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Record W1504171394 · doi:10.26443/ijwpc.v1i2.2

Humanizing clinical dentistry through a person-centred model

2014· article· en· W1504171394 on OpenAlexaffvenue
Nareg Apelian, Jean‐Noël Vergnes, Christophe Bedos

Bibliographic record

VenueInternational Journal of Whole Person Care · 2014
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsReductionismPositivismPsychological interventionMedicinePower (physics)Public health interventionsDental healthPsychologyEpistemologyMedical educationPsychotherapistDentistryNursingPhilosophy

Abstract

fetched live from OpenAlex

The clinical approach in dentistry stems from a biomedical model of health that is anchored in positivism. This biomedical model was never explicitly developed or reflected on, but rather implicitly acquired as a product of historical circumstance. A reductionist understanding of health served dentistry well in the past, when health afflictions were mostly acute. Today, however, in the age of chronic illnesses, the current clinical approach is no longer adequate: patients and dentists are both dissatisfied, and there are problems with dental education and dental public health. After a thorough review of the literature, highlighting the current state of the profession, we propose an alternative clinical model upon which updated approaches can be based. We call this model "Person-Centred Dentistry". Our proposed model is rooted on the notion of sharing of power between the dentist and the patient: a sharing of power in the relationship and epistemology. This leads to an expanded understanding of the person and the illness; a co-authoring of treatment plans; and interventions that focus not only on eliminating disease but also on patient needs.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

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

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 head0.121
GPT teacher head0.404
Teacher spread0.283 · 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 designQualitative
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

Citations49
Published2014
Admission routes2
Has abstractyes

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