Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 17 appraisals
Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Telehealth Competency Evaluation Tools: A Scoping Review
INTRODUCTION: Telehealth is an integral part of healthcare. Exposure to telehealth education is essential for both students and health care professionals to support its effective adoption and appropriate utilization. This scoping review aims to explore whether and which telehealth competencies are being assessed and the methods used to evaluate them among health care professionals and students. METHODS: An electronic literature search was performed using six electronic databases between January 2024 and February 2025. We included studies where telehealth competencies or their components were evaluated by some type of tool (validated or researcher created). Strict inclusion and exclusion criteria were used, and each article was evaluated by at least two reviewers. RESULTS: Out of 1,217 articles screened by title and abstract, 75 met inclusion criteria, with 36 of those selected for inclusion in this review. Participants were evaluated mostly by researcher-created tools that lacked psychometric properties or adapted nontelehealth evaluation tools. Few validated/reliable tools directly measured telehealth competencies. DISCUSSION: The results of this review illustrate there exists a lack of available validated/reliable evaluation tools to appraise telehealth competencies. Few studies included an evaluation of all telehealth competencies but rather focused only on communication and technology proficiency; none evaluated the appropriate use of telehealth or digital disparities. CONCLUSIONS: More research is needed to develop validated telehealth evaluation tools that can be used across disciplines and encompass all telehealth competencies. Additionally, true research methods are needed to adequately assess the impact of telehealth education on the performance and confidence of learners.
3 Aug 2026
Read appraisal →Simulation in healthcare : journal of the Society for Simulation in Healthcare
Future of Biometric Technology in Healthcare Simulation
Biometric technology shows substantial promise to enhance patient safety and transform provider training. In patient care, biometric technology enables outpatient providers to optimize chronic disease by alerting providers to changes in patient conditions with real-time data. In provider training, biometric technology can inform training environments and curriculum. Certainly, there are hurdles to technology implementation including hardware fragility, cost, and software integration. Despite challenges, biometric technology has been effectively implemented in simulations and real patient settings. Looking forward, future developments focused on data security and privacy, standardizing data collection, and improving system compatibility will facilitate the wider adoption of biometric technology and improve health care quality, especially in resource-limited settings. Collaborative efforts among informatics experts, patient safety advocates, and health care providers are essential to overcome challenges and fully leverage biometric technology's potential in enhancing patient outcomes. The purpose of this commentary is to review current applications, identify key challenges, and offer recommendations to the simulation community for testing biometric technology, use in training programs, and facilitating systems integration to improve outcomes.
2 Aug 2026
Read appraisal →International journal of nursing education scholarship
Effect of concept mapping on critical thinking skills in nursing students: a systematic review with meta-analysis
BACKGROUND: Critical thinking (CT) among nursing students is crucial for delivering high-quality nursing care to patients. Concept mapping (CM) is one of the evidence-based pedagogies that helps to improve CT in individuals. OBJECTIVES: The objective of this review and meta-analysis was to evaluate the impact of concept mapping on CT abilities, academic achievement, and clinical skills in nursing students. METHODS: This systematic review and meta-analysis aimed to identify published articles on the effect of CM on CT in nursing students, written in English and published from 2011 to 2024. The articles were sourced from SCOPUS, Web of Science (WoS), ScienceDirect, Google Scholar, and PubMed databases. To ensure a comprehensive and relevant search, the following MeSH terms were used: "Effectiveness" OR "Impact," AND "Concept Mapping," AND "CT," AND "Nursing Student," AND "RCT" OR "Randomized Controlled Trials" OR "Quasi-Experimental." This study used the Cochrane Collaboration's Risk of Bias (RoB) tool and Standardized Mean Difference (SMD) for outcome measurement, with results analyzed using RevMan Web. RESULTS: This study analyzed 14 RCTs and quasi-experimental studies involving 1,747 participants (E=870, C=877). The meta-analysis found that concept mapping enhanced nursing students' CT skills (MD=4.86, 95 % CI [2.16 to 7.56], p=0.0004), academic achievements (MD=3.38, 95 % CI [0.76 to 5.99], p=0.01), and performance in clinical practice (MD=5.94, 95 % CI [3.22 to 8.65], p<0.0001) when compared to routine instructional methods. CONCLUSIONS: CM provides valuable insights into enhancing CT and clinical skills in nursing students, eventually preparing them to become excellent nursing professionals in the healthcare system.
