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Record W1965675356 · doi:10.1097/aog.0000000000000708

Association of Health Literacy With Adherence to Screening Mammography Guidelines

2015· article· en· W1965675356 on OpenAlexaff
Ian K. Komenaka, Jesse Nodora, Chiu-Hsieh Hsu, Marı́a Elena Martı́nez, Sonal Gandhi, Marcia E. Bouton, Anne E. Klemens, Lauren I. Wikholm, Barry D. Weiss

Bibliographic record

VenueObstetrics and Gynecology · 2015
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsCentre for Family Medicine
Fundersnot available
KeywordsMedicineHealth literacyMammographyOdds ratioConfidence intervalLogistic regressionDemographyBreast cancerFamily medicineGynecologyGerontologyCancerHealth careInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the relationship of health literacy and screening mammography. METHODS: All patients seen at a breast clinic underwent prospective assessment of health literacy from January 2010 to April 2013. All women at least 40 years of age were included. Men and women diagnosed with breast cancer before age 40 years were excluded. Routine health literacy assessment was performed using the Newest Vital Sign. Demographic data were also collected. Medical records were reviewed to determine if patients had undergone screening mammography: women aged 40-49 years were considered to have undergone screening if they had another mammogram within 2 years. Women 50 years or older were considered to have undergone screening mammography if they had another mammogram within 1 year. RESULTS: A total of 1,664 consecutive patients aged 40 years or older were seen. No patient declined the health literacy assessment. Only 516 (31%) patients had undergone screening mammography. Logistic regression analysis that included ethnicity, language, education, smoking status, insurance status, employment, income, and family history found that only three factors were associated with not obtaining a mammogram: low health literacy (odds ratio [OR] 0.27, 95% confidence interval [CI] 0.19-0.37; P<.001), smoking (OR 0.64, 95% CI 0.47-0.85; P=.002), and being uninsured (OR 0.66, 95% CI 0.51-0.85; P=.001). CONCLUSION: Of all the sociodemographic variables examined, health literacy had the strongest relationship with use of screening mammography.

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)0.005
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 score0.300
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
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 head0.138
GPT teacher head0.391
Teacher spread0.253 · 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

Citations84
Published2015
Admission routes1
Has abstractyes

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