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Record W4404930263 · doi:10.1002/jgc4.1995

Evaluation of face validity and core concepts of a novel knowledge scale for inherited heart disease: A pilot study

2024· article· en· W4404930263 on OpenAlexaffabout
Susan Christian, Tara Dzwiniel, Amy J. L. Baker, Barbara B. Biesecker, Kennedy Borle, Roya Mostafavi, Jill Slamon, Hannah Wand, Laura Yeates

Bibliographic record

VenueJournal of Genetic Counseling · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsUniversity of British ColumbiaAlberta Health ServicesUniversity of Alberta
Fundersnot available
KeywordsGenetic counselingContext (archaeology)Genetic testingMedicineMedical geneticsFace validityScale (ratio)Family medicineMedical educationDiseasePsychologyClinical psychologyPathologyPsychometricsGenetics

Abstract

fetched live from OpenAlex

The rising demand for genetic counseling has prompted the implementation of various innovative service delivery models, such as patient webinars, videos, chatbots, and the integration of genetic testing into mainstream healthcare. To ensure patients receive adequate information for informed decision-making, validated measures to assess these models are essential but currently limited in the setting of inherited heart disease. We aimed to develop and initiate validation of a cardiac knowledge scale, as part of the Multidimensional Model of Informed Choice measure, to assess whether patients (probands and family members) with inherited cardiomyopathies, arrhythmias, and aortopathies are provided with sufficient knowledge to make informed decisions about genetic testing. Content expert genetic counselors identified eight core concepts addressed during genetic counseling sessions; from these, eight true/false knowledge questions were created. Questions were reviewed by 22 international cardiac genetics counselors with additional changes made. Initial validation steps of the knowledge scale were conducted at two sites: the Edmonton Medical Genetic Clinic, University of Alberta Hospital in Edmonton, Canada, and the Genetic Heart Disease Clinic, Royal Prince Alfred Hospital in Sydney, Australia. Face validity was evaluated through nine patient interviews, resulting in minor revisions to four questions and major revisions to one question. An additional five patient interviews were conducted to evaluate the revised questions. The core concepts addressed in each question were further evaluated in the context of patient decision-making about genetic testing. All participants described the eight concepts as either helpful or essential in their decision-making process. The cardiac knowledge scale is a promising measure created to evaluate the informed choice of patients and their families affected by an inherited heart condition. The next step of validation includes trialing the cardiac knowledge scale with a real-world sample of patients deciding about genetic testing for inherited heart disease.

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)0.078
metaresearch head score (Gemma)0.124
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.078
Threshold uncertainty score0.414

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0780.124
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.088
GPT teacher head0.375
Teacher spread0.287 · 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 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

Citations4
Published2024
Admission routes2
Has abstractyes

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