Identification badges: a potential fomite?
Bibliographic record
Abstract
BACKGROUND: Staff identification badges are mandatory in all hospitals. The purpose of this study was to assess microbial contamination of identification badges at a Canadian tertiary centre. Risk factors for badge contamination were also investigated. METHODS: Badges were cultured from 118 subjects including secretaries, physicians, nurses, and allied health workers. Subjects also completed a demographic questionnaire. Badge contamination was analyzed according to profession, workplace, duration of badge use, presence of a plastic cover, how the badge was worn, and cleaning frequency. RESULTS: 13.6% of the badges were contaminated with significant pathogens. S. aureus was isolated in 6.8% of the badges, gram-negative bacilli in 5.9%. Contamination was highest in nurses (21.4% versus 9.4-14.3% in other professions) and in the ICU (22.6% versus 8.3%-14.3% at other locations). Neither association was statistically significant. Covered and non-covered badges had similar contamination rates (12% and 17.1%) as did badges worn around the neck compared with those worn clipped to clothing (13.0% versus 14.6%). Contamination of recently cleaned badges was not statistically different from those that had not. CONCLUSION: Identification badges do not appear to be a major reservoir for pathogenic organisms. Badges can, however, harbour disease-causing organisms and should be cleaned regularly.
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.
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".