The efficacy of alcohol-based hand sanitizers used in a series, modifying the ASTM E2755 method with a shorter hand sanitizer application time
Why this work is in the frame
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Bibliographic record
Abstract

 Background: Alcohol-based hand sanitizers are becoming increasingly common in healthcare settings in an effort to control communicable bacteria, viruses and fungi of health significance. Much research has been done on the effectiveness of alcohol-based hand sanitizers but few studies look at the effectiveness when combined with more typical usage, such as varying application times and amounts. Methods: We looked at the efficacy of the microbial killing power of an alcohol-based hand sanitizer when used in a series of 5 applications. ASTM E2755 was used with the modification of a shorter application time (8 seconds from the recommended 30 seconds) of the sanitizer to better reflect actual healthcare worker usage. Results: We found an increase in the amount of indicator bacteria on the gloved hands of the subjects after repeated applications. However the increase was not significant enough in that a 2-log reduction of indicator bacteria was still achieved. Using a One Sample T-Test we found a very low probability value (<0.00000), indicating that the results were statistically significant. Conclusions: There is an increase of bacteria on gloved hands after repeated use of alcohol-based hand sanitizers. The results show a decrease in their effectiveness, most likely due to a build up of various non-alcohol components in hand sanitizers. However even with the 8 second application time there was still a greater than two log reduction even after 5 serial contaminations and applications. This cautiously shows that there is significantly less danger posed by more common shorter application times than originally thought. These findings have a potential impact on hand hygiene education as other factors, such as frequency or sanitizer amounts can be safely emphasized over application times.
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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 | 0.004 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it