Using the perception evaluation of safety climate for the development of leaders
Bibliographic record
Abstract
The object of this research is to verify the perception by nursing professionals on Safety Climate in brazilian private institutions which initiated the preparatory program for the Qmentum International Certification, and use this result to structure strategy of development of leaders in their institutions. The analysis of the perception of Safety Climate was made based on the modified version of the Patient Safety Climate in Health Care Organizations and Canadian Patient Safety Climate Survey. This form is composed of thirty-eight items distributed in ten dimensions, whose answers are evaluated with the Likert scale. The answers were categorized into: Positive for Agree, Attention for Partially Agree, Negative for Do not agree and Not Applicable. The dimensions with negative results above 20% were considered unfavorable safety climate perception and positive results and attention above 80%, favorable. The research questionnaire was answered by 1060 nursing professionals. The negative perceptions identified were related to Security Resources; Team Recognition; Team Leadership; Psychological Security; and Communication. The analysis showed that the favorable results are related to High Leadership; Learning and Work Norms and the recognition that patient safety is a strategic priority. Given this finding, GNDI High Leadership structured the Leadership Development Program, one of whose objectives is to develop nursing professionals in positions of supervision and management in non-technical competences such as empathy, dialogue, respect, recognition, quality and security and communication, negotiation and conflict management. This program started in April and is due to finish in November 2019.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".