Maximizing Learning in Healthcare Simulation: Managing Cognitive Load
In the realm of healthcare simulation, design considerations for effective learning lies in understanding and optimizing cognitive load. The Healthcare Simulation Dictionary defines Cognitive Load as the amount of information the working memory of the participant and facilitator can manage at any given point. Simulation educators can draw from research and best practices to guide the creation of simulation scenarios that enable learners to achieve desired learning outcomes. In this article by Melissa Tulley, MSN, RN, CHSE, the concepts of cognitive load and its implications for healthcare simulation design will be explored to provide practical advice for architects of healthcare simulation scenarios.
Recognize Cognitive Challenges
When designing healthcare simulations, an essential function for simulation designers is to acknowledge the inherent cognitive load learners face. Cognitive load can be divided into three main types: intrinsic, extraneous, and germane. Intrinsic cognitive load is the inherent mental effort required by a task. Cognitive Load in clinical simulation depends on the complexity and novelty of the material being learned. The brain has a limited capacity for processing such information, and when capacity is exceeded, learning and problem-solving can become challenging.
Extraneous load is the cognitive load imposed by the instructional design, format, or environment. Poorly designed training materials or confusing instructions can unnecessarily increase extraneous cognitive load, diverting mental resources from the actual learning process. Germane cognitive load is associated with productive mental effort directly related to understanding and integrating new information into existing knowledge structures. Effective learning occurs when the simulation designer can increase the germane load while minimizing the extraneous load.
Neuroscience has provided invaluable insights into the nature of cognitive load and how the human brain handles information during training. Working memory is a limited-capacity system that temporarily holds and processes information. High cognitive load can overload working memory, impairing the retention and manipulation of new information. Functional MRI studies have shown increased activity in prefrontal cortex regions during high-load tasks. Neuroimaging studies suggest that experts in a domain exhibit greater neural efficiency. Thanks to streamlined neural pathways and efficient mental models, learners can process complex information with less cognitive load. In real-life patient care, professionals expend significant cognitive energy to make critical decisions for each patient.
The interpretation of vast amounts of data and critical thinking processes ensure the right decisions are made for optimal patient care. In simulation scenarios, we replicate these demanding healthcare environments. However, we also introduce an additional cognitive load, which stems from the participant’s conscious or subconscious efforts to distinguish between what is simulated and what is not. This phenomenon, often referred to as the “cognitive third space of simulation,” adds complexity to the learning process.
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Design Choices and the Zone of Proximal Development
The principles discussed here extend to various decisions made in scenario design. The learning design must consider the Zone of Proximal Development (ZPD) developed by the Russian psychologist Lev Vygotsky, which is particularly relevant in the context of education and, in this case, simulation education. The ZPD is crucial for understanding how learners acquire new knowledge and skills, especially when applied in education through healthcare simulation. The ZPD can be defined as the range of tasks and activities that a learner can perform with the help and guidance of a more knowledgeable person, typically a teacher, mentor, or, in the case of simulation education, the educational system itself; somewhat like a competency level.
The concept highlights that learners are dynamic in their abilities but can progress when provided with the right support and scaffolding. ZPD plays a pivotal role in shaping the cognitive load experienced by learners. For example, when dealing with diagnostic imaging like chest X-rays, should you provide an explicit result or have participants interpret the image? There’s no one-size-fits-all answer. The key is to align the decision with the cognitive load that best serves your learners, considering their zone of proximal development. In other words, educators must assess the learner’s current level of competence, understanding what they can do independently and what they cannot. Scaffolding provided through prompts, cognitive aids or guidance reduces difficulty levels but lifts cognitive load to allow for targeted learning to occur.
Be sure to check out 5 Ways to Avoid Cognitive Overload in Virtual Simulation Training for virtual specific concepts.
How to Channel Cognitive Energy
Simulation architects have the power to guide participants’ cognitive energy toward what is most important for the learning objectives. Here is a specific example to consider about the interpretation of test results in an electronic health record. The format in which these results are presented can significantly impact cognitive load. Some electronic health records color-code results, making recognition easier to distinguish between normal and abnormal values. Others may provide visual aids such as reference ranges. Simulating the format and presentation of the clinician’s EHR decreases cognitive load.
Additionally, when considering ZPD, experienced clinicians understand that the healthcare team members must interpret test results in the context of the individual patient’s health status. Critical thinking can be enhanced for the learners when consideration is given to a normal value for one patient. Healthcare simulation design choices matter. Here are three options that have different pros and cons.
All these approaches are valid, but the choice should align with the intended learning objectives and the ZPD. If interpreting test results in detail is crucial for the learners, then providing comprehensive information is appropriate. However, if these results are peripheral to the case’s bigger picture, a more streamlined approach reduces unnecessary cognitive load.
Moving Beyond Realism
A common misconception in healthcare simulation design is the pursuit of realistic clinical atmospheres. However, successful modern simulationists recognize that the goal is not to replicate reality but to optimize learning. Replication of every aspect of clinical practice can introduce unnecessary cognitive load. In cases where certain elements aren’t significantly relevant to the learning objectives, avoid including them in the scenario. Requiring learners to engage in non-essential activities can be a waste of time and an imposition on their cognitive processing capacity. Of course, the simulation designer must consider the level of the participants and the overall clinical simulation scenario objectives.
