The evidence‐based medicine model of clinical practice: scientific teaching or belief‐based preaching?
Bibliographic record
Abstract
RATIONALE: Evidence-based medicine (EBM) is commonly advocated as a 'gold standard' of clinical practice. A prominent definition of EBM is: the integration of best research evidence with clinical expertise and patient values. Over time, various versions of a conceptual model or framework for implementing EBM (i.e. how to practice EBM) have been developed. AIMS AND OBJECTIVES: This paper (i) traces the evolution of the different versions of the conceptual model; (ii) tries to make explicit the underlying goals, assumptions and logic of the various versions by exploring the definitions and meaning of the components identified in each model, and the methods suggested for integrating these into clinical practice; and (iii) offers an analytic critique of the various model iterations. METHODS: A literature review was undertaken to identify, summarize, and compare the content of articles and books discussing EBM as a conceptual model to guide physicians in clinical practice. RESULTS: Our findings suggest that the EBM model of clinical practice, as it has evolved over time, is largely belief-based, because it is lacking in empirical evidence and theoretical support. The model is not well developed and articulated in terms of defining model components, justifying their inclusion and suggesting ways to integrate these in clinical practice. CONCLUSION: These findings are significant because without a model that clearly defines what constitutes an EBM approach to clinical practice we cannot (i) consistently teach clinicians how to do it and (ii) evaluate whether it is being done.
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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 | 0.055 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.041 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".