The experience and views of mental health nurses regarding nursing care delivery in an integrated, inpatient setting
Bibliographic record
Abstract
Positive and effective consumer outcomes hinge on having in place optimal models of nursing care delivery. The aim of this study was to ascertain the experience and views of mental health nurses, working in hospitals in an area mental health service, regarding nursing care delivery in those settings. Surveys (n = 250) were sent to all mental health nurses working in inpatient settings and 118 (47%) were returned. Results showed that the quality of nursing care achieved high ratings (by 87%), and that two-thirds of respondents were proud to be a mental health nurse and would choose to be a mental health nurse again. Similarly, the majority (71%) would recommend mental health nursing to others. Concern was, however, expressed about the continuity and consistency of nursing work and information technology resources. Nurses with community experiences rated the importance of the following items, or their confidence, higher than those without previous community placements: the importance of interdisciplinary teamwork; the importance of participating in case review; the importance of collaborating with community staff; confidence in performing mental state examinations; and confidence in collaborating with community staff, suggesting that this placement had positive effects on acute care nursing.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".