Surgeon Perception and Attitude Toward the Moral Imperative of Institutionally Addressing Second Victim Syndrome in Surgery
Bibliographic record
Abstract
BACKGROUND: Second victim syndrome (SVS) is described as when healthcare providers encounter significant moral distress after traumatic patient care events. Although broadly recognized in medicine, this remains underrecognized in surgery, and no systemic approaches exist to mitigate potential harms of SVS among surgeons. When SVS is left unaddressed, surgeons not only suffer personal psychological harm but their ability to care for future patients can also be compromised. The aim was to examine surgeons' perceptions and attitudes regarding mitigation of SVS. STUDY DESIGN: This study was conducted at a tertiary-care university hospital using a mixed-methods approach coupling quantitative and qualitative assessments including a 13-item survey, follow-up focus group, and semistructured interviews, The Wilcoxon signed rank test was used for quantitative analysis and content analysis used to report qualitative findings. RESULTS: Surgeons believe SVS is a universal experience among surgeons that healthcare institutions have a moral obligation to address. Surgeons further believe that any effective mitigation strategy must receive legal protection similar to morbidity and mortality conferences. The culture, tenor, and tone of review processes after surgical complications can either reduce or exacerbate the burden of SVS. Successful interventions must be easily accessible, voluntary, and culturally acceptable. Surgeons may suffer greater SVS compared with nonprocedural physicians as adverse events can be inevitable in operation and may potentially be a high-frequency outcome depending on patient population. CONCLUSIONS: Surgeons agreed that healthcare organizations have a moral imperative to assist surgeons in navigating the psychosocial impacts of SVS after adverse surgical outcomes. The success of mitigation strategies was viewed as ethically relevant to patients and surgeons and dependent on the culture, tenor, and tone of the process.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".