Adaptation and Validation of the Creativity Anxiety Scale in the Turkish Context

Year 2025, Volume: 7 Issue: 2, 124 - 142

Oktay Erbay , Semahat İncikabı , Feyza Aliustaoğlu , Lutfi İncikabı

https://doi.org/10.71249/ssci.1793460

Abstract

The Creativity Anxiety Scale (CAS; Daker et al., 2020) has been validated in several contexts, but no Turkish adaptation has yet been undertaken. This study aimed to adapt the CAS into Turkish and evaluate its psychometric properties among 344 middle school students. Following a rigorous translation–back translation procedure and expert review, confirmatory factor analysis (CFA) was conducted. The initial two-factor model, distinguishing creativity anxiety (CA) from non-creativity anxiety (NCA), showed poor fit. Sequentially freeing residual covariances between matched CA–NCA items substantially improved fit, yielding excellent indices (CFI = 0.987; TLI = 0.983; RMSEA = 0.042; SRMR = 0.023). Reliability analyses indicated strong internal consistency (α = .93 for CA; α = .91 for NCA). However, the near-unity correlation between CA and NCA suggests overlap with general evaluative anxiety and potential method effects. Despite these limitations, the Turkish CAS provides a valid and reliable instrument to investigate creativity-specific anxiety and its educational implications in the Turkish context.

Keywords

Creative Anxiety , Creative Anxiety Scale , Turkish Adaptation

Yaratıcılık Kaygı Ölçeği'nin Türkçeye Uyarlanması ve Geçerlik Çalışması

Abstract

Yaratıcılık Kaygısı Ölçeğinin (Creativity Anxiety Scale, CAS; Daker ve ark., 2020) farklı bağlamlarda geçerlik ve güvenirlik çalışmaları yapılmış olmasına rağmen, Türkçe uyarlaması henüz gerçekleştirilmemiştir. Bu çalışmada CAS’ın Türkçeye uyarlanması ve 344 ortaokul öğrencisi üzerinde psikometrik özelliklerinin incelenmesi amaçlanmıştır. Çeviri–geri çeviri süreci ve uzman görüşü sonrasında doğrulayıcı faktör analizi (DFA) uygulanmıştır. Yaratıcılık kaygısı (CA) ve yaratıcılık dışı kaygı (NCA) boyutlarını ayıran başlangıçtaki iki faktörlü modelin uyum indeksleri düşük bulunmuştur. Ancak CA–NCA eşleşen maddeler arasındaki hata kovaryanslarının serbest bırakılması ile model uyumu aşamalı olarak iyileşmiş ve mükemmel uyum değerleri elde edilmiştir (CFI = 0,987; TLI = 0,983; RMSEA = 0,042; SRMR = 0,023). Güvenirlik analizleri, alt boyutlar için yüksek iç tutarlılık göstermiştir (CA için α = 0,93; NCA için α = 0,91). Bununla birlikte, CA ve NCA arasındaki korelasyonun 1'e oldukça yakın çıkması, genel değerlendirme kaygısı ile örtüşme ve olası yöntem etkilerine işaret etmektedir. Bu sınırlılıklara rağmen, Türkçe CAS, yaratıcılığa özgü kaygının incelenmesi ve eğitimsel yansımalarının araştırılması için geçerli ve güvenilir bir ölçme aracı olarak kullanılabilir.

