Team Communications in the Operating Room
Bibliographic record
Abstract
PURPOSE: Although the communication that occurs within health care teams is important to both team function and the socialization of novices, the nature of team communication and its educational influence are not well documented. This study explored the nature of communications among operating room (OR) team members from surgery, nursing, and anesthesia to identify common communicative patterns, sites of tension, and their impact on novices. METHOD: Paired researchers observed 128 hours of OR interactions during 35 procedures from four surgical divisions at one teaching hospital. Brief, unstructured interviews were conducted following each observation. Field notes were independently read by each researcher and coded for emergent themes in the grounded theory tradition. Coding consensus was achieved via regular discussion. Findings were returned to insider "experts" for their assessment of authenticity and adequacy. RESULTS: Patterns of communication were complex and socially motivated. Dominant themes were time, safety and sterility, resources, roles, and situation. Communicative tension arose regularly in relation to these themes. Each procedure had one to four "higher-tension" events, which often had a ripple effect, spreading tension to other participants and contexts. Surgical trainees responded to tension by withdrawing from the communication or mimicking the senior staff surgeon. Both responses had negative implications for their own team relations. CONCLUSIONS: Team communications in the OR follow observable patterns and are influenced by recurrent themes that suggest sites of team tension. Tension in team communication affects novices, who respond with behaviors that may intensify rather than resolve interprofessional conflict.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".