & Yildirim, S. (2018). The relationship between levels of nomophobia prevalence and internet addiction among high school students: The factors influencing Nomophobia. International Journal of Research in Education and Science, 4(1), 215-225. doi:10.21890/ijres.383153.
  • Gezgin, D. M., & Çakır, Ö. (2016). Analysis of nomofobic behaviors of adolescents regarding various factors. Journal of Human Sciences, 13(2), 2504-2519. doi:10.14687/jhs.v13i2.3797
  • 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. doi:10.1016/j.chb.2016.05.091
  • Han, S., Kim, K. J., & Kim, J. H. (2017). Understanding nomophobia: Structural equation modeling and semantic network analysis of smartphone separation anxiety. Cyberpsychology, Behavior, and Social Networking, 20(7), 419-427. doi:10.1089/cyber.2017.0113
  • Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling. Retrieved from http://processmacro.org/download.html
  • Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press.
  • Hayes, A. F., Montoya, A. K., & Rockwood, N. J. (2017). The analysis of mechanisms and their contingencies: PROCESS versus structural equation modeling. Australasian Marketing Journal, 25(1), 76-81. doi:10.1016/j.ausmj.2017.02.001
  • Hoffman, D. L. & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60(3), 50-68. doi:10.1177/002224299606000304
  • Hoffman, D. L., & Novak, T. P. (2009). Flow online: Lessons learned and future prospects. Journal of Interactive Marketing, 23(1), 23-34. doi:10.1016/j.intmar.2008.10.003
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.doi:10.1080/10705519909540118
  • Huang, L. Y., Hsieh, Y. J., & Wu, Y. C. J. (2014). Gratifications and social network service usage: The mediating role of online experience. Information & Management, 51(6), 774-782. doi:10.1016/j.im.2014.05.004
  • Guo, Y. M., & Poole, M. S. (2009). Antecedents of flow in online shopping: A test of alternative models. Information Systems Journal, 19(4), 369-390. doi:10.1111/j.1365-2575.2007.00292.x
  • Kara, M., Baytemir, K., & Inceman-Kara, F. (2019). Duration of daily smartphone usage as an antecedent of nomophobia: Exploring multiple mediation of loneliness and anxiety. Behaviour & Information Technology, 1-14. doi:10.1080/0144929X.2019.1673485
  • Kaur, P., Dhir, A., Chen, S., & Rajala, R. (2016a). Flow in context: Development and validation of the flow experience instrument for social networking. Computers in Human Behavior, 59, 358-367. doi:10.1016/j.chb.2016.02.039
  • Kaur, P., Dhir, A., Chen, S., & Rajala, R. (2016b). Understanding online regret experience using the theoretical lens of flow experience. Computers in Human Behavior, 57, 230-239. doi:10.1016/j.chb.2015.12.041
  • Khang, H., Kim, J. K., & Kim, Y. (2013). Self-traits and motivations as antecedents of digital media flow and addiction: The Internet, mobile phones, and video games. Computers in Human Behavior, 29(6), 2416-2424. doi:10.1016/j.chb.2013.05.027
  • Kim, H. K., & Davis, K. E. (2009). Toward a comprehensive theory of problematic Internet use: Evaluating the role of self-esteem, anxiety, flow, and the self-rated importance of Internet activities. Computers in Human Behavior, 25(2), 490-500. doi:10.1016/j.chb.2008.11.001
  • King, A. L. S., Valença, A. M., & Nardi, A. E. (2010). Nomophobia: the mobile phone in panic disorder with agoraphobia: reducing phobias or worsening of dependence?. Cognitive and Behavioral Neurology, 23(1), 52-54. doi:10.1097/WNN.0b013e3181b7eabc
  • King, A. L. S., Valença, A. M., Silva, A. C. O., Baczynski, T., Carvalho, M. R., & Nardi, A. E. (2013). Nomophobia: Dependency on virtual environments or social phobia?. Computers in Human Behavior, 29(1), 140-144. doi:10.1016/j.chb.2012.07.025
  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205-223. doi:10.1287/isre.13.2.205.83
  • Lauricella, A. R., Cingel, D. P., Blackwell, C., Wartella, E., & Conway, A. (2014). The mobile generation: Youth and adolescent ownership and use of new media. Communication Research Reports, 31(4), 357-364. doi:10.1080/08824096.2014.963221
