“Nudge” in the clinical consultation – an acceptable form of medical paternalism?
Bibliographic record
Abstract
BACKGROUND: Libertarian paternalism is a concept derived from cognitive psychology and behavioural science. It is behind policies that frame information in such a way as to encourage individuals to make choices which are in their best interests, while maintaining their freedom of choice. Clinicians may view their clinical consultations as far removed from the realms of cognitive psychology but on closer examination there are a number of striking similarities. DISCUSSION: Evidence has shown that decision making is prone to bias and not necessarily rational or logical, particularly during ill health. Clinicians will usually have an opinion about what course of action represents the patient's best interests and thus may "frame" information in a way which "nudges" patients into making choices which are considered likely to maximise their welfare. This may be viewed as interfering with patient autonomy and constitute medical paternalism and appear in direct opposition to the tenets of modern practice. However, we argue that clinicians have a responsibility to try and correct "reasoning failure" in patients. Some compromise between patient autonomy and medical paternalism is justified on these grounds and transparency of how these techniques may be used should be promoted. SUMMARY: Overall the extremes of autonomy and paternalism are not compatible in a responsive, responsible and moral health care environment, and thus some compromise of these values is unavoidable. Nudge techniques are widely used in policy making and we demonstrate how they can be applied in shared medical decision making. Whether or not this is ethically sound is a matter of continued debate but health care professionals cannot avoid the fact they are likely to be using nudge within clinical consultations. Acknowledgment of this will lead to greater self-awareness, reflection and provide further avenues for debate on the art and science of clinical communication.
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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 | 0.126 | 0.207 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.073 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.015 | 0.018 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".