SKILLQUBE stands out as a groundbreaking innovative solution that brings clinical simulation training to new heights. Innovation is the cornerstone of progress in the realm of medical simulation. With advancements in technology, the landscape of medical education is evolving rapidly, offering more immersive and effective learning experiences. One of the best-known learning theories in the simulation community is the Cognitive Load Theory (CLT). In a nutshell, CLT describes the competition between different cognitive loads (intrinsic, extrinsic and germane cognitive load). While extrinsic and intrinsic cognitive load represent an impediment to the learning process, learning-related cognitive load is closely linked to learning success. This HealthySimulation.com article by Tobias Sambale, Paramedic and Educator from SKILLQUBE, will show how intrinsic and extrinsic cognitive load can be reduced through the targeted use of simulation technology.
How Cognitive Load Theory Applies to Clinical Learning
Cognitive Load Theory (CLT) is applicable to healthcare simulation to provide a framework for simulation design. CLT is an instructional theory that focuses on the relationship between the working memory and long-term memory. CLT can guide educators to design learning opportunities to promote information transfer from short-term memory to working memory to long-term memory. Too much information at one time can actually hinder learning as barriers in the transfer of information from the working memory to long term memory. There are three loads associated with learning:
- Intrinsic: complexity of the material to be learned
- Extrinsic: distractors of learning
- Germane: allows for transformation of learning from working memory to long-term memory
The Specific Requirements in Simulation Training
Simulation training causes a very special form of excitement. Although similar to the excitement of real patient care, differences remain. Many participants in simulation training feel observed and “as if they are taking an exam”. Due to the multi-professional teams, there are usually also real hierarchies between the participants and each of them wants to make the best possible impression on the trainers and the group. In addition, simulation scenarios are always accompanied by artifacts. The resuscitation phantom or the patient actor are not real patients. There are rules as to which measures can be carried out realistically (e.g. intubation on the resuscitation phantom) and which should only be suggested (intubation on the patient actor).
The intrinsic and extrinsic cognitive load is therefore significantly higher than in reality. One goal of SKILLQUBE is to align simulation products as closely as possible to reality (e.g. through realistic operation of a defibrillator) and to reduce friction (e.g. simple retrieval of image material or laboratory values on a tablet). Additional distracting factors and artifacts are thus reduced. This can be illustrated using a case study.
Case Study Scenario: An Unconscious Patient
Scenario: Unconscious Patient. The team of an emergency department (consultants, residents, nurses) is confronted with the following simulation scenario as part of an “in-situ” simulation:
“A 76-year-old somnolent patient is admitted to your emergency department. The emergency services report that he has been found laying on the floor of his living room in a reduced general condition. He was oriented to the person and place, but not to the time and situation. GCS 13 (3/4/6). Injuries could not be ruled out, but no concrete evidence was initially found during the examination.
Vital Signs: RF 22/min, SpO2 92% without oxygen, HR 114/min, BP 94/51, Temp 34.5°C/94.1
Measures Taken: Oxygen administration (6 L/min via non-rebreather mask), infusion therapy (500 ml warmed Ringer’s solution) and continuous monitoring of vital signs. Catecholamine therapy was initially considered but the EMS team decided against. The spine was immobilized due to the impaired consciousness and suspected fall.”
Assignment: The consultant/facilitator assigns the roles. The roles of resident and a nurse are instructed to stabilize the patient’s respiratory situation (Airway and breathing). In the meantime, a sonography according to the RUSH protocol is performed. The rest of the team will establish monitoring and perform an arterial blood gasses (ABG). A CT scan is requested.
Scans: The following CT scans of the head and cervical spine are found to be normal. Threatening injuries can therefore be ruled out as far as possible. The patient’s condition remains critical. Invasive ventilation is therefore initiated. The CT of the thorax shows a diffuse milky glass-like infiltrate. The laboratory also indicates an inflammatory process. In addition, there are strongly increased retention parameters, a CK of 41,240 U/L and a myoglobinuria. A working diagnosis of atypical pneumonia and rhabdomyolysis after recumbent muscular trauma following a suspected fall is made and antibiotic treatment is initiated. In addition, the intensive care unit will be involved so that the patient can be transferred for a decision to start dialysis treatment.
Overview: The participants moved through three phases of care:
- Stabilization
- Differential diagnosis
- Targeted therapy and further care
Each phase offered the opportunity for very different learning objectives. As this was an in-situ simulation, there must be time available for unplanned events. So, how can SKILLQUBE help the learners to achieve their goals and impact cognitive load/ The answer is the tablet-based simulators. The tablets can display laboratory and diagnostic findings, vital sounds, and ventilator settings/
One learning objective in the stabilization phase could relate to optimizing the oxygen supply. For example, a decision has to be made as to whether invasive ventilation is necessary.
During the differential diagnosis phase, the focus could be on laboratory findings (possibly including tox screening) and imaging. In addition to therapeutic measures, targeted therapy may also focus on communicative aspects, such as consultation with the intensive care unit. In each phase, the participants have different information needs in order to achieve the learning objectives.
During stabilization, for example, the focus is on displaying the monitors, the ventilator and the blood gas analysis, while more precise examination results and findings (e.g. by displaying X-ray images) should be available for differential diagnostics. Participants also need to know how to contact the intensive care unit. Is there a telephone available for this, for example?
Reducing Complexity to Minimize CLT Overload
Such a scenario must be well prepared. However, the process is extensive, complex and offers many potential sources of error. This means that both the intrinsic and extrinsic cognitive load for the participants is very high. Display errors can worsen the immersive experience or connection problems could lead to important vital signs not being available in time. Such incidents inevitably lead to a reduction in the learning outcome. To avoid this, the use of methods and technologies that work together harmoniously makes sense.
One key to this is a central control unit that breaks down the scenario into logical phases and transmits the necessary information to the monitors and ventilators used. SKILLQUBE developed qubeCONTROL for this, an iPad-based control unit with which we can run our monitor and ventilator simulators in parallel. The vital parameters of the simulated patients are transmitted in real time and therapeutic interventions, such as ventilation settings or defibrillation, are also received without delay.
SKILLQUBE further developed the qubeASSESS to provide participants in simulation training with additional data. They can receive intensive care parameters, laboratory values, image files, PDFs and much more on another iPad. This avoids parallel queries about values and information and allows participants to focus fully on the scenario. The targeted use of technology directly reduces the extrinsic cognitive load. The intrinsic cognitive load is indirectly reduced by making the medical scenario more precise. In this way, learning success can be increased in a targeted manner.
