Simulation-based Education and Training
Expert-defined terms from the Postgraduate Certificate in Medical Education and Simulation course at London School of Planning and Management. Free to read, free to share, paired with a professional course.
Adaptive Learning #
Adaptive Learning
Explanation #
A teaching strategy that modifies instructional content in real time based on learner performance, aiming to close gaps and accelerate mastery. Example: A simulation platform that increases scenario complexity after a learner successfully completes basic tasks. Practical application: Used in virtual patient encounters to tailor difficulty to each resident’s skill level. Challenges: Requires robust data analytics and may increase cognitive load for instructors who must interpret performance metrics.
After‑Action Review (AAR) #
After‑Action Review (AAR)
Explanation #
A structured discussion that follows a simulation, focusing on what was intended, what occurred, and why discrepancies arose. Example: After a cardiac arrest scenario, the facilitator guides the team through a review of decision points and communication breakdowns. Practical application: Enhances team situational awareness and promotes continuous improvement. Challenges: Time constraints and facilitator skill level can limit depth of analysis.
Airway Management Trainer #
Airway Management Trainer
Explanation #
A device that replicates the anatomy of the upper airway for practicing intubation, laryngoscopy, and related techniques. Example: A high‑fidelity manikin with interchangeable airway models for different age groups. Practical application: Allows repeated practice without patient risk, essential for anesthesia and emergency medicine trainees. Challenges: Limited tactile realism compared with live tissue; cost of high‑fidelity models.
Algorithmic Simulation #
Algorithmic Simulation
Explanation #
A simulation driven by a predefined set of rules that dictate outcomes based on learner inputs, often used for diagnostic reasoning. Example: A virtual case where selecting the correct laboratory test leads to a specific diagnosis pathway. Practical application: Useful for teaching differential diagnosis in internal medicine. Challenges: May oversimplify complex clinical reasoning and require extensive programming.
Anchoring Bias #
Anchoring Bias
Explanation #
A mental shortcut where clinicians rely heavily on the first piece of information encountered, potentially overlooking later data. Example: Assuming a patient’s headache is migraine because of prior history, missing signs of subarachnoid hemorrhage. Practical application: Debriefings can highlight anchoring bias to improve diagnostic vigilance. Challenges: Hard to eradicate; requires repeated exposure to varied cases.
Animation‑Based Simulation #
Animation‑Based Simulation
Explanation #
Use of animated sequences to depict physiological processes or clinical scenarios, enhancing visual learning. Example: An animated heart showing electrical conduction abnormalities during arrhythmia training. Practical application: Supplements hands‑on practice for concepts difficult to demonstrate physically. Challenges: May lack interactivity; requires high‑quality graphics.
Assessment of Learning (AoL) #
Assessment of Learning (AoL)
Explanation #
Systematic evaluation of learner competence, often using checklists, rating scales, or performance metrics within simulations. Example: Scoring a learner’s performance during a simulated central line insertion using a validated rubric. Practical application: Provides data for credentialing and curriculum refinement. Challenges: Ensuring reliability and validity across different raters.
Authentic Context #
Authentic Context
Explanation #
The degree to which a simulation mirrors the real‑world environment, including physical setting, equipment, and patient characteristics. Example: A mock emergency department stocked with actual monitors, medication carts, and realistic lighting. Practical application: Increases transferability of skills to clinical practice. Challenges: Higher cost and logistical complexity for high‑authenticity setups.
Benchmarking #
Benchmarking
Explanation #
Comparing learner or program performance against established standards or peer institutions to identify gaps. Example: Measuring simulation‑based procedural success rates against national benchmarks for laparoscopic skills. Practical application: Guides curriculum adjustments and resource allocation. Challenges: Requires access to comparable data and may be influenced by differing assessment tools.
Blended Learning #
Blended Learning
Explanation #
An instructional approach that combines face‑to‑face simulation sessions with online preparatory or supplemental material. Example: Learners complete an online module on sepsis pathophysiology before participating in a high‑fidelity scenario. Practical application: Optimizes classroom time for active practice. Challenges: Learner engagement with pre‑work can be variable; technology infrastructure must be reliable.
Body‑Sensor Simulation #
Body‑Sensor Simulation
Explanation #
Integration of sensors (e.G., Heart‑rate, motion) on the learner to capture real‑time physiological data during simulation. Example: A mannequin that adjusts vital signs based on the learner’s stress level measured by a wearable. Practical application: Provides objective data on learner stress and workload. Challenges: Calibration issues and potential privacy concerns.
