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Psychophysiological Stress Response in Medical Students During Simulation-Based Communication Training -Study Protocol

Observational Stress

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: Simulation-Based Communication Training.
Who it may be relevant to
Registry conditions: Stress. Basic parameters: No limits · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Czechia
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Analysis of Predictors of Stress Reactions in Medical Students During Simulation-Based Training

Overview

In this study, researchers will examine key predictors of stress reactions in medical students participating in simulation-based communication training. By using psychometric questionnaires and physiological measurements, the study will assess how psychological traits, resilience, and self-efficacy impact stress responses during simulated patient interactions. These simulations use live actors to portray emotionally challenging scenarios, such as communicating with anxious or aggressive patients. The results aim to identify factors that contribute to heightened stress, ultimately guiding the development of targeted stress-management strategies to improve students' readiness for real-world clinical settings.

Detailed description

Aims of the Study and Main Hypotheses

The primary aim of the study is to identify key predictors of stress responses in third-year medical students during simulation-based communication training. In this context, "stress" is operationalized both through continuous physiological measurements-principally heart rate variability (HRV) recorded via Polar chest bands-and through a battery of psychometric assessments. The study is designed to evaluate:

Primary Aim:

To determine the predictive value of psychological traits (e.g., resilience, self-efficacy) on physiological stress markers (e.g., HRV stability) and subjective stress ratings during high-fidelity patient interactions with live actors.

Hypothesis: Students exhibiting higher levels of resilience and self-efficacy will demonstrate lower physiological stress responses (i.e., more stable HRV) and report lower subjective stress.

Comparison of Stressors Across Scenarios:

To examine whether different simulated patient interactions-such as those involving anxious, aggressive, silent, or emotionally distressed patients-elicit distinct stress responses. This component will allow for the evaluation of scenario-specific stress effects, which could have implications for tailoring simulation training.

Influence of Personality Traits:

To investigate how personality characteristics, particularly neuroticism and extraversion, influence the magnitude of stress responses during simulations. This analysis will provide insight into the extent to which individual differences moderate stress levels.

Practical Application:

To inform the development of targeted interventions, such as tailored stress management or coping programs, specifically designed for students who are identified as being highly reactive to stress during simulations.

Study Design and Methodology

The study employs an observational cohort design. Data will be collected from third-year medical students enrolled in the Medical Psychology and Psychosomatics course, who participate in simulation-based patient interactions. The detailed methodological framework is as follows:

Data Collection Phases:

Phase 1 (Baseline): Two days prior to simulation sessions, participants will complete a comprehensive set of psychometric questionnaires to assess baseline levels of stress, anxiety, resilience, and self-efficacy.

Phase 2 (Pre-Simulation): Immediately before the simulation begins, students will fill out a pre-simulation questionnaire aimed at capturing their immediate stress and anxiety levels.

Phase 3 (Post-Simulation): Directly after the simulation, a post-simulation questionnaire will be administered to record acute stress responses.

Phase 4 (Post-Debriefing): Following the debriefing session, students will complete a final set of questionnaires to assess any changes in stress levels after reflective processing.

Physiological Monitoring:

Throughout the simulation, continuous HRV data will be collected using Polar chest bands. These devices provide objective, high-resolution data on the autonomic responses of students during live interactions with standardized patients.

Additionally, each simulation session will be supplemented by observational assessments provided by trained actors (standardized patients), focusing on indicators such as body language, communication style, and overall stress manifestation.

Outcome Measures While the primary outcomes relate to physiological markers (HRV) and subjective stress ratings, secondary outcomes will explore the moderating effects of personality traits and the impact of different scenario types on stress responses. These outcomes will serve as predictors for tailoring future simulation-based interventions, ensuring that the training environment can be optimized to both challenge students and support their learning effectively.

Interventions

  • Behavioral Simulation-Based Communication Training
    In our study, the intervention is more of an experimental situation - a scenario. High-fidelity scenarios include patients played by real actors displaying anxiety, aggression, silence, and emotional distress in various clinical situations such as delivering serious news or frustration for waiting for physicians. The average time of each simulation is 12 minutes.

Primary outcome measures

  • Change in heart rate variability (HRV) using HR band Polar H10 [Time frame: 2,5 hours during each simulation]
  • State-Trait Anxiety Inventory X-II [Time frame: 2 days before first simulation]
  • Affective Circumplex [Time frame: 5 minutes before the simulation]
  • NASA Task Load Index (NASA-TLX) [Time frame: 5 minutes after the simulation]
Secondary outcome measures (6)
  • Toronto Empathy Questionnaire [Time frame: 2 days before first simulation]
  • The Brief Resilience Scale [Time frame: 2 days before first simulation]
  • General Self-Efficacy Scale (GSE) [Time frame: 2 days before first simulation]
  • Perceived Stress Scale (PSS) [Time frame: 2 days before first simulation]
  • The Big Five Inventory-10 (BFI-10) [Time frame: 2 days before first simulation]
  • Rosenberg Self-Evaluation Scale (RSES) [Time frame: 2 days before first simulation]

Eligibility criteria

Inclusion criteria

  • Enrollment as a 3rd-year medical student at the Faculty of Medicine, Masaryk University.
  • Participation in the Medical Psychology and Psychosomatics course.
  • Active involvement in simulation-based communication training sessions.
  • Signed informed consent provided before the start of the study.
  • Willingness to wear physiological monitoring devices (e.g., chest strap) during simulations.

Exclusion criteria

  • Inability or unwillingness to complete all phases of data collection, including pre- and post-simulation assessments.
  • Absence of a smartphone with Bluetooth connectivity.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model
Cohort

Study locations

Czechia · 1 center
  • Faculty of Medicine, Masaryk University — Brno

Publications

  • Dunton H, Leng O, Catlow J, Hancock J, Metcalf J. Stress and heart rate in high-fidelity training scenarios for undergraduate medical students. Future Hosp J. 2016 Jun 1;3(Suppl 2):s16. doi: 10.7861/futurehosp.3-2s-s16. No abstract available. PMID 31098245
  • Peabody JE, Ryznar R, Ziesmann MT, Gillman L. A Systematic Review of Heart Rate Variability as a Measure of Stress in Medical Professionals. Cureus. 2023 Jan 29;15(1):e34345. doi: 10.7759/cureus.34345. eCollection 2023 Jan. PMID 36865953
  • van Dulmen S, Tromp F, Grosfeld F, ten Cate O, Bensing J. The impact of assessing simulated bad news consultations on medical students' stress response and communication performance. Psychoneuroendocrinology. 2007 Sep-Nov;32(8-10):943-50. doi: 10.1016/j.psyneuen.2007.06.016. Epub 2007 Aug 6. PMID 17689196

Identifiers

NCT: NCT06906614 · SIMU2025

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