Promoting a Hand Hygiene Program Using Social Media: An Observational Study
Bibliographic record
Abstract
BACKGROUND: Hand hygiene is an important component in infection control to protect patient safety and reduce health care-associated infection. OBJECTIVE: Our aim was to evaluate the efficacy of different social media on the promotion of a hand hygiene (HH) program. METHODS: The observational study was conducted from May 5 to December 31, 2014, at a 2600-bed tertiary care hospital. A 3-minute video of an HH campaign in 8 languages was posted to YouTube. The Chinese version was promoted through three platforms: the hospital website, the hospital group email, and the Facebook site of a well-known Internet illustrator. The video traffic was analyzed via Google Analytics. HH compliance was measured in November 2013 and 2014. RESULTS: There were 5252 views of the video, mainly of the Chinese-language version (3509/5252, 66.81%). The NTUH website had 24,000 subscribers, and 151 of them viewed the video (connection rate was 151/24,000, 0.63%). There were 9967 users of the hospital email group and the connection rate was 0.91% (91/9967). The connection rate was 6.17% (807/13,080) from Facebook, significantly higher than the other 2 venues (both P<.001). HH compliance sustained from 83.7% (473/565) in 2013 to 86.7% (589/679) in 2014 (P=.13) among all HCWs. CONCLUSIONS: Facebook had the highest connection rate in the HH video campaign. The use of novel social media such as Facebook should be considered for future programs that promote hand hygiene and other healthy behaviors.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| 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".