Using Simulation to Teach Gender-Affirming Care Concepts in Nursing Education.

BACKGROUND: LGBTQIA+ (lesbian, gay, bisexual, trans-gender, queer or questioning, intersex, asexual), and gender-nonconforming (GNC) individuals have limited access to quality care, leading to health disparities. Lack of training and implicit bias are significant contributors to discrimination. Nursing schools must provide opportunities for student interaction with vulnerable populations, and interacting with transgender and GNC individuals during clinical experiences may be challenging. METHOD: Simulated experiences offer opportunities for students to develop clinical competencies. Students participated in a simulation on caring for transgender and GNC populations. Students participated in a prebriefing session, viewed a simulation video, and engaged in a debriefing session. Participants completed a pre- and postsurvey to assess their knowledge and perceived confidence. RESULTS: Students' confidence in providing gender affirming care was improved by the activity. CONCLUSION: Students prioritize providing competent care to vulnerable populations. In-class simulation is an effective method for improving students' clinical competencies in a safe, nonjudgmental setting. [J Nurs Educ. 2024;63(4):241-246.].

Creating Structures to Support Quality Matters Certification Within a School of Nursing.

BACKGROUND: Best practices for online course design aim to improve teaching and learning by emphasizing the relationship between a course's learning outcomes and all other parts of the course, from assessments to technology to student interaction with peers and instructors. The transition and expanded opportunities to online or hybrid learning in nursing education demonstrate the need for quality online learning experiences. METHOD: A university initiative to ensure high quality remote courses focused on expanding Quality Matters (QM) certification of hybrid and online courses, which ensures that a course has been developed according to standards for online learning. RESULTS: Currently, 20 courses within a school of nursing are QM certified with 4 more actively preparing for formal review this academic year. CONCLUSION: This experience can aid schools to develop faculty competencies in evidence-based, online navigation and course design, and systematically improve the online learning experiences for all students. [J Nurs Educ. 2024;63(4):205-211.].

Guidelines to support newly qualified professional nurses for effective clinical practice.

BACKGROUND:  Transitioning to a professional role is difficult for newly qualified professional nurses. Given the challenges that these nurses experience during the transition to practice, support is essential for them to become efficient, safe, confident, and competent in their professional roles. OBJECTIVES:  The purpose of this study was to explore the transition experiences of newly qualified professional nurses to develop a preceptorship model. METHOD:  This study employed a qualitative approach to purposively collect data. Concept analyses were conducted applying the steps suggested by Walker and Avant, and the related concepts were classified utilising the survey list of Dickoff, James and Wiedenbach's practice theory. RESULTS:  A preceptorship model for the facilitation of guidance and support in the clinical area for newly qualified professional nurses was developed. The model consists of six components, namely, the clinical environment, the operational manager and preceptor, the newly qualified professional nurse, the preceptorship, the assessment of learning, and the outcome. CONCLUSION:  The study revealed that newly qualified professional nurses face many transition challenges when entering clinical practice. They are thrown far in, experience a reality shock, and are not ready to start performing their professional role. The participants agreed that guidance and support are needed for their independent practice role.Contribution: The preceptorship model for newly qualified professional nurses would be necessary for the transition period within hospitals. This preceptorship model may be implemented by nursing education institutions as part of their curriculum to prepare pre-qualifying students for the professional role.

Final-year nursing students' perceptions of humanistic education in nursing: a cross-sectional descriptive study.

BACKGROUND: Humanistic education is an important part of nursing education. Final-year nursing students' perceptions of nursing humanistic education are under-investigated. This study aimed to examined final-year nursing students' perceptions of nursing humanistic education in both school and hospital. METHODS: This was a cross-sectional descriptive study conducted from May to June 2022 among 107 final-year nursing students with a self-designed questionnaire. RESULTS: Final-year nursing students recognized the importance of humanistic education, scoring above 4.0 on a 1-5 scale, while their initiative to enhance humanistic qualities was relatively low. Students' satisfaction with the number of humanities courses offered was only 3.7 ± 0.862. Moreover, 62.6% of students believed there was a need to enhance humanistic environmental development including corridor culture. The "monotonous teaching format" (63.6%) and "teaching methods" (64.5%) have emerged as focal points that students identified as needing attention and improvement. CONCLUSIONS: In the future, nursing humanistic education can be enhanced by increasing the proportion of humanities, improving teaching methods, stimulating students' learning motivation, and strengthening the construction of humanistic environment.

Effectiveness of gamification in nursing degree education.