Architecting Effective Learning
In moderate to complex healthcare simulation scenarios, the role of the designer is pivotal. Hundreds of design decisions impact how participants extract data from the experience to enhance their performance. Awareness of the cognitive load placed on learners is crucial for real patient care and clinical simulation. Designers must understand the influence of their choices and be deliberate in their decisions to enhance the efficiency and effectiveness of the simulation-based learning process. By maximizing learning and managing cognitive load, simulationists can ensure that clinical simulation scenarios are realistic and valuable for professional development.
Examples of Considerations in Design Decisions
The following healthcare simulation design situations offer specific examples of how cognitive load can be managed effectively.
- Diagnostic Imaging Interpretation Scenario: Your simulation focuses on diagnosing a patient with respiratory symptoms, and a chest X-ray is part of the diagnostic process.
- Cognitive Load Management: You can choose how to present the chest X-ray results.
- Option A: Provide a clear interpretation by saying, “The chest X-ray shows pneumonia.”
- Option B: Display the chest X-ray image and ask participants to interpret it.
- Consideration: If the learning objective is to teach learners how to identify pneumonia on a chest X-ray, Option B is appropriate for reinforcing the learner’s image interpretation skills. However, if the focus is on clinical decision-making or treatment planning, Option A reduces cognitive load, allowing learners to concentrate on broader aspects of patient care.
- Cognitive Load Management: You must decide how to present medication information:
- Option A: Provide detailed drug information (e.g., dosage, administration route, side effects) for each medication the learner must administer.
- Option B: Offer a simplified medication chart indicating which medications to administer without detailed information.
- Consideration: If the simulation primarily aims to teach medication administration skills, Option A can be valuable for learners. However, if the focus is on broader patient management, Option B streamlines cognitive load, allowing learners to prioritize clinical decision-making over medication details.
- Cognitive Load Management: How do you present the patient’s medical history?
- Option A: Provide a lengthy electronic health record with extensive patient history details, including all relevant and irrelevant information.
- Option B: Offer a concise summary of crucial patient history points relevant to the current case, eliminating distractors, and leading the clinician to the priority information.
- Consideration: Option B is efficient when quick decision-making and prioritization are crucial in clinical scenarios. Learners can focus on the most pertinent aspects of the patient’s history without getting lost in irrelevant details. However, Option A is appropriate in situations where a detailed patient history review is a critical learning objective.
- Cognitive Load Management: How do you incorporate clinical decision support systems?
- Option A: Fully replicate real-world decision support tools, with all the complexity they entail.
- Option B: Simplify the decision support tool to focus on key features and streamline usability in specific use cases.
- Consideration: If the goal is to teach learners how to navigate complex clinical decision support systems within a time-sensitive patient encounter, decrease the cognitive load by adding embedded participants as guides or experts for system utilization. However, suppose the focus is on demonstrating the application of the tool’s core functions and how to use them effectively. In that case, Option B minimizes unnecessary cognitive load, ensuring learners grasp the essential concepts without feeling overwhelmed. Also, the simulation lab’s “Voice of God,” the overhead speaker, can be used to guide learners through the system from the control room.
- Cognitive Load Management: How do you facilitate communication among participants?
- Option A: Set up the simulation to include the realities of communicating over the phone or mimicking electronic health record messaging. If the specialist or specific team member is never at the bedside in real life, plan to recreate that reality.
- Option B: Facilitate face-to-face or verbal communication between participants.
- Consideration: Option A is effective if the learning objective is to practice and improve communication skills within a dispersed healthcare team. However, Option B reduces the cognitive load associated with written messaging to address broader communication attitudes and teamwork and encourages participants to focus on effective collaboration and team problem-solving.
In all these examples, the key is to align the design choices with the specific learning objectives and the level of cognitive load that best serves the learners. Effective healthcare simulation design requires thoughtful consideration of how to optimize the learning experience while minimizing unnecessary cognitive burdens.
Melissa Jo Tully, BSN, MHPE, RN-BC, is a highly accomplished healthcare professional with a passion for education and patient safety. With a Master’s degree in Health Professional Education from the College of Medicine at Vanderbilt University, Melissa has honed her expertise in developing innovative programs to enhance healthcare performance and quality. As an experienced nurse, Melissa followed her passion for lifelong learning by exploring nursing specialties through her early nursing career as a float nurse, including working in critical care, emergency room, labor and delivery, and hospice. Melissa brings a wealth of knowledge and experience to her role. Since 2009, she has been dedicated to simulation-based education programs at Vanderbilt Medical Center, at All Children’s Hospital Johns Hopkins Medicine, and HCA Northside Hospital where she has made significant contributions to improving patient outcomes through the power of simulation. Melissa has successfully developed instructor training and led orientation programs, nurse residency simulation programs, resuscitation, physician residency programs, standardized patient programs for communication training. While at John’s Hopkins she started the initiative to begin 3D printing for pre surgical planning, as well contributed to the construction design of the Simulation Center in the Research and Education Building. Melissa launched her career in consulting, by starting Medical Simulation Consulting. Her firm’s primary focus lies in designing, developing, and evaluating simulation programs that integrate augmented and virtual reality technology, as well as audiovisual technologies. She has contributed her expertise to virtual reality projects for Shadow Health, VCom 3D, SynDaver, and Lumeto. Driven by a deep-rooted desire to enhance patient safety and quality of care, Melissa continuously seeks opportunities to push the boundaries of simulation-based education. Through her expertise and leadership, she inspires and empowers healthcare professionals to strive for continuous improvement and make a positive impact on the lives of patients. Melissa Tully is a trailblazer in healthcare simulation education, and her dedication to advancing the field is evident in her contributions and achievements.