Background/Objectives: Culturally competent nursing care is essential in multicultural settings, but organizational conditions may influence its delivery. This study examined the association between the nursing practice environment and culturally competent behaviors among surgical nurses in Riyadh, Saudi Arabia, and whether this association remained significant after adjustment. Methods: This multicenter cross-sectional study included 422 surgical nurses recruited by convenience sampling from January to March 2026. Participants completed the 31-item Practice Environment Scale of the Nursing Work Index (PES-NWI) and the 14-item Cultural Competence Behaviors (CCB) subscale of the Cultural Competence Assessment. Analyses included descriptive statistics, Cronbach’s alpha, Spearman’s rank correlation, and an adjusted general linear model with heteroscedasticity-consistent type 3 (HC3)-robust standard errors. Results: The mean PES-NWI score was 3.04 ± 0.46; nursing foundations for quality of care had the highest domain score (3.16 ± 0.43), whereas staffing and resource adequacy had the lowest (2.87 ± 0.63). Among the 404 participants with valid CCB scores, the mean CCB score was 4.48 ± 1.53. The PES-NWI composite score showed a moderate positive association with CCB (ρ = 0.303, p < 0.001). The adjusted model was statistically significant (F(14, 389) = 8.28, p < 0.001; R² = 0.230). Adding the PES-NWI composite score explained an additional 9.1% of the variance in CCB (ΔR² = 0.091, p < 0.001); the adjusted association remained positive (B = 1.037, HC3-robust standard error = 0.172, 95% confidence interval = 0.699–1.375, p < 0.001). Conclusions: The nursing practice environment had a moderate positive unadjusted association with CCB, and this association remained statistically significant after adjustment. Longitudinal studies are needed to clarify the temporal direction of this relationship.

Background: Generative artificial intelligence (AI) tools are increasingly used in academia to retrieve information, draft manuscripts, and support learning activities. Despite growing research on AI use and literacy in academia, few studies have examined negative perceptions of such use. This study aimed to assess the relationship between AI literacy and fear of negative evaluation among students and researchers in Saudi Arabia. Methods: A cross-sectional, correlational, descriptive study was conducted among researchers and students from private and public institutions. Data were collected from August to October 2025 using the Meta Artificial Intelligence Literacy Scale and the Brief Fear of Negative Evaluation Scale. Data were analyzed using an independent t-test and multiple linear regression. Results: Among the 154 participants who responded to the questionnaire, moderate AI literacy and low fear of negative evaluation were reported, with strongest agreement on evaluating AI’s advantages and disadvantages and on solving complex tasks. However, researchers reported significantly stronger concerns than students across multiple items, particularly on items related to being judged when using AI. Age and AI self-efficacy were significant positive predictors of fear of negative evaluation, indicating that older participants and those with higher AI confidence reported slightly higher levels of concern. Conclusions: This study highlights the need for structured AI education, clear guidelines, and supportive environments to ensure responsible and confident use. Despite the low overall fear of negative evaluation, researchers’ concerns about using AI highlight the importance of supportive environments and clear guidelines. Stronger concern among older and more confident participants indicates the need to reinforce ethical practice and accountability to promote confident, responsible engagement with AI.