Boundary‑Based Learning #
Boundary‑Based Learning
Explanation #
Designing simulations that push learners just beyond their current competence, encouraging growth without overwhelming them. Example: Providing limited decision‑support cues in a trauma scenario for intermediate learners. Practical application: Promotes progressive mastery. Challenges: Determining the optimal difficulty threshold for diverse learners.
Brigade Training Model #
Brigade Training Model
Explanation #
A framework that emphasizes coordinated, multi‑disciplinary practice using simulation to improve team dynamics and communication. Example: A joint simulation for surgeons, anesthesiologists, and nurses focusing on operating‑room crisis management. Practical application: Reduces adverse events through improved teamwork. Challenges: Scheduling across professions and aligning learning objectives.
Cadaver‑Based Simulation #
Cadaver‑Based Simulation
Explanation #
Utilization of human cadavers for hands‑on practice of invasive procedures, offering authentic tissue handling. Example: Practicing thoracostomy on a fresh‑frozen cadaver. Practical application: Provides unparalleled realism for surgical skill acquisition. Challenges: Limited availability, ethical considerations, and need for specialized facilities.
Case‑Based Learning (CBL) #
Case‑Based Learning (CBL)
Explanation #
An educational strategy where learners analyze and discuss real or simulated patient cases to apply knowledge. Example: Small groups work through a simulated diabetic ketoacidosis case before debrief. Practical application: Enhances critical thinking and integrates theory with practice. Challenges: Requires skilled facilitation to keep discussions focused.
Check‑List #
Check‑List
Explanation #
A concise, itemized list used during simulation to ensure each step of a procedure is performed correctly. Example: A surgical time‑out checklist before incision. Practical application: Reduces errors and reinforces best practices. Challenges: Over‑reliance may impede adaptability in unexpected situations.
Clinical Decision‑Support Simulation #
Clinical Decision‑Support Simulation
Explanation #
Simulations that embed decision‑support tools within a digital patient chart, mirroring real‑world workflow. Example: A simulated EHR that alerts the learner to abnormal lab values during a sepsis scenario. Practical application: Trains learners to use technology effectively while maintaining clinical reasoning. Challenges: Technical integration and risk of alert fatigue.
Closed‑Loop Communication #
Closed‑Loop Communication
Explanation #
A communication technique where the sender transmits a message, the receiver repeats it back, and the sender confirms accuracy. Example: “Administer 1 mg epinephrine IV,” followed by “1 mg epinephrine IV, confirmed.”
Practical application #
Minimizes miscommunication during high‑stress simulations. Challenges: Requires consistent practice to become automatic.
Coaching Model #
Coaching Model
Explanation #
An instructional approach where an experienced educator provides real‑time guidance, observation, and corrective input during simulation. Example: A senior anesthetist observes a trainee’s airway management and offers micro‑tips throughout the scenario. Practical application: Accelerates skill acquisition and self‑reflection. Challenges: Balancing support with learner autonomy; potential for over‑directiveness.
Competency‑Based Education (CBE) #
Competency‑Based Education (CBE)
Explanation #
An educational paradigm focused on achieving defined competencies rather than time‑based progression. Example: Learners must demonstrate proficiency in simulated resuscitation before advancing to clinical duties. Practical application: Aligns training with accreditation standards. Challenges: Defining measurable competencies and ensuring inter‑rater reliability.
Conceptual Mapping #
Conceptual Mapping
Explanation #
A visual tool that organizes related concepts, facilitating deeper understanding of complex topics. Example: Mapping the cascade of events in septic shock during debrief. Practical application: Helps learners integrate new knowledge with existing frameworks. Challenges: Time‑intensive and may be less effective for novices.
Confidence Interval (CI) in Simulation Research #
Confidence Interval (CI) in Simulation Research
Explanation #
A range of values that likely contain the true population parameter, used to interpret simulation study outcomes. Example: Reporting a 95 % CI for the improvement in procedural skill after a simulation curriculum. Practical application: Informs evidence‑based curriculum development. Challenges: Requires statistical expertise and adequate sample sizes.
