Unpacking the Broad Landscape of Intraoperative Stressors for Clinical Personnel: A Mixed-Methods Systematic Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: The main goals of this mixed-methods systematic review are to identify what types of intraoperative stressors for operating room personnel have been reported in collected studies and examine the characteristics of each intraoperative stressor. Methods: With a systematic literature search, we retrieved empirical studies examining intraoperative stress published between 2010 and 2020. To synthesize findings, we applied two approaches. First, a textual narrative synthesis was employed to summarize key study information of the selected studies by focusing on surgical platforms and study participants. Second, a thematic synthesis was employed to identify and characterize intraoperative stressors and their subtypes. Results: Ninety-four studies were included in the review. Regarding the surgical platforms, the selected studies mainly focused on minimally invasive surgery and few studies examined issues around robotic surgery. Most studies examined intra-operative stress from surgeons' perspectives but rarely considered other clinical personnel such as nurses and anesthetists. Among seven identified stressors, technical factors were the most frequently examined followed by individual, operating room environmental, interpersonal, temporal, patient, and organizational factors. Conclusion: By presenting stressors as multifaceted elements affecting collaboration and interaction between multidisciplinary team members in the operating room, we discuss the potential interactions between stressors which should be further investigated to build a safe and efficient environment for operating room personnel.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it