Teamwork and Safety Attitudes in Complex Aortic Surgery at a Dutch Hospital: Cross-Sectional Survey Study
Bibliographic record
Abstract
BACKGROUND: Improving teamwork in surgery is a complex goal and difficult to achieve. Human factors questionnaires, such as the Safety Attitudes Questionnaire (SAQ), can help us understand medical teamwork and may assist in achieving this goal. OBJECTIVE: This paper aimed to assess local team and safety culture in a cardiovascular surgery setting to understand how purposeful teamwork improvements can be reached. METHODS: Two cardiovascular surgical teams performing complex aortic treatments were assessed: an endovascular-treatment team (ETT) and an open-treatment team (OTT). Both teams answered an online version of the SAQ Dutch Edition (SAQ-NL) consisting of 30 questions related to six different domains of safety: teamwork climate, safety climate, job satisfaction, stress recognition, perceptions of management, and working conditions. In addition, one open-ended question was posed to gain more insight into the completed questionnaires. RESULTS: The SAQ-NL was completed by all 23 ETT members and all 13 OTT members. Team composition was comparable for both teams: 57% and 62% males, respectively, and 48% and 54% physicians, respectively. All participants worked for 10 years or more in health care. SAQ-NL mean scores were comparable between both teams, with important differences found between the physicians and nonphysicians of the ETT. Nonphysicians were less positive about the safety climate, job satisfaction, and working climate domains than were the physicians (P<.05). Additional education on performed procedures, more conjoined team training, as well as a hybrid operating room were suggested by participants as important areas of improvement. CONCLUSIONS: Nonphysicians of a local team performing complex endovascular aortic aneurysm surgery perceived safety climate, job satisfaction, and working conditions less positively than did physicians from the same team. Open-ended questions suggested that this is related to a lack of adequate conjoined training, lack of adequate education, and lack of an adequate operating room. With added open-ended questions, the SAQ-NL appears to be an assessment tool that allows for developing strategies that are instrumental in improving quality of care.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".