Influenza Vaccination and Decisional Conflict among Regulated and Unregulated Direct Nursing Care Providers in Long-Term–Care Homes
Bibliographic record
Abstract
The purpose of this study was to determine whether direct nursing care providers have decisional conflict about receiving influenza vaccinations and characteristics associated with decisional conflict. The researchers used a self-administered questionnaire mailed to direct nursing care providers in two long-term-care organizations. Most direct nursing care providers in both organizations (80% and 93%, respectively) intended to get the influenza vaccine. Unregulated direct nursing care providers had more decisional conflict than regulated providers, especially related to feeling uninformed about the pros and cons of influenza vaccination. Unclear valuing of the pros and cons of influenza vaccination was related to the age of the direct care providers in both organizations. Decisional conflict and influenza vaccination practices may be determined, in part, by age and by the culture of a health care organization. A decision aid to improve knowledge and clarify values may improve decision quality and increase influenza vaccination rates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".