Research Article
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Year 2023, Volume: 10 Issue: 3, 226 - 246, 01.05.2023
https://doi.org/10.17275/per.23.53.10.3

Abstract

References

  • Ahorsu, D. K., Lin, C.-Y., Imani, V., Saffari, M., Griffiths, M. D., & Pakpour, A. H. (2022). The fear of COVID-19 scale: Development and initial validation. International Journal of Mental Health and Addiction, 20(3), 1537–1545. https://doi.org/10.1007/s11469-020-00270-8
  • Akkaş Baysal, E., & Ocak, G. (2021). Opinions of the teachers on the compensation of learning loss caused by the COVID-19 outbreak. Kastamonu Education Journal, 29(4), 173-184. https://doi.org/10.24106/kefdergi.811834
  • Al-Furaih, S. A. A., & Al-Awidi, H. M. (2020). Teachers’ change readiness for the adoption of smartphone technology: personal concerns and technological competency. Technology, Knowledge and Learning, 25(2), 409-432. https://doi.org/10.1007/s10758-018-9396-6
  • Balhara, Y. P. S., Verma, K., & Bhargava, R. (2018). Screen time and screen addiction: Beyond gaming, social media and pornography– A case report. Asian Journal of Psychiatry, 35, 77-78. https://doi.org/10.1016/j.ajp.2018.05.020
  • Berdibayeva, S., Garber, A., Ivanov, D., Massalimova, A., Kukubayeva, A., & Berdibayev, S. (2016). Psychological prevention of older adolescents’ interpersonal relationships, who are prone to internet addiction. Procedia - Social and Behavioral Sciences, 217, 984–989. https://doi.org/10.1016/j.sbspro.2016.02.081
  • Borhany, T., Shahid, E., Siddique, W. A., & Ali, H. (2018). Musculoskeletal problems in frequent computer and Internet users. Journal of Family Medicine and Primary Care, 7(2), 337–339. https://doi.org/10.4103/jfmpc.jfmpc_326_17
  • Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., & Zheng, J. (2020). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 287, 112934. https://doi.org/10.1016/j.psychres.2020.112934
  • Caplan, S. E., & High, A. C. (2006). Beyond excessive use: The interaction between cognitive and behavioral symptoms of problematic internet use. Communication Research Reports, 23(4), 265-271. https://doi.org/10.1080/08824090600962516
  • Caplan, S. E. (2010). Theory and measurement of generalized problematic Internet use: A two-step approach. Computers in Human Behavior, 26(5), 1089-1097. https://doi.org/10.1016/j.chb.2010.03.012
  • Cheever, N. A., Moreno, M. A., & Rosen, L. D. (2018). When does internet and smartphone use become a problem? In M. A. Moreno & A. Radovic (Ed.), Technology and Adolescent Mental Health (ss. 121-131). Springer International Publishing. https://doi.org/10.1007/978-3-319-69638-6_10
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  • Colomo Magaña, E., Cívico Ariza, A., Ruiz Palmero, J., & Sánchez Rivas, E. (2021). Problematic use of ICTs in trainee teachers during COVID-19: A sex-based analysis. Contemporary Educational Technology, 13(4). https://eric.ed.gov/?id=EJ1316731
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  • Duan, L., Shao, X., Wang, Y., Huang, Y., Miao, J., Yang, X., & Zhu, G. (2020). An investigation of mental health status of children and adolescents in china during the outbreak of COVID-19. Journal of Affective Disorders, 275, 112-118. https://doi.org/10.1016/j.jad.2020.06.029
  • Fernandes, B., Biswas, U. N., Mansukhani, R. T., Casarín, A. V., & Essau, C. A. (2020). The impact of COVID-19 lockdown on internet use and escapism in adolescents. Revista de Psicología Clínica Con Niños y Adolescentes, 7(3), 59–65.
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  • Kaffenberger, M. (2021). Modelling the long-run learning impact of the Covid-19 learning shock: Actions to (more than) mitigate loss. International Journal of Educational Development, 81, 102326. https://doi.org/10.1016/j.ijedudev.2020.102326
  • Karadağ, E., & Kiliç, B. (2019). Technology addiction among students according to teacher views. Current Approaches in Psychiatry, 11, 101-117. https://doi.org/10.18863/pgy.556689
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Development and Validation of a Screen Fatigue Scale

Year 2023, Volume: 10 Issue: 3, 226 - 246, 01.05.2023
https://doi.org/10.17275/per.23.53.10.3

Abstract

Due to rapid development in information and communication technologies (ICT), daily life has been digitized with increasing momentum, and the COVID-19 pandemic has accelerated this situation more than ever. Depending on these developments and the excessive use of ICT, many new concepts have emerged, including screen fatigue. To this respect, this study aims to develop a scale that determines screen fatigue among adolescents caused by excessive screen use and test the scale’s psychometric properties. The research was conducted with an exploratory sequential, mixed-method research design. In the study’s first phase, qualitative data were obtained through a literature review and focus group interviews to develop an initial item pool. Based on the qualitative data analysis, a 56-item item pool was formed. In the quantitative phase, the item pool was administered to 365 students for the exploratory factor analyses (EFA). After determining the dimensions of the scale through EFA, it was administered to 417 students for confirmatory factor analysis (CFA). Quantitative data demonstrated that the scale has satisfactorily reliable and valid. A final scale was obtained, including 24 items and four factors named behavioral, physical, affective, and cognitive symptoms of screen fatigue.

