Young People’s Knowledge of Antibiotics and Vaccinations and Increasing This Knowledge Through Gaming: Mixed-Methods Study Using e-Bug
Bibliographic record
Abstract
BACKGROUND: e-Bug, led by Public Health England, educates young people about important topics: microbes, infection prevention, and antibiotics. Body Busters and Stop the Spread are 2 new e-Bug educational games. OBJECTIVE: This study aimed to determine students' baseline knowledge, views on the games, and knowledge improvement. METHODS: Students in 5 UK educational provisions were observed playing 2 e-Bug games. Before and after knowledge and evaluation questionnaires were completed, and student focus groups were conducted. RESULTS: A total of 123 junior and 350 senior students completed the questionnaires. Vaccination baseline knowledge was high. Knowledge increased significantly about antibiotic use, appropriate sneezing behaviors, and vaccinations. In total, 26 student focus groups were conducted. Body Busters was engaging and enjoyable, whereas Stop the Spread was fast-paced and challenging but increased vaccination and health behavior intentions. CONCLUSIONS: e-Bug games are an effective learning tool for students to enhance knowledge about microbes, infection prevention, and antibiotics. Game-suggested improvements should help increase enjoyment.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".