Survey on Use of and Attitudes Toward Influenza Vaccination Among Emergency Department Staff in a New York Metropolitan Hospital
Bibliographic record
Abstract
OBJECTIVE: Recognizing that the potential transmission of influenza virus would be concentrated at a hospital's primary point of entry, we determined rates of staff compliance with the influenza vaccination recommendations of the Advisory Committee on Immunization Practices (ACIP) in the Emergency Department (ED). We describe the basic knowledge concerning influenza transmission and factors influencing vaccination decisions among ED staff. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: A large urban teaching hospital. Participants included ED staff, visiting professionals from other departments, and emergency medical service personnel transferring patients to the hospital. RESULTS: Of 230 surveys that were distributed, 200 were completed. One hundred one respondents (51%) were female. The overall influenza vaccination rate was 50%. Having had influenza previously was the most instrumental factor in whether or not a respondent chose vaccination (P<.001). Use of the Employees Health Services Free Vaccine Program (FVP) was a very important factor influencing whether ED staff sought influenza vaccination (P<.0001). Prior knowledge of the ACIP recommendations proved to be not statistically important (P=.03). A significant factor for respondents declining vaccination was the concern that illness could be caused by the vaccine (P<.0001). Variables such as sex of the respondents (P=.6714) and type of job (P=.3628) were not associated with vaccination. CONCLUSION: Despite ACIP recommendations, 50% of respondents did not receive an influenza vaccination. Misconceptions regarding influenza vaccine efficacy, concerns about adverse effects, and fear of contracting illness were significantly associated with noncompliance with vaccination. Variables that were important contributors to compliance with vaccination were prior influenza illness and services rendered by the FVP.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 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".