  • Liu, H., Chu, H., Huang, Q., & Chen, X. (2016). Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce. Computers in Human Behavior, 58, 306-314. doi:10.1016/j.chb.2016.01.012
  • Mendoza, J. S., Pody, B. C., Lee, S., Kim, M., & McDonough, I. M. (2018). The effect of cellphones on attention and learning: The influences of time, distraction, and nomophobia. Computers in Human Behavior, 86, 52-60. doi:10.1016/j.chb.2018.04.027
  • Novak, T. P., Hoffman, D. L., & Yung, Y. F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22-42. doi:10.1287/mksc.19.1.22.15184
  • Rains, S. A., & Brunner, S. R. (2015). What can we learn about social network sites by studying Facebook? A call and recommendations for research on social network sites. New Media & Society, 17(1), 114-131. doi:10.1177/1461444814546481
  • Seo, D. G., Park, Y., Kim, M. K., & Park, J. (2016). Mobile phone dependency and its impacts on adolescents’ social and academic behaviors. Computers in Human Behavior, 63, 282-292. doi:10.1016/j.chb.2016.05.026
  • Sırakaya, M. (2018). Examination of associate students' nomophobia levels according to smartphone use. Mersin University Journal of the Faculty of Education, 14(2), 714-727. doi:10.17860/mersinefd.359458
  • Škařupová, K., Ólafsson, K., & Blinka, L. (2016). The effect of smartphone use on trends in European adolescents’ excessive Internet use. Behaviour & Information Technology, 35(1), 68-74. doi:10.1080/0144929X.2015.1114144
  • Stavropoulos, V., Griffiths, M. D., Burleigh, T. L., Kuss, D. J., Doh, Y. Y., & Gomez, R. (2018). Flow on the Internet: a longitudinal study of Internet addiction symptoms during adolescence. Behaviour & Information Technology, 37(2), 159-172. doi:10.1080/0144929X.2018.1424937
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston, MA:Pearson.
  • Tams, S., Legoux, R., & Léger, P. M. (2018). Smartphone withdrawal creates stress: A moderated mediation model of nomophobia, social threat, and phone withdrawal context. Computers in Human Behavior, 81, 1-9. doi:10.1016/j.chb.2017.11.026
  • Yang, S., Lu, Y., Wang, B., & Zhao, L. (2014). The benefits and dangers of flow experience in high school students’ internet usage: The role of parental support. Computers in Human Behavior, 41, 504-513.doi:10.1016/j.chb.2014.09.039
  • Yang, X., Zhou, Z., Liu, Q., & Fan, C. (2019). Mobile phone addiction and adolescents’ anxiety and depression: The moderating role of mindfulness. Journal of child and family studies, 28(3), 822-830. doi:10.1007/s10826-018-01323-2
  • Yildirim, C., & Correia, A. P. (2015). Exploring the dimensions of nomophobia: Development and validation of a self-reported questionnaire. Computers in Human Behavior, 49, 130-137. doi:10.1016/j.chb.2015.02.059
  • Yildirim, C., Sumuer, E., Adnan, M., & Yildirim, S. (2016). A growing fear: Prevalence of nomophobia among Turkish college students. Information Development, 32(5), 1322-1331. doi:10.1177/0266666915599025
  • Yıldız Durak, H. (2018). What would you do without your smartphone? Adolescents’ social media usage, locus of control, and loneliness as a predictor of nomophobia. Addicta: The Turkish Journal on Addictions, 5(3), 543-557. doi:10.15805/addicta.2018.5.3.0025
  • Yildiz Durak, H. (2019). Investigation of nomophobia and smartphone addiction predictors among adolescents in Turkey: Demographic variables and academic performance. The Social Science Journal, 56(4), 492-517. doi:10.1016/j.soscij.2018.09.003
There are 48 citations in total.

Details

Primary Language English
Subjects Studies on Education
Journal Section Research Articles
Authors

Mehmet Kara 0000-0003-2758-2015

Publication Date January 1, 2021
Acceptance Date November 3, 2020
Published in Issue Year 2021 Volume: 8 Issue: 1

Cite

APA Kara, M. (2021). High Schoolers’ Usage Intensity of Mobile Social Media and Nomophobia: Investigating the Mediating Role of Flow Experience. Participatory Educational Research, 8(1), 409-422. https://doi.org/10.17275/per.21.24.8.1