Perceptions and Competence in Evidence-Based Medicine
Bibliographic record
Abstract
Background:The Journal of Bone and Joint Surgery, American Volume (The Journal) recently initiated a section called “Evidence-Based Orthopaedics.” Furthermore, a level-of-evidence rating is now used in The Journal to help readers in clinical decision-making. Little is known about whether this recent emphasis has influenced surgeons' perceptions about and competence in evidence-based medicine. Therefore, we examined perceptions and competence in evidence-based medicine among Dutch orthopaedic surgeons. Methods: Members of the Dutch Orthopaedic Association were surveyed to examine their attitudes toward evidence-based medicine and their competence in evidence-based medicine. We evaluated competences using a newly developed instrument tailored to surgical practice. Results: Of the 611 members, 367 surgeons (60%) responded. Orthopaedic surgeons welcomed evidence-based medicine. Practical evidence-based medicine resources were perceived as the best method to move from opinion-based or experience-based to evidence-based practice. Four variables were significantly and positively associated with the competence instrument: (1) a younger age, particularly between thirty-six and forty-five years (p = 0.007), (2) experience of less than ten years (p = 0.032), (3) having a PhD degree (p < 0.001), and (4) working in an academic or teaching setting (p = 0.004). The majority of the respondents were aware of The Journal's evidence-based medicine section (84%) and level-of-evidence ratings (65%), and 20% used The Journal's evidence-based medicine abstracts in clinical decision-making. This increased awareness of evidence-based medicine was also reflected in the frequent use of Cochrane reviews in clinical decision-making (27% of the respondents). Surgeons who used and those who were aware of but did not use The Journal's evidence-based medicine abstracts or Cochrane reviews in clinical decision-making had significantly higher competence instrument scores than those who were unaware of these resources (p = 0.03 and p < 0.001, respectively). Conclusions: Evidence-based medicine is welcomed by Dutch orthopaedic surgeons. The recent emphasis on evidence-based medicine is reflected in an increased awareness about The Journal's evidence-based medicine section, levels of evidence, and the largest evidence-based medicine resource: the Cochrane reviews. Younger orthopaedic surgeons had better knowledge about evidence-based medicine. The development and use of evidence-based resources as well as preappraised summaries such as The Journal's evidence-based medicine abstracts and Cochrane reviews were perceived as the best way to move from opinion-based to evidence-based orthopaedic practice.
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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 | 0.016 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".