An international survey of bacterial contamination and householders’ knowledge, attitudes and perceptions of hygiene
Bibliographic record
Abstract
This prospective, multinational study was conducted in 20 homes in eight cities or regions in different countries to determine the level of microbiological contamination of common surfaces and items, and investigate the attitudes and perceptions of householders towards cleaning and hygiene. Environmental Health Practitioners took eight standardised swabs in each home. The swabs were cultured for a range of micro-organisms. Householders ( n=160) were also interviewed regarding their cleaning habits and perceptions of hygiene. Overall, 28% of surfaces or items tested in the study had ‘moderate bacterial growth’ or ‘heavy bacterial growth’. Kitchen cloths were the most contaminated items, with 86% having moderate bacterial growth or heavy bacterial growth; kitchen taps were the second most contaminated items, with 52% having moderate bacterial growth or heavy bacterial growth. High proportions (>50%) of kitchen cloths contained coliforms, Enterobacteriaceae and Pseudomonas spp. The visual appearance of surfaces and items frequently (30%) did not correspond to their level of contamination with micro-organisms. The majority of householders (65%) cleaned to make the house ‘look clean, smell nice and remove germs’; however, householders’ perceptions of the cleanliness of their homes frequently did not correspond to microbiological reality. In conclusion, further research and education are needed regarding hygiene in the home.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".