Background There is no standardized, widely accepted process for individualized clinical reasoning remediation. Objective We describe a novel, targeted assessment and coaching process that allows for individualized intervention for residents and fellows struggling with clinical reasoning. Methods Residents and fellows at the University of Virginia with performance concerns are referred to COACH (Committee on Achieving Competence Through Help) and assessed by a remediation expert. A subset is referred to a clinical reasoning remediation coach who performs an additional assessment and cocreates an individualized remediation plan. Following remediation, residents and fellows are reassessed by their respective programs. We report the frequency of struggle, remediation time invested, and academic outcomes. Results From 2017 to 2022, 114 residents and fellows referred to COACH met inclusion criteria, of which 38 (33%) had a deficiency in clinical reasoning. Targeted assessment revealed the following microskill deficits: hypothesis generation (16 of 38, 42%); data gathering (6 of 38, 16%); problem representation (7 of 38, 18%); hypothesis refinement (3 of 38, 8%); and management (6 of 38, 16%). Remediation required a mean of nearly 23 hours per trainee. Of the 38 trainees, 33 (87%) are in good standing at the time of writing. Conclusions Our unique program offers a feasible, targeted approach to clinical reasoning remediation based on our current understanding of the clinical reasoning process. Early hypothesis generation was the most common microskill deficit identified.

Artificial intelligence (AI) in the form of ChatGPT has rapidly attracted attention from physicians and medical educators. While it holds great promise for more routine medical tasks, may broaden one\'s differential diagnosis, and may be able to assist in the evaluation of images, such as radiographs and electrocardiograms, the technology is largely based on advanced algorithms akin to pattern recognition. One of the key questions raised in concert with these advances is: What does the growth of artificial intelligence mean for medical education, particularly the development of critical thinking and clinical reasoning? In this commentary, we will explore the elements of cognitive theory that underlie the ways in which physicians are taught to reason through a diagnostic case and compare hypothetico-deductive reasoning, often employing illness scripts, with inductive reasoning, which is based on a deeper understanding of mechanisms of health and disease. Issues of cognitive bias and their impact on diagnostic error will be examined. The constructs of routine and adaptive expertise will also be delineated. The application of artificial intelligence to diagnostic problem solving, along with concerns about racial and gender bias, will be delineated. Using several case examples, we will demonstrate the limitations of this technology and its potential pitfalls and outline the direction medical education may need to take in the years to come.

The decision to euthanize a compromised pig can be challenging for pig farmers and veterinarians. To understand more about the challenges in Germany, a cross-sectional online survey was conducted. Based on a hybrid design, the responses of 39 veterinarians and 62 pig farmers were analyzed to generate a list of common clinical signs associated with the euthanasia of sows, fatteners, and piglets. Moreover, a set of influences on the farm, due to economic and personal considerations, were found to shape the decision-making process. The two most salient reasons outlined for the delay of timely euthanasia were uncertainty and misinterpretation of the chance for healing. The lack of valid clinical signs or a sound justification was most frequently mentioned as a challenge to the general decision-making process. In summation, this study highlights the need to generate a valid taxonomy for clinical signs that includes their development in a compromised pig over time. Future studies should elaborate on the justification of euthanasia decisions to facilitate the resolution of ethical dilemmas among the involved pig farmers and veterinarians. Lastly, the results suggest that clinical reasoning and consultation skills should be included when decision-making behavior is to be trained.

