Development of Simple and Advanced Adult Proximal Tibia Simulators for a Decentralized Simulation-Based Education Model to Teach Paramedics-in-Training the Intraosseous Infusion Procedure
Bibliographic record
Abstract
Introduction During the COVID-19 pandemic, public health had advised practicing social distancing which led to the temporary shutdown of simulation laboratories or centralized simulation-based education model, shared spaces that healthcare workers such as paramedics use to train on important hands-on clinical skills for the job. One such skill is intraosseous (IO) access and infusion, the delivery of fluids and medication through the marrow or medullary cavity of the bone which provides fast and direct entry into the central venous system. This skill is critical in emergencies when peripheral access is not immediately available. To continue the training of paramedics in life-saving skills like IO infusion in the post-pandemic era, a decentralized simulation-based education (De-SBE) model was proposed. The De-SBE relies on the availability of inexpensive and flexible simulators that can be used by learners outside of the simulation laboratory. However, to date, there is a paucity of simulation design methods that stimulate creativity and ideation, and at the same time, provide evidence of validity for these simulators. Our exploratory research aimed to test a novel approach that combines components of development-related constraints, ideation, and consensus (CIC) approach to develop and provide content validity for simulators to be used in a De-SBE model. Materials and methods The development of the IO simulators was constrained to follow a design-to-cost approach. First, a modified design thinking session was conducted with three informants from paramedicine and medicine to gather ideas for the development of two IO simulators (simple and advanced). Next, to sort through, refine, and generate early evidence of the content validity of the simulators, the initial ideas were integrated into a two-round, modified Delphi process driven by seven informants from paramedicine and medicine. In addition, we surveyed the participants on how well they liked the CIC approach. Results The CIC approach generated a list of mandatory and optional features that could be added to the IO simulators. Specifically, six features (one mandatory and four optional) for the existing simple IO simulator and eight (three mandatories and five optional) for the advanced IO simulators were identified. Following a design-to-cost approach, the features classified as mandatory for the simple and advanced IO simulators were integrated into the final designs to maintain the feasibility of production for training purposes. The surveys with the participants showed that the CIC approach worked well in the group setting by allowing for various perspectives to be shared freely and ending with a list of features for IO simulator designs that could be used in the future. Some improvements to the approach included flagging for potential users to determine what works best concerning the mode of delivery (online or in person), and duration of the stages to allow for more idea generation. Conclusion The CIC approach led to the manufacturing of simple and advanced IO simulators that would suit a training plan catered to teach the IO access and infusion procedure decentrally to paramedics-in-training. Specifically, they have been designed in a manner that allows them to be made easily accessible to the trainees i.e., low costs and high mobility, and work cohesively with online learning management systems which further facilitates the use of a De-SBE model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".