Bibliographic record
Abstract
This thesis presents a research study, conducted for my PhD. This research used mixed qualitative and quantitative methods to address four central questions: How do interdisciplinary team members perceive error and error reporting? How do patients perceive error and error reporting? What are the areas of congruence and conflict between different healthcare professionals' approaches to error and patients' needs and perspectives? Why are certain events not described as errors and not addressed in a systematic fashion that would improve patient safety? This study was conducted in the grounded theory tradition and included two phases. The first phase investigated the perceptions of OR team members and patients regarding error definition and error reporting; the second phase sought to elaborate two of the dominant themes from the first phase. The first three chapters of this thesis provide background information about the context, theoretical foundation, and design of the research. The following three chapters present the results of the study in the form of three self-contained articles that have been published or submitted to academic journals. The first of these articles describes and compares surgical team members' and patients' perceptions of error, its reporting, and its disclosure from the first phase of the study. It is published in the journal Surgery. The second article explores operating room (OR) nurses' error reporting preferences from the second phase of the study. This article has been submitted to an applied nursing research journal. The third article sought to probe the factors influencing whether team members saw error events in everyday work as problematic or whether they rationalized such occurrences to support the status quo. The analysis draws on three concepts from organizational and psychological theory to explore team members' responses to these error scenarios. This article has been submitted to the journal Quality and Safety in Healthcare. The final chapter draws the three papers together into an extended discussion about the significance and future implications of this work.
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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 | 0.027 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".