Use of, Effectiveness of, and Attitudes Regarding Influenza Vaccine Among House Staff
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
OBJECTIVE: To determine influenza vaccination rates, vaccine effectiveness, and factors influencing vaccination decisions among house staff. DESIGN: Cross-sectional survey. SETTING AND PARTICIPANTS: All residents registered at the University of Toronto were surveyed after the 1999-2000 influenza season. Of the 1,159 questionnaires mailed, 670 (58%) could be evaluated. RESULTS: Influenza-like illnesses were reported by 36% of house staff. The vaccination rate was 51% among respondents, being highest for community and occupational medicine and pediatric staff (77% and 75%) and lowest for psychiatry, surgery, and radiology staff (32%, 36%, and 36%). Vaccinees reported significantly fewer episodes of illness (42 vs 54 per 100 subjects; P = .03) and fewer days of illness (272 vs 374 per 100 subjects; P = .02); absenteeism was not different (63 vs 69 per 100 subjects; P = .69). Self-protection was the most common reason for vaccination. Vaccinees believed the vaccine was more effective than did non-vaccinees (P < .01). Non-vaccinees considered influenza-like symptoms the most important side effect of the vaccine. Busy schedules and inconvenience were the most common reasons for not getting vaccinated. Overall, 44% of house staff believed the influenza vaccine should be mandatory. CONCLUSIONS: Influenza-like illness was common among house staff. They tended to work through their illnesses, potentially putting patients at risk. They were motivated mostly by self-protection and did report a benefit. Despite busy schedules and an unfounded fear of getting influenza symptoms from the vaccine, many thought the vaccine should be mandatory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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