Background: Previous research in nursing has found favorable results from the use of teaching methodologies alternative to lectures. One of the complementary methodologies used for university teaching is gamification, or the inclusion of game elements, creating a dynamic learning environment that allows the acquisition of knowledge and the development of other skills necessary for nursing students. The purpose of this study was to evaluate the effect of a gamification session on student satisfaction and knowledge scores in nursing students in simulated laboratory practice. Methods: A pre-post quasi-experimental study was conducted with 122 students from the nursing degree program who participated in the research. The evaluation consisted of four sessions of three hours each. In two sessions, participants were trained through a vertical methodology, by means of theoretical training provided by teaching staff, and two hours of clinical simulation, where the students were able to practice the techniques on professional simulators. At the other two sessions, participants received an explanation of the theoretical aspects of the session, one hour of clinical simulation, and one hour of gamification, in which they had to pass tests based on the performance of practical activities on the subject of the session. At the end of the gamification session, all the participants received a certificate as winners of the "nursing game". Results: There was an improvement in the satisfaction and the knowledge level in the gamification sessions. Both were statistically significant (P < 0.001). There was an improvement in the items related to the development of critical thinking and the mobilizing concepts from theory to practice in the gamification sessions. Conclusion: The intervention was effective in improving the satisfaction of the sessions received and in knowledge development.

["L'étudiant expert", a podcast for student nurses]. / "L'étudiant expert", un podcast à destination des étudiants infirmiers.

For the past three years, the Institut de formation interhospitalier Théodore-Simon (Ifits) has been embarking on a magnificent adventure to meet its student nurses, collecting their words and testimonials in a series of podcasts, the main aim of which is to shed as much light as possible on the reality of nursing studies. This article retraces the genesis of the project and demonstrates the added value of this tool for future professionals and trainers alike.

Clinical virtual simulation: predictors of user acceptance in nursing education.

BACKGROUND: Using virtual patients integrated in simulators expands students' training opportunities in healthcare. However, little is known about the usability perceived by students and the factors/determinants that predict the acceptance and use of clinical virtual simulation in nursing education. OBJECTIVES: To identify the factors/determinants that predict the acceptance and use of clinical virtual simulation in learning in nursing education. METHODS: Observational, cross-sectional, analytical study of the use of clinical virtual simulation in nursing to answer the research question: What factors/determinants predict the acceptance and use of a clinical virtual simulator in nursing education? We used a non-probabilistic sampling, more specifically a convenience sample of nursing degree students. The data were collected through a questionnaire adapted from the Technology Acceptance Model 3. In technology and education, the Technology Acceptance Model is a theoretical model that predicts the acceptance of the use of technology by users. RESULTS: The sample comprised 619 nursing students, who revealed mean values of perceived usefulness (M = 5.34; SD = 1.19), ease of use (M = 4.74; SD = 1.07), and intention to use the CVS (M = 5.21; SD = 1.18), in a Likert scale of seven points (1-the worst and 7 the best possible opinion). This study validated the use of Technology Acceptance Model 3 adapted and tested the related hypotheses, showing that the model explains 62% of perceived utility, 32% of ease of use, and 54% of intention to use the clinical virtual simulation in nursing by nursing students. The adequacy of the model was tested by analysis of the direct effects of the relationships between the internal constructs (PU-BI, ß = 0.11, p = 0.012; PEOU-BI, ß = -0.11, p = 0.002) and the direct relations between some of the constructs internal to the Technology Acceptance Model 3 and the external determinants Relevance for learning and Enjoyability. In the proposed model, the external constructs that best predicted perceived usefulness, ease of use, and behaviour intention to use the clinical virtual simulation in nursing were Relevance for learning and Enjoyability. CONCLUSIONS: These study results allowed us to identify relevance for learning and enjoyability as the main factors/determinants that predict the acceptance and use of clinical virtual simulation in learning in nursing.

[The Future of Nursing Education: Necessary Elements and Implementation Strategies for Learning Artificial Intelligence].

As populations age, average life expectancy increases and the complexity of diseases rises, leading to nursing care and healthcare systems facing severe challenges related to inadequate resources. Artificial intelligence (AI), including elements such as investigation, integration, learning, prediction, and decision-making, holds significant potential for application in clinical care not only to enhance care quality but also to help guide the future direction of healthcare. AI applications are already being increasingly utilized to improve the quality of clinical care and to streamline workflows. However, because nursing education has lagged behind in terms of adopting AI, greater attention must be given to training up nursing students with AI-related knowledge and application skills. AI technologies should be integrated into nursing curricula and clinical internships to adapt to the rapidly changing high-tech healthcare environment, enabling the more-effective use of AI technology in providing high-quality and safe nursing care.