26 July 2026
Read appraisal →Journal of medical Internet research
AI-Powered Simulation for Nursing Education: Mixed Methods Systematic Review
BACKGROUND: Traditional simulation-based nursing education is often constrained by high costs, resource intensity, and limited scalability. AI-powered simulations offer dynamic, scalable, and personalized alternatives. However, the empirical evidence regarding their pedagogical effectiveness and learner acceptance remains fragmented. OBJECTIVE: This study aimed to systematically evaluate and synthesize evidence on the effectiveness and learner perceptions of AI-powered simulations in nursing education. METHODS: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we systematically searched 11 electronic databases (PubMed, CINAHL, Embase, Web of Science, Cochrane Library, Scopus, SinoMed, CNKI, Wanfang, VIP, and Google Scholar) for studies published between January 2014 and September 2025. Two independent reviewers performed study selection, data extraction, and quality appraisal using design-specific tools (risk of bias 2 tool [RoB 2; Cochrane Bias Methods Group] for randomized controlled trials [RCTs], Risk Of Bias in Nonrandomized Studies of Interventions [ROBINS-I; Cochrane Bias Methods Group] for nonrandomized studies, Mixed Methods Appraisal Tool [MMAT] for mixed methods, Joanna Briggs Institute [JBI] for qualitative, and Agency for Healthcare Research and Quality [AHRQ] for cross-sectional studies). Quantitative data were synthesized narratively, and qualitative findings were integrated using JBI meta-aggregation. A convergent segregated approach with joint display was used to generate meta-inferences. RESULTS: Nineteen studies involving 1253 participants (primarily prelicensure nursing students, with some interdisciplinary cohorts) were included. AI modalities comprised generative AI/large language models (n=7), AI-driven virtual patients/mannequins (n=5), AI-enhanced virtual/mixed reality (n=5), and chatbots (n=2). Three studies were RCTs, 4 were quasiexperimental with control groups, 3 were uncontrolled pre-post studies, 4 were mixed methods, 4 were qualitative, and one was a cross-sectional survey. Quantitative synthesis showed that evidence from RCTs and controlled quasiexperimental studies indicates significant improvements in cognitive knowledge and affective outcomes, including self-efficacy and communication confidence; however, effects on complex psychomotor skills were inconsistent, with one RCT finding AI-assisted simulation inferior to standardized patient simulation. Findings from uncontrolled designs are preliminary. Qualitative meta-aggregation revealed that learners valued safe, repeatable, nonjudgmental practice environments that reduced anxiety and bridged the theory-practice gap. Persistent challenges included technical frustrations, "robotic" interactions, lack of nonverbal cues, and system instability, collectively constituting an "authenticity gap." CONCLUSIONS: AI-powered simulations show promise for developing foundational clinical reasoning and communication skills in nursing education, though the evidence base is limited by the predominance of uncontrolled designs, reliance on self-reported measures, and absence of longitudinal data on skill retention or clinical transfer. Due to current technological limitations in replicating physical and emotional authenticity, AI should be implemented as a complementary tool alongside traditional simulation methods and clinical placements, rather than as a replacement. Future research should prioritize longitudinal outcomes, standardized competency measures, RCTs with active comparators, and implementation strategies addressing technical barriers.
22 July 2026
Read appraisal →BMJ open
Pedagogical strategies for enhancing critical thinking in nursing students using large language models: a mixed-methods systematic review protocol.
