Attitudes and perceptions of registered nurses during and shortly after acute care restructuring in Newfoundland and Labrador
Bibliographic record
Abstract
OBJECTIVES: To monitor changes in registered nurses' perceptions of the impact of seven years of health care restructuring in Newfoundland and Labrador (NL) and to measure the attitudinal and behavioural reactions over four years comparing the St John's region, where hospital aggregation occurred, to other regions of the province. METHODS: Data were collected on acute care nurses' personal characteristics and perceptions of the importance of reform and its impact on workplace conditions and health care quality in 1995, 1999, 2000 and 2002. Nurses' attitudes and intentions were monitored across three time periods (i.e. 1999, 2000 and 2002). RESULTS: Perceived workplace conditions and health care quality, as well as attitudes and behaviours were generally negative. However, there was some improvement over time. The temporal sequence of scores suggests that restructuring had an adverse impact on nurses' attitudes. Few significant regional differences were observed. CONCLUSIONS: Although health services restructuring had an adverse impact on nurses' attitudes, aggregation of hospitals in St John's region was achieved without further deterioration. Provincial wide initiatives are needed to promote more positive work environments and increase the organizational effectiveness.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".