Contextual Fidelity #
Contextual Fidelity
Explanation #
The extent to which the simulation replicates the contextual variables (e.G., Noise, interruptions) of the clinical setting. Example: Adding background chatter and overhead alarms in an emergency department simulation. Practical application: Prepares learners for real‑world distractions. Challenges: Balancing realism with learner focus; risk of cognitive overload.
Continuing Professional Development (CPD) Simulation #
Continuing Professional Development (CPD) Simulation
Explanation #
Simulation activities designed for practicing clinicians to update and maintain competencies. Example: Annual simulation‑based airway management refresher for anesthesiologists. Practical application: Supports regulatory requirements and patient safety. Challenges: Engaging busy professionals and measuring long‑term impact.
Co‑Creation of Scenarios #
Co‑Creation of Scenarios
Explanation #
Involving learners in the development of simulation scenarios to ensure relevance and ownership. Example: Residents contribute case details for a neonatal resuscitation scenario. Practical application: Increases motivation and aligns training with actual clinical challenges. Challenges: Time required for collaboration and potential variability in scenario quality.
Credibility Gap #
Credibility Gap
Explanation #
The disparity between a learner’s expectation of realism and the actual fidelity of the simulation, which can undermine engagement. Example: Learners notice unrealistic mannequin skin texture, reducing immersion. Practical application: Guides designers to prioritize critical fidelity elements. Challenges: Managing expectations while working within budget constraints.
Debriefing Model #
PEARLS
Explanation #
A five‑step approach—Planning, Engagement, Analysis, Reflection, Learning, and Summary—used to conduct effective debriefs. Example: Facilitator follows PEARLS to guide a discussion after a trauma simulation. Practical application: Standardizes debrief quality across facilitators. Challenges: Requires facilitator training and flexibility to adapt to learner needs.
Deliberate Practice #
Deliberate Practice
Explanation #
Focused, repetitive performance of a skill with immediate feedback and incremental difficulty adjustments. Example: Repeatedly practicing central line insertion on a task trainer until competence is achieved. Practical application: Proven to improve procedural proficiency. Challenges: Demands time, resources, and expert feedback.
Design Thinking in Simulation #
Design Thinking in Simulation
Explanation #
A problem‑solving methodology that emphasizes empathy, ideation, and testing to create learner‑focused simulation experiences. Example: Conducting focus groups with nurses to refine a medication‑error scenario. Practical application: Produces more relevant and engaging simulations. Challenges: Requires cross‑functional collaboration and flexibility.
Diagnostic Reasoning Simulation #
Diagnostic Reasoning Simulation
Explanation #
Simulated patient encounters that challenge learners to generate differential diagnoses, order investigations, and reach a final diagnosis. Example: An interactive platform where learners select labs and imaging to narrow down causes of chest pain. Practical application: Enhances critical thinking and reduces diagnostic error. Challenges: Complex programming and need for evidence‑based content.
Distributed Practice #
Distributed Practice
Explanation #
Scheduling learning sessions over time rather than massed in a single block, improving long‑term retention. Example: Conducting brief simulation drills weekly instead of a single intensive workshop. Practical application: Aligns with adult learning principles and improves skill durability. Challenges: Requires coordinated scheduling and ongoing commitment.
Dyad Practice #
Dyad Practice
Explanation #
Two learners work together on a simulation task, alternating roles of performer and observer, providing mutual feedback. Example: Two residents alternate performing a lumbar puncture while the other observes and critiques. Practical application: Maximizes resource utilization and promotes peer teaching. Challenges: May reduce individual hands‑on time; requires clear role delineation.
E #
Learning Integration
Explanation #
Incorporating online modules, quizzes, and multimedia resources to complement face‑to‑face simulation. Example: A pre‑simulation module on sepsis guidelines accessed via the LMS. Practical application: Standardizes baseline knowledge before hands‑on practice. Challenges: Ensuring learner completion and aligning online content with simulation objectives.
Embedded Simulation #
Embedded Simulation
Explanation #
Conducting simulation activities within the actual clinical environment, using real equipment and staff. Example: Running a mock code in a pediatric ward during a low‑acuity period. Practical application: Provides authentic context and immediate relevance. Challenges: Disruption to patient care and need for rapid set‑up.
Entrustable Professional Activity (EPA) #
Entrustable Professional Activity (EPA)
Explanation #
A core clinical task that a trainee can be entrusted to perform unsupervised once sufficient competence is demonstrated. Example: Performing a focused abdominal exam in a simulated setting as an EPA. Practical application: Bridges assessment and real‑world responsibility. Challenges: Defining clear entrustment thresholds and ensuring consistent assessment.