INTRODUCTION: Large language models (LLMs) are rapidly normalising in nursing education. However, evidence regarding their impact on critical thinking-a cornerstone of safe clinical practice-remains inconsistent. Current syntheses have largely focused on student satisfaction and general utility, leaving the specific instructional mechanisms that cultivate this competency unexplored. This mixed-methods systematic review aims to identify effective pedagogical strategies for fostering critical thinking, providing evidence-based guidance to safeguard clinical competency in an artificial intelligence-integrated workforce. METHODS AND ANALYSIS: This review will follow a convergent segregated mixed-methods design in accordance with the Joanna Briggs Institute (JBI) methodology. A systematic search will be conducted across CINAHL, ERIC, MEDLINE, PsycINFO and Scopus supplemented by grey literature sources (ProQuest Dissertations, MedRxiv). The search will be limited to English-language studies published from January 2023 to June 2026. Eligible studies will include undergraduate nursing students exposed to structured LLM-based pedagogical interventions. Methodological quality will be appraised using design-specific JBI Critical Appraisal Checklists. Outcomes will be classified using a modified Kirkpatrick framework to distinguish objective competence from subjective confidence. Quantitative data will be synthesised narratively following Synthesis Without Meta-analysis guidelines, and qualitative data thematically. Streams will be integrated using a Joint Display Analysis to generate meta-inferences on effective instructional design. Finally, confidence in the cumulative evidence will be assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE) and GRADE-Confidence in the Evidence from Reviews of Qualitative research. ETHICS AND DISSEMINATION: As a systematic review of existing literature, this study does not require ethical approval. Findings will be disseminated through a peer-reviewed publication, conference presentations and a visual guide for educators.
11 July 2026
Read appraisal →Computers, informatics, nursing : CIN
Bridging the Gap Between Potential and Practice: An Integrative Review of Generative Artificial Intelligence in Nursing
BACKGROUND: Generative artificial intelligence (GAI) has emerged as a transformative tool in health care, particularly with the integration of large language models (LLMs) into electronic health record (EHR) systems. These tools have the potential to enhance clinical decision-making, increase efficiencies, and decrease time in the EHR. However, despite expanding availability, adoption in nursing practice remains limited. This integrative review aimed to synthesize the literature and explore barriers related to the integration of GAI tools into nursing practice. METHODS: We conducted an integrative search of peer-reviewed literature published between November 2022 and July 2025 to examine the current evidence while assessing for methodological quality. The retrieved articles were screened for title, abstract, and full text eligibility. We synthesized themes related to GAI adoption by nurses, focusing on ethical, educational, and workflow-related factors that influence use. RESULTS: A total of 10 studies met criteria including 7 qualitative descriptive design, 2 case reports, and 1 experimental clinical trial. Four key barriers emerged: educational gaps, ethical concerns, data transparency issues, and workflow misalignment contributing to nurses' hesitancy to engage with GAI tools. Recommendations include involvement of nurses in the design, implementation, and evaluation of GAI tools and mandatory AI curricula in nursing education. CONCLUSIONS: Overcoming barriers requires nurse involvement in GAI design efforts, targeted education, and governance models that foster trust and usability. Nurse-centered integration of GAI tools has the potential to advance workforce efficiencies while preserving patient safety.
4 July 2026
Read appraisal →JMIR nursing
Digital Health Literacy and Attitudes Toward Telehealth Use in Practice Among Nursing Students in Saudi Arabia: Cross-Sectional Study
BACKGROUND: Nursing students are the future workforce, and their readiness to use digital health tools is important. Previous studies have focused on knowledge and attitudes; however, they have not examined the wide range of digital health literacy levels that may influence nursing students' attitudes toward using telehealth in clinical settings. OBJECTIVE: This study aimed to determine the relationship between nursing students' digital health literacy and their attitudes toward telehealth use in practice. METHODS: A cross-sectional design was used. The sample consisted of undergraduate nursing students enrolled in a Bachelor of Nursing program at a selected Saudi Arabian university. The online survey used 2 scales: the Digital Health Care Literacy Scale and the Nurses' Attitudes Toward Use of a Telehealth Scale. RESULTS: A total of 273 students participated (mean age 21.3, SD 1.9 years). Most of the nursing students demonstrated a high digital health literacy level (n=184, 67.4%; mean Digital Health Care Literacy Scale score 11.9 out of 15, SD 3.1). Digital health literacy was a significant predictor of positive attitudes toward telehealth use in practice (adjusted odds ratio 1.48, 95% CI 1.28-1.71; P<.001). Male students were significantly less likely to report positive attitudes than female students (adjusted odds ratio 0.62, 95% CI 0.39-0.97; P=.03). However, academic year, telehealth workshops, and informatics courses were not significantly associated with positive attitudes toward telehealth use in practice. CONCLUSIONS: Higher levels of literacy appear to correlate with more positive attitudes toward telehealth use in practice. However, current formal education and workshops had no apparent influence on digital health literacy. This suggests a potential need for strengthening digital training and development in nursing education. This may enhance telehealth readiness and support future digital health care delivery.
