The DOI matches its Crossref record; 121 of the 125 references it cites were found in a registry or an index.
The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence
Open accessAbstract
The present study adapted the General Attitudes toward Artificial Intelligence Scale (GAAIS) to Turkish and investigated the impact of personality traits, artificial intelligence anxiety, and demographics on attitudes toward artificial intelligence. The sample consisted of 259 female (74%) and 91 male (26%) individuals aged between 18 and 51 (Mean = 24.23). Measures taken were demographics, the Ten-Item Personality Inventory, the Artificial Intelligence Anxiety Scale, and the General Attitudes toward Artificial Intelligence Scale. The Turkish GAAIS had good validity and reliability. Hierarchical Multiple Linear Regression Analyses showed that positive attitudes toward artificial intelligence were significantly predicted by the level of computer use (β = 0.139, p = 0.013), level of knowledge about artificial intelligence (β = 0.119, p = 0.029), and AI learning anxiety (β = −0.172, p = 0.004). Negative attitudes toward artificial intelligence were significantly predicted by agreeableness (β = 0.120, p = 0.019), AI configuration anxiety (β = −0.379, p < 0.001), and AI learning anxiety (β = −0.211, p < 0.001). Personality traits, AI anxiety, and demographics play important roles in attitudes toward AI. Results are discussed in light of the previous research and theoretical explanations.
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“while Kaya et al. (2024) showed that age did not predict attitudes toward AI.”
From Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs (2024) · cites this paper as Kaya et al., 2024
Citations
Cites
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Principles and Practice of Structural Equation Modeling
Tabri, N., & Elliott, C. M. (2012) · Canadian Graduate Journal of Sociology and Criminology · doi:10.15353/cgjsc.v1i1.3787 · Cited by 39,094
Research Design: Qualitative, Quantitative, and Mixed Methods Approaches
Creswell, J. W. (1994) · Cited by 35,213
Pls-Sem: indeed a silver bullet
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011) · Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679190202 · Cited by 21,631
Einax, J. W., Zwanziger, H. W., & Geiß, S. (1997) · Wiley eBooks · doi:10.1002/352760216x.ch5 · Cited by 18,779
Research design: qualitative, quantitative, and mixed methods approaches
Caldas, M. (2003) · Revista de Administração Contemporânea · doi:10.1590/s1415-65552003000100015 · Cited by 18,688
(2017) · Cited by 16,319
Confirmatory factor analysis for applied research
Brown, T. A. (2007) · Choice Reviews Online · doi:10.5860/choice.44-2769 · Cited by 15,621
(1998) · DigitalCommons - Kennesaw State University (Kennesaw State University) · Cited by 13,997
The future of employment: How susceptible are jobs to computerisation?
Frey, C. B., & Osborne, M. A. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.08.019 · Cited by 8,727
Research works printed but not linked: 11
- Chuang, L.-M., Liu, C.-C., & Kao, H.-K. (2016). The adoption of fintech service: TAM perspective. International Journal of Management Administrative Sciences, 3(7), 1–15.
- Circiumaru A. (2022). [ Futureproofing EU law the case of algorithmic discrimination] [Unpublished master’s thesis]. University of Oxford.
- Costa, P. T., & McCrae, R. R. (1992). Revised NEO Personality Inventory and NEO Five-Factor Inventory: Professional manual. Psychological Assessment Resources.
- 10.2759/835661 · DOI
- Figueiredo M. M. (2019). [Artificial Intelligence acceptance: Morphological elements of the acceptance of Artificial Intelligence] [Unpublished master’s thesis]. Católica Porto Business School.
- 10.1080/1369183x.2013.8261 · DOI
- Mark, L., Davis, J., Dow, T., Godfrey, W., & Proyas, A. (2004). I, robot movie [Motion picture]. 20th Century Fox.
- Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
- Reinhart, R. J. (2018, March 6). Most Americans already using artificial intelligence products. Gallup. https://perma.cc/RVY5-WP9W
- Sánchez-Nicolás, E. (2019, August 29). All “big five” tech firms listened to private conversations. EUobserver. https://euobserver.com/science/145759
- Thanabordeekij, P., Sudtasan, T., & Tanamee, D. (2020). Integrating trust into the technology acceptance model: The case of mobile banking adoption in Myanmar. Panyapiwat Journal, 12(3), 107–119.
