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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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
Sorted by citations
Schiavo, G., Businaro, S., & Zancanaro, M. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102537 · Cited by 284
Perceptions and Acceptance of Artificial Intelligence: A Multi-Dimensional Study
Gerlich, M. (2023) · Social Sciences · doi:10.3390/socsci12090502 · Cited by 278
Chang, P., Zhang, W., Cai, Q., & Guo, H. (2024) · Psychology Research and Behavior Management · doi:10.2147/prbm.s441444 · Cited by 259
Mah, D.-K., & Groß, N. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00490-1 · Cited by 218
“Schepman and Rodway (2023) showed that younger people were more likely to show positive general attitudes toward AI than older people, while Kaya et al. (2024) showed that age did not predict attitudes toward AI.”
Bergdahl, J., Latikka, R., Celuch, M., Savolainen, I., Soares Mantere, E., Savela, N., & Oksanen, A. (2023) · Telematics and Informatics · doi:10.1016/j.tele.2023.102013 · Cited by 204
Exploring the artificial intelligence anxiety and machine learning attitudes of teacher candidates
Hopcan, S., Türkmen, G., & Polat, E. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-12086-9 · Cited by 182
The technology acceptance model and adopter type analysis in the context of artificial intelligence
Ibrahim, F., Münscher, J., Daseking, M., & Telle, N.-T. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1496518 · Cited by 205
Ellikkal, A., & Rajamohan, S. (2024) · Vilakshan – XIMB Journal of Management · doi:10.1108/xjm-02-2024-0023 · Cited by 180
Chen, D., Liu, W., & Liu, X. (2024) · Acta Psychologica · doi:10.1016/j.actpsy.2024.104442 · Cited by 173
Rodway, P., & Schepman, A. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100150 · Cited by 144
Self-citationZhu, W., Huang, L., Zhou, X., Li, X., Shi, G., Ying, J., & Wang, C. (2025) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2024.2323277 · Cited by 143
Artificial intelligence for higher education: benefits and challenges for pre-service teachers
Kalniņa, D., Nīmante, D., & Baranova, S. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1501819 · Cited by 162
Bae, H., Hur, J., Park, J., Choi, G. W., & Moon, J. (2024) · Online Learning · doi:10.24059/olj.v28i3.4543 · Cited by 155
Gender differences in artificial intelligence: the role of artificial intelligence anxiety
Russo, C., Romano, L., Clemente, D., Iacovone, L., Gladwin, T. E., & Panno, A. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1559457 · Cited by 126
Park, K., & Yoon, H. Y. (2024) · Public Relations Review · doi:10.1016/j.pubrev.2024.102507 · Cited by 137
The interplay between teachers’ trust in artificial intelligence and digital competence
Lucas, M., Zhang, Y., Bem‐Haja, P., & Vicente, P. N. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12772-2 · Cited by 141
Chen, C., Hu, W., & Wei, X. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2024.2440877 · Cited by 116
Exploring Factors That Support Pre-service Teachers’ Engagement in Learning Artificial Intelligence
Ayanwale, M. A., Frimpong, E. K., Opesemowo, O. A. G., & Sanusi, I. T. (2024) · Journal for STEM Education Research · doi:10.1007/s41979-024-00121-4 · Cited by 128
Seyfi, S., Kim, M. J., Nazifi, A., Murdy, S., & Vo‐Thanh, T. (2025) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2025.104105 · Cited by 113
Ku, E. C. S., & Chen, C.-D. (2024) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2024.102757 · Cited by 110
Cengiz, S., & Peker, A. (2025) · Current Psychology · doi:10.1007/s12144-025-07433-7 · Cited by 107
Dingel, J., Kleine, A., Cecil, J., Sigl, A., Lermer, E., & Gaube, S. (2024) · Journal of Medical Internet Research · doi:10.2196/57224 · Cited by 116
Zhan, E. S., Molina, M. D., Rheu, M., & Peng, W. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2261731 · Cited by 112
Gu, C., Zhang, Y., & Zeng, L. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03879-5 · Cited by 110
Collie, R. J., & Martin, A. J. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100224 · Cited by 105
The effect of source disclosure on evaluation of AI-generated messages
Lim, S., & Schmälzle, R. (2024) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2024.100058 · Cited by 113
AI as an Artist? A Two-Wave Survey Study on Attitudes Toward Using Artificial Intelligence in Art
Latikka, R., Bergdahl, J., Savela, N., & Oksanen, A. (2023) · Poetics · doi:10.1016/j.poetic.2023.101839 · Cited by 108
Alkhwaldi, A. F. (2024) · Sustainability · doi:10.3390/su16020934 · Cited by 83
Subaşı, D. Ö., Sümengen, A. A., Semerci, R., Şimşek, E., Çakır, G. N., & Temizsoy, E. (2024) · Journal of Advanced Nursing · doi:10.1111/jan.16335 · Cited by 83
The Artificial Intelligence Paradox: Opportunity or Threat for Humanity?