24 June 2026
Read appraisal →International journal of nursing education scholarship
Leadership education for nurse practitioners: a systematic review of interventions, pedagogies and gaps
Nurse practitioners (NPs) often lead interprofessional healthcare teams, yet many receive little or no formal leadership training. As healthcare systems grow in complexity and demand greater accountability, the need for strong and effective NP leadership has intensified. However, leadership development within NP education remains poorly defined and often lacks theoretical grounding. This systematic review explores interventions designed to build NP leadership skills. Following PRISMA and BEME Guide No. 13 guidelines, a search (July 2022, updated April 2024) identified peer-reviewed English-language articles from 1980 onward. Studies involving NPs at any training or practice stage were included if they described a leadership intervention. Of 3,058 articles, eight met inclusion criteria. Most studies originated in the U.S., featured isolated leadership interventions, and lacked NP clinical faculty involvement. Experiential learning and mentorship were common. Leadership domains emphasized cognitive and emotional intelligence, with little focus on leader character development. Evaluation of leadership interventions were limited. Overall, few theoretically informed, robust NP leadership interventions exist. Future efforts should prioritize comprehensive, longitudinal, and theory-based approaches to strengthen leadership capacity within NP education and practice.
24 June 2026
Read appraisal →JMIR nursing
Digital Leadership Scale for Clinical Nurses: Development and Validation of an Instrument
BACKGROUND: The rapid advancement of digital technologies, combined with the evolving complexity of health care environments, has introduced a new paradigm in nursing practice. Clinical nurses are now required not only to deliver safe and effective patient care but also to demonstrate competencies in digital literacy and innovation. Among these emerging competencies, digital leadership has become a critical attribute-enabling nurses to lead digital transformation, ensure patient safety, enhance care quality, and support system-level change within health care organizations. Despite its increasing relevance, there is a notable absence of validated measurement tools tailored to assess digital leadership in clinical practice. OBJECTIVE: This study aimed to develop and psychometrically validate a Digital Leadership Scale for Clinical Nurses (DLS-CN) to systematically evaluate the digital leadership capabilities of nurses working in clinical settings. METHODS: The scale development process followed a rigorous multistep procedure. Initial items were derived from previous qualitative research involving a literature review and in-depth interviews, complemented by an additional literature review conducted in this study. The content validity of 38 preliminary items was evaluated by 9 experts over 2 rounds. A pilot test was conducted with 30 nurses, followed by cognitive interviews with 5 nurses to refine item clarity and relevance. The final set of items was administered to 446 clinical nurses across various health care institutions. Data were randomly split for exploratory factor analysis and confirmatory factor analysis. Additional analyses were conducted to evaluate item discrimination, convergent validity, and internal consistency using IBM SPSS 25.0 and AMOS 23.0. RESULTS: The finalized DLS-CN consists of 29 items grouped under four domains: (1) ability to use digital technology, (2) digital safety management, (3) digital collaboration mindset, and (4) organizational influence. These 4 factors explained 56.9% of the total variance. The scale showed strong internal consistency (Cronbach α=0.95). Convergent validity was demonstrated through strong positive correlations with the Nursing Informatics Competency Scale (Pearson correlation coefficient r=0.82; P<.001) and the Self-Leadership Scale (Pearson correlation coefficient r=0.83; P<.001). CONCLUSIONS: The DLS-CN is a valid and reliable instrument for measuring digital leadership among clinical nurses. It offers a practical tool for educators, administrators, and researchers to assess and enhance digital leadership capabilities-ultimately supporting the digital transformation of health care systems.
