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Record W1682616181 · doi:10.5750/ejpch.v2i1.705

Commentary on Discussion Paper by Miles, A and Mezzich J.E. (2011). Person-centred medicine as an emergent model of clinical practice: The devil is in the details

2014· article· en· W1682616181 on OpenAlexaff
Cathy Charles, Amiram Gafni

Bibliographic record

VenueEuropean Journal for Person Centered Healthcare · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMental Health and Psychiatry
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMeaning (existential)Clinical PracticeProcess (computing)PsychologyTask (project management)Alternative medicineMedical practiceEpistemologyMedicineMedical educationPsychotherapistNursingComputer scienceManagement

Abstract

fetched live from OpenAlex

Miles and Mezzich have written a comprehensive review of the origins, development and current status of two influential international movements aimed at shaping the practice of medicine - evidence-based medicine (EBM) and patient-centred care. As the authors point out, these two movements have been largely independent of each other with little crossover of ideas as each pursues its own goals of trying to broaden its influence. Miles and Mezzich propose to take the strengths of both movements and to create a new integrated model of person-centred care (PCC) which is evidence-informed (rather than evidence-based) and incorporates a role for patient values in clinical decision-making. While laudable and logical to try to move forward with this approach which integrates two seemingly contradictory principles underlying each movement (clinical practice based on the findings of clinical research evidence and clinical practice that is responsive to patients’ values, preferences and beliefs), this task is not easy and, as the authors themselves note, the model that results from this process is still in elementary form. By proposing this new integrated model, the authors hope to stimulate further debate on the meaning of a person centred-care approach to medical practice.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.235
GPT teacher head0.393
Teacher spread0.158 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations3
Published2014
Admission routes1
Has abstractyes

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