Creating a gold medal Olympic and Paralympics health care team: a satisfaction survey of the mobile medical unit/polyclinic team training for the Vancouver 2010 winter games
Bibliographic record
Abstract
BACKGROUND: The mobile medical unit/polyclinic (MMU/PC) was an essential part of the medical services to support ill or injured Olympic or Paralympics family during the 2010 Olympic and Paralympics winter games. The objective of this study was to survey the satisfaction of the clinical staff that completed the training programs prior to deployment to the MMU. METHODS: Medical personnel who participated in at least one of the four training programs, including (1) week-end sessions; (2) web-based modules; (3) just-in-time training; and (4) daily simulation exercises were invited to participate in a web-based survey and comment on their level of satisfaction with training program. RESULTS: A total of 64 (out of 94 who were invited) physicians, nurses and respiratory therapists completed the survey. All participants reported favorably that the MMU/PC training positively impacted their knowledge, skills and team functions while deployed at the MMU/PC during the 2010 Olympic Games. However, components of the training program were valued differently depending on clinical job title, years of experience, and prior experience in large scale events. Respondents with little or no experience working in large scale events (45%) rated daily simulations as the most valuable component of the training program for strengthening competencies and knowledge in clinical skills for working in large scale events. CONCLUSION: The multi-phase MMU/PC training was found to be beneficial for preparing the medical team for the 2010 Winter Games. In particular this survey demonstrates the effectiveness of simulation training programs on teamwork competencies in ad hoc groups.
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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 | 0.004 | 0.014 |
| 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 | 0.001 |
| 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".