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Record W4399591978 · doi:10.1111/scd.13033

Exploring the association of self‐rated oral health with self‐rated general and mental health among older adults in a resource‐poor context: Insights for advancing Sustainable Development Goal 3

2024· article· en· W4399591978 on OpenAlexaff
Daniel Amoak, Roger Antabe, Joseph Asumah Braimah, Williams Agyemang‐Duah, Yujiro Sano, Isaac Luginaah

Bibliographic record

VenueSpecial Care in Dentistry · 2024
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsQueen's UniversityThe Scarborough HospitalNipissing UniversityWestern University
Fundersnot available
KeywordsMental healthMedicineContext (archaeology)Environmental healthOral healthSocioeconomic statusGerontologyCross-sectional studyLogistic regressionPsychiatryPopulationFamily medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Older adults in Ghana have been disproportionately affected by oral health issues such as caries and periodontitis. This situation calls for comprehensive attention within health and healthcare policies, due to the established connections between oral health and other aspects of health and well-being in high-income countries, including physical and mental health. However, there is a significant gap in the literature when it comes to exploring the association of oral health with physical and mental health in resource-constrained settings like Ghana. METHODS: To address this void, we collected a cross-sectional sample comprising older adults aged 60 and above (n = 1073) and analyzed self-rated health measures to investigate the relationship between oral health and general and mental health in Ghana. RESULTS: The results of our logistic regression analysis revealed a significant association: older adults who reported poor oral health were more likely to rate their general (OR = 5.10; p < .001) and mental health (OR = 4.78, p < .001) as poor, compared to those with good oral health, even after accounting for demographic and socioeconomic variables. CONCLUSIONS: Based on these findings, we discuss the policy implications of our findings, especially in the context of advancing Sustainable Development Goal 3 in Ghana and other resource-constrained settings.

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 score0.227
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.278
Teacher spread0.266 · 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
Published2024
Admission routes1
Has abstractyes

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