Ergonomic Simulation #
Ergonomic Simulation
Explanation #
Designing simulation environments that reflect optimal ergonomic principles to reduce strain and error. Example: Positioning monitors at eye level during a simulated operating room case. Practical application: Reinforces safe equipment handling habits. Challenges: May require modification of existing simulation labs.
Event‑Based Learning #
Event‑Based Learning
Explanation #
Learning that occurs as a direct response to a specific clinical event, often captured through simulation. Example: Debriefing after a simulated adverse drug reaction to extract teaching points. Practical application: Makes learning highly relevant and memorable. Challenges: Requires rapid facilitation and may be limited by unplanned events.
Expertise Reversal Effect #
Expertise Reversal Effect
Explanation #
Providing less guidance to experts and more to novices; overly detailed instruction can hinder advanced learners. Example: Using a basic task trainer for senior residents who already master the skill. Practical application: Tailors simulation difficulty to learner level. Challenges: Accurately assessing learner expertise to adjust support.
Facilitator Training Program #
Facilitator Training Program
Explanation #
Structured curriculum designed to equip educators with the knowledge and skills needed to run effective simulations. Example: A 2‑day workshop covering scenario design, debriefing techniques, and assessment tools. Practical application: Improves consistency and quality of simulation delivery. Challenges: Allocating time for busy clinicians and maintaining ongoing competence.
Feedback Sandwich #
Feedback Sandwich
Explanation #
A feedback method that starts with positive comments, inserts areas for improvement, and ends with encouraging remarks. Example: “Your communication was clear, however the medication dosage was off; overall you handled the crisis well.”
Practical application #
Helps maintain learner morale while addressing gaps. Challenges: May be perceived as formulaic; requires authentic engagement.
Fidelity Ladder #
Fidelity Ladder
Explanation #
A conceptual model that categorizes simulation fidelity from low (task trainers) to high (full‑scale immersive environments). Example: Using a low‑fidelity chest tube model for basic skill acquisition before progressing to a high‑fidelity torso trainer. Practical application: Guides educators in selecting appropriate fidelity levels for learning objectives. Challenges: Misinterpretation can lead to unnecessary expense.
Formative Assessment #
Formative Assessment
Explanation #
Evaluation intended to inform learners of their current performance and guide future improvement, without high‑stakes consequences. Example: Real‑time checklist scores during a simulated resuscitation used to coach the team. Practical application: Supports ongoing skill development. Challenges: Learners may undervalue low‑stakes feedback if not emphasized.
Functional Fidelity #
Functional Fidelity
Explanation #
The degree to which the simulated task replicates the functional aspects of the real task, regardless of physical appearance. Example: A virtual reality colonoscopy that mimics tissue resistance and navigation cues. Practical application: Allows focus on skill acquisition without exact physical replication. Challenges: May not translate to real‑world tactile expectations.
Gamification in Simulation #
Gamification in Simulation
Explanation #
Incorporating game elements—such as scores, leaderboards, and challenges—into simulation to increase engagement. Example: Assigning points for each correct step in a simulated sepsis protocol. Practical application: Boosts learner motivation and competitive spirit. Challenges: Over‑emphasis on competition can detract from reflective learning.
Global Rating Scale (GRS) #
Global Rating Scale (GRS)
Explanation #
A tool that provides an overall assessment of a learner’s performance using a Likert‑type scale across multiple domains. Example: Rating a learner’s communication on a 1‑5 scale during a simulated handover. Practical application: Offers quick, holistic evaluation. Challenges: Subjectivity can affect inter‑rater reliability.
High‑Fidelity Manikin #
High‑Fidelity Manikin
Explanation #
A sophisticated mannequin capable of displaying realistic vital signs, airway patency, and pharmacologic responses. Example: A SimMan™ used for advanced cardiac arrest scenarios. Practical application: Enables realistic crisis management training. Challenges: High acquisition and maintenance costs; requires technical support.
Human Factors Engineering #
Human Factors Engineering
Explanation #
The study of how humans interact with equipment and environments, applied to improve simulation design and reduce error. Example: Designing a medication‑safety simulation that mirrors real pharmacy workflows. Practical application: Enhances realism and promotes safe practices. Challenges: Requires interdisciplinary expertise.