24 June 2026
Read appraisal →Medical education online
Cross-cultural adaptation and psychometric evaluation of the artificial intelligence learning intention scale (AILIS) among medical sciences students: a methodological study
BACKGROUND: This study aimed to adapt and psychometrically evaluate the Artificial Intelligence Learning Intention Scale (AILIS) among Iranian medical sciences students. METHODS: This methodological psychometric study was conducted among 800 medical sciences students at Babol University of Medical Sciences, Iran. The AILIS was translated and culturally adapted into Persian using a standardized cross-cultural adaptation process. Construct validity was examined through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Reliability was assessed using Cronbach's alpha, McDonald's omega, and the intraclass correlation coefficient (ICC). Convergent and discriminant validity were evaluated using composite reliability (CR) and average variance extracted (AVE). Measurement invariance across gender and structural stability were assessed using multi-group confirmatory factor analysis and exploratory graph analysis (EGA). RESULTS: EFA supported a four-factor structure consisting of Epistemic Capacity, Psychological Attitudes, Facilitating Environments, and Psychological and Behavioral Outcomes, explaining 44.55% of the total variance, with factor loadings greater than 0.40. Confirmatory factor analysis indicated an acceptable model fit, supporting the proposed factor structure (χ²/df = 3.42, RMSEA = 0.078, CFI = 0.932). Internal consistency and test-retest reliability were satisfactory, with Cronbach's alpha ranging from 0.854 to 0.904, McDonald's omega from 0.854 to 0.899, and ICC from 0.750 to 0.860. Composite reliability values were adequate, while AVE values indicated acceptable but partially limited evidence of convergent validity. Discriminant validity was generally supported. In addition, multi-group analysis demonstrated measurement invariance across gender, and exploratory graph analysis confirmed the structural stability of the four-factor model. CONCLUSION: The Persian AILIS is a valid and reliable instrument for assessing AI learning intention among medical sciences students. Beyond its psychometric robustness, the instrument may support curriculum planning, evaluation of AI-related educational interventions, and evidence-based decision-making in medical sciences education by providing a standardized measure of students' intentions to engage with AI learning.
20 June 2026
Read appraisal →JMIR nursing
Assessing Digital Literacy Among Nursing Faculty Under the Artificial Intelligence-Enhanced Technological Pedagogical Content Knowledge Framework: Cross-Sectional Survey Analysis
BACKGROUND: Digital literacy has become a core competence for nursing faculty to adapt to the digital transformation of education, improve teaching quality, and cultivate innovative nursing talents. OBJECTIVE: This study aimed to investigate the digital literacy status and influencing factors among nursing faculty in colleges and universities in Fujian province, China. METHODS: A cross-sectional survey analysis was conducted among 339 participants from July 2023 to June 2024 by selecting nursing faculty from 3 medical universities and 5 colleges in Fujian province. A general information questionnaire and a teacher digital literacy questionnaire (designed based on the artificial intelligence-enhanced technological pedagogical content knowledge theoretical model) were used to conduct the survey. The questionnaires included the following dimensions: an intelligent integration ethics layer (digital social responsibility), attention to the moral boundaries of applying technology; an awareness layer (digital awareness), the willingness to actively adapt to technological changes; a knowledge layer (digital technology knowledge and skills), mastery of the integration point of intelligent tools and subject teaching; an ability layer (digital application), the ability to design intelligent teaching plans; and a thinking layer (professional development; innovative thinking for the critical integration of technology). Statistical analysis included descriptive statistics, a 1-way ANOVA, Pearson correlation analysis, and multiple linear regression (using SPSS 28.0 software). RESULTS: The overall digital literacy of the nursing faculty was at a medium level (mean score 101.92, SD 16.47), with the highest score in digital awareness (mean 20.21, SD 9.43) and the lowest score in digital technology knowledge and skills (mean 9.68, SD 2.92). For the dimension of digital technology knowledge and skills, both age (β=-.142; P=.009) and years of teaching (β=-.147; P=.006) were significant negative predictors. Regarding digital application, age was found to be a significant negative predictor (β=-0.124; P=.02) but teaching experience was a positive predictor (β=0.123, P=.02). Similarly, age also had a significant negative impact on the professional development dimension (β=-.153; P=.005) and the overall digital literacy level (β=-.136; P=.01). CONCLUSIONS: The digital literacy of nursing faculty is at a medium level, with especially low scores in technical knowledge. Age and teaching experience are key influencing factors. Recommendations to promote balanced development of awareness and skills include providing targeted training for senior faculty, integrating courses with clinical practice, optimizing the allocation of digital resources, promoting interdisciplinary cooperation, and strengthening ethical and safety training.
