Public health nurse perceptions of evolving work and how work is managed: A qualitative study
Bibliographic record
Abstract
AIM: To explore public health nurse (PHN) perspectives of their evolving work and how public health nurse work is managed in a Canadian health region. BACKGROUND: Professional and public health organisations describe public health nurse practice roles as population-focused work. Health care management directs public health nurse work to achieve specific goals. METHODS: In this qualitative study, data were collected during focus groups with 42 public health nurse participants in one health region. Focus group data were analysed for meanings and themes. RESULTS: Public health nurses perceived increasing immunizations and limited resources for public health nurse work meant that population-focused care for the public was rationed or missing. Participants perceived the health care organisation directed, managed and assigned public health nurse specialist work; however, public health nurses managed their client-focused practice with knowledge, reasoning and support from colleagues. CONCLUSIONS: Evolving visible public health nurse work was managed by health organisational management directives to increase immunizations and disease control. Public health nurses managed their evolving visible and invisible work supported by their knowledge, practice values and public health nurse colleagues. IMPLICATIONS FOR NURSING MANAGEMENT: Nursing management must lead and communicate the vision supporting better health, better population-focused care and health outcomes to public health nurse and stakeholders, while reviewing resources needed to optimize public health nursing and improve population health.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".