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Record W4317567670 · doi:10.1371/journal.pone.0280358

Community perspectives on cardiovascular disease control in rural Ghana: A qualitative study

2023· article· en· W4317567670 on OpenAlexfundno aff
B. V. Patil, Isla Hutchinson Maddox, Raymond Aborigo, Allison Squires, Denis Awuni, Carol R. Horowitz, Abraham Oduro, James F. Phillips, Khadija R. Jones, David J. Heller

Bibliographic record

VenuePLoS ONE · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsnot available
FundersResolve to Save LivesArmy Research OfficeFogarty International CenterNational Institutes of HealthYork UniversityMailman School of Public Health, Columbia UniversityIcahn School of Medicine at Mount SinaiTeva Pharmaceutical IndustriesArnhold Institute for Global HealthHess Corporation
KeywordsMedicineDiseasePsychological interventionRural areaFamily medicineNursingQualitative researchPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Cardiovascular disease (CVD) prevalence is high in Ghana-but awareness, prevention, and treatment is sparse, particularly in rural regions. The nurse-led Community-based Health Planning and Services program offers general preventive and primary care in these areas, but overlooks CVD and its risk factors. METHODS: We conducted in-depth interviews with 30 community members (CM) in rural Navrongo, Ghana to understand their knowledge and beliefs regarding the causes and treatment of CVD and the potential role of community nurses in rendering CVD care. We transcribed audio records, coded these data for content, and qualitatively analyzed these codes for key themes. RESULTS: CMs described CVD as an acute, aggressive disease rather than a chronic asymptomatic condition, believing that CVD patients often die suddenly. Yet CMs identified causal risk factors for CVD: not only tobacco smoking and poor diet, but also emotional burdens and stressors, which cause and exacerbate CVD symptoms. Many CMs expressed interest in counseling on these risk factors, particularly diet. However, they felt that nurses could provide comprehensive CVD care only if key barriers (such as medication access and training) are addressed. In the interim, many saw nurses' main CVD care role as referring to the hospital. CONCLUSIONS: CMs would like CVD behavioral education from community nurses at local clinics, but feel the local health system is now too fragile to offer other CVD interventions. CMs believe that a more comprehensive CVD care model would require accessible medication, along with training for nurses to screen for hypertension and other cardiovascular risk factors-in addition to counseling on CVD prevention. Such counseling should build upon existing community beliefs and concerns regarding CVD-including its behavioral and mental health causes-in addition to usual measures to prevent CVD mortality such as diet changes and physical exercise.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0090.006
Scholarly communication0.0020.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.078
GPT teacher head0.334
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2023
Admission routes1
Has abstractyes

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