[Embracing the Era of Artificial Intelligence: Innovation and Preparation in Nursing Education].

Rapid recent advances in information technology have opened the door for artificial intelligence (AI)-related technologies to be applied extensively across many industries. The Ministry of Education has emphasized the importance of cultivating advanced-level professionals in diverse fields, particularly in smart machinery, the Asia-Silicon Valley sector, green energy technology, biotechnology, national defense, new agricultural, and circular economy industries, to enhance innovation and promote industrial competitiveness (Kuo, 2019). While interdisciplinary talent in AI and digital innovation is being actively developed elsewhere, nursing education remains in the exploratory phase of AI and digital technology talent cultivation. Although AI is now a well-known term, the competencies required for its application in nursing remain unclear. Moreover, most nursing professionals are unfamiliar with how to best integrate AI into nursing expertise or practice settings. With the application of AI in the healthcare industry now unstoppable, it is vital to consider how to help nursing students adapt to healthcare's new technology landscape (Huang et al., 2021). AI facilitates the digital simulation of human thought patterns, logic, and behaviors with the goal of assisting human users solve problems, especially those that are time-consuming and require repetitive processing. The development of AI requires interdisciplinary collaboration among domain experts, data scientists, software engineers, robotics experts, and computer programmers. Such collaboration is essential to developing products able to meet the demands of the times and to help students become competent future nursing professionals (Murray, 2018). Nurses spend the most time interacting with patients and are thus best able to understand the perceptions and challenges of patients and their families. Collaborating with professionals from interdisciplinary fields is the best strategy for achieving optimal healthcare outcomes. However, nursing schools have yet to provide a clear response to the impact of AI on nursing education. Nursing educational institutions must enable nursing students to comprehend the concepts and principles of AI and equip them with AI literacy to allow them to unleash their potential, continuously innovate, and stay abreast with the times (Ng et al., 2021). In this issue, experts and scholars currently engaged in AI-related research in the nursing discipline share their research findings in the realms of machine learning, deep learning, emotional recognition, and natural language application. These articles offer insights into the implications of AI, suggest how nursing education may best respond to emerging AI trends, and provide the authors' perspectives on nursing education reform. The editor hopes readers will be inspired to explore new concepts, gain a deeper understanding of the application and significance of AI, and apply AI to address clinical and educational challenges to foster competent nursing professionals for tomorrow.

[Subverting the Future of Teaching: Artificial Intelligence Innovation in Nursing Education].

Artificial intelligence (AI) technologies, including machine learning, deep learning, natural language processing, generative AI, the metaverse and other iterations, are rapidly changing the landscape of education. Related technologies not only enhance the teaching and learning process but also improve the quality and availability of educational content. AI facilitates educational transformation, reshapes teaching models, and helps students achieve their personalized learning needs, thus improving learning outcomes, learning efficiencies, and teaching practices. Despite the many AI application cases in nursing management and clinical practice, the application of AI in nursing education remains in its infancy. Machine learning has been used to predict the academic performance and graduation results of nursing students, thereby facilitating the early identification of additional support needs. Natural language processing technology has been used to develop chatbots and virtual teachers to assist learning, providing personalized learning support to help students overcome learning obstacles. Also, generative AI technologies such as ChatGPT (chat generative pre-trained transformer) have been used to create simulated patient cases and as a tool for grading academic writing automatically. Moreover, the combination of generative AI technology and the metaverse has introduced new possibilities to nursing education, allowing students to learn in a more-immersive virtual environment. Despite the significant benefits brought by AI to nursing education, its implementation and integration still face multiple challenges, including high costs, the need to provide technical training to teachers, and the need to address issues such as academic integrity and data privacy. The authors hope this article will help promote interdisciplinary cooperation between nursing educators and information and communication experts and the development of AI-assisted teaching to open a new chapter in nursing education.

Core components of end-of-life care in nursing education programs: a scoping review.