Keywords

Yaratıcılık Kaygısı , Yaratıcılık Kaygısı Ölçeği , Türkçe Uyarlaması

References

• Ashcraft, M. H. & Faust, M. W. (1994). Mathematics anxiety and mental arithmetic performance: An exploratory investigation. Cogn. Emot. 8, 97–125. https://doi.org/10.1080/02699939408408931
• Ashcraft, M. H. (2002). Math anxiety: Personal, educational, and cognitive consequences. Current Directions in Psychological Science, 11(5), 181-185. https://doi.org/10.1111/1467-8721.00196
• Barroso, C., Ganley, C. M., McGraw, A. L., Geer, E. A., Hart, S. A., & Daucourt, M. C. (2021). A meta-analysis of the relation between math anxiety and math achievement. Psychological Bulletin, 147(2), 134. https://doi.org/10.1037/bul0000307
• Bicer, A., Lee, Y., Perihan, C., Capraro, M. M., & Capraro, R. M. (2020). Considering mathematical creative self-efficacy with problem posing as a measure of mathematical creativity. Educational Studies in Mathematics, 105(3), 457–485.
• Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). Guilford Press.
• Bullock Muir, A., Tribe, B., & Forster, S. (2024). Creativity on tap? The effect of creativity anxiety under evaluative pressure. Creativity Research Journal, 1-10. https://doi.org/10.1080/10400419.2024.2330800
• Byrne, B. M. (2016). Structural Equation Modeling with AMOS (3rd ed.). Routledge.
• Byron, K., & Khazanchi, S. (2011). A meta-analytic investigation of the relationship of state and trait anxiety to performance on figural and verbal creative tasks. Personality and Social Psychology Bulletin, 37(2), 269-283.
• Cai, J., & Leikin, R. (2018). Call for papers: Educational studies in mathematics special issue. Educational Studies in Mathematics, 99(3), 243–244. https://doi.org/10.1007/s10649-018-9858-8
• Choe, K. W., Jenifer, J. B., Rozek, C. S., Berman, M. G., & Beilock, S. L. (2019). Calculated avoidance: Math anxiety predicts math avoidance in effort-based decision-making. Science advances, 5(11), eaay1062. https://doi.org/10.1126/sciadv.aay1062
• Daker, R. J., Cortes, R. A., Lyons, I. M., & Green, A. E. (2020). Creativity anxiety: Evidence for anxiety that is specific to creative thinking, from STEM to the arts. Journal of Experimental Psychology: General, 149(1), 42. https://doi.org/10.1037/xge0000630
• Daker, R. J., Viskontas, I. V., Porter, G. F., Colaizzi, G. A., Lyons, I. M., & Green, A. E. (2023). Investigating links between creativity anxiety, creative performance, and state-level anxiety and effort during creative thinking. Scientific reports, 13(1), 17095. https://doi.org/10.1038/s41598-023-39188-1
• Dowker, A., Sarkar, A., & Looi, C. Y. (2016). Mathematics anxiety: What have we learned in 60 years? Frontiers in Psychology, 7, 508. https://doi.org/10.3389/fpsyg.2016.00508
• Döner, S., Efe, Y., & Elmalı, F. (2024). Turkish adaptation of the state–trait anxiety inventory short version (STAIS‐5, STAIT‐5). International Journal of Nursing Practice, 30. https://doi.org/10.1111/ijn.13304
• Duan, H., Wang, X., Wang, Z., Xue, W., Kan, Y., Hu, W., & Zhang, F. (2019). Acute stress shapes creative cognition in trait anxiety. Frontiers in psychology, 10, 1517.
• Fetterly, J. M. (2020). Fostering mathematical creativity while impacting beliefs and anxiety in mathematics. Journal of Humanistic Mathematics, 10(2), 102-128.
• Herianto, H., Sofroniou, A., Fitrah, M., Rosana, D., Setiawan, C., Rosnawati, R., et al. (2024). Quantifying the relationship between self-efficacy and mathematical creativity: A meta-analysis. Education Sciences, 14(11), Article 1251.
• Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.
• Karakelle, S., & Saraç, S. (2022). Creative Mindsets Scale: Turkish Validity and Reliability. Cyprus Turkish Journal of Psychiatry & Psychology. https://doi.org/10.35365/ctjpp.22.2.01
• Kline, R. B. (2016). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press.
• Levav-Waynberg, A., & Leikin, R. (2012). The role of multiple solution tasks in developing knowledge and creativity in geometry. The Journal of Mathematical Behavior, 31(1), 73-90.
• Lyons, I. M., Ramirez, G., Maloney, E. A., Rendina, D. N., Levine, S. C., & Beilock, S. L. (2018). Spatial anxiety: A novel questionnaire with subscales for measuring three aspects of spatial anxiety. Journal of Numerical Cognition, 4(3), 526-553. https://doi.org/10.5964/jnc.v4i3.154
