Dergiler / Journal of Gifted Education and Creativity / 2026 / Volume: 13 Issue: 1

The moderating role of AI anxiety in the relationship between high school students’ levels of malicious creativity and doomscrolling

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Yayın Tarihi
2026-06-30
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The findings suggest that there may be some correlations between secondary school students’ digital consumption habits and concerns regarding technology, and their tendencies towards malicious creativity.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In a digitalising world, the effects of the intense and negative content flow to which adolescents are exposed on cognitive processes constitute a critical area of study in the cyberpsychology literature.
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Temel Bulgular & Veri:The study was conducted with the participation of 162 volunteer secondary school students attending four different secondary schools and a Science and Arts Centre (SAC) in the province of Ankara.
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Sonuç & Katkı:The findings suggest that there may be some correlations between secondary school students’ digital consumption habits and concerns regarding technology, and their tendencies towards malicious creativity.
🔬Tür:Uygulamalı Anket & Alan Araştırması
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:AI anxiety · Cyberpsychology · Digital ethics

Abstract

In a digitalising world, the effects of the intense and negative content flow to which adolescents are exposed on cognitive processes constitute a critical area of study in the cyberpsychology literature. The primary aim of this study is to examine the moderating role of AI anxiety in the relationship between high school students’ levels of malicious creativity and their doomscrolling behaviours, using a correlational survey model. The study was conducted with the participation of 162 volunteer secondary school students attending four different secondary schools and a Science and Arts Centre (SAC) in the province of Ankara. The “Malicious Creativity Scale”, the “Doomscrolling Scale” and the “Artificial Intelligence Anxiety Scale” were used to collect the data. For data analysis, SPSS statistical software and the PROCESS macro add-in (Model 1) developed by Andrew F. Hayes were utilised. The results of the correlation analysis indicate a moderate, positive and statistically significant relationship between high school students’ levels of doomscrolling and their tendencies towards malicious creativity. Furthermore, positive and statistically significant relationships were identified between the level of AI anxiety and the other two variables. In the analysis of the moderating role—the central issue of the study—it was determined that AI anxiety does not have a statistically significant moderating function in the relationship between malicious creativity and doomscrolling. This result suggests that secondary school students may not yet have internalised AI technology as a direct threat. The research findings were discussed within the framework of the ‘Online Disinhibition Effect Theory’; it was assessed that the psychological distance created by the digital screen and the sense of anonymity facilitate adolescents’ rationalisation of their destructive creativity impulses. The findings suggest that there may be some correlations between secondary school students’ digital consumption habits and concerns regarding technology, and their tendencies towards malicious creativity.

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Bu Makaleye Atıf Yap

Ağaoğlu, O., Akçay, H. E., Baş, T. (2026). The moderating role of AI anxiety in the relationship between high school students’ levels of malicious creativity and doomscrolling. Journal of Gifted Education and Creativity, Volume: 13 Issue: 1. https://doi.org/10.5281/zenodo.21035047

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Kaynakça (25)

