Predicting Seasonal Influenza Vaccination Among Hospital-Based Nurses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A descriptive cross-sectional online survey of a convenience sample of 202 hospital-based nurses was conducted to explore the factors associated with influenza vaccination. The findings suggest that the independent predictors of influenza vaccination were perception of job as a risk increasing factor (OR = 12.14; 95% CI [1.89, 78.08]), workplace vaccination clinics and campaigns (OR = 2.88; 95% CI [1.12, 7.38]), vaccination in the previous season (OR = 34.80; 95% CI [12.99, 93.28]), viewing vaccination as an inconvenience (OR = 0.22; 95% CI [0.07, 0.67]), and one's belief that the immune system provides better protection than the vaccine (OR = 0.29; 95% CI [0.11, 0.77]). In conclusion, the findings support the existing literature with regards to low vaccination rates among health care providers. Furthermore, the identification of the predictors of influenza vaccination among nurses may assist administrators and policy makers with the implementation of evidence-based vaccination strategies.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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