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Record W1988734517 · doi:10.1186/1748-5908-4-14

EXACKTE2: Exploiting the clinical consultation as a knowledge transfer and exchange environment: a study protocol

2009· article· en· W1988734517 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueImplementation Science · 2009
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsUniversité LavalUniversity of OttawaWestern UniversityCentre hospitalier universitaire de Québec
FundersCanadian Institutes of Health Research
KeywordsMedicinePresentation (obstetrics)PhoneRegretKnowledge translationHealth administrationProtocol (science)Health services researchFamily medicineHealth informaticsSet (abstract data type)Medical educationNursingPublic healthAlternative medicineKnowledge managementComputer sciencePathology

Abstract

fetched live from OpenAlex

BACKGROUND: While the evidence suggests that the way physicians provide information to patients is crucial in helping patients decide upon a course of action, the field of knowledge translation and exchange (KTE) is silent about how the physician and the patient influence each other during clinical interactions and decision-making. Consequently, based on a novel relationship-centered model, EXACKTE(2) (EXploiting the clinicAl Consultation as a Knowledge Transfer and Exchange Environment), this study proposes to assess how patients and physicians influence each other in consultations. METHODS: We will employ a cross-sectional study design involving 300 pairs of patients and family physicians from two primary care practice-based research networks. The consultation between patient and physician will be audio-taped and transcribed. Following the consultation, patients and physicians will complete a set of questionnaires based on the EXACKTE(2) model. All questionnaires will be similar for patients and physicians. These questionnaires will assess the key concepts of our proposed model based on the essential elements of shared decision-making (SDM): definition and explanation of problem; presentation of options; discussion of pros and cons; clarification of patient values and preferences; discussion of patient ability and self-efficacy; presentation of doctor knowledge and recommendation; and checking and clarifying understanding. Patients will be contacted by phone two weeks later and asked to complete questionnaires on decisional regret and quality of life. The analysis will be conducted to compare the key concepts in the EXACKTE(2) model between patients and physicians. It will also allow the assessment of how patients and physicians influence each other in consultations. DISCUSSION: Our proposed model, EXACKTE(2), is aimed at advancing the science of KTE based on a relationship process when decision-making has to take place. It fosters a new KTE paradigm by putting forward a relationship-centered perspective and has the potential to reveal unknown mechanisms that underline effective KTE in clinical contexts. This will result in better understanding of the mechanisms that may promote a new generation of knowledge transfer strategies.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
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 head0.568
GPT teacher head0.640
Teacher spread0.072 · 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