  1. Akben, G., Coşkun, H., & Akben, C. (2024). The Malicious Creativity Scale (MCS): A study on adaptation, validity and reliability in Turkish. Buca Faculty of Education Journal, 61, 1810–1826. https://doi.org/10.53444/deubefd.1388714
  2. Akkaya, B., Özkan, A., & Özkan, H. (2021). Artificial Intelligence Anxiety (AIA) Scale: Turkish adaptation, validity and reliability study. Alanya Academic Review, 5(2), 1125–1146. https://doi.org/10.29023/alanyaakademik.833668
  3. Ankara Governor’s Office. (2026). Education. https://www.ankara.gov.tr/egitim
  4. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173– 1182. https://doi.org/10.1037/0022-3514.51.6.1173
  5. Büyüköztürk, Ş. (2023). Handbook of data analysis for the social sciences: Statistics, research design, SPSS applications and reporting (35th ed.). Pegem Akademi Publishing.
  6. Cengiz, H. (2025). The relationship between doomscrolling, artificial intelligence anxiety, and job finding anxiety among university students. OPUS Journal of Society Research, 22(4), 1260–1275. https://doi.org/10.26466/opusjsr.1695844
  7. Cropley, D. H., Kaufman, J. C., & Cropley, A. J. (2008). Understanding malevolent creativity. In J. Chan & K. Thomas (Eds.), Handbook of research on creativity (pp. 185–195). Edward Elgar Publishing.
  8. Dinler, B. (2024). An investigation of the relationship between fear of missing out and catastrophising in adolescents and depression, anxiety, and stress: The regulatory role of mindfulness [Unpublished master’s thesis]. Atatürk University Institute of Educational Sciences.
  9. Dow, G. T. (2017). The dark tetrad and malevolent creativity. In The dark tetrad of personality (pp. 77–98). Academic Press.
  10. Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE Publications.
  11. Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw-Hill.
  12. George, D., & Mallery, P. (2010). SPSS for Windows Step by Step: A Simple Guide and Reference, 17.0 update (10th ed.). Pearson.
  13. Gündoğdu, R. (2025). An investigation of the relationship between doomscrolling, rumination and mental well- being in adults [Unpublished master’s thesis]. Yıldız Technical University Institute of Social Sciences.
  14. Hao, N., Tang, M., Yang, J., Wang, Q., & Runco, M. A. (2016). A new tool to measure malevolent creativity: The malevolent creativity behaviour scale. Frontiers in Psychology, 7, 682. https://doi.org/10.3389/fpsyg.2016.00682
  15. Kaplan, S. (2025). An examination of the role of proactive personality in the relationship between artificial intelligence anxiety and career adaptation skills among university students [Unpublished master’s thesis]. Istanbul University-Cerrahpaşa Graduate School of Education.
  16. Plucker, J. A., Beghetto, R., & Dow, G. T. (2004). Why isn’t creativity more important to educational psychologists? Potentials, pitfalls, and future directions in creativity research. Educational Psychologist, 39, 83–96. https://doi.org/10.1207/s15326985ep3902_1
  17. Satıcı, S. A., Kayış, A. R., & Çelik, E. (2022). The Turkish adaptation of the Doomscrolling Tendency Scale (DTS): A validity and reliability study. Current Psychology, 41(10), 7175–7185. https://doi.org/10.1007/s11482-022-10110-7
  18. Sharma, S., Mittal, N., & Anand, P. (2022). The mediating role of rumination between doomscrolling and mental well-being. Psychological Reports, 131(1), 205–218. https://doi.org/10.1007/s10942-025-00625-x
  19. Sternberg, R. J. (2010). The dark side of creativity and how to combat it. In D. H. Cropley, J. C. Kaufman, A. R. Cropley, & M. A. Runco (Eds.), The dark side of creativity. Cambridge University Press.
  20. Suler, J. (2004). The online disinhibition effect. CyberPsychology & Behavior, 7(3), 321–326. https://doi.org/10.1089/1094931041291232
  21. Tadik, H., Bahar, A. K., & Runco, M. (2025). The social context of malevolent creativity. Behavioral Sciences, 15(5), Article 630. https://doi.org/10.3390/bs15050630
  22. Visser, B., & Campbell, S. (2018). Measuring the dark side of personality. In T. Shackleford, & V. Ziegler-Hill (Eds.), Sage handbook of personality and individual differences (Vol. 1, pp. 573–591). Sage. https://doi.org/10.4135/9781526451163.n27
  23. Wang, Y., & Wang, J. (2019). Integrating TAM and TPB with trust to explain behavioural intention to use AI in education. Computers in Human Behavior, 95, 238–245. https://doi.org/10.1016/j.chb.2018.11.034
  24. Yüzkeccier, K. (2025). The role of AI anxiety in the readiness of students in faculties of sports sciences for the AI era [Unpublished master’s thesis]. Karamanoğlu Mehmetbey University Institute of Social Sciences.
  25. Zhang, W., Liang, Q., Qiao, X., & Hao, N. (2024). Unfairness breeds malice: Malevolent creativity is influenced by the perceived unfairness of others. Thinking Skills and Creativity, 53, Article 101586. https://doi.org/10.1016/j.tsc.2024.101586