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Record W4407865229 · doi:10.1093/her/cyaf006

Think-aloud test of online education for patients with cardiac diseases: do they meet the needs of women?

2025· article· en· W4407865229 on OpenAlexaffabout
Emily A Gunning, Rachael Pamela Carson, Emma Schotanus, Jordan Henderson, Amy Eccles, Sherry L. Grace, Gabriela Lima de Melo Ghisi

Bibliographic record

VenueHealth Education Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity Health NetworkToronto Rehabilitation InstituteYork UniversityUniversity of Toronto
Fundersnot available
KeywordsTest (biology)MedicinePsychologyRead aloudMedical educationClinical psychologyPhysical therapyLinguisticsReading (process)

Abstract

fetched live from OpenAlex

Patient education is a core component of cardiovascular rehabilitation (CR). Recent guidelines call for tailored materials to support women, given their unique needs and preferences. This study investigated women patient's perspectives of online CR educational materials (Cardiac College, Toronto). Through a cross-sectional design, a think-aloud protocol followed by semistructured qualitative interviews was used to collect data on women's perceptions of the comprehensive educational webpages with regard to content, format, visuals, length/volume, difficulty, applicability, implementability and suggestions for improvement. Thirty-eight current and previous CR program participants completed 1-h Zoom interviews. Transcripts were coded thematically using best practices in NVivo by two researchers independently. Four themes emerged: (I) materials met their needs (content, presentation, and empowerment), (II) suggestions for improvement in presentation (website design, text, and visuals), (III) content (volume, additions, and difficulty), and (IV) optimizing reach and implementability (inclusiveness, barriers, and dissemination). Overall, the education content met women's needs and was relatable, but should be updated for currency, visual appeal, and searchability. Cardiac College for Women may meet these needs and preferences.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.238
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.031
GPT teacher head0.460
Teacher spread0.429 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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