BACKGROUND: Standardized patient (SP) encounters allow medical students to practice physical examination skills and clinical reasoning. SP cases are used for learning and assessment, but recorded encounters can also be valuable curriculum evaluation tools. We aimed to review SP encounters to improve abdominal examination skills and the broader physical examination curriculum.
METHODS: We reviewed recorded SP encounters of third-year medical students on surgery clerkship rotation. Students examined a cisgender woman presenting with acute right lower abdominal pain. We observed abdominal examinations to determine which maneuvers were attempted and completed correctly. We then used these outcomes to develop targeted clerkship training for the subsequent student cohort. Our intervention targeted abdominal examination gaps by explaining how to integrate abdominal examination findings with a focused history for surgical patients. We evaluated the intervention\'s impact on abdominal examination skills with third-year medical students in comparison (2021-2022, n = 119) and intervention (2022-2023, n = 132) groups.
RESULTS: In both the comparison and intervention groups, nearly all students attempted at least 1 general examination maneuver like auscultation, palpation, percussion, or rebound tenderness. Only 40% of students in the comparison group attempted an advanced maneuver like the Rovsing, Psoas, or Obturator sign. After the intervention, 75% of students in the intervention group attempted an advanced maneuver (χ2(1, 251) = 31.0, p < .001). Cohorts did not gain skills over time through the clerkship. Rebound tenderness was frequently assessed incorrectly by students in both groups, with many avoiding the right lower quadrant entirely.
CONCLUSIONS: This project highlights how medical students struggle to utilize abdominal examination maneuvers and integrate findings. The results also showed that students did not consistently learn advanced examination skills either before or during clerkship rotation, which may be commonly assumed by clinical faculty. Finally, this work demonstrates how SP encounters can be used to evaluate and improve surgical education curriculum.

Introduction The coronavirus 2019 pandemic highlighted virtual learning (VL) as a promising tool for medical education, yet its effectiveness in teaching clinical reasoning (CR) remains underexplored. Past studies have suggested VL can effectively prepare students for clinical settings. Informed by the Milestones of Observable Behaviours for CR (MOBCR) and whole-case theoretical frameworks, the Mock Wards (MW) program was created using a novel blended in-person learning (IPL) and VL platform. MW consisted of case-based small-group formats for medical students interested in learning approaches and differentials to commonly encountered presenting symptoms and diagnoses in internal medicine. This study sought to use MW\'s blended design to qualitatively analyze CR development and compare its utility between VL and IPL. Methods Qualitative analysis was conducted using in-depth semi-structured interviews with first-year pre-clerkship medical students (n = 8) who completed the MW program and participated in the study. The interview guide was informed by the MOBCR framework. Interview transcripts were analyzed using a directed qualitative content analysis approach. Translational coding and HyperRESEARCHTM (Researchware, Inc., Randolph, MA) software-generated mind maps guided the theme development. Results Three overarching themes were constructed: (1) tailoring pedagogical frameworks to learning modalities, (2) learning through interactivity, and (3) balancing accessibility with learner engagement. Participants emphasized that teaching CR skills is modality-specific and not fully interchangeable, with IPL being superior in facilitating social cohesion, non-verbal communication, and feedback. In contrast, VL required structured approaches and relied more on verbal communication and pre-made digital materials. IPL also enhanced interactivity, peer relationships, and spontaneous communication, whereas VL faced challenges such as social awkwardness and technological constraints hindering effective collaboration. VL provided superior accessibility to facilitate distributed learning and management of concurrent academic obligations. Conclusion The MW-blended platform highlights the importance of focusing on modality-tailored pedagogies, emphasizing group interactability, and balancing VL accessibility against decreased engagement within the IPL environment when teaching CR skills. Blended education models may benefit from a scaffolding approach, using IPL as a prerequisite to VL to improve CR development and alignment within a learner\'s zone of proximal development.

Background and objectives There is a crucial need to embrace modern methodologies for enhancing medical education in disciplines such as Family Medicine. The study introduces the SNAPPS (Summarize, Narrow, Analyze, Probe, Plan, and Select) model, a six-step mnemonic representing a learner-centered case presentation approach that streamlines fact reporting while encouraging clinical reasoning, aiming to evaluate the effectiveness of the SNAPPS method as compared to the traditional model of case presentation in Family Medicine outpatient clinics and to gain insights into how students and preceptors perceive it. Methods A randomized controlled trial was conducted in Family Medicine outpatient clinics in Erbil, Iraq, from March 15, 2023, to August 30, 2023. Using convenience sampling, all Family Medicine board residents (n=30) in Erbil and six preceptors from the Community and Family Medicine department/College of Medicine/Hawler Medical University were randomly assigned into two groups by using the RAND function in Microsoft Excel (Microsoft Corporation, Redmond, Washington, United States). The SNAPPS method was introduced to the SNAPPS group employing approved tools and methods, while no intervention was needed in the control group. Subsequently, 30 cases were presented in each group with a total of 60 case presentations; the case presentations served as the units for data analysis. Feedback and data were gathered after each presentation using validated data recording sheets. Results The study showed a significant advantage for the SNAPPS group over the control group in terms of time efficiency, number of basic clinical attributes covered, and justified diagnoses (P value < 0.001). In the SNAPPS group, 90% of the students sought clarification and information, surpassing 30% in the control group (P-value < 0.001). Almost all SNAPPS group students (96.7%) discussed case-related topics, compared to 43.3% in the controls (P-value<0.001). The SNAPPS group received superior overall ratings from both preceptors and students. Conclusion The SNAPPS method enhances clinical diagnostic reasoning in Family Medicine outpatient clinics. It is time-efficient and encourages students to articulate uncertainties, pose questions, and identify case-related topics for self-study.

