Immersive hand hygiene trainer for physicians – a story-based serious game
Bibliographic record
Abstract
We inserted filmed sequences based on a plot of two physicians interacting with different patients during ward rounds into an interactive computer interface allowing the physician 'gamer' to decide where to use hand hygiene and disposable gloves. Hand hygiene being a very repetitive and often subconsciously executed task, virtual immersion might increase learning and improve long-term retention. Thus, we used both an emotionally engaging but also distracting plot to create role identity and simulate mental load typical for medical activity on the ward. Design features were refined through individual think-aloud protocols and target group testing. Immediate feedback messages and a result tracking mechanism were added. The design specifications could all be met. The resulting application proofed equally suitable for the training of hand hygiene observers. Computing the user’s results allows for benchmarking. A serious game was successfully launched immersing the ‘gamer’ into the real-life challenge of hand hygiene. Post-launch evaluation and clinical effectiveness have to be performed in a next step.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".