Camptodactyly-Arthropathy-Coxa Vara-Pericarditis Syndrome: The First Familial Case in China and Novel Mutations of the Proteoglycan 4 Gene
Bibliographic record
Abstract
Introduction Although registered nurses (RNs) are central in patient care, we have not found prior research that specifically addresses how RNs assess the safety of patient care at their workplace and how factors in RNs’ work environment are related to their assessments. This study aims to address these issues. Methods 9236 RNs working with inpatient care in 79 acute-care hospitals in Sweden completed a national population-based survey, including Practice Environment Scale of the Nursing Work Index—Revised and items from Agency for Healthcare Research and Quality9s Hospital Survey on Patient Safety Culture. Correlation coefficients (Pearson and Spearman) and proportional odds regression were used for analysis. Results Nursing work environment factors were strongly related to RNs’ assessments of patient safety. RNs’ perception of having adequate staffing and resources improved their assessment of patient safety by at least two and a half times (OR 2.74 CI 2.52 to 2.97). RNs with a higher level of involvement in direct patient care gave a better patient safety grade than RNs with a more supervisory role. Most, but not all, patient safety culture items were related to RNs’ assessed patient safety grade. We found that work experience seemed to have no influence on RNs’ patient safety assessment. Conclusions While previous research emphasises patient-to-nurse ratios in strengthening patient safety practices, this study complements this by emphasising RNs’ own perception of having enough staff and resources to provide quality nursing care, as well as having good collegial nurse–physician relations and the presence of visible and competent nursing leadership—all factors highly related to RNs’ assessment of the safety of patient care at their workplace.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".