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Record W2773778147 · doi:10.1097/rnj.0000000000000099

Validation of a Scale to Assess Patients’ Comprehension of Frequently Used Cardiology Terminology: The Cardiac TERM Scale in Brazilian Portuguese

2017· article· en· W2773778147 on OpenAlexaff
Gabriela Lima de Melo Ghisi, Rafaella Zulianello dos Santos, Raquel Rodrigues Britto, Christiani Decker Batista Bonin, Thaianne Cavalcante Sérvio, Luiz Fernando Schmidt, Magnus Benetti, Sherry L. Grace

Bibliographic record

VenueRehabilitation Nursing · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsYork UniversityToronto Rehabilitation InstituteUniversity Health Network
Fundersnot available
KeywordsScale (ratio)Brazilian PortugueseTerminologyReliability (semiconductor)Test (biology)PsychologyMedicinePhysical therapyDiscriminant validityConcurrent validityPortuguesePsychometricsClinical psychologyTerm (time)Internal consistency

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this study was to psychometrically validate the translation of a questionnaire on patient understanding of cardiology terminology (TERM) to Brazilian Portuguese. DESIGN: After piloting the translation and cross-cultural adaptation, the 16-item TERM questionnaire was psychometrically tested. METHODS: Internal and test-retest reliability, as well as validity, were assessed in 322 cardiac patients. FINDINGS: Internal (α = .88) and test-retest reliability (all weighted Kappa > 0.63) exceeded the minimum recommended standards. Criterion validity was supported by significant differences in mean scores by socioeconomic indicators (p < .01). Discriminant validity was supported in that cardiac rehabilitation participants had significantly higher TERM scores (p < .001). Participants did not correctly define any of the terms, and a floor effect was identified in all terms. CONCLUSIONS: The Cardiac TERM Scale was demonstrated to have good reliability and validity. CLINICAL RELEVANCE: The scale can be used by healthcare professionals, such as nurses. Results can be used to inform patient education, which could in turn impact patient adherence to medical advice and hence 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)0.003
metaresearch head score (Gemma)0.002
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 score0.048
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.065
GPT teacher head0.446
Teacher spread0.381 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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