First‐person perspective video to enhance simulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Simulation training is increasingly being used as part of the undergraduate medical curriculum, but it remains time and faculty member intensive. To improve efficacy, videos have been used prior to the simulation of practical procedures; however, using videos prior to simulation training concerning the management of patients who are unwell has not been investigated. The aim of this project was to see whether clinical decision-making and non-technical skills can be improved if a video is used prior to simulation training, and uniquely to enhance the authenticity we filmed it using a first-person perspective. METHODOLOGY: We conducted a randomised controlled trial with 40 final-year medical students randomised into two groups. One group viewed a video filmed in first person prior to a simulation scenario, whereas the other group did not view the video. The two groups then carried out the simulation and were assessed with 'time to' investigation and treatment decisions. Further quantitative data were collected for non-technical skills using the Ottawa Crisis Resource Management (OCRM) score. Qualitative data were collected from the students as to the perceived ease of use and helpfulness of the video. Simulation training is increasingly being used as part of the undergraduate medical curriculum RESULTS: The students who watched the video appeared to perform better in clinical decision-making and non-technical skills. The students were extremely receptive to the use of a first-person perspective video, and highlighted its perceived realism and its help as a memory aid. DISCUSSION: The use of this style of video was warmly received by students and opens the possibility of further use to enhance simulation training.
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.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 it