Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 4 appraisals
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 →Medical education online
Consensus and learning climate in temporary versus permanent teams in team-based learning
BACKGROUND: In team-based learning, students are typically placed in fixed teams based on the idea that stable group membership fosters collaboration: as teammates get to know each other, they share more information, resolve differences and feel motivated to contribute. This rationale had not been tested in a randomized controlled trial. OBJECTIVE: The study compares team-based learning in temporary teams with the default permanent teams regarding individual and team readiness assurance test performance (iRAT, tRAT), reaching team consensus, the learning climate, and intrinsic motivation. DESIGN: In a randomized controlled trial, first-year medical students were assigned either to permanent TBL teams or to teams that were re-assigned for each problem. The team readiness assurance test (tRAT) votes, submitted individually and covertly, served as an indirect indicator for team consensus (concordant versus discordant tRAT vote). RESULTS: Discordant tRATs (n = 268, 11.8% of all votes) were submitted more frequently in temporary than in permanent teams, both for correct and incorrect majority decisions. The self-rated learning climate was more cooperative in permanent than in temporary teams, while intrinsic motivation and tRAT scores were similar for both types of teams. A poorer learning climate was associated with a higher proportion of discordant tRATs. CONCLUSION: Working in temporary teams does not lead to inferior intrinsic motivation; this was previously also shown for knowledge gain. However, the poorer learning climate, together with reaching a consensus less often, might indicate that at least some members of temporary teams feel not adequately appreciated in the discussion and do not accept the majority decision. With instructional strategies promoting a cooperative learning climate in temporary teams, preclinical TBL courses might serve as an early promoter of the relational team competencies required for subsequent clinical workplace learning in temporary teams.
1 July 2026
Read appraisal →JMIR medical education
Health Professional Students' Use of Generative Artificial Intelligence During Clinical Placements: Cross-Sectional Online Survey Study
BACKGROUND: Generative artificial intelligence (GenAI) is rapidly expanding in higher education and clinical practice. However, its use during clinical placements, where cognitive demands and responsibility for patient care increase, remains insufficiently documented. OBJECTIVE: This study aimed to characterize self-reported GenAI use during clinical placements, perceived benefits and risks, and related training and governance needs. METHODS: We conducted a cross-sectional online survey at a French university (July 17 to September 30, 2025). Eligible participants were students in medicine, pharmacy, nursing, midwifery, or physiotherapy who were currently in, or had completed within the past 18 months, a clinical placement. A 61-item questionnaire (comprising closed- and open-ended items) assessed GenAI use, task patterns, perceived benefits or risks, and training or governance needs. A composite index classified self-perceived GenAI maturity as minimal, limited, moderate, or high. Group comparisons used χ2 tests; maturity gradients used trend tests. RESULTS: A total of 388 students responded (n=308, 79.4% women), mainly nursing students (n=217, 55.9%). Overall, 204 (52.6%) students reported using GenAI during clinical placements. Use differed across disciplines (χ24=10.71; P=.03), with lower uptake in midwifery (6/23, 26%; odds ratio 0.30, 95% CI 0.11-0.77). Adoption increased markedly with self-perceived maturity (minimal: 2/22, 9% vs high: 22/29, 76%; trend P<.001). Among the 204 users, the most commonly reported uses were information retrieval (n=159, 77.9%), bibliographic search (n=152, 74.5%), and translation or rephrasing (n=145, 71.1%); patient-facing activities were less frequently reported (eg, patient-document drafting or communication preparation: n=78, 38.2%). Although most users reported never entering direct patient identifiers, 48 (23.5%) reported at least 1 disclosure of patient-identifying information, and 96 (47.1%) reported processing real medical content perceived as anonymized. The most endorsed perceived benefits among the 388 students were documentation support (n=315, 81.2%) and improved access to information (n=266, 68.5%). The most endorsed risks were dependency (n=353, 90.9%), skill erosion (n=329, 84.8%), and confidentiality breaches (n=339, 87.4%). Training needs were highest for ethics or regulatory training (294/378, 77.7%) and a best-practice clinical guide (292/373, 78.3%). CONCLUSIONS: GenAI is already used by a substantial proportion of French students in health professions during clinical placements, predominantly for information and documentation support rather than patient-facing activities. Self-perceived readiness is strongly associated with adoption. Reported disclosures and concurrent concerns about dependency, skill erosion, and confidentiality support the need for structured curricula and clear governance frameworks to enable responsible, patient-centered integration of GenAI into clinical education.
3 May 2026
Read appraisal →PloS one
Successful student learning outcomes in Moroccan higher education: Causal configurations of pedagogical, motivational, and ICT conditions using fuzzy-set Qualitative Comparative Analysis (fsQCA)
As the demand for better educational quality and improved student performance grows, institutions face increasing challenges in making their teaching methods more effective to ensure successful learning outcomes. Most practical recommendations tend to focus on isolated effects, but learning success usually results from interconnected factors that work together. Drawing on constructivist Learning Theory, this study examines pedagogical and motivational factors that can positively impact learning results in higher education within Moroccan universities. The main goal is to identify and evaluate the nonlinear individual effects and the interactive causal configurations involving multiple conditions, such as teacher motivation, pedagogical leadership, self-efficacy, instructional innovation, ICT use, and student motivation, on learning outcomes. Empirical data were gathered through a questionnaire completed by 349 Moroccan university students, using measurement scales for key variables. The analysis employed the fuzzy-set Qualitative Comparative Analysis (fsQCA) method, which helps identify different combinations and causal pathways that lead to high academic achievement. Findings suggest that excellent learning outcomes are not caused by a single factor but by the interaction of several interdependent conditions. Different "recipes" can produce similar strong results. Certain combinations, especially those with strong teacher motivation, effective leadership, and strategic ICT use, proved to be reliable configurations, showing that technology is most impactful when integrated into supportive pedagogical and motivational environments. These results can help redefine and evaluate integrated educational policies, considering the complex interactions among individual, pedagogical, and technological factors. This approach promotes more effective and equitable learning environments through coherent bundles of mutually reinforcing interventions, instead of isolated efforts. Ultimately, this research enables educators and policymakers to develop more targeted strategies, utilize resources more efficiently, and improve overall educational effectiveness.
23 Apr 2026
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