References

  • Ahorsu, D. K., Lin, C.-Y., Imani, V., Saffari, M., Griffiths, M. D., & Pakpour, A. H. (2022). The fear of COVID-19 scale: Development and initial validation. International Journal of Mental Health and Addiction, 20(3), 1537–1545. https://doi.org/10.1007/s11469-020-00270-8
  • Akkaş Baysal, E., & Ocak, G. (2021). Opinions of the teachers on the compensation of learning loss caused by the COVID-19 outbreak. Kastamonu Education Journal, 29(4), 173-184. https://doi.org/10.24106/kefdergi.811834
  • Al-Furaih, S. A. A., & Al-Awidi, H. M. (2020). Teachers’ change readiness for the adoption of smartphone technology: personal concerns and technological competency. Technology, Knowledge and Learning, 25(2), 409-432. https://doi.org/10.1007/s10758-018-9396-6
  • Balhara, Y. P. S., Verma, K., & Bhargava, R. (2018). Screen time and screen addiction: Beyond gaming, social media and pornography– A case report. Asian Journal of Psychiatry, 35, 77-78. https://doi.org/10.1016/j.ajp.2018.05.020
  • Berdibayeva, S., Garber, A., Ivanov, D., Massalimova, A., Kukubayeva, A., & Berdibayev, S. (2016). Psychological prevention of older adolescents’ interpersonal relationships, who are prone to internet addiction. Procedia - Social and Behavioral Sciences, 217, 984–989. https://doi.org/10.1016/j.sbspro.2016.02.081
  • Borhany, T., Shahid, E., Siddique, W. A., & Ali, H. (2018). Musculoskeletal problems in frequent computer and Internet users. Journal of Family Medicine and Primary Care, 7(2), 337–339. https://doi.org/10.4103/jfmpc.jfmpc_326_17
  • Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., & Zheng, J. (2020). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 287, 112934. https://doi.org/10.1016/j.psychres.2020.112934
  • Caplan, S. E., & High, A. C. (2006). Beyond excessive use: The interaction between cognitive and behavioral symptoms of problematic internet use. Communication Research Reports, 23(4), 265-271. https://doi.org/10.1080/08824090600962516
  • Caplan, S. E. (2010). Theory and measurement of generalized problematic Internet use: A two-step approach. Computers in Human Behavior, 26(5), 1089-1097. https://doi.org/10.1016/j.chb.2010.03.012
  • Cheever, N. A., Moreno, M. A., & Rosen, L. D. (2018). When does internet and smartphone use become a problem? In M. A. Moreno & A. Radovic (Ed.), Technology and Adolescent Mental Health (ss. 121-131). Springer International Publishing. https://doi.org/10.1007/978-3-319-69638-6_10
  • Chen, R. N., Liang, S. W., Peng, Y., Li, X. G., Chen, J. B., Tang, S. Y. ve Zhao, J. B. (2020). Mental health status and change in living rhythms among college students in China during the COVID-19 pandemic: A large-scale survey. Journal of Psychosomatic Research, 137, 110219. https://doi.org/10.1016/j.jpsychores.2020.110219
  • Chin, W. W. (1998). Commentary: Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), vii-xvi.
  • Cho, E., & Kim, S. (2015). Cronbach’s coefficient alpha: Well known but poorly understood. Organizational Research Methods, 18(2), 207-230. https://doi.org/10.1177/1094428114555994
  • Colomo Magaña, E., Cívico Ariza, A., Ruiz Palmero, J., & Sánchez Rivas, E. (2021). Problematic use of ICTs in trainee teachers during COVID-19: A sex-based analysis. Contemporary Educational Technology, 13(4). https://eric.ed.gov/?id=EJ1316731
  • Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (Third edition). SAGE.
  • Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17(2), 187-195. https://doi.org/10.1016/S0747-5632(00)00041-8
  • Demir, M. R., & Yildizli, H. (2022). Educational processes and learning at home during COVID-19: Parents’ experiences with distance education. International Review of Research in Open and Distributed Learning, 23(3), 1–20. https://doi.org/10.19173/irrodl.v23i2.5870
  • Duan, L., Shao, X., Wang, Y., Huang, Y., Miao, J., Yang, X., & Zhu, G. (2020). An investigation of mental health status of children and adolescents in china during the outbreak of COVID-19. Journal of Affective Disorders, 275, 112-118. https://doi.org/10.1016/j.jad.2020.06.029