Cited by
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Kayaoğlu, S. Ç., ERASLAN, Ş. S., & Tufan, S. (2026) · Nursing Open · doi:10.1002/nop2.70776
Kalaycıoğlu, O., Jahanshahi, A. A., Chalise, S., Aranda, G. M. Z., & Orozco, J. A. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7459546
Rodrigues, M. A. D. S., & Dubeux, V. J. C. (2026) · Technovation · doi:10.1016/j.technovation.2026.103712
Zahedkazemi, E., Khany, R., & Shoja, L. (2026) · Discover Education · doi:10.1007/s44217-026-02094-5
Kim, T. H., Chang, B., & Kim, K. H. (2026) · Corporate Social Responsibility and Environmental Management · doi:10.1002/csr.70996
Nhat, H. T. K. (2026) · Tạp chí Khoa học Đại học Công Thương. · doi:10.62985/j.huit_ojs.vol26.no3e.582
Uysal, B., Kamer, H., SARIYILDIZ, A. Y., TİYEK, R., & ASLAN, Ö. F. (2026) · Healthcare · doi:10.3390/healthcare14183078
Suwanroj, T., Chanakul, B., Siripan, A., Nilsook, P., Leekitchwatana, P., Kaewkamjan, K., Saeung, O., Amnuaysin, O., Issaro, S., & Areepong, T. (2026) · International Journal of Information and Education Technology · doi:10.18178/ijiet.2026.16.9.2698
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Gobet, F. R., Yousaf, O., Evans, N., & Chatfield-Jouin, F. (2026) · The Journal of Humanistic Counseling · doi:10.1002/johc.70065
Annak, İ. M., Irmak, B., & Karadağ, M. (2026) · Journal of PeriAnesthesia Nursing · doi:10.1016/j.jopan.2026.09.010
Thipsri, N. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.101346
Leventoğlu, E., & Ayçiçek, B. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-02319-4
Ohmoto, Y., Terada, K., Iwanaga, R., & Kumazaki, H. (2026) · JMIR Formative Research · doi:10.2196/98367
Yurtçu, A. (2026) · International Journal Of Eurasia Social Sciences · doi:10.70736/ijoess.2512
Bekiroğlu, H. A. (2025) · Journal of Higher Education and Science · doi:10.5961/higheredusci.1613974
Mete, E., Benli, R. K., KILIÇ, B. B., & YAŞARER, Ö. (2026) · Work · doi:10.1177/10519815261492327
Işık, M. A., & Şat, S. Ö. (2026) · Ordu Üniversitesi Hemşirelik Çalışmaları Dergisi · doi:10.38108/ouhcd.1622974
Al-Kaabi, A., & Qutran, Y. A. (2026) · Discover Education · doi:10.1007/s44217-026-02204-3
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Zohreh, K. (2026) · Sosyal Bilimlerde Akademik Çalışmalar Dergisi/ Journal of Academic Studies in Social Sciences · doi:10.71284/sobac.202624
Redlich, M.-C., Nordmann, K., Rabbani, S., Schaller, M., & Fischer, F. (2026) · Springer eBooks · doi:10.1007/978-3-032-35691-8_457
Karaca, İ., Gül, H., & Erel, S. (2026) · Balıkesır Health Sciences Journal · doi:10.53424/balikesirsbd.1905384
Nicoli, F., Buzzelli, G., Burgoon, B. M., & Sacchi, S. (2026) · Social Science Computer Review · doi:10.1177/08944393261493959
Demirtaş, F. A., Gümüşay, M., & Ayyıldız, B. (2026) · International Journal of Sexual Health · doi:10.1080/19317611.2026.2746090
The attitudes towards generative AI among games development professionals and students
Sikorski, Ł., Matulewski, J., & Czerwonka, M. (2026) · Human Technology · doi:10.14254/1795-6889.2026.22-2.10
Li, Y., & Mao, E. (2026) · SAGE Open · doi:10.1177/21582440261493838 · Cited by 1
Gevher, M., Öncü, S. E., Koçdar, S., & Erdoğdu, E. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14170-2
Designing a pipeline linking professional development to AI-supported instructional practice
Kim, A. (2026) · Computers & Education · doi:10.1016/j.compedu.2026.105764
Singh, N., & Sharma, T. (2026) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-026-00726-z
Generative AI and Large Language Models: Transformers, Prompt Engineering, and AI Agents
Hanchate, D. B., Satarakar, P. A., & Shelar, M. D. (2026) · doi:10.70593/978-81-6632-134-4
Massano‐Cardoso, I., Nogueira, F., Figueiredo, S., & Galhardo, A. B. (2026) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-026-00728-x
Alsudays, H. A., & Alsudays, S. (2026) · Psychology Research and Behavior Management · doi:10.2147/prbm.s648836
Zhu, H., Chen, J., & Zhang, H. (2026) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2026.104934
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Yankouskaya, A., Rahman, M. M., Noman, M., & Ali, R. (2026) · Lecture notes in computer science · doi:10.1007/978-981-92-6910-5_17
Christopoulos, A., Mystakidis, S., Perikos, I., Bourazeri, A., Michael, A., & Laakso, M. (2026) · Applied Cognitive Psychology · doi:10.1002/acp.70298
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Xing, X., & Liang, X. (2026) · European Journal of Education · doi:10.1111/ejed.70893
Gökalp, M. G., & Yonar, S. (2026) · Acibadem Universitesi Saglik Bilimleri Dergisi · doi:10.31067/acusaglik.1978196
Lin, P.-Y., Chai, C. S., & Zhou, Y. (2026) · SAGE Open · doi:10.1177/21582440261500778
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Metadata
- Authors
- Kaya, F., Aydin, F., Schepman, A., Rodway, P., Yetişensoy, O., & Demir Kaya, M.
- Affiliations
- Atatürk University (TR)
- Department of Counseling and Guidance, Sivas Cumhuriyet University, Sivas, Turkey
- University of Chester (GB)
- Department of Social Sciences, Bayburt University, Bayburt, Turkey
- Department of Psychology, Ataturk University, Erzurum, Turkey
- Corresponding author
- Schepman, Astrid
- Venue
- International Journal of Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2022-12-07
- Volume
- 40
- Issue
- 2
- Pages
- 497-514
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W4311843323
- Cited by
- 688
- References
- 125
- Citations by year
- 2026: 264 · 2025: 283 · 2024: 120 · 2023: 20 · 2022: 1
- FWCI
- 146.38
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Journal of Human-Computer Interaction (publishedVersion, cc-by-nc-nd)
- ChesterRep (University of Chester) (submittedVersion, cc-by-nc-nd)
- DSpace@Bayburt (submittedVersion, other-oa)
- Topics
- Social Sciences › Gender Studies › Gender and Technology in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Keywords
- attitudes toward AI, AI anxiety, personality traits, agreeableness, computer use, AI knowledge, scale adaptation, Turkish adaptation, demographic factors
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