Bozkurt, V., & Gürsoy, D. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2297114 · Cited by 86
Artificial Intelligence, AI literacy, Digital literacy, AI literacy scale
ÇELEBİ, C., YILMAZ, F., DEMİR, U., & KARAKUŞ, F. (2023) · Öğretim Teknolojisi ve Hayat Boyu Öğrenme Dergisi - Instructional Technology and Lifelong Learning · doi:10.52911/itall.1401740 · Cited by 77
Brauner, P., Glawe, F., Liehner, G. L., Vervier, L., & Ziefle, M. (2025) · AI & Society · doi:10.1007/s00146-026-03023-8 · Cited by 90
Yurt, E., & Kaşarcı, İ. (2024) · International Journal of Technology in Education · doi:10.46328/ijte.725 · Cited by 76
Artificial intelligence skills and their impact on the employability of university graduates
Ramos, H. C. P., Caro, O. C., Bardales, E. S., Huatangari, L. Q., Trigoso, J. A. C., Guevara, J. L. M., & Santos, R. C. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1629320 · Cited by 96
Nursing students' attitudes and literacy toward artificial intelligence: a cross-sectional study
Sümengen, A. A., Subaşı, D. Ö., & Çakır, G. N. (2024) · Teaching and learning in nursing · doi:10.1016/j.teln.2024.10.022 · Cited by 71
Salem, G. M. M., El‐Gazar, H. E., Mahdy, A. Y., Alharbi, T. A. F., & Zoromba, M. A. (2024) · Journal of Nursing Management · doi:10.1155/2024/6992824 · Cited by 67
Alejandro, I. M. V., Sanchez, J. M. P., Sumalinog, G. G., Mananay, J. A., Goles, C. E., & Fernandez, C. B. (2024) · STEM Education · doi:10.3934/steme.2024024 · Cited by 71
AI readiness scale for teachers: Development and validation
Ramazanoğlu, M., & Akin, T. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13087-y · Cited by 64
Attitudes Towards AI: The Interplay of Self-Efficacy, Well-Being, and Competency
Naiseh, M., Babiker, A., Alshakhsi, S. A. A., Cemiloglu, D., Al‐Thani, D., Montag, C., & Ali, R. (2025) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-025-00486-2 · Cited by 70
Park, K., & Yoon, H. Y. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-05116-z · Cited by 66
Yalcinkaya, T., Ergin, E., & Yucel, S. C. (2024) · Teaching and Learning in Nursing · doi:10.1016/j.teln.2024.07.008 · Cited by 57
Model of AI acceptance in higher education: arguing teaching staff and students perspectives
Hazaimeh, M., & Al‐Ansi, A. M. (2024) · International Journal of Information and Learning Technology · doi:10.1108/ijilt-01-2024-0005 · Cited by 56
Hong, S. J. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108460 · Cited by 60
Lund, B. D., Mannuru, N. R., & Agbaji, D. A. (2024) · Journal of Information Science · doi:10.1177/01655515241282001 · Cited by 55
Development and validation of generative artificial intelligence attitude scale for students
Marengo, A., Karaoglan-Yilmaz, F. G., Yılmaz, R., & Ceylan, M. (2025) · Frontiers in Computer Science · doi:10.3389/fcomp.2025.1528455 · Cited by 54
Wu, H., Liu, W., & Zeng, Y. (2024) · Acta Psychologica · doi:10.1016/j.actpsy.2024.104376 · Cited by 54
Arkan, B., Dallı, Ö. E., & Varol, B. (2025) · Nurse Education Today · doi:10.1016/j.nedt.2025.106765 · Cited by 55
Weber, S., Wyszynski, M., Godefroid, M., Plattfaut, R., & Niehaves, B. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.02.009 · Cited by 54
