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Record W2010978853 · doi:10.1016/j.berh.2009.12.013

Addressing patient beliefs and expectations in the consultation

2010· article· en· W2010978853 on OpenAlexaboutno aff
Chris J. Main, Rachelle Buchbinder, Mark Porcheret, Nadine E. Foster

Bibliographic record

VenueBest Practice & Research Clinical Rheumatology · 2010
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
FundersVersus Arthritis
KeywordsIdentification (biology)Style (visual arts)Patient carePsychologyFocus (optics)Process (computing)Health communicationHealth careMedicineMedical educationNursingComputer science

Abstract

fetched live from OpenAlex

In this article, we specifically focus on the identification and management of patient beliefs and expectations during consultations with health-care professionals (HCPs). In examination of the nature and purpose of communication during consultations, we evaluate the research relating to doctor-patient communication, present the Calgary-Cambridge framework and highlight the identification and management of the patient's beliefs and expectations as a key part of this process. Having identified what can go wrong, we identify the characteristics of effective consultations and consider strategies for improving communication. In recommending a clear and more focussed approach to the identification and management of patient beliefs and expectations, we consider not only the nature of the therapeutic climate, but also the style and content that could enhance the effectiveness of the communication. Having identified techniques for facilitating self-disclosure, we conclude by offering suggestions on how to 'close down' the consultation and hand over responsibility to the patient.

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)0.007
metaresearch head score (Gemma)0.203
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.203
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.634
GPT teacher head0.649
Teacher spread0.015 · 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.

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

Citations85
Published2010
Admission routes1
Has abstractyes

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