Long-Term Care Nurses' Experiences With Patient Safety Incident Management
Bibliographic record
Abstract
BACKGROUND: Global trends in the aging population will increase the demands for long-term care (LTC) resources. Due to recent pressures to deliver more complex care, there is further risk to resident safety in LTC. Emphasis on the management and the delivery in safe and quality resident care in LTC is required. PURPOSE: The purpose of this study was to describe nurses' experiences with patient safety incident (PSI) management involving residents living in LTC. METHODS: Using a qualitative descriptive approach, 9 nurses were recruited in 3 LTC homes. Semistructured interviews were conducted, and data were analyzed using inductive content analysis. RESULTS: Three main categories emerged: commitment to resident safety, workplace culture, and emotional reaction. CONCLUSIONS: Providing nurses with an opportunity to share their PSI management experiences highlights the current factors influencing frontline resident safety in LTC. Study results can inform nursing practice and policy development to support PSI identification and management.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".