Does Pre‐Clerkship physician assistant POCUS training improve Knowledge and confidence in Clerkship?
Bibliographic record
Abstract
Introduction With the technological progress of different types of portable Ultrasound machines, there is a growing demand for all health care providers to perform bedside Ultrasonography, also known as Point of Care Ultrasound (POCUS). This technique is becoming extremely useful as part of the Clinical Skills/Anatomy teaching in the undergraduate Medical field curriculum. Teaching/training health care providers how to use these portable Ultrasound machines can complement their physical examination findings and help in a more accurate diagnosis, which leads to a faster diagnosis and better patient outcomes. In addition, using portable Ultrasound machines can add more safety measurements to every therapeutic/diagnostic procedure when it is done under an Ultrasound guide. Ultrasound is one of the different imaging modalities that health care providers depend on to reach their diagnosis, while also being the least invasive method Aim To assess the effect of pre‐clerkship POCUS training on their knowledge and confidence of POCUS training during their clerkship Method The research we report in this manuscript is a preliminary qualitative study. It provides the template for future models for teaching hands on Ultrasound for all health care providers in different learning institutions. The McMaster Physician Assistant program is a two‐year course; we introduce POCUS training to the first and second year Physician Assistant curriculum. We have a total of 24 Physician Assistant students at each level of the program; at each level we divide them into three equal groups, supervised by a tutor. Each group uses one portable General Electric Ultrasound machine, which is projected onto a large plasma screen. We dim the room lights to get better quality screen images. Our session lasts for 90 minutes, the first 20 minutes being an introduction to how to use the machine and probe orientation, as well as some anatomy landmarks. Every student will have the chance to scan their peers at least one time during our session. Our objective is a pure “hands on” scanning of the neck and the abdomen performed by the students. With the correlations to their anatomy background knowledge, they were able to identify normal Thyroid Glands and major neck vessels, Liver, abdominal Aorta, inferior vena cava, Gall Bladder, and the Kidneys. Result A questionnaire was handed to the second year (clerkship) Physician Assistant students to evaluate their hands on ultrasound session experience. And the effect of their previous POCUS training at pre‐clerkship level in enhancing more confidence on their most recent training. Answers were collected and data was analyzed into multiple graphs (as illustrated in this poster). Discussion and Conclusion These results illustrate the importance of the prior POCUS training for Physician Assistant students at their pre‐clerkship level, to build up more confidence in their scanning ability, improve the orientation of their ultrasound images, and to better understand the relation of the probe’s position to the corresponding images during their clerkship POCUS training. Support or Funding Information Education program anatomy, McMaster University
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".