Evaluación de la ansiedad en simulación clínica de alta fidelidad: Impacto de escenarios y el contexto externo
The doctoral thesis by compendium of articles titled "Assessment of Anxiety in High-Fidelity Clinical Simulation: Impact of Scenarios and the External Context" investigates how anxiety affects medical students during advanced high-fidelity clinical simulations, and how it can be measured a...
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| Formato: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Recursos: | Universidad de Valladolid |
| Repositorio: | UVaDOC. Repositorio Documental de la Universidad de Valladolid |
| OAI Identifier: | oai:uvadoc.uva.es:10324/79916 |
| Acesso em linha: | https://doi.org/10.35376/10324/79916 https://uvadoc.uva.es/handle/10324/79916 |
| Access Level: | acceso abierto |
| Palavra-chave: | Ansiedad Anxiety High-fidelity clinical simulat Simulación clínica de alta fid Undergraduate students Estudiantes pregrado STAI 32 Ciencias Médicas |
| Resumo: | The doctoral thesis by compendium of articles titled "Assessment of Anxiety in High-Fidelity Clinical Simulation: Impact of Scenarios and the External Context" investigates how anxiety affects medical students during advanced high-fidelity clinical simulations, and how it can be measured and managed to optimize learning. Objectives: • To determine the correlation between the State-Trait Anxiety Inventory (STAI) questionnaire score and pupil diameter, as measured by pupillometry. • To develop a predictive model of anxiety based on pupil diameter. • To compare students' anxiety levels before, during, and after the COVID-19 pandemic. • To analyze the impact of different clinical scenarios (sepsis, myocardial infarction, polytrauma, anaphylactic shock) on anxiety. • To identify which scenarios generate extreme anxiety (>25% increase after simulation). Methodology Three main studies were conducted to address the stated objectives: • A randomized, blinded simulation-based clinical trial with sixth-year students, in which anxiety (STAI) and pupil diameter were measured before and after major trauma and anaphylactic shock simulations. • A prospective cohort study, comparing anxiety in simulations carried out in three periods: pre-pandemic, during the pandemic, and post-vaccination. • Another randomized clinical trial, in which anxiety changes were analyzed in critical prehospital scenarios, assigning students to different clinical cases (polytrauma, anaphylactic shock, acute myocardial infarction, and sepsis). Main results: • Objective correlation: A statistically significant correlation was found between the pre/post-simulation change in STAI and pupil diameter. The predictive model of anxiety based on pupillometry showed a high discriminative capability (AUC=0.876), with the change in pupil diameter being the only significant variable. This validates pupillometry as an objective, non-invasive, and repeatable tool for identifying students with high anxiety during clinical simulation. • Impact of external context: During the COVID-19 pandemic, students' anxiety levels increased significantly compared to the pre-pandemic and post-vaccination periods, regardless of sex, age, previous experience, or simulation role. This underscores the importance of the social and healthcare context as an emotional modulator. • Differences according to scenario: Polytrauma and anaphylactic shock scenarios produced the greatest increase in anxiety, whereas sepsis and myocardial infarction generated less impact. Polytrauma, in particular, showed the worst post-simulation anxiety levels. • Effects on learning: A moderate level of anxiety can be beneficial for learning and performance (Yerkes-Dodson law), but excessive levels act as cognitive blockers, interfering with working memory and the application of knowledge. Identifying students with disabling anxiety allows for intervention to transform the experience into a learning opportunity. Educational implications The thesis highlights the need for educators/trainers in clinical simulation to: • Be aware of the impact of anxiety and adopt strategies to mitigate it (prebriefing, adjustment of difficulty, structured debriefing). • Use pupillometry as a complementary tool to identify and support vulnerable students. • Recognize that certain scenarios require extra preparation and emotional support. Conclusions Anxiety in high-fidelity clinical simulation is a multifactorial phenomenon, influenced both by external context (such as the pandemic) and by the nature of the clinical scenario. It can and should be measured objectively to personalize educational intervention. Proper management of anxiety is key to maximizing learning and the psychological safety of future healthcare professionals. |
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