• Meier, M. A., Ehrengruber, A., Spitzley, L., Eller, N., Reiterer, C., Rieger, M., et al. (2024). The prediction of mathematical creativity scores: Mathematical abilities, personality, and creative self-beliefs. Learning and Individual Differences, 113, 102473.
• Ministry of National Education [MoNE]. (2024). Common Text of Curricula in The Century of Türkiye Education Model (TYMM). MoNE
• Paldi, P., & Khuzaini, N. (2024). A systematics literature review of the problem-solving approach in mathematics learning: Fostering creativity and reducing math anxiety. Journal of Educational Technology and Mathematics, 1(2), 16-22.
• Ramirez, G., Fries, L., Gunderson, E., Schaeffer, M. W., Maloney, E. A., Beilock, S. L., & Levine, S. C. (2019). Reading anxiety: An early affective impediment to children’s success in reading. Journal of Cognition and Development, 20(1), 15-34. https://doi.org/10.1080/15248372.2018.1526175
• Ren, Z., Daker, R. J., Shi, L., Sun, J., Beaty, R. E., Wu, X., ... & Qiu, J. (2021). Connectome-based predictive modeling of creativity anxiety. NeuroImage, 225, 117469. https://doi.org/10.1016/j.neuroimage.2020.117469
• Riedel, H. P., Taylor, I. A., & Melnyk, W. T. (1983). Effects of creative and noncreative problem-solving on anxiety. Perceptual and motor skills, 56(3), 835-844.
• Rosen, Y., Stoeffler, K., & Simmering, V. (2020). Imagine: Design for Creative Thinking, Learning, and Assessment in Schools. Journal of Intelligence, 8. https://doi.org/10.3390/jintelligence8020016
• Runco, M. A., & Jaeger, G. J. (2012). The standard definition of creativity. Creativity Research Journal, 24(1), 92–96. https://doi.org/10.1080/10400419.2012.650092
• Sayı, A., & Akgul, S. (2021). Psychometric properties of Guiding Creative Thinking Competency Scale. Thinking Skills and Creativity. https://doi.org/10.1016/j.tsc.2021.100811
• Silver, E. A. (1997). Fostering creativity through instruction rich in mathematical problem solving and problem posing. Zdm, 29(3), 75-80.
• Silvia, P. J., & Kimbrel, N. A. (2010). A dimensional analysis of creativity and mental illness: Do anxiety and depression symptoms predict creative cognition, creative accomplishments, and creative self-concepts?. Psychology of aesthetics, creativity, and the arts, 4(1), 2.
• Sridevi, K. V. (2013). A study of relationship among general anxiety, test anxiety and academic achievement of higher secondary students. Journal of Education and Practice, 4(1), 122-130.
• Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson.
• Tjoe, H. (2019). “Looking back” to solve differently: Familiarity, fluency, and flexibility. In P. Liljedahl, & M. Santos- Trigo. (Eds.), Mathematical Problem Solving ICME-13 Monographs (pp. 3–20). New York, NY: Springer-Verlag.
• Turhan, B., & Güven, M. (2014). The effect of mathematics instruction with problem posing approach on problem solving success, problem posing ability and views towards mathematics. Cukurova University Faculty of Education Journal, 43(2).
• Voica, C., Singer, F. M., & Stan, E. (2020). How are motivation and self-efficacy interacting in problem-solving and problem-posing?. Educational Studies in Mathematics, 105(3), 487-517.
• Yuan, X., & Sriraman, B. (2011). An exploratory study of relationships between students’ creativity and mathematical problem-posing abilities. The elements of creativity and giftedness in mathematics, 5-28.
• Xiang, S., Li, Y., Daker, R. J., Li, Y., Guo, X., Lei, W., ... & Hu, W. (2025). Linking creativity anxiety to two creative cognitive styles through creative self-efficacy and novelty seeking. Creativity Research Journal, 37(1), 56-70. https://doi.org/10.1080/10400419.2023.2275981
• Zanon, C., Brenner, R., Baptista, M., Vogel, D., Rubin, M., Al-Darmaki, F., Gonçalves, M., Heath, P., Liao, H., Mackenzie, C., Topkaya, N., Wade, N., & Zlati, A. (2020). Examining the Dimensionality, Reliability, and Invariance of the Depression, Anxiety, and Stress Scale–21 (DASS-21) Across Eight Countries. Assessment, 28, 1531 - 1544. https://doi.org/10.1177/1073191119887449
• Zheng, Y., Ren, J., Li, F., & Huang, F. (2024). Trait anxiety negatively affected creative discovery under pressure conditions: Evidence from behavioral responses and ERPs. Personality and Individual Differences, 231, 112821.