Exploring stakeholder perceptions around implementation of the Operating Room Black Box for patient safety research: a qualitative study using the theoretical domains framework
Bibliographic record
Abstract
BACKGROUND: Systematically observing clinical performance in the operating room (OR) to support patient safety initiatives faces numerous logistical and methodological challenges. These may be solved by new audio-video recording technologies like the OR Black Box, which is a tool similar to black boxes in aviation. This study aimed to identify barriers and enablers that may influence patients', clinicians' and senior leadership team members' support of the OR Black Box in order to guide its future implementation. METHODS: Patients, clinicians and senior leadership team members were recruited to participate in semistructured interviews informed by the theoretical domains framework (TDF) to identify factors relevant to planning OR Black Box implementation. Deidentified interview transcripts were analysed in duplicate following a TDF coding structure. RESULTS: Data saturation was achieved at 15 patients, 17 clinicians and 9 senior leadership team members. Seven domains were relevant for patients, nine for clinicians and four for senior leadership. Knowledge and Beliefs about consequences were barriers and enablers for all three groups. Memory, attention and decision processes and Social influences were enablers for both clinicians and senior leadership. Environmental context and resources, Emotion and Behavioural regulation were found to be barriers and enablers for both clinicians and patients. Social/professional role and identity and Reinforcement were enablers for patients only and Optimism and Intentions were barriers and enablers to clinicians. CONCLUSIONS: While most stakeholders were supportive of the OR Black Box, we identified many key areas that need to be addressed during its implementation. It is critical to ensure all stakeholders have adequate and accurate information about the OR Black Box system and research goals, and that the OR Black Box is positioned as a patient safety initiative for learning from and improving practice.
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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 | 0.035 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.006 |
| 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".