Behavioral integrity for safety, priority of safety, psychological safety, and patient safety: A team-level study.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article clarifies how leader behavioral integrity for safety helps solve follower's double bind between adhering to safety protocols and speaking up about mistakes against protocols. Path modeling of survey data in 54 nursing teams showed that head nurse behavioral integrity for safety positively relates to both team priority of safety and psychological safety. In turn, team priority of safety and team psychological safety were, respectively, negatively and positively related with the number of treatment errors that were reported to head nurses. We further demonstrated an interaction effect between team priority of safety and psychological safety on reported errors such that the relationship between team priority of safety and the number of errors was stronger for higher levels of team psychological safety. Finally, we showed that both team priority of safety and team psychological safety mediated the relationship between leader behavioral integrity for safety and reported treatment errors. These results suggest that although adhering to safety protocols and admitting mistakes against those protocols show opposite relations to reported treatment errors, both are important to improving patient safety and both are fostered by leaders who walk their safety talk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 it