Surgeon perceptions and utilization of evidence-based medicine
Bibliographic record
Abstract
OBJECTIVE: Knowledge translation approaches for augmenting the use of evidence in medical practice require identifying potential barriers to implementation. Important but poorly understood determinants of the uptake of knowledge translation tools are the intrinsic characteristics of health professionals themselves. In this study, the authors explored how surgeons' perceptions of evidence-based medicine (EBM) and their behavior in response to new evidence affect their awareness and use of evidence-based summaries designed for application at the point of care. METHODS: Faculty surgeons in two North American pediatric Hydrocephalus Clinical Research Networks, who had shunt infection prevention protocol compliance data for more than 10 shunt procedures in their respective clinical registries during the study period (September 2021-March 2023), participated in a cross-sectional survey regarding their attitudes, knowledge, and behaviors related to EBM and evidence-based practice. Univariable associations between these surgeon characteristics and two dependent variables were sought: 1) compliance with the steps of a perioperative protocol designed to minimize the incidence of shunt infection and 2) knowledge of evidence-based guidelines and recommendations relevant to the care of children with hydrocephalus. RESULTS: Ninety-two of 212 eligible surgeons responded to the survey. Most were inclined to implement new evidence in surgical practice. Compliance with the shunt infection prevention protocol was higher for those whose responses about their behavior in response to new information on the effectiveness of clinical strategies suggested that they value evidence over experience (i.e., those who actively seek or are receptive to new evidence) compared to those whose practice is driven by practical and pragmatic considerations (OR 5.27, 95% CI 1.08-25.74 for seekers and OR 4.32, 95% CI 1.48-12.58 for receptives vs pragmatists, p = 0.01). Overall knowledge of pediatric hydrocephalus-related guidelines was modest. Surgeons with a more favorable attitude toward the construct of EBM tended to correctly identify most of the published guideline statements presented to them (OR 1.07, 95% CI 1.00-1.16 for every 10-point increment on a 100-point visual analog scale, p = 0.05). CONCLUSIONS: The authors demonstrate that surgeons have variable knowledge of, and behave differently to, evidence that should influence care. Measurable surgeon characteristics are associated with the application of evidence in surgical practice. Thus, to improve the use of evidence-based summaries at the point of care, surgeon attitudes and behaviors should be assessed when designing knowledge translation interventions.
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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 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".