Maida, E., Moccia, M., Palladino, R., Borriello, G., Affinito, G., Clerico, M., Repice, A. M., Sapio, A. D., Iodice, R., Spiezia, A. L., et al. (2024) · Journal of Neurology · doi:10.1007/s00415-024-12328-x · Cited by 54
Tuncer, G. Z., & Tuncer, M. (2024) · Digital Health · doi:10.1177/20552076241277025 · Cited by 57
Maxwell, D., Oyarzun, B., Kim, S., & Bong, J. Y. (2025) · TechTrends · doi:10.1007/s11528-025-01109-6 · Cited by 80
Dergaa, I., Fekih‐Romdhane, F., Glenn, J. M., Fessi, M. S., Chamari, K., Dhahbi, W., Zghibi, M., Bragazzi, N. L., Aissa, M. B., Guelmami, N., et al. (2023) · New Asian Journal of Medicine · doi:10.61838/kman.najm.1.2.4 · Cited by 47
How Do Employees Form Initial Trust in Artificial Intelligence: Hard to Explain But Leaders Help
Xu, Y., Huang, Y., Wang, J., & Zhou, D. (2022) · Asia Pacific Journal of Human Resources · doi:10.1111/1744-7941.12402 · Cited by 56
Çayak, S. (2024) · Journal of Educational Technology and Online Learning · doi:10.31681/jetol.1490307 · Cited by 47
Pre-Service Turkish Language Teachers’ Anxiety and Attitudes Toward Artificial Intelligence
Eyüp, B., & Kayhan, S. (2023) · International Journal of Education and Literacy Studies · doi:10.7575/aiac.ijels.v.11n.4p.43 · Cited by 46
Avoiding excessive AI service agent anthropomorphism: examining its role in delivering bad news
Mulcahy, R. F., Riedel, A. S., Keating, B. W., Beatson, A., & Letheren, K. (2023) · Journal of Service Theory and Practice · doi:10.1108/jstp-04-2023-0118 · Cited by 48
Liu, Y., Park, Y., & Wang, H. (2024) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2024.104176 · Cited by 50
Developing and Validating a Scale of Artificial Intelligence Anxiety Among Chinese EFL Teachers
Liu, X., & Liu, Y. (2025) · European Journal of Education · doi:10.1111/ejed.12902 · Cited by 49
Wang, G., Obrenovic, B., Gu, X., & Godinić, D. (2025) · Current Psychology · doi:10.1007/s12144-025-07357-2 · Cited by 52
Haesevoets, T., Verschuere, B., & Roets, A. (2025) · Government Information Quarterly · doi:10.1016/j.giq.2025.102029 · Cited by 45
Personality and acceptance as predictors of ChatGPT use
de Winter, J., Dodou, D., & Eisma, Y. B. (2024) · Discover Psychology · doi:10.1007/s44202-024-00161-2 · Cited by 43
Liu, J. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2544006 · Cited by 43
The key role of design and transparency in enhancing trust in AI-powered digital agents
Glassberg, I., Brender‐Ilan, Y., & Zwilling, M. (2025) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2025.100770 · Cited by 42
On artificial intelligence and global mental health
Montag, C., Ali, R., Al‐Thani, D., & Hall, B. J. (2023) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2023.103855 · Cited by 40
Affective neuroscience theory and attitudes towards artificial intelligence
Montag, C., Ali, R., & Davis, K. L. (2024) · AI & Society · doi:10.1007/s00146-023-01841-8 · Cited by 42
Karaarslan, D., Kahraman, A., & Ergın, E. (2024) · Journal of Pediatric Nursing · doi:10.1016/j.pedn.2024.04.031 · Cited by 40
Türk, N., Batuk, B., Kaya, A., & Yıldırım, O. (2025) · BMC Psychology · doi:10.1186/s40359-025-03559-2 · Cited by 38
Wen, F., Li, Y., Zhou, Y., An, X., & Zou, Q. (2024) · Journal of Educational Technology Development and Exchange · doi:10.18785/jetde.1701.07 · Cited by 39
