Using practical wisdom to facilitate ethical decision-making: a major empirical study of phronesis in the decision narratives of doctors
Bibliographic record
Abstract
Abstract BackgroundMedical ethics has recently seen a drive away from multiple prescriptive approaches, where physicians are inundated with guidelines and principles, towards alternative, less deontological perspectives. This represents a clear call for theory building that does not produce more guidelines. Phronesis (practical wisdom) offers an alternative approach for ethical decision-making based on an application of accumulated wisdom gained through previous practice dilemmas and decisions experienced by practitioners. Phronesis, sometimes referred to as the ‘executive virtue’, offers a way to navigate the practice virtues for any given case to reach a final decision on the way forward. However, very limited empirical data exist to support the theory of phronesis -based medical decision-making, and what does exist tends to focus on individual practitioners rather than practice-based communities of physicians.MethodsThe primary research question was: What does it mean to medical practitioners to make ethically wise decisions for patients and their communities? A three-year ethnographic study explored the practical wisdom of doctors (n=131) and used their narratives to develop theoretical understanding of the concepts of ethical decision-making. Data collection included narrative interviews and observations with hospital doctors and General Practitioners at all stages in career progression. The analysis draws on neo-Aristotelian and MacIntyrean concepts of practice- based virtue ethics and was supported by an arts-based film production process.FindingsWe found that individually doctors conveyed many different practice virtues and those were consolidated into fifteen virtue continua that convey the participants’ collective practical wisdom, including the phronesis virtue. This study advances the existing theory on phronesis as a decision-making approach because only now a theoretical ‘collective practical wisdom’ exists. ConclusionGiven the arguments that doctors feel professionally and personally vulnerable in the context of ethical decision-making, our contribution in the form of a moral debating resource can support before, during and after decision-making reflection. The potential implications are that these theoretical findings can be used by educators and practitioners as a non-prescriptive alternative to improve ethical decision-making, thereby addressing the call in the literature, and benefit patients and their communities, as well.
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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 | 0.021 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".