Artificial intelligence can be an important tool in developing creative thinking while supporting individualized learning and problem-solving skills in educational processes. However, the effect of artificial intelligence on creative thinking may differ depending on factors such as students’ digital literacy level and the academic support they receive. In this context, how artificial intelligence can encourage creative thinking in educational processes and how this process is shaped by digital literacy and academic support stands out as an issue to be investigated. This study artificial intelligence to determine the effect of artificial intelligence use on creative thinking skills in nursing students, the mediating role of digital literacy in this effect, and the situational mediating effect of academic support. This cross-sectional and descriptive correlational study was conducted with 426 nursing students from three universities in different regions of Turkey during the fall semester of 2024–2025. Simple random sampling method was used. Data were collected through demographic information form and four valid and reliable scales. Research findings show that using artificial intelligence substantially and significantly affects Creative Thinking (β = 0.70, p < 0.001). Digital literacy plays mediating role in this relationship, indirectly strengthening the effect of artificial intelligence use on creative thinking (β = 0.422, LLCI = 0.357, ULCI = 0.490). As a moderating factor of this relationship, the academic support creates a more limited effect at low levels of academic support (Effect = 0.224). At the same time, it maximizes this effect at high levels of support (Effect = 0.298). The effect of artificial intelligence use on Creative Thinking is significantly strengthened by the mediating role of digital literacy and the moderating role of academic support. These findings suggest that developing digital skills and strengthening academic support mechanisms are critical to integrating artificial intelligence technologies into educational processes. Artificial intelligence significantly increases the creative thinking tendencies of nursing students both directly and through digital literacy. The academic support is a critical factor that strengthens the development of creative thinking skills by regulating the effect of artificial intelligence usage on digital literacy. Integrating artificial intelligence applications into the curriculum and developing digital literacy skills in nursing education programs can potentially increase the creative thinking and problem-solving competencies of 21st-century health professionals.

Background and Objectives: Checkpoint kinase 2 (CHEK2) is a tumor suppressor gene involved in DNA repair and cell cycle regulation. Pathogenic or likely pathogenic (P/LP) variants in CHEK2 are associated with increased cancer risk. Conversely, recent large cohort studies have identified certain variants that, despite being classified as P/LP by in silico analysis, are considered low risk. Thus, the genotype–phenotype correlations of CHEK2 require a better understanding. In this study, we aimed to characterize germline CHEK2 variants from a group of individuals who applied to cancer genetic clinics in the Marmara Region of Türkiye. We also aimed to assess the phenotypic impacts of these variants by using a new score of statistically significant in silico predictors (SSIPs). Methods: We analyzed 1707 individuals with high risk cancer predisposition, focusing on germline CHEK2 variants, using SSIP scores and population-specific data. Results:CHEK2 variants appeared in approximately 8% of cases. The SSIP scores indicated that the missense mutation, p.Arg117Gly, significantly impairs DNA repair. Almost half of the variants had higher allele frequencies than the variants listed in the Genome Aggregation Database (gnomAD), and three variants had significantly higher frequencies compared to the variants listed on the Turkish Variome database (p.Thr476Met, p.Arg137Gln, c.592+3A>T), emphasizing the importance of population-specific data. Conclusions: This comprehensive analysis of CHEK2 variants in the Turkish population provides crucial insights for cancer geneticists and oncologists. Our findings will help to enhance the evaluation and management of cancer predisposition associated with CHEK2 in Türkiye and other regions that have significant Turkish populations.