Moderating Role of General Attitude Towards Artificial Intelligence in The Relationship Between Attitudes Towards Medical Error and Proactive Behavior
Öz
Purpose: The aim of this study is the investigation of the moderating role of general attitudes towards artificial intelligence in the relationship between medical error attitudes (causes of medical errors and medical error approaches) and proactive behaviour, within the context of social cognitive theory. Methodology: The study was conducted using a quantitative research approach. The study sample included 399 healthcare workers identified using convenience sampling. The research data were collected at two different points in time using a time-lagged data collection method; analyses were carried out after the data obtained from the two data collection processes were matched. Findings: The research found that both the causes of medical errors and medical error approaches have a positive and significant effect on proactive behaviour. Similarly, it was found that general attitudes towards artificial intelligence also have a positive effect on proactive behaviour. However, the results of the moderation analysis indicate that general attitudes towards artificial intelligence act as a moderator in the effect of the causes of medical errors and medical error approaches on proactive behaviour. Accordingly, it was determined that where general attitudes towards artificial intelligence are high, the positive effect of the causes of medical errors and medical error approaches on proactive behaviour is weakened. Originality: This study contributes to extending Social Cognitive Theory in the context of attitudes toward emerging technologies such as artificial intelligence in healthcare. The findings demonstrate that the influence of individual cognitive factors on behaviour differs across contexts and contribute to the literature by explaining the relationship between attitudes toward medical errors, general attitudes toward artificial intelligence, and the proactive behaviour of healthcare professionals.
Anahtar Kelimeler
- General attitude towards artificial intelligence
- Attitude towards Medical error
- Proactive behaviour
- Social cognitive theory
- Health workers
Destekleyen Kurum
Etik Beyan
Kaynakça
- Al Murshidi, G., ElSayary, A., Ragab, K., & Al Zaabi, A. (2025). Understanding teachers’ adoption of AI: Insights from innovation diffusion and social cognitive theories. Journal of Information Technology Education: Research, 24, Article 35, 1-25. https://doi.org/10.28945/5643
- Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.
- Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52(1), 1–26. https://doi.org/10.1146/annurev.psych.52.1.1
- Bandura, A. (2004). Health promotion by social cognitive means. Health Education & Behavior, 31(2), 143–164. https://doi.org/10.1177/1090198104263660
- Bandura, A. (2010). Social-cognitive theory. In R. B. Ewen, An introduction to theories of personality (7th ed.). Psychology Press.
- Bartlett, J. E., Kotrlik, J. W., & Higgins, C. C. (2001). Organizational research: Determining appropriate sample size in survey research. Information Technology, Learning, and Performance Journal, 19(1), 43–50.
- Batuk, B., Kaya, A., Yıldırım, O., & Türk, N. (2024). Investigation of variables predicting university students’ acceptance levels of generative artificial intelligence. 25. Uluslararası Psikolojik Danışmanlık ve Rehberlik Kongresi, Ankara.
- Bekar, F. (2022). İşin anlamlılığı ve işe yabancılaşmanın proaktif davranış ile ilişkisi: İşte kendini geliştirmenin aracılık etkisi [Yayımlanmamış doktora tezi]. Gümüşhane Üniversitesi Lisansüstü Eğitim Enstitüsü.
Ayrıntılar
Birincil Dil
İngilizce
Konular
Örgütsel Davranış
Bölüm
Araştırma Makalesi
Yazarlar
Fevziye Bekar
*
0000-0003-1692-4294
Türkiye
Yayımlanma Tarihi
4 Ekim 2026
Gönderilme Tarihi
6 Mart 2026
Kabul Tarihi
16 Eylül 2026
Yayımlandığı Sayı
Yıl 2026 Cilt: 13 Sayı: 2