Las personas con enfermedades crónicas y graves, necesitan ser escuchadas, entendidas y atendidas a su ritmo. Los profesionales necesitan herramientas sencillas y eficientes que les faciliten una buena comunicación con sus pacientes, en el menor tiempo posible. Ojetivo: describir un protocolo sistemático de comunicación en cinco pasos. Método: Se ha diseñado un enfoque cualitativo basado en la revisión documental, que ha incluido la revisión bibliográfica y de evidencias para apoyar el análisis y poder llegar a conclusiones con la información extraída del proceso. Resultado: Como resultado se propone un protocolo básico de comunicación fundamentado en el counselling y en los principios de la bioética moderna, capaz de facilitar las funciones de informar, motivar la adhesión terapéutica, promover cambios de conducta, abordar situaciones de comunicación difícil y, especialmente, de tener un encuentro auténtico con el paciente y su familia. Por conclusión sin comunicación eficaz no hay encuentro, y sin encuentro, la relación clínica entre profesional y paciente se puede convertir en un intercambio de palabras vacías, de imposiciones de tratamientos, que difícilmente el paciente va a cumplir adecuadamente. Los tiempos cambian y la Medicina participativa va encontrando un lugar más adecuado en el entorno clínico.

From the beginning of their clinical training, medical students demonstrate difficulties when incorporating patient perspectives. This study aimed to assess if students, after an instructional programme, increased their sensitivity towards patients’ needs and carried out bidirectional conversations. An observational study involving 109 medical students prior to their clerkships was designed. They attended a five-step training programme designed to encourage the use of communication skills (CSs) to obtain patients’ perspectives. The course developed experiential and reflective educational strategies. The students improved their use of CSs throughout three sessions, and the overall score for these patient consultations went up in the opinions of both the external observer (EO) (5; 6.6; 7.5) and the simulated patients SPs (5.3; 6.6; 7.8). Most of the students (83.9%) considered that the CSs addressed were useful for clinical practice, particularly the interviews and the feedback received by the SP and the lecturer. The programme seems to help the students use CSs that facilitate a more bidirectional conversation in a simulated learning environment. It is feasible to integrate these skills into a broader training programme. More research is needed to assess whether the results are applicable to students in real settings and whether they influence additional outcomes.

El sufrimiento aparece de manera natural y espontánea cuando no tenemos recursos para hacer frente a una situación que se convierte en una amenaza. Acompañar el sufrimiento no es tarea fácil y requiere destrezas, habilidades y conocimientos, así como desarrollo personal. Identificar y abordar el sufrimiento es una de las principales funciones de la práctica clínica. Poder identificar cómo esta experiencia afecta a los profesionales sanitarios, así como generar estrategias para hacerle frente podría protegernos y facilitar el ejercicio de la ayuda. Este artículo tiene como objetivo principal realizar una revisión teórica, acompañada de claves prácticas, para presentar cinco cuestiones previas que configuran un conocimiento esencial para el acompañamiento. Se pretende estimular la reflexión y el aprendizaje de habilidades que nos permitan desarrollar nuestras acciones desde la consciencia y en coherencia con nuestros valores y objetivos.

Background: Higher education training in Medicine has considerably evolved in recent years. One of its main goals has been to ensure the training of students as future adequately qualified general practitioners (GPs). Tools need to be developed to evaluate and improve the teaching of Urology at the undergraduate level. Our objective is to identify the knowledge and skills needed in Urology for the real clinical practice of GPs. Methods: An anonymous self-administered survey was carried out among GPs of Primary Care and Emergencies which sought to evaluate urological knowledge and necessary urological skills. The results of the survey were exported and descriptive statistics were performed using IBM SPSS Statistics version 19.0. Results and limitations: A total of 127 answers were obtained, in which ‘Urological infections’, ‘Renal colic’, ‘PSA levels and screening for prostate cancer’, ‘Benign prostatic hyperplasia’, ‘Hematuria’, ‘Scrotal pain’, ‘Prostate cancer diagnosis’, ‘Bladder cancer diagnosis’, ‘Urinary incontinence’, and ‘Erectile dysfunction’ were rated as Very high or High formative requirements (>75%). Regarding urological skills, ‘Abdominal examination’, ‘Interpretation of urinalysis’, ‘Digital rectal examination’, ‘Genital examination’, and ‘Transurethral catheterization’ were assessed as needing Very high or High training in more than 80% of the surveys. The relevance of urological pathology in clinical practice was viewed as Very high or High in more than 80% of the responses. Conclusions: This study has shown helpful results to establish a differentiated prioritization of urological knowledge and skills in Primary Care and Emergencies. Efforts should be aimed at optimizing the teaching in Urology within the Degree of Medicine which consistently ensures patients’ proper care by future GPs.