  • Fernandes, B., Biswas, U. N., Mansukhani, R. T., Casarín, A. V., & Essau, C. A. (2020). The impact of COVID-19 lockdown on internet use and escapism in adolescents. Revista de Psicología Clínica Con Niños y Adolescentes, 7(3), 59–65.
  • Gökalp, Z. Ş., Saritepeci, M., & Durak, H. Y. (2022). The relationship between self-control and procrastination among adolescent: The mediating role of multi screen addiction. Current Psychology. https://doi.org/10.1007/s12144-021-02472-2
  • Guo, Y., Liao, M., Cai, W., Yu, X., Li, S., Ke, X., Tan, S., Luo, Z., Cui, Y., Wang, Q., Gao, X., Liu, J., Liu, Y., Zhu, S., & Zeng, F. (2021). Physical activity, screen exposure and sleep among students during the pandemic of COVID-19. Scientific Reports, 11(1), 8529. https://doi.org/10.1038/s41598-021-88071-4
  • Hu, L., & 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. https://doi.org/10.1080/10705519909540118
  • Janwantanakul, P., Pensri, P., Jiamjarasrangsi, W., & Sinsongsook, J. (2009). Associations between prevalence of self-reported musculoskeletal symptoms of the spine and biosychosocial factors among office workers, Journal of Occupational Health, 51, 114-122.
  • Kaffenberger, M. (2021). Modelling the long-run learning impact of the Covid-19 learning shock: Actions to (more than) mitigate loss. International Journal of Educational Development, 81, 102326. https://doi.org/10.1016/j.ijedudev.2020.102326
  • Karadağ, E., & Kiliç, B. (2019). Technology addiction among students according to teacher views. Current Approaches in Psychiatry, 11, 101-117. https://doi.org/10.18863/pgy.556689
  • Khan, M. A. (2021). COVID-19’s impact on higher education: A rapid review of early reactive literature. Education Sciences, 11(8), 421. https://doi.org/10.3390/educsci11080421
  • Király, O., Potenza, M. N., Stein, D. J., King, D. L., Hodgins, D. C., Saunders, J. B., Griffiths, M. D., Gjoneska, B., Billieux, J., Brand, M., Abbott, M. W., Chamberlain, S. R., Corazza, O., Burkauskas, J., Sales, C. M. D., Montag, C., Lochner, C., Grünblatt, E., Wegmann, E., … Demetrovics, Z. (2020). Preventing problematic internet use during the COVID-19 pandemic: Consensus guidance. Comprehensive Psychiatry, 100, 152180. https://doi.org/10.1016/j.comppsych.2020.152180
  • Koayess, P., & McCaw, T. (2020). Mitigating screen fatigue in virtual learning. ICERI2020 Proceedings, 4979–4979. https://doi.org/10.21125/iceri.2020.1079
  • Kuhfeld, M., Soland, J., Tarasawa, B., Johnson, A., Ruzek, E., & Liu, J. (2020). Projecting the potential impact of COVID-19 school closures on academic achievement. Educational Researcher, 49(8), 549-565. https://doi.org/10.3102/0013189X20965918
  • Kuhfeld, M., & Tarasawa, B. (2020). The COVID-19 slide: What summer learning loss can tell us about the potential impact of school closures on student academic achievement. https://www.nwea.org/content/uploads/2020/05/Collaborative-Brief_Covid19-Slide-APR20.pdf
  • LaRose, R., Lin, C. A., & Eastin, M. S. (2003). Unregulated internet usage: Addiction, habit, or deficient self-regulation? Media Psychology, 5(3), 225-253. https://doi.org/10.1207/S1532785XMEP0503_01
  • Lee, A. (2020). Wuhan novel coronavirus (COVID-19): Why global control is challenging? Public Health, 179, A1-A2. https://doi.org/10.1016/j.puhe.2020.02.001
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There are 67 citations in total.

Details

Primary Language English
Subjects Other Fields of Education
Journal Section Research Articles
Authors

Gürbüz Ocak 0000-0001-8568-0364

Rüveysa Günhan 0000-0002-8028-4378

Ahmet Murat Uzun 0000-0002-1852-8802

Akın Karakuyu 0000-0001-7370-5464

Early Pub Date May 14, 2023
Publication Date May 1, 2023
Acceptance Date April 5, 2023
Published in Issue Year 2023 Volume: 10 Issue: 3

Cite

APA Ocak, G., Günhan, R., Uzun, A. M., Karakuyu, A. (2023). Development and Validation of a Screen Fatigue Scale. Participatory Educational Research, 10(3), 226-246. https://doi.org/10.17275/per.23.53.10.3