Students’ GAI Acceptance: Role of Demographics, Creative Mindsets, Anxiety, Attitudes
Avcı, Ü. (2024) · Journal of Computer Information Systems · doi:10.1080/08874417.2024.2386545 · Cited by 40
Zhang, T., & Tong, Q. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2429889 · Cited by 39
Teachers’ artificial intelligence (AI) literacy: an exploratory study
Deshen, M., Harari, R., & Aharony, N. (2026) · Smart Learning Environments · doi:10.1186/s40561-026-00433-5 · Cited by 40
Boztepe, H., Akdeniz Kudubeş, A., Semerci Şahin, R., Durmuş Sarıkahya, S., & Çınar Özbay, S. (2025) · Nurse Education in Practice · doi:10.1016/j.nepr.2025.104568 · Cited by 38
Uludağ, F., Kılıç, E., & Çelik, H. E. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-05641-x · Cited by 41
The mediating role of security anxiety in internet threat avoidance behavior
Wang, X., Li, Y., Khasraghi, H. J., & Trumbach, C. C. (2023) · Computers & Security · doi:10.1016/j.cose.2023.103429 · Cited by 41
How future work self salience shapes the effects of interacting with artificial intelligence
Voigt, J., & Strauss, K. (2024) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2024.104054 · Cited by 41
Irgang, L., Sestino, A., Barth, H., & Holmén, M. (2025) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2024.123967 · Cited by 40
Lee, S., Jones-Jang, S. M., Chung, M., Kim, N., & Choi, J. (2024) · Information Research an international electronic journal · doi:10.47989/ir291647 · Cited by 36
Türkçe Öğretmeni Adaylarının Yapay Zekâya Yönelik Tutumlarının İncelenmesi
SARİKAYA, B., & KAVAN, N. (2024) · Elektronik Eğitim Bilimleri Dergisi · doi:10.55605/ejedus.1550010 · Cited by 36
AI anxiety and knowledge payment: the roles of perceived value and self-efficacy
Chen, J., He, M., & Sun, J. (2025) · BMC Psychology · doi:10.1186/s40359-025-02510-9 · Cited by 42
Madathil, J. C. (2025) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2025.104381 · Cited by 36
Blösser, M., & Weihrauch, A. (2023) · European Journal of Marketing · doi:10.1108/ejm-01-2023-0009 · Cited by 35
The Roles of Social Perception and AI Anxiety in Individuals’ Attitudes Toward ChatGPT in Education
Wang, C., Li, X., Liang, Z., Sheng, Y., Zhao, Q., & Chen, S. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2365453 · Cited by 38
Attitudes and anxiety levels of nursing students toward artificial intelligence
Sarman, A., & Tuncay, S. (2024) · Teaching and learning in nursing · doi:10.1016/j.teln.2024.12.006 · Cited by 43
Uygungil-Erdogan, S., Şahin, Y., Sökmen-Alaca, A. İ., Oktaysoy, O., Altıntaş, M., & Topçuoğlu, V. (2025) · Behavioral Science · doi:10.3390/bs15030249 · Cited by 32
The influence of mental state attributions on trust in large language models
Colombatto, C., Birch, J., & Fleming, S. M. (2025) · Communications Psychology · doi:10.1038/s44271-025-00262-1 · Cited by 34
“Each point represents one participant (total N = 410), and error bands represent 95% con fi dence intervals. systems may shape attributions of speci fi c mental capacities, users ’ beliefs may also depend on characteristics of the users themselves, such as demo-graphics or personality traits 27 – 29 .”