Hybrid Simulation #
Hybrid Simulation
Explanation #
Combining different simulation modalities (e.G., A task trainer attached to a high‑fidelity manikin) to achieve specific learning goals. Example: Attaching a laparoscopic trainer to a torso manikin for intra‑abdominal procedures. Practical application: Provides targeted realism where needed. Challenges: Integration complexity and potential for technical issues.
Immersive Simulation #
Immersive Simulation
Explanation #
A simulation that fully engages the learner’s senses, often using VR headsets or 360° environments, to create a sense of “being there.”
Example #
A VR operating room where learners perform a laparoscopic cholecystectomy. Practical application: Enables practice of rare or hazardous scenarios without risk. Challenges: Motion sickness, hardware cost, and content development.
In‑Situ Simulation (ISS) #
In‑Situ Simulation (ISS)
Explanation #
Conducting simulation exercises in the actual clinical setting with the regular staff and equipment. Example: A mock code in the intensive care unit during a scheduled downtime. Practical application: Identifies latent safety threats and improves team readiness. Challenges: Coordination with patient care, potential disruption, and need for rapid set‑up.
Instructional Design #
Instructional Design
Explanation #
The systematic process of creating educational experiences, including analysis, design, development, implementation, and evaluation. Example: Using the ADDIE framework to develop a simulation curriculum on obstetric emergencies. Practical application: Ensures alignment of objectives, activities, and assessments. Challenges: Time‑intensive and may require expertise in pedagogy.
Interprofessional Simulation #
Interprofessional Simulation
Explanation #
Simulation activities that involve learners from multiple health professions working together to achieve patient‑centered goals. Example: A joint trauma resuscitation drill with physicians, nurses, and paramedics. Practical application: Improves communication, role clarity, and patient safety. Challenges: Aligning schedules and curricular expectations across professions.
Learning Curve #
Learning Curve
Explanation #
The graphical representation of improvement in performance over repeated practice or exposure. Example: Plotting procedural success rates across successive simulation sessions. Practical application: Helps educators identify when learners achieve competence. Challenges: Individual variability may obscure group trends.
Learning Objectives #
Learning Objectives
Explanation #
Clear, measurable statements describing what learners should know or be able to do after a simulation. Example: “Demonstrate the correct sequence of steps for rapid sequence intubation.”
Practical application #
Guides scenario design and assessment. Challenges: Overly broad objectives can dilute focus; overly narrow objectives may limit depth.
Learning Management System (LMS) #
Learning Management System (LMS)
Explanation #
Software that hosts educational content, tracks learner progress, and facilitates communication. Example: Uploading pre‑simulation modules to Canvas for resident access. Practical application: Centralizes learning resources and records performance data. Challenges: Integration with simulation hardware and ensuring user adoption.
Learning Transfer #
Learning Transfer
Explanation #
The extent to which skills and knowledge acquired in simulation are applied to real clinical practice. Example: Residents who performed well in simulated code scenarios also demonstrate improved response times in actual emergencies. Practical application: The ultimate goal of simulation‑based education. Challenges: Measuring transfer objectively and accounting for confounding variables.
Live‑Feedback Systems #
Live‑Feedback Systems
Explanation #
Real‑time displays that provide learners with immediate data on their actions, such as timing, pressure, or physiological changes. Example: A monitor showing chest compression depth during a CPR simulation. Practical application: Enables instant correction and reinforces correct technique. Challenges: Information overload and potential distraction.
Macro‑Simulation #
Macro‑Simulation
Explanation #
Simulation that encompasses entire health‑care systems, often involving multiple departments and external agencies. Example: A city‑wide mass casualty incident exercise coordinated across hospitals and EMS. Practical application: Tests organizational readiness and inter‑agency coordination. Challenges: Logistical complexity, high resource demand, and need for extensive planning.
Micro‑Simulation #
Micro‑Simulation
Explanation #
Focused, brief simulations targeting a single skill or component, often using low‑fidelity models. Example: A 5‑minute knot‑tying station for surgical residents. Practical application: Efficiently builds foundational skills. Challenges: May lack contextual integration.
Mixed Reality (MR) #
Mixed Reality (MR)
Explanation #
A technology that overlays digital content onto the physical world, allowing interaction with both real and virtual objects. Example: Wearing AR glasses that display patient vitals on a mannequin during a procedure. Practical application: Enhances situational awareness and decision‑making. Challenges: Hardware cost, calibration, and potential technical glitches.
