Impact of health reform on registered psychiatric nursing practice
Bibliographic record
Abstract
This paper addresses the impact of health reform on registered psychiatric nursing practice. Over a nine-month period, seven focus groups were conducted with registered psychiatric nurses (RPNs; n = 33) from a variety of practice settings in south central regions of the province of Manitoba located in western Canada. Analysis of data collected from the focus groups are summarized according to the four probing questions utilized in this study, and are discussed in relation to: past registered psychiatric nursing, influential factors, future for registered psychiatric nursing, and proactive strategies. It is acknowledged that while reform has created an increase in the degree and level of independence for RPNs, findings suggest that some RPNs are concerned about insufficient preparation for these new and expanded roles, and all study participants are concerned about the current and future shortage of RPNs. Recommendations include commitment of sufficient funding and employer support for advanced education of RPNs as well as provision of additional funding for increases in the number of available seats for psychiatric nursing education, additional RPN faculty resources and a graduate education programme specifically designed for RPNs.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".