How gender shapes interprofessional teamwork in the operating room: a qualitative secondary analysis
Bibliographic record
Abstract
BACKGROUND: Despite substantial implications for healthcare provider practice and patient outcomes, gender has yet to be systematically explored with regard to interprofessional operating room (OR) teamwork. We aimed to explore and describe how gender and additional social identity factors shape experiences and perceptions of teamwork in the OR. METHODS: This study was a qualitative secondary analysis of semi-structured interviews with OR team members conducted between November 2018 and July 2019. Participants were recruited across hospitals in Ontario, Canada. We conducted both purposive and snowball sampling until data saturation was reached. Transcripts were analyzed thematically by two independent research team members, moving from open to axial coding. RESULTS: Sixty-six interviews of OR healthcare professionals were completed: anesthesia (n=17), nursing (n=19), perfusion (n=2), and surgery (n=26). Traditional gender roles, norms, and stereotypes were perceived and experienced by both women and men, but with different consequences. Both women and men participants described challenges that women face in the OR, such as being perceived negatively for displaying leadership behaviours. Participants also reported that interactions and behaviours vary depending on the team gender composition, and that other social identities, such as age and race, often interact with gender. Nevertheless, participants indicated a belief that the influence of gender in the OR may be modified. CONCLUSIONS: The highly gendered reality of the OR creates an environment conducive to breakdowns in communuication and patient safety risks in addition to diminishing team morale, psychological safety, and provider well-being. Consequently, until teamwork interventions adequately account for gender, they are unlikely to be optimally effective or sustainable.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".