BACKGROUND: Versatile large language models (LLMs) have the potential to augment diagnostic decision-making by assisting diagnosticians, thanks to their ability to engage in open-ended, natural conversations and their comprehensive knowledge access. Yet the novelty of LLMs in diagnostic decision-making introduces uncertainties regarding their impact. Clinicians unfamiliar with the use of LLMs in their professional context may rely on general attitudes towards LLMs more broadly, potentially hindering thoughtful use and critical evaluation of their input, leading to either over-reliance and lack of critical thinking or an unwillingness to use LLMs as diagnostic aids. To address these concerns, this study examines the influence on the diagnostic process and outcomes of interacting with an LLM compared with a human coach, and of prior training vs no training for interacting with either of these \'coaches\'. Our findings aim to illuminate the potential benefits and risks of employing artificial intelligence (AI) in diagnostic decision-making.
METHODS: We are conducting a prospective, randomised experiment with N=158 fourth-year medical students from Charité Medical School, Berlin, Germany. Participants are asked to diagnose patient vignettes after being assigned to either a human coach or ChatGPT and after either training or no training (both between-subject factors). We are specifically collecting data on the effects of using either of these \'coaches\' and of additional training on information search, number of hypotheses entertained, diagnostic accuracy and confidence. Statistical methods will include linear mixed effects models. Exploratory analyses of the interaction patterns and attitudes towards AI will also generate more generalisable knowledge about the role of AI in medicine.
BACKGROUND: The Bern Cantonal Ethics Committee considered the study exempt from full ethical review (BASEC No: Req-2023-01396). All methods will be conducted in accordance with relevant guidelines and regulations. Participation is voluntary and informed consent will be obtained. Results will be published in peer-reviewed scientific medical journals. Authorship will be determined according to the International Committee of Medical Journal Editors guidelines.

We present the case of a 17-year-old adolescent boy admitted to the Pediatric Intensive Care Unit with an extensive necrotizing soft tissue infection who subsequently developed altered mental status and autonomic instability. Altered mental status is a common occurrence in critically ill children with a broad differential of etiologies. After ruling out organic causes of encephalopathy, management is typically focused on avoiding deliriogenic agents, including benzodiazepines. Dopamine antagonist medications may also be administered adjunctively to manage agitation or delirium that is refractory to other measures. We review the workup and differential diagnosis for altered mentation in critically ill children and discuss the current understanding of a rare etiology of altered mental status in the pediatric population.

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UNASSIGNED: The development of critical thinking (CT) has been a universal goal in higher education. A systematic review of the literature was conducted to evaluate the effectiveness of currently used pedagogical practices to foster CT/ clinical reasoning (CR)/ clinical judgment (CJ) skills and/or dispositions in undergraduate medical students.
UNASSIGNED: PubMed, Web of Science and Scopus databases were searched from January 2010 to April 2021 with a predefined Boolean expression.
UNASSIGNED: Of the 3221 articles originally identified, 33 articles were included by using PICOS methodology. From these, 21 (64%) reported CR pedagogical practices and 12 (36%) CT pedagogical practices.
UNASSIGNED: Overall, pedagogical practices such as cognitive/visual representation, simulation, literature exposure, test-enhancing and team-based learning, clinical case discussion, error-based learning, game-based learning seem to enhance CT/CR skills and/or dispositions. Further research is required to identify the optimal timing, duration and modality of pedagogical interventions for effectively foster CT/CR in medical education.