BACKGROUND Large Language Models from the field of Artificial Intelligence have been one of the tools that have a great and real impact on the daily lives of people. In this regard, they emerge as an aid in specific fields such as education helping educators in cumbersome tasks such as periodical evaluations. OBJECTIVE This paper is focused in analyzing the benefits of Large Language Models and in particular Chain of Thought strategy for the task of evaluating the writing in Spanish of medical records by students. The aim is two-fold: first we try to save time and re-sources and second, we use the reasonings of the Chain of Thought to evaluate the ru-brics and its interpretations. METHODS The proposed solution studies the application of two models such as Llama 3.1 and Claude 3.5 in combination with two strategies One-Shot and Chain of Thought to evaluate how medicine students write medical records in Spanish. First, machine learn-ing metrics are applied to measure the performance of the solutions. Then, different statistical analysis is obtained at clinical record and item level. Finally, the differences between proposed models and evaluators are studied in-depth. RESULTS Machine learning metrics indicate that, at first, Claude got an Accuracy over 86% and no substantial differences among them. However, an in-depth analysis high-lights the potential of Chain of Thought both for identifying evaluator errors and for addressing issues in the rubrics. Applying this analysis, we have found 317 human errors which, after a correction, have set the Accuracy in 94.6%. CONCLUSIONS Chain of Thought demonstrates strong potential for supporting the evalua-tion of clinical records written in Spanish by medical students and providing feedback to them. More importantly, it shows significant promise in assisting professors by as-sessing the quality of their rubrics and identifying possible errors.

Background: Large language models in artificial intelligence have been among the tools with a significant and real impact on people’s daily lives. In this regard, they serve as an aid in specific fields, such as education, helping educators with cumbersome tasks such as periodic evaluations. Objective: This study focused on analyzing the benefits of large language models, particularly the chain-of-thought (CoT) strategy, for the task of evaluating students’ Spanish-language medical record writing. The aim was 2-fold: first, we attempted to save time and resources, and second, we used the reasoning of the CoT strategy to evaluate the rubrics and their interpretations. Methods: The proposed solution assessed the application of 2 models—Llama 3.1 and Claude 3.5—in combination with one-shot and CoT to evaluate how medical students write medical records in Spanish. First, machine learning metrics were applied to measure the performance of the solutions. Then, different statistical analyses were performed at the clinical record and item levels. Finally, differences between the proposed models and evaluators were studied in depth. Results: A maximum of 3807 items were evaluated. Claude obtained the best accuracy with slight differences between one-shot and CoT (86.4% and 85.0%, respectively). However, Claude with CoT outperformed the rest of the combinations on all complementary metrics, initially achieving a sensitivity of 94.2%, specificity of 59.5%, precision of 85.8%, and F ₁ -score of 89.6%. Expert review of CoT reasoning determined that 63.8% of the discrepancies were model hits, raising Claude’s final accuracy to 94.6% (SD 4.3%). In the final phase, sensitivity was 98.0% (SD 2.3%), specificity improved to 83.3% (SD 14.3%), and F ₁ -score reached 96.2% (SD 3.3%). Sectional analysis showed greater difficulties in the “History of present illness” section (n=125 discordances). Conclusions: CoT demonstrated strong potential for supporting the evaluation of clinical records written in Spanish by medical students and providing feedback to them. More importantly, it showed significant promise in assisting professors by assessing the quality of their rubrics and identifying possible errors.