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Record W2064312940 · doi:10.1097/hjh.0b013e32835476e1

Getting the message across

2012· review· en· W2064312940 on OpenAlexaff
Emily Jolles, Alexander M. Clark, Branko Braam

Bibliographic record

VenueJournal of Hypertension · 2012
Typereview
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineComprehensionContext (archaeology)Health literacyNonverbal communicationHealth communicationEmpathyAffect (linguistics)LiteracyHealth careDevelopmental psychologyCommunicationPsychologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

Effective communication is a prerequisite for any successful encounter between patient and provider. Nevertheless, it is unclear how/where communication can impact/affect adherence to antihypertensive medication, and maintenance of lifestyle changes to control blood pressure targets. Poor physician communication is correlated with a higher risk of treatment nonadherence. Given the high rates of hypertension globally, this review serves to enlighten aspects of the communication exchange from a provider, context, and patient perspective. Relevant articles were analyzed to assess barriers, solutions, and optimizations for communication with hypertensive patients. To support the findings, a model of communication in the context of hypertension treatment is presented, which comprises three phases: comprehension and acceptance, translation into action, and long-term retention. Secondly, an analysis of care providers (bedside manner, verbal/nonverbal communication, empathy and sex, time, knowledge base), context (format and tailoring of the message, and physical environment), and patient-related factors (sex, socio-economic status, language and health literacy, culture, age, psychological factors) were assessed in relation to hypertension. Current literature is limited regarding reciprocal communication, adaptive packaging of messages, and active verification of effective communication. To improve communication, hypertension care programs could benefit from better communication training, more team-based approaches, and flexible tools based on information technology.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.004
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 head0.588
GPT teacher head0.512
Teacher spread0.076 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations72
Published2012
Admission routes1
Has abstractyes

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