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Oral Health Literacy Framework: The Pathway to Improved Oral Health

2021· article· en· W4323340142 on OpenAlexaff
Francisco Ramos‐Gomez, Tamanna Tiwari

Bibliographic record

VenueJournal of the California Dental Association · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsInstitute of Population and Public Health
Fundersnot available
KeywordsHealth literacyLiteracyOral healthHealth equityMedicineMechanism (biology)PsychologyPolitical scienceFamily medicineHealth careNursingPublic health

Abstract

fetched live from OpenAlex

Background: Oral health literacy (OHL) is the degree to which a patient receives, gains, processes and understands basic oral health knowledge, the services available to them and the behaviors required of them to make healthy decisions.Types of studies reviewed: Studies reviewed focused on oral health disparities, barriers to OHL and patient-provider communication, parental engagement and factors contributing to the improvement of OHL for vulnerable communities.Results: The consequences of low OHL are far reaching and compounded by disparities that already exist for patients and communities on multiple levels. This article discusses barriers to OHL, the impact of OHL on oral health and oral health disparities and recommendations for improving patient OHL.Practical implications: The article provides a proposed conceptual framework that discusses the potential mechanism of upstream and intermediate factors impacting OHL and how OHL affects oral health outcomes.

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)0.011
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.040
GPT teacher head0.433
Teacher spread0.393 · 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 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

Citations10
Published2021
Admission routes1
Has abstractyes

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