14 June 2026
Read appraisal →JMIR nursing
Simulation-Based Training for Nursing Students to Improve Patient Safety: Systematic Review
BACKGROUND: Patient safety is a fundamental pillar of health care quality. Simulation-based training provides a controlled environment for nursing students to develop safety competencies and error-recognition skills before clinical practice. OBJECTIVE: This systematic review aimed to describe and characterize the simulation-based education features and modalities used to address patient safety outcomes in undergraduate nursing students, identifying the strategies that contribute to improvements in safety-related competencies. METHODS: A systematic review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines across PubMed, Web of Science, Scopus, CINAHL, Cochrane, and Lilacs (2019-2024). Inclusion criteria focused on original studies involving undergraduate nursing students and simulation interventions measuring patient safety outcomes. Studies in languages other than English, Spanish, or Portuguese were excluded. Two reviewers independently performed study selection and data extraction. Methodological quality was assessed using Joanna Briggs Institute tools, applying a 60% quality threshold for inclusion. Results were synthesized through a narrative approach. RESULTS: A total of 20 studies from 12 countries were included. The methodological quality was high (n=14) and moderate (n=6). Findings revealed that high-fidelity simulation and virtual reality are the primary strategies used. Simulation proved effective in enhancing both technical skills (medication administration accuracy) and nontechnical skills (communication via SBAR [Situation, Background, Assessment, Recommendation] and ISBAR [Identification, Situation, Background, Assessment, Recommendation] tools, teamwork, and adverse event reporting). Key strategies contributing to safety included repetitive practice and interprofessional simulation, which significantly improved error detection and clinical judgment. CONCLUSIONS: Simulation is an essential pedagogical strategy for preparing nursing students to deliver safe care. Practical implications include the need to integrate structured simulation into nursing curricula to bridge the theory-practice gap. Future research should prioritize longitudinal designs to assess the retention of these safety skills in clinical settings and develop standardized metrics for measuring patient safety outcomes.
28 May 2026
Read appraisal →Prehospital and disaster medicine
Evaluating Nursing Students' Performance and Retention of BLS/AED Knowledge and Skills One Year After Training: A Randomized Controlled Trial
INTRODUCTION: Nurses often serve as the initial responders in cases of cardiac arrest, making cardiopulmonary resuscitation (CPR) competence essential to effective resuscitation. It is therefore important for nursing students to possess sufficient CPR knowledge and skills for future clinical practice. OBJECTIVE: The aim of this study was to examine whether CPR post-qualification training is needed in maintaining knowledge and skills and if face-to-face or online training is more effective as an educational method in preserving CPR knowledge and skills in nursing students. METHODS: A three-group, parallel randomized-controlled, single-blind design was used. The participants were 133 nursing students, randomly assigned to the face-to-face group (n = 43), the e-learning group (n = 43), and the control group (n = 47). Before randomization, all participants (n = 133) successfully completed the European Resuscitation Council (ERC) standard five-hour Basic Life Support/Automated External Defibrillation (BLS/AED) course (t0) and a questionnaire based on the 2021 ERC Guidelines to assess their knowledge. Six months later, Group A received face-to-face training, Group B received e-learning training, and Group C had no intervention. Six months after interventions, all participants (n = 133) were re-assessed on the same questionnaire, and they were given the same scenario of cardiopulmonary arrest that was used during the initial BLS course to assess the skills that they retained (t1) with the use of the ERC CPR/AED 11-item checklist. The collected data were analyzed with inferential "among group" analysis involving Kruskal-Wallis's and Pearson's Chi-Squared test and inferential "within group" analysis including Wilcoxon's Signed-Rank and McNemar's test. Multiple linear regression was used for adjusting