An Introduction to the Management of Labour and Delivery - A Simulation-Based Obstetrics Workshop for Medical Students
Bibliographic record
Abstract
Abstract The following is a description of a simulation-based workshop for undergraduate medical students during their first week of clerkship in Obstetrics. This workshop was developed to complement the didactic lectures that medical students receive as part of their clerkship and addresses the basics of intrapartum management so that students can feel more like part of the team during their first days in the case room. There are several reasons why medical students may have limited exposure to aspects of obstetrics during their clerkship. The short duration of the rotation, the reduced availability of patients willing to have medical students observe and perform obstetrical techniques, and the potential for unpredictable, serious complications to occur in seconds are all conditions that conspire to create reduced learning opportunities for clerks. Unfortunately, it is the very same practical opportunities that medical students are excluded from that serve to increase their understanding and interest in the speciality. Given the successful implementation simulation education in residency programs, its use in undergraduate medical education may serve as a practical solution to the marginalization of medical students during their obstetrics rotation. The current curriculum was designed for a simulation-based workshop during the first week of the obstetrics clerkship to instruct students in the diagnosis of labour and gain an appreciation for the decisions that are made as part of intra-partum management. Prior to the development of this curriculum, formal teaching for clerkship students in obstetrics and gynaecology at our institution consisted solely of didactic lectures. The objective of this simulation-based innovation was to alleviate the students' anxiety at the beginning of their rotation through providing opportunities to practice clinical skills necessary for success during clerkship. Furthermore, it was thought that engaging the students early on in their clinical training could help to foster an interest in pursuing postgraduate training in obstetrics and gynecology. This workshop was developed in accordance with the educational objectives described in the US-based Association of Professors of Gynecology and Obstetrics (APGO). This simulation follows a single obstetrical patient whose clinical course is followed by the students from presentation to the obstetrical assessment unit until spontaneous vaginal delivery and immediate postpartum care. Through use of a high-fidelity mannequin, this simulation provides students the opportunity to examine the patient throughout the course of her labour to assess dilation and ultimately perform a vaginal delivery. The workshop also incorporates elements of interactive teaching and round table discussion that encourages student participation. You will find a full curriculum document which can be used as an instructors manual, as well as a pre- and post-test which can be used to assess learning during the workshop, and a hand-out for students summarizing the objectives of the session. This workshop has been in use at our institution since the 2008–2009 and has been incredibly well-received by students, as evidenced by anonymous written evaluations. Their confidence and knowledge-base during their first days on service in labour & delivery are noticeably improved, and we documented successful learning on a pre- and post-test comparison, as published in “Medical Education” in 2010.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.040 | 0.014 |
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".