Public health nurses’ experiences during the H1N1/09 response
Bibliographic record
Abstract
OBJECTIVE: H1N1/09 was the first pandemic flu ever responded to with mass vaccinations. Public health nurses (PHNs) were pivotal in implementing the H1N1/09 vaccination clinics. With the ongoing threat of pandemic influenza and other viral outbreaks, much can be learned from these PHNs' H1N1/09 experiences. This study's purpose was to explore PHNs' experiences in the H1N1/09 mass vaccination clinics. DESIGN AND SAMPLE: In a qualitative interpretive description, 23 PHNs (16 immunizers, seven supervisors) who worked in a large Canadian municipal public health agency, participated in semistructured interviews. RESULTS: Three overarching themes were identified. 'Anticipating an Emergency' discusses participants' experiences learning about the pandemic response and their role preparation. 'Surviving the Chaos' reflects the challenges of the clinics, particularly during the first few hectic weeks of the response. 'Persevering Over Time' encompasses participants' experiences as they became familiar with clinics' operations and their own responsibilities. CONCLUSIONS: Participants' experiences have implications for future public health pandemic planning and research. Key recommendations include to communicate with PHNs in a timely manner about their clinic roles, and to provide PHNs with appropriate training to optimize clinics' operations. This will help support PHNs in their roles to protect the public and provide quality population care.
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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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".