demographic characteristics. RESULTS: Based on pairwise differences between independent groups, both intervention groups presented higher scores in knowledge at t1 (P < 0.001) and in skills at t1 (P < 0.001) compared to the control group. Moreover, both training methods demonstrated comparable effectiveness. Based on comparisons between paired groups, there was also a statistically significant decrease in the Skill Score in the control group after one year (P < 0.001). Most skills were notably higher, primarily in the e-learning group, and to a lesser extent in the face-to-face group. In specific, intervention groups demonstrated statistically significant improvement in nine of the eleven assessed skills (all P < 0.05). CONCLUSION: The current study showed that post-qualification training is needed to retain CPR knowledge and skills of nursing students, and that face-to-face and e-learning training had similar outcomes.
23 May 2026
Read appraisal →Journal of medical Internet research
GenAI-Supported Virtual Patients in Health Care Education: Systematic Review
BACKGROUND: Generative artificial intelligence (GenAI) is enhancing virtual patient simulations in health care education by enabling dynamic, adaptive interactions, reshaping how clinical skills are taught. A synthesis of the current evidence is needed to guide implementation and future research, given the pace of technological advancement. OBJECTIVE: This systematic review aims to synthesize empirical research on the design, implementation, and educational impact of GenAI-supported virtual patients in health care education. METHODS: A systematic search was conducted across 5 databases (CINAHL, Medline, Embase, Scopus, and Web of Science) from their inception to March 19, 2026. Reference lists of included studies and relevant systematic reviews were also screened. Peer-reviewed studies in English that evaluated GenAI-supported virtual patients using quantitative or mixed methods were included. Two reviewers independently screened studies and extracted data. Study quality and risk of bias were assessed critically using JBI (Joanna Briggs Institute) checklists, with disagreements resolved by consensus. RESULTS: A total of 15 studies met the inclusion criteria (total participants N=645), spanning health care disciplines, including nursing, medicine, pharmacy, radiography, and medical first-responder training. The virtual patients varied in design; input modalities included text (9 studies), voice (5 studies), or hybrid (1 study); output was text (9 studies), speech (5 studies), or both (1 study); 6 studies used 3D-embodied avatars, while 9 used nonembodied interfaces. A total of 13 studies used OpenAI GPT models (eg, ChatGPT), 1 used a fine-tuned model from a different provider, and 1 evaluated multiple model families (Claude, GPT, and open-source). Further, 6 studies used controlled experimental designs, including 3 randomized controlled trials (RCTs); the remainder were cross-sectional or prepost evaluations. Primary outcomes included user perceptions (14 studies), communication skills (4 studies), clinical reasoning (3 studies), and performance (7 studies). In controlled comparisons, GenAI-supported virtual patients consistently improved outcomes relative to control conditions: for example, enhanced clinical decision-making (RCT, n=21), ophthalmology history-taking skills (RCT, n=26), and medical history-taking performance (crossover RCT, n=20). The evidence base is characterized by brief intervention durations, a predominant reliance on single-session interactions, and a general lack of underpinning educational theory. No meta-analysis was performed due to the limited number of studies and significant heterogeneity in designs, interventions, and outcome measures. CONCLUSIONS: The evidence supports the feasibility and acceptability of GenAI-supported virtual patients, with positive learner perceptions and promising outcomes for skills development. However, critical limitations remain in emotional-behavioral complexity, simulation adaptability, and research design rigor (eg, limited use of control groups and validated instruments). The review offers educators, instructional designers, and policymakers actionable insights for integrating dynamic, artificial intelligence-driven simulations while identifying crucial gaps-such as the need for theoretical grounding, longitudinal studies, and standardized design protocols-that must be addressed for safe and effective implementation.
