Virtual simulation offers a powerful educational tool with considerable, albeit underexplored potential. This technology immerses students in lifelike digital scenarios, fostering the acquisition of knowledge and skills necessary for their future careers. This study aimed to assess knowledge acquisition and satisfaction outcomes among students using a virtual simulation teaching approach. The specific objectives were (1) to compare pre-and posttest knowledge acquisition, (2) to investigate the influence of prior professional experience on knowledge, and (3) to explore satisfaction levels with virtual simulation. One hundred and fifty-nine nursing students participated in a virtual simulation-based clinical intervention, entailing the resolution of a virtual adult patient hospitalized with respiratory pathology. Sociodemographic data and prior professional experience were collected, and knowledge was evaluated through pre-to-post tests. Satisfaction levels were assessed using open-ended questions. Quantitative data were analyzed using descriptive statistics, Wilcoxon, Mann–Whitney U, and Cohen’s tests, while qualitative data underwent keyword-in-context analysis. Significant differences were noted between pre- and posttest knowledge levels, with prior experience showing no significant impact on knowledge acquisition. Participants reported high levels of satisfaction. Lexicometric analysis identified four clusters of words related to the key terms “simulation”, “learn”, “activity”, and “knowledge”. Virtual clinical simulation effectively enhances knowledge acquisition and fosters satisfaction, with students recognizing the positive impact of this approach on their learning. Consequently, virtual simulation contributes to the training of competent health professionals.

Background: Decision making is a pivotal component of nursing education worldwide. This study aimed to accomplish objectives: (1) Cross-cultural adaptation and psychometric validation of the Nursing Anxiety and Self-Confidence with Clinical Decision Making (NASC-CDM©) scale from English to Spanish; (2) Comparison of nursing student groups by academic years; and (3) Analysis of the impact of work experience on decision making. Methods: Cross-sectional comparative study. A convenience sample comprising 301 nursing students was included. Cultural adaptation and validation involved a rigorous process encompassing translation, back-translation, expert consultation, pilot testing, and psychometric evaluation of reliability and statistical validity. The NASC-CDM© scale consists of two subscales: self-confidence and anxiety, and 3 dimensions: D1 (Using resources to gather information and listening fully), D2 (Using information to see the big picture), and D3 (Knowing and acting). To assess variations in self-confidence and anxiety among students, the study employed the following tests: Analysis of Variance tests, homogeneity of variance, and Levene’s correction with Tukey’s post hoc analysis. Results: Validation showed high internal consistency reliability for both scales: Cronbach’s α = 0.920 and Guttman’s λ2 = 0.923 (M = 111.32, SD = 17.07) for self-confidence, and α = 0.940 and λ2 = 0.942 (M = 80.44, SD = 21.67) for anxiety; and comparative fit index (CFI) of: 0.981 for self-confidence and 0.997 for anxiety. The results revealed a significant and gradual increase in students’ self-confidence (p =.049) as they progressed through the courses, particularly in D2 and D3. Conversely, anxiety was high in the 1st year (M = 81.71, SD = 18.90) and increased in the 3rd year (M = 86.32, SD = 26.38), and significantly decreased only in D3. Work experience positively influenced self-confidence in D2 and D3 but had no effect on anxiety. Conclusion: The Spanish version (NASC-CDM-S©) was confirmed as a valid, sensitive, and reliable instrument, maintaining structural equivalence with the original English version. While the students’ self-confidence increased throughout their training, their levels of anxiety varied. Nevertheless, these findings underscored shortcomings in assessing and identifying patient problems.

