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Related Concept Videos

Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

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Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
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Related Experiment Video

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Setup and Execution of the Rapid Cycle Deliberate Practice Death Notification Curriculum
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Safely Debriefing Unexpected Simulation Death: How We Did It.

Joseph C L'Huillier1, Sasha M Ulrich2, Sarah A Jung3

  • 1University at Buffalo, Jacobs School of Medicine and Biomedical Sciences, Department of Surgery, Buffalo, New York.

Journal of Surgical Education
|November 5, 2025
PubMed
Summary
This summary is machine-generated.

Medical simulation training for surgical interns can help manage anxiety related to patient death. A structured debriefing using the GAS model effectively processed emotional responses and scientific content after unexpected simulation deaths.

Keywords:
bootcampdeathdebriefingpsychological safetysimulationsimulation death

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Area of Science:

  • Medical Education
  • Surgical Training
  • Patient Simulation

Background:

  • Medical students often report feeling unprepared for patient death.
  • Simulation training offers a controlled environment for practicing responses to patient death.
  • Structured debriefing is crucial for processing simulated experiences.

Purpose of the Study:

  • To assess the impact of unexpected patient death during surgical simulation on medical students' anxiety.
  • To develop and evaluate a debriefing tool for managing emotional and scientific aspects of simulation-related patient death.

Main Methods:

  • Nineteen surgical residents participated in a preparatory course with a decision-making simulation.
  • Six participants experienced unexpected patient death within the simulation.
  • Anxiety levels were measured before and after a structured debriefing using the Gather Analyze Summarize (GAS) model.

Main Results:

  • Learners who experienced simulation death reported high anxiety pre-debriefing.
  • Post-debriefing anxiety levels in those who experienced death were similar to those who did not.
  • A bi-directional debriefing instrument was developed based on the GAS model.

Conclusions:

  • Unexpected patient death in simulation, when followed by structured debriefing, can be a valuable learning experience.
  • The developed debriefing tool addresses both the emotional and scientific components of simulation death.
  • This approach can help surgical educators prepare trainees to manage the emotional impact of patient death.