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Record W4410589683 · doi:10.1093/heapro/daaf067

Determinants of chronic non-communicable disease screening among adults in Ghana

2025· article· en· W4410589683 on OpenAlexafffund
Irenius Konkor, M. Anwar Waqar, Vincent Kuuire

Bibliographic record

VenueHealth Promotion International · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoUniversity of Toronto MississaugaCanada Research Chairs
KeywordsEnvironmental healthNon-communicable diseaseDeveloping countryNeighbourhood (mathematics)UrbanizationSocial capitalMedicineSocial determinants of healthLogistic regressionDiseaseEconomic growthPsychologySocioeconomicsPublic healthSociologySocial scienceEconomics

Abstract

fetched live from OpenAlex

The pervasiveness and growing concern of non-communicable diseases (NCDs) in developing countries, which were considered not in the distant historical past, as diseases of only the affluent and of developed countries, is no longer in doubt. The proportion of deaths attributable to NCDs today includes figures never witnessed in any previous historical period. Delayed screening is one of the drivers of this worrying trend. The objective of this study, therefore, was to examine the determinants of NCD screening in Ghana. We fitted logistic regression models to a sample of 1342 individuals who successfully completed a cross-sectional survey across three cities in Ghana. Results show that factors such as knowledge on the causes of NCDs, health insurance, high neighbourhood social capital, poor self-rated health, and exposure to NCDs campaign messages significantly predicted an increased likelihood of NCDs screening. However, socio-cultural beliefs such as developing NCDs being the will of God or the enemy being able to spiritually inflict an individual with NCDs were found to be associated with a lower likelihood of screening for NCDs. Beyond the traditional determinants of health, this study expands the analytical gaze and frontiers of the determinants of NCDs in Ghana through the lens of socio-cultural belief systems. While improving access to healthcare, exposure and knowledge through educational programs as well as building community social capital might be important in scaling up NCD screening, dismantling untenable beliefs and misconceptions is similarly crucial.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.355
Teacher spread0.323 · 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 designObservational
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

Citations3
Published2025
Admission routes2
Has abstractyes

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