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Record W2906077577 · doi:10.1177/2059799118814394

A theory-based self-report measure of health literacy: The Calgary Charter on Health Literacy scale

2018· article· en· W2906077577 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMethodological Innovations · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsHealth literacyCronbach's alphaScale (ratio)CharterLiteracyHealth carePublic healthPsychologyReliability (semiconductor)GerontologyMedicineMedical educationApplied psychologyPsychometricsClinical psychologyNursingPolitical scienceGeographyPedagogy

Abstract

fetched live from OpenAlex

We set out to test a theory-based measure of health literacy. To do so, we included the newly developed Calgary Charter on Health Literacy scale in Pre- and Post-evaluation of the Life Enhancement Program at multiple sites. The program focusing on health literacy and the prevention of chronic disease is conducted with health-care provider organization partners across the United States. In testing the reliability and validity of the new measure of health literacy, Cronbach’s alpha is very acceptable level at 0.80. There are numerous statistically significant correlations between the change in health literacy and participants’ changes in knowledge, attitudes, beliefs, behaviors, and health status. Data and analysis indicate that the Calgary Charter on Health Literacy Scale is a valid and reliable measurement tool in the contexts and with the populations they were tested within. More testing is necessary and warranted in a wider variety of contexts and populations—ideally to include large representative random samples and comparison groups. We recommend that policymakers increase focus on advancing health literacy as an evidence-based approach to reach the goals of improved individual and public health at a lower cost.

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.

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)0.052
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.685
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0520.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.299
GPT teacher head0.556
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