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Record W2117119848 · doi:10.1177/1744987108088636

“I didn’t tell them. Well, they never ask”. Lay understandings of hypertension and their impact on chronic disease management: implications for nursing practice in primary care

2008· article· en· W2117119848 on OpenAlexaff
Gina Higginbottom

Bibliographic record

VenueJournal of research in nursing · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFocus groupPreparednessEthnic groupNursingStatus quoDiseaseHealth careQualitative researchMedicinePsychologySociologyPolitical science

Abstract

fetched live from OpenAlex

Abstract In the United Kingdom, as in other developed nations, there has been an increased research focus on ethnicity and the mediation of ethnicity on health and illness experience. This paper examines how lay understandings may affect chronic disease management and the steps primary care nurses may take to optimize care delivery for patients/families, using the example of hypertension in the African-Caribbean community. A focused ethnographic approach was adopted for this study. Data were first collected using focus group interviews (2), semi-structured interviews (21), and vignette interviews (5). Data were analyzed with the assistance of Atlas/ti qualitative analysis software using the principles developed by Roper and Shapira. Findings are presented using Kleinman’s seminal work as a theoretical framework: a) the aetiology or cause of the condition, b) the timing and mode of onset, c) the patho-physiological processes involved, d) the natural history and severity of the illness, e) the appropriate treatment for the condition. The paper concludes that it is incumbent upon primary health care nurses to recognize and take account of the lay explanations of health illness that patients/families hold. Failure to do so may compromise effective care-giving.

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)0.000
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 score0.496
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.159
GPT teacher head0.467
Teacher spread0.309 · 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

Citations9
Published2008
Admission routes1
Has abstractyes

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