Nursing workload and patient safety - a mixed method study with an ecological restorative approach
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to analyze the potential association between nursing workload and patient safety in the medical and surgical inpatient units of a teaching hospital. METHOD: a mixed method strategy (sequential explanatory design). RESULTS: the initial quantitative stage of the study suggest that increases in the number of patients assigned to each nursing team lead to increased rates of bed-related falls, central line-associated bloodstream infections, nursing staff turnover, and absenteeism. During the subsequent qualitative stage of the research, the nursing team stressed medication administration, bed baths, and patient transport as the aspects of care that have the greatest impact on workload and pose the greatest hazards to patient, provider, and environment safety. CONCLUSIONS: The findings demonstrated significant associations between nursing workload and patient safety. We observed that nursing staff with fewer patients presented best results of care-related and management-related patient safety indicators. In addition, the tenets of ecological and restorative thinking contributed to the understanding of some of the aspects in this intricate relationship from the standpoint of nursing providers. They also promoted a participatory approach in this study.
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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 | 0.019 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".