Multimodal Debrief #
Multimodal Debrief
Explanation #
A debriefing approach that incorporates several media—video, audio, performance metrics—to enrich reflection. Example: Reviewing a recorded simulation while discussing team communication. Practical application: Provides concrete evidence for learners to self‑evaluate. Challenges: Requires recording equipment and time for review.
Multisensory Simulation #
Multisensory Simulation
Explanation #
Simulation that engages multiple senses—touch, sound, sight—to increase immersion and realism. Example: Adding realistic heart sounds and tactile pulse feedback to a mannequin. Practical application: Improves skill retention and situational awareness. Challenges: Integration of diverse technologies and cost.
Near‑Peer Teaching #
Near‑Peer Teaching
Explanation #
More advanced learners facilitate education for those slightly less experienced, often within simulation contexts. Example: Senior residents lead a basic airway management workshop for junior residents. Practical application: Reinforces knowledge for both teacher and learner. Challenges: Ensuring teaching quality and providing appropriate oversight.
Non‑Technical Skills (NTS) #
Non‑Technical Skills (NTS)
Explanation #
Cognitive and interpersonal abilities essential for safe practice, distinct from clinical technical skills. Example: Crew Resource Management (CRM) principles taught through a simulated operating‑room crisis. Practical application: Reduces medical errors and improves patient outcomes. Challenges: Measuring NTS objectively and integrating them into assessment.
Objective Structured Clinical Examination (OSCE) #
Objective Structured Clinical Examination (OSCE)
Explanation #
A series of timed stations where learners perform clinical tasks assessed by trained examiners using standardized criteria. Example: A station where the learner obtains a focused history from a standardized patient with chest pain. Practical application: Provides reliable, high‑stakes assessment of clinical competence. Challenges: Resource intensive and requires extensive standardization.
Observer Role #
Observer Role
Explanation #
A designated learner who watches a simulation without direct participation, focusing on observation and feedback. Example: A senior resident observes a junior performing a lumbar puncture to later provide constructive critique. Practical application: Enhances analytical skills and promotes peer feedback. Challenges: May limit hands‑on experience; requires clear guidance on observation focus.
On‑Site Simulation #
On‑Site Simulation
Explanation #
Conducting simulation within the actual clinical area, using existing equipment and staff, without moving participants to a dedicated lab. Example: A mock code run in the neonatal intensive care unit during a scheduled low‑census period. Practical application: Increases realism and reveals latent safety threats. Challenges: Coordination with patient care and potential interruptions.
Operant Conditioning #
Operant Conditioning
Explanation #
A learning process where behavior is shaped by consequences; positive outcomes increase likelihood of repetition. Example: Providing immediate praise after a correct medication administration in simulation. Practical application: Encourages desired clinical behaviors. Challenges: Over‑reliance on external rewards may diminish intrinsic motivation.
Outcome‑Based Education #
Outcome‑Based Education
Explanation #
An educational approach that defines desired results first and then designs curriculum and assessments to achieve those outcomes. Example: Specifying that learners will demonstrate effective crisis communication as an outcome of a simulation module. Practical application: Aligns teaching with accreditation standards. Challenges: Requires clear, measurable outcomes and robust assessment tools.
Parallel Play #
Parallel Play
Explanation #
Two or more learners work on the same task simultaneously, each focusing on their own performance while observing each other. Example: Two trainees practice suturing on separate models side‑by‑side. Practical application: Increases efficiency and fosters peer learning. Challenges: May lead to competition rather than cooperation if not facilitated.
Patient Safety Incident (PSI) Simulation #
Patient Safety Incident (PSI) Simulation
Explanation #
A simulated scenario designed to replicate a real‑world patient safety event for training and system improvement. Example: A medication‑error simulation where a wrong drug is administered, prompting team response. Practical application: Teaches error recognition, reporting, and mitigation. Challenges: Balancing realism with emotional impact on learners.
Performance Metrics #
Performance Metrics
Explanation #
Quantitative measures that capture learner actions, timing, accuracy, or other objective data during simulation. Example: Time to first defibrillation in a cardiac arrest scenario. Practical application: Provides objective feedback and tracks progress over time. Challenges: Selecting relevant metrics and ensuring they reflect true competence.
