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Record W2337542326 · doi:10.1177/0261927x15587015

How Patients Perceive Their Doctors’ Communication

2015· article· en· W2337542326 on OpenAlexaffabout
Susan Baker, Bernadette Watson

Bibliographic record

VenueJournal of Language and Social Psychology · 2015
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsCape Breton University
Fundersnot available
KeywordsWillingness to communicateHealth communicationInterpersonal communicationPsychologyHealth carePerceptionCompetence (human resources)Social psychologyContext (archaeology)Health belief modelMedicineNursingHealth promotionPublic healthCommunication

Abstract

fetched live from OpenAlex

By emphasizing the value of health professionals’ communication skills in creating positive health care experiences, researchers have tended to study health communication as an interpersonal encounter. Interactions in the health context, though, are inherently intergroup. Using the language and social psychology approach, this study emphasizes those intergroup features of health communication. We used mixed methods and applied communication accommodation theory and the willingness to communicate construct to the health context. Participants in Canada and Australia ( N = 371) were asked about their perceptions of their health consultations. Multiple regression analyses revealed that health communication competence was the best predictor of patient willingness to communicate. Differences between patients’ accounts of positive and negative health care experiences were clearly differentiated by their perceptions of the health professionals’ communication strategies. The potential effects of these strategies on patient participation are discussed.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.097
GPT teacher head0.447
Teacher spread0.350 · 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

Citations42
Published2015
Admission routes2
Has abstractyes

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