Introduction: Debriefing as a learning activity aims to elevate participants' competence through communicative interaction. This activity is an integral component of any formative simulation. Thus, the primary objective of this study was to explore debriefing as a communicative experience in nursing students within the context of interactive virtual simulation. The secondary objectives were: 1) To investigate the typology of interactions based on participants' discourse and 2) To identify the actions that students use to develop knowledge during debriefing. Method: A qualitative exploratory study design involving six debriefing groups was conducted with 105 s-year nursing students. The debriefing sessions were analyzed following interactive virtual simulations in an in-person setting in the classroom. All sessions were recorded and transcribed verbatim. A mixed (deductive and inductive) content analysis approach was used. Results: A total of 2187 units of meaning were identified and categorized into 3 themes (interaction by participant, interaction by communicative action, and interaction by participant's communicative goal); nine subthemes (facilitator-student, student-student and student-facilitator; declarative - unidirectional, reactive - bidirectional and multidirectional-interactive; individualistic, competitive, and collaborative), and 5 categories (providing information; generating creative solutions; processing critical and deliberative information; positive interdependence and psychosocial relationships). Conclusion: The students developed knowledge and practical communication skills, particularly reinforcing soft skills through collaborative interactions, predominantly multidirectional-interactive in nature. The facilitator and the interpersonal relationships among the participants fostered a safe and positive environment.

Empathy is central to humanised nursing but vulnerable to erosion in demanding academic and clinical settings. Positive mental health (PMH) encompassing emotional, psychological, and social well-being, may regulate how self-compassion is statistically linked to empathic engagement. However, evidence in nursing students remains limited. To examine the statistical association of positive mental health in the relationship between self-compassion and empathy among undergraduate nursing students within a structural equation modelling (SEM) framework. Observational, analytical, cross-sectional study. A total of 402 nursing students from a public university completed validated measures of self-compassion, empathy, and PMH. SEM with latent variables was conducted using diagonally weighted least squares (DWLS) to account for ordinal and non-normal data. Model fit was assessed using multiple indices, acknowledging the complexity of the latent structure. Self-compassion was positively associated with PMH (β = 0.772, p < 0.001), which related positively to empathy (β = 0.689, p < 0.001). The indirect effect via PMH was positive (β = 0.532, p < 0.001), while the direct effect of self-compassion on empathy was negative when controlling for PMH (β = -0.553, p < 0.001), indicating an inconsistent mediation pattern. The model explained 59.6% of the variance in positive mental health and 19.3% in empathy. PMH appears to be a key correlate in the association between self-compassion and empathy. Findings suggest that emotional well-being may be an important foundation for relational competence, although the study's cross-sectional nature precludes causal inferences and the marginal model fit warrants a cautious interpretation. Fostering empathy may require more than interpersonal skills training. Nursing curricula could benefit from integrating positive mental health promotion, including training in self-compassion and emotional regulation, to support empathic and humanised nursing practice across educational and clinical contexts.

Artificial intelligence (AI) is rapidly transforming nursing education and clinical practice. Understanding students' perceptions is essential for designing effective and equitable AI-enhanced learning strategies. The Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) offers a robust model for examining factors that shape acceptance and use. To integrate qualitative evidence on nursing students' perceptions of incorporating AI into academic education, using the UTAUT2 model to interpret constructs influencing acceptance and use. A qualitative deductive meta-synthesis was conducted following Dixon-Woods' framework. A systematic search (October 2024-July 2025) in PubMed, CINAHL, and Web of Science identified qualitative studies and qualitative findings from mixed-method research published between 2020 and 2025. Methodological quality was appraised using ENTREQ guidelines and the Joanna Briggs Institute's Qualitative Assessment and Review Instrument (QARI). Data were thematically synthesized according to UTAUT2 constructs. Nursing students perceive AI as a tool to enhance learning and efficiency (performance expectancy) yet concerns about the complexity and digital competencies persist (effort expectancy). Faculty support and institutional context emerge as key factors in promoting acceptance (social influence and facilitating conditions). Intention to use relates to interest and prior experience (hedonic motivation). Cost remains a barrier (price value), while accumulated experience strengthens adoption (habit). AI represents a valuable resource in nursing education, offering opportunities for personalized learning, improved access to information, and enhanced competency development. Effective integration requires addressing technical, ethical, equity-related, and training barriers. Importantly, AI should complement, rather than replace, the human dimension of nursing education.