Persistence of unsafe practice in everyday work: an exploration of organizational and psychological factors constraining safety in the operating room
Bibliographic record
Abstract
This paper explores the factors that influence the persistence of unsafe practice in an interprofessional team setting in health care, towards the development of a descriptive theoretical model for analyzing problematic practice routines. Using data collected during a mixed method interview study of 28 members of an operating room team, participants' approaches to unsafe practice were analyzed using the following three theoretical models from organizational and cognitive psychology: Reason's theory of "vulnerable system syndrome", Tucker and Edmondson's concept of first and second order problem solving, and Amalberti's model of practice migration. These three theoretical approaches provide a critical insight into key trends in the interview data, including team members' definition of error as the breaching of standards of practice, nurses' sense of scope of practice as a constraint on their reporting behaviours, and participants' reports of the forces influencing tacit agreements to work around safety regulations. However, the relational factors underlying unsafe practice routines are poorly accounted for in these theoretical approaches. Incorporating an additional theoretical construct such as "relational coordination" to account for the emotional human features of team practice would provide a more comprehensive theoretical approach for use in exploring unsafe practice routines and the forces that sustain them in healthcare team settings.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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 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".