BACKGROUND: So far, there have been many studies on end-of-life nursing care education around the world, and in many cases, according to the cultural, social, and spiritual contexts of each country, the results have been different. The present study intends to gain general insight into the main components of end-of-life care in nursing education programs by reviewing scientific texts and the results of investigations. METHODS: This study was a scoping review conducted with the Arksey and O'Malley methodology updated by Peters et al. First, a search was made in Wos, ProQuest, Scopus, PubMed, Science Direct, Research Gate, and Google Scholar databases to find studies about end-of-life care education programs. Then, the screening of the found studies was done in four stages, and the final articles were selected based on the inclusion and exclusion criteria of the studies. Due to the nature of the research, editorials, letters, and commentaries were excluded. The screening steps are shown in the PRISMA-ScR diagram. RESULTS: 23 articles related to end-of-life care education programs were reviewed. The studies included eleven descriptive and cross-sectional studies, two qualitative studies, eight interventional studies, one concept analysis article, and one longitudinal study. By summarizing the data from the studies, six themes were obtained as the main components of end-of-life care education: principles of end-of-life care, communication skills, physical considerations, psychosocial and spiritual considerations, ethical considerations, and after-death care. CONCLUSION: End-of-life care is one of the most challenging nursing care in the world. Since many nurses are not prepared to provide such care, the information obtained from this review can help nursing education and treatment managers develop more comprehensive training programs to improve the quality of end-of-life care.

Doctoral Nursing Education: Year 1 Survival Tips.

The inaugural year of a doctoral nursing program is a challenging transition from a clinical practitioner to a scholarly expert. Drawing on personal and peer experiences, we offer a comprehensive guide for thriving in this transformative period. Covering crucial aspects such as work-life balance, time management, research skills, and self-care, we offer insights to empower future doctoral nursing students, equipping them to confidently navigate the challenges and emerge as successful scholars in the field. [J Contin Educ Nurs. 2024;55(4):157-160.].

The effect of interactive learning method on nursing students' learning of movement requirement: A randomized controlled study.

BACKGROUND: Interactive learning is one of the active learning methods used to develop students' knowledge and skills. OBJECTIVES: This study was conducted to determine the effect of the interactive learning method with questions prepared according to Bloom's taxonomy on nursing students' learning of the need for movement. DESIGN: It is a randomized controlled study conducted in May 2023. PARTICIPANTS: This study was conducted with 134 first-year nursing students taking the Fundamentals of Nursing course. The students were randomly divided into control (n = 67) and experimental (n = 67). METHOD: The data was collected by using a form delineating descriptive characteristics, a test assessing the necessity of movement knowledge, an analysis of a specific case study, and an assessment form for gathering student opinions on interactive learning. The queries within the data collection form were tailored to align with Bloom's taxonomy. Following the theoretical instruction, each student participated in the mobility needs knowledge test and case analysis (pre-test). The instructional session for the control group involved conventional lecture-style teaching supplemented with a question-and-answer format, while the experimental group received instruction through an interactive learning approach. One week subsequent to this, all students retook the mobility needs knowledge test and case analysis (post-test). Subsequently, feedback regarding the interactive learning method was solicited from the students. RESULTS: The knowledge test revealed a statistically significant difference, with the control group exhibiting a higher median comprehension score in the post-test compared to the experimental group (p < 0.05). Regarding the case analysis, statistical analysis demonstrated that the experimental group surpassed the control group in median scores for comprehension, synthesis, and total scores, with a significant difference (p < 0.05). Additionally, most students expressed favorable opinions toward the interactive learning approach. CONCLUSIONS: It is recommended that studies on interactive learning be repeated in different subjects in nursing education. CLINICALTRIALS: gov ID:NCT05868278.

Enhancing nursing education for Indigenous students: Indigenous nursing students' insights and strategies.

BACKGROUND: Indigenous nursing students contended with far-reaching challenges during the pandemic that significantly altered their experiences of nursing education. These experiences are poorly understood by nursing educators and strategies for Indigenous nursing student success rarely involve the insights of current Indigenous nursing students. AIM: The aim of this article is to offer Indigenous-student derived recommendations regarding strategies for improving their experiences and success within nursing education during the pandemic and beyond. DESIGN AND METHODS: This qualitative study employed an Indigenous methodology including land-based learning, ceremony, and sharing circles. PARTICIPANTS AND SETTING: Indigenous nursing students (n = 17) from a Western Canadian school of nursing participated in one of three sharing circles. RESULTS: Indigenous nursing students recommended institutional and program adaptations along with increases to cultural safety for enhancing their experience in nursing education. Institutional and program strategies included: decreasing course loads and class sizes; an Indigenous-specific cohort; a transition program after course failure; increasing academic supports such as additional clinical skills and academic writing practice. Recommendations for increasing cultural safety included: mandatory and recurrent cultural safety training for faculty, staff and students; differential learning and evaluation strategies; and increased inclusion of Indigenous ceremonies and practices. CONCLUSION: The findings of this study provide insights that can help guide curriculum development, pedagogical approaches, and policy development to improve nursing education for Indigenous students.