Train-the-Trainers in hand hygiene: a standardized approach to guide education in infection prevention and control
Bibliographic record
Abstract
BACKGROUND: Harmonization in hand hygiene training for infection prevention and control (IPC) professionals is lacking. We describe a standardized approach to training, using a "Train-the-Trainers" (TTT) concept for IPC professionals and assess its impact on hand hygiene knowledge in six countries. METHODS: We developed a three-day simulation-based TTT course based on the World Health Organization (WHO) Multimodal Hand Hygiene Improvement Strategy. To evaluate its impact, we have performed a pre-and post-course knowledge questionnaire. The Wilcoxon signed-rank test was used to compare the results before and after training. RESULTS: Between June 2016 and January 2018 we conducted seven TTT courses in six countries: Iran, Malaysia, Mexico, South Africa, Spain and Thailand. A total of 305 IPC professionals completed the programme. Participants included nurses (n = 196; 64.2%), physicians (n = 53; 17.3%) and other health professionals (n = 56; 18.3%). In total, participants from more than 20 countries were trained. A significant (p < 0.05) improvement in knowledge between the pre- and post-TTT training phases was observed in all countries. Puebla (Mexico) had the highest improvement (22.3%; p < 0.001), followed by Malaysia (21.2%; p < 0.001), Jalisco (Mexico; 20.2%; p < 0.001), Thailand (18.8%; p < 0.001), South Africa (18.3%; p < 0.001), Iran (17.5%; p < 0.001) and Spain (9.7%; p = 0.047). Spain had the highest overall test scores, while Thailand had the lowest pre- and post-scores. Positive aspects reported included: unique learning environment, sharing experiences, hands-on practices on a secure environment and networking among IPC professionals. Sustainability was assessed through follow-up evaluations conducted in three original TTT course sites in Mexico (Jalisco and Puebla) and in Spain: improvement was sustained in the last follow-up phase when assessed 5 months, 1 year and 2 years after the first TTT course, respectively. CONCLUSIONS: The TTT in hand hygiene model proved to be effective in enhancing participant's knowledge, sharing experiences and networking. IPC professionals can use this reference training method worldwide to further disseminate knowledge to other health care workers.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".