Procedures Can Be Learned on the Web: A Randomized Study of Ultrasound‐guided Vascular Access Training
Bibliographic record
Abstract
OBJECTIVES: Web-based learning has several potential advantages over lectures, such as anytime-anywhere access, rich multimedia, and nonlinear navigation. While known to be an effective method for learning facts, few studies have examined the effectiveness of Web-based formats for learning procedural skills. The authors sought to determine whether a Web-based tutorial is at least as effective as a didactic lecture for learning ultrasound-guided vascular access (UGVA). METHODS: Participating staff emergency physicians (EPs) and junior emergency medicine (EM) residents with no UGVA experience completed a precourse test and were randomized to either a Web-based or a didactic group. The Web-based group was instructed to use an online tutorial and the didactic group attended a lecture. Participants then practiced on simulators and live models without any further instruction. Following a rest period, participants completed a four-station objective structured clinical examination (OSCE), a written examination, and a postcourse questionnaire. Examination results were compared using a noninferiority data analysis with a 10% margin of difference. RESULTS: Twenty-one residents and EPs participated in the study. There were no significant differences in mean OSCE scores (absolute difference = -2.8%; 95% confidence interval [CI] = -9.3% to 3.8%) or written test scores (absolute difference = -1.4%; 95% CI = -7.8% to 5.0%) between the Web group and the didactic group. Both groups demonstrated similar improvements in written test scores (26.1% vs. 25.8%; p = 0.95). Ninety-one percent (10/11) of the Web group and 80% (8/10) of the didactic group participants found the teaching format to be effective (p = 0.59). CONCLUSIONS: Our Web-based tutorial was at least as effective as a traditional didactic lecture for teaching the knowledge and skills essential for UGVA. Participants expressed high satisfaction with this teaching technology. Web-based teaching may be a useful alternative to didactic teaching for learning procedural skills.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".