11 May 2026
Read appraisal →The Journal of nursing education
Enhancing Nursing Students' Interdisciplinary Competence via ARCS-Based Digital Health Care Design
BACKGROUND: Digital literacy is increasingly essential in modern nursing education, yet many students lack confidence and prior exposure to digital tools. METHOD: A 6-week project-based course, guided by the ARCS motivational model comprising Attention, Relevance, Confidence, and Satisfaction, engaged 40 first-year nursing students in designing health care applications using the Figma digital platform. The instructional process was organized into three progressive phases: motivational induction, design implementation, and final presentation. RESULTS: Students demonstrated a significant increase in learning motivation (t = 15.784, p < .001) and rated Figma's usability as excellent (System Usability Scale = 84.87). Reflections indicated enhanced digital confidence, interdisciplinary collaboration, and the ability to translate nursing knowledge into practical applications. CONCLUSION: Integrating motivational strategies with project-based learning and an intuitive digital platform effectively promoted student engagement, skill acquisition, and meaningful learning. This model offers a scalable approach for embedding digital competence into nursing curricula.
5 May 2026
Read appraisal →JMIR nursing
Application of the Technology Acceptance Model to Predict Nursing Students' Intention to Use Informatics: Cross-Sectional Study
BACKGROUND: Nursing informatics is essential for digital health transformation; however, the technology acceptance of undergraduate nursing students in Saudi Arabia remains underexplored. OBJECTIVE: This study examined factors influencing nursing students' intention to use informatics technologies using the technology acceptance model. METHODS: A cross-sectional survey was conducted with 132 undergraduate nursing students. Data were analyzed using descriptive, correlational, and hierarchical regression analyses. RESULTS: Perceived usefulness (mean 3.68, SD 1.22) and perceived ease of use (mean 3.64, SD 1.32) were the strongest predictors of acceptance, together explaining 87% of the variance (R²=0.87; β=0.323 for usefulness, P<.001; β=0.195 for ease of use, P=.032). Only 25.8% (n=34) of the students often used electronic health records, while 31.8% (n=42) had no electronic health record experience, indicating a clear gap in practical informatics exposure. CONCLUSIONS: Nursing students' acceptance of informatics is primarily driven by its perceived usefulness and perceived ease of use. These findings highlight the urgent need to integrate practical, user-centered informatics training and clinical simulation into undergraduate nursing curricula to better prepare students for technology-based practice.
16 Apr 2026
Read appraisal →Games for health journal
The Effect of Emergency Escape Room Simulation on Knowledge, Anxiety, and Satisfaction Levels of Students: A Randomized Controlled Trial
BACKGROUND: The aim of this study is to determine the effect of escape room simulation intervention on the knowledge, anxiety, and satisfaction levels of students in emergency nursing education. METHODS: This randomized controlled study was conducted with 40 students studying at the nursing faculty of a university in Istanbul. The students in the intervention group (n = 20) were given an escape room simulation intervention related to emergency nursing education. The students in the control group (n = 20) were not given any intervention other than the traditional education method. Data were collected using the Knowledge Test, State Anxiety Scale, and Visual Analog Scale for satisfaction. RESULTS: The knowledge level of the students in the intervention group measured immediately after the education (P = 0.003), 1 week after the education (P < 0.001), and 1 month after the education (P < 0.001) was found to be significantly higher than that of the control group. While no significant difference was found in anxiety levels before and after the education between the groups, a significant difference was found in anxiety levels before and after the training in the intervention group (P < 0.001). The satisfaction level measured immediately after the education was found to be significantly higher in the intervention group than in the control group (P < 0.001). CONCLUSION: This study show that escape room simulation increased emergency nursing knowledge and satisfaction and reduced anxiety levels of the students. It is recommended that escape room simulation intervention be used in more studies in nursing education. The study was registered on ClinicalTrials.gov.tr with the number NCT06619119.
11 Apr 2026
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