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Record W2136426040 · doi:10.1186/1472-6939-15-31

“Nudge” in the clinical consultation – an acceptable form of medical paternalism?

2014· article· en· W2136426040 on OpenAlexaff
Ajay Aggarwal, Joanna Davies, Richard Sullivan

Bibliographic record

VenueBMC Medical Ethics · 2014
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsPaternalismCompromiseNudge theoryPhilosophy of medicineAutonomyPsychologyHealth careFraming (construction)Freedom of choiceSocial psychologyLaw and economicsMedicinePolitical scienceSociologyLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.234
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.234
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.594
GPT teacher head0.601
Teacher spread0.007 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations50
Published2014
Admission routes1
Has abstractyes

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