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Health Literacy as an Empowerment Tool for Low-Income Mothers

2006· article· en· W2014928556 on OpenAlexaff
Caroline Porr, Jane Drummond, Solina Richter

Bibliographic record

VenueFamily & Community Health · 2006
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsUniversity of AlbertaCapital District Health Authority
Fundersnot available
KeywordsOperationalizationHealth literacyEmpowermentConceptualizationHealth careSocioeconomic statusLiteracyHealth equityPsychologyMandateSociologyPublic relationsMedicinePedagogyPolitical scienceEconomic growthEnvironmental healthComputer scienceEconomics

Abstract

fetched live from OpenAlex

Health literacy commonly refers to the extent to which one can access and accurately interpret healthcare information. Statistics reveal that limited health literacy is prevalent among those of lower socioeconomic status. When working with low-income mothers, it is recommended in this article that healthcare professionals operationalize a broader conceptualization of health literacy than assessment of reading levels and translating knowledge of risk factors for illness and disease. Nutbeam's continuum of functional, interactive, and critical health literacy directs healthcare professionals to expand their health education mandate to encompass equipping low-income mothers with the necessary knowledge and skills to gain control over their lives and optimize the healthy development of their children. Tenets from social cognitive theory, principles from interdependence theory, and strategies from Freire's empowerment education model are integral to successful progression along Nutbeam's health literacy continuum.

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)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.052
GPT teacher head0.474
Teacher spread0.422 · 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 designNot applicable
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

Citations83
Published2006
Admission routes1
Has abstractyes

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