Motivation, Concerns, and Attitudes Towards AI: Differences by Gender, Age, and Culture
Rahman, M. M., Babiker, A., & Ali, R. (2024) · Lecture notes in computer science · doi:10.1007/978-981-96-0573-6_28 · Cited by 48
Montag, C., & Ali, R. (2025) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-025-00481-7 · Cited by 34
Development and psychometric evaluation of the artificial intelligence attitude scale for nurses
Yıldırım, T. Ö., & Karaman, M. (2025) · BMC Nursing · doi:10.1186/s12912-025-03098-6 · Cited by 36
User Characteristics in Explainable AI: The Rabbit Hole of Personalization?
Nimmo, R., Constantinides, M., Zhou, K., Quercia, D., & Stumpf, S. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642352 · Cited by 39
Obenza, B. N., Caballo, J. H. S., Caangay, R. B. R., Makigod, T. E. C., Almocera, S. M., Bayno, J. L. M., Camposano, J. J. R., Cena, S. J. G., Garcia, J. A. K., Labajo, B. F. M., et al. (2024) · American Journal of Applied Statistics and Economics · doi:10.54536/ajase.v3i1.2510 · Cited by 35
Generative Artificial Intelligence as a Lifelong Learning Self Efficacy: Usage and Competence Scale
Arslankara, V. B., & Usta, E. (2024) · Journal of Teacher Education and Lifelong Learning · doi:10.51535/tell.1489304 · Cited by 32
Wang, X., Lin, X., & Shao, B. (2024) · Journal of Business Ethics · doi:10.1007/s10551-024-05894-7 · Cited by 33
Alamäki, A. V., Khan, U. A., Kauttonen, J., & Schlögl, S. (2024) · Education Sciences · doi:10.3390/educsci14121386 · Cited by 31
Cecil, J., Kleine, A., Lermer, E., & Gaube, S. (2025) · BMC Health Services Research · doi:10.1186/s12913-025-12715-8 · Cited by 39
Are Turkish pre-service teachers worried about AI? A study on AI anxiety and digital literacy
Ayduğ, D., & Altınpulluk, H. (2025) · AI & Society · doi:10.1007/s00146-025-02348-0 · Cited by 31
Falebita, O. S. (2024) · Interdisciplinary Journal of Education Research · doi:10.38140/ijer-2024.vol6.20 · Cited by 30
The role of personality traits in predicting educational use of generative AI in higher education
Arpacı, İ., Kuşci, İ., & Gibreel, O. (2025) · Scientific Reports · doi:10.1038/s41598-025-16339-0 · Cited by 30
The impact of AI anxiety on career decisions of college students
Duan, N., Li, L., Lin, G., & Chen, H. (2026) · Scientific Reports · doi:10.1038/s41598-026-37648-y · Cited by 30
The Impact of Gender, Seniority, Knowledge, and Interest on Attitudes to Artificial Intelligence
Kovačević, A., & Demić, E. (2024) · IEEE Access · doi:10.1109/access.2024.3454801 · Cited by 29
Falebita, O. S. (2024) · Journal of Mathematics Instruction Social Research and Opinion · doi:10.58421/misro.v4i1.309 · Cited by 29
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review