Personal Protective Equipment (PPE) Simulation #
Personal Protective Equipment (PPE) Simulation
Explanation #
Training that focuses on correct use of PPE in simulated clinical environments, especially during infectious disease outbreaks. Example: A simulation of donning and doffing PPE for a COVID‑19 patient encounter. Practical application: Reduces risk of contamination and improves compliance. Challenges: Keeping protocols up‑to‑date with evolving guidelines.
Phantom Model #
Phantom Model
Explanation #
A synthetic construct that mimics human anatomy for practicing invasive procedures. Example: A silicone breast model for needle biopsy training. Practical application: Allows repetitive skill practice without biological specimens. Challenges: May not replicate exact tissue resistance or tactile feedback.
Physical Fidelity #
Physical Fidelity
Explanation #
The extent to which the physical aspects of a simulation (mannequin, instruments, setting) match the real clinical environment. Example: Using authentic defibrillator pads on a high‑fidelity manikin. Practical application: Enhances immersion and skill transfer. Challenges: Higher cost and maintenance requirements.
Pitfall Identification #
Pitfall Identification
Explanation #
The process of recognizing common mistakes or hazards within a simulation to inform future training. Example: Noting that learners consistently missed a medication allergy check in a simulated admission. Practical application: Directs curriculum revisions and targeted remediation. Challenges: Requires systematic observation and data collection.
Planning Phase (Simulation Design) #
Planning Phase (Simulation Design)
Explanation #
The initial stage of simulation development where goals, resources, and logistics are defined. Example: Conducting a needs analysis to determine gaps in pediatric resuscitation skills before creating a scenario. Practical application: Ensures relevance and feasibility. Challenges: Time‑intensive and may require stakeholder consensus.
Pre‑Briefing #
Pre‑Briefing
Explanation #
A concise session prior to simulation that outlines objectives, roles, and ground rules, preparing learners for the experience. Example: Explaining the scenario premise, safety measures, and confidentiality before a trauma drill. Practical application: Reduces anxiety and aligns learner focus. Challenges: Balancing sufficient information with preserving the element of surprise.
Procedural Simulation #
Procedural Simulation
Explanation #
Simulation focused on the acquisition and refinement of specific clinical procedures. Example: Practicing central venous catheter placement on a task trainer. Practical application: Builds competence before patient exposure. Challenges: May lack contextual decision‑making elements.
Psychological Fidelity #
Psychological Fidelity
Explanation #
The extent to which a simulation elicits the same mental and emotional responses as the real clinical situation. Example: Inducing stress through time pressure in a simulated code. Practical application: Encourages realistic decision‑making under pressure. Challenges: Managing learner stress to prevent burnout.
Quality Assurance (QA) in Simulation #
Quality Assurance (QA) in Simulation
Explanation #
Systematic processes to monitor, evaluate, and enhance the effectiveness of simulation programs. Example: Conducting annual reviews of scenario outcomes and facilitator performance. Practical application: Maintains high educational standards and compliance. Challenges: Requires dedicated resources and data management.
Rapid Cycle Deliberate Practice (RCDP) #
Rapid Cycle Deliberate Practice (RCDP)
Explanation #
A method where learners repeatedly perform a skill, receive immediate feedback, and restart the cycle until mastery is achieved. Example: Repeating a simulated intubation three times with brief coaching after each attempt. Practical application: Accelerates skill acquisition in high‑stakes procedures. Challenges: Requires facilitator expertise and may limit time for other learning objectives.
Recall Bias #
Recall Bias
Explanation #
A systematic error occurring when participants inaccurately remember past events, affecting the reliability of self‑reported simulation outcomes. Example: Learners over‑estimating the frequency of skills practiced during a simulation course. Practical application: Highlights the need for objective performance data. Challenges: Difficult to eliminate without objective measurement tools.
Reflective Practice #
Reflective Practice
Explanation #
The habit of thoughtfully analyzing one’s actions and thought processes to foster continuous improvement. Example: A learner journals about their decision‑making during a simulated sepsis case. Practical application: Deepens learning and promotes professional growth. Challenges: Requires time and guidance to be effective.
Remote Simulation #
Remote Simulation
Explanation #
Simulation delivered via internet platforms, allowing participants in different locations to engage synchronously or asynchronously. Example: A virtual reality trauma scenario accessed by learners across multiple hospitals. Practical application: Expands access to specialized training without travel. Challenges: Bandwidth limitations, technology compatibility, and reduced tactile feedback.