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Record W4402249855 · doi:10.1136/bmjopen-2024-090084

Genetics Navigator: protocol for a mixed methods randomized controlled trial evaluating a digital platform to deliver genomic services in Canadian pediatric and adult populations

2024· article· en· W4402249855 on OpenAlexafffundabout
Guylaine D’Amours, Marc Clausen, Stephanie Luca, Emma Reble, Rita Kodida, Daniel Assamad, François P. Bernier, Lauren Chad, Gregory Costain, Irfan A. Dhalla, Hanna Faghfoury, Jan M. Friedman, Stacy Hewson, Trevor Jamieson, Josh Silver, Cheryl Shuman, Matthew Osmond, June Carroll, Rebekah Jobling, Anne‐Marie Laberge, Melyssa Aronson, Eriskay Liston, Jordan Lerner‐Ellis, Christian R. Marshall, Michael Brudno, Quỳnh Phạm, Frank Rudzicz, Ronald D. Cohn, Muhammad Mamdani, Maureen Smith, Serena Shastri-Estrada, Emily Seto, Kevin E. Thorpe, Wendy J. Ungar, Robin Z. Hayeems, Yvonne Bombard

Bibliographic record

VenueBMJ Open · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsPublic Health OntarioVector InstituteToronto General HospitalStructural Genomics ConsortiumMount Sinai HospitalDalhousie UniversityCentre Hospitalier Universitaire Sainte-JustineChildren's Hospital of Eastern OntarioInstitute for Clinical Evaluative SciencesUniversity of OttawaSinai Health SystemToronto Rehabilitation InstituteAlberta Children's HospitalUniversity Health NetworkUniversity of TorontoSickKids FoundationUniversity of British ColumbiaUniversité de MontréalHospital for Sick ChildrenSt. Michael's Hospital
FundersInstitute of Health Services and Policy ResearchFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsMedicineMedical geneticsGenetic counselingHealth careRandomized controlled trialTest (biology)Genetic testingFamily medicineEmpowermentNursing

Abstract

fetched live from OpenAlex

INTRODUCTION: Genetic testing is used across medical disciplines leading to unprecedented demand for genetic services. This has resulted in excessive waitlists and unsustainable pressure on the standard model of genetic healthcare. Alternative models are needed; e-health tools represent scalable and evidence-based solution. We aim to evaluate the effectiveness of the Genetics Navigator, an interactive patient-centred digital platform that supports the collection of medical and family history, provision of pregenetic and postgenetic counselling and return of genetic testing results across paediatric and adult settings. METHODS AND ANALYSIS: We will evaluate the effectiveness of the Genetics Navigator combined with usual care by a genetics clinician (physician or counsellor) to usual care alone in a randomised controlled trial. One hundred and thirty participants (adults patients or parents of paediatric patients) eligible for genetic testing through standard of care will be recruited across Ontario genetics clinics. Participants randomised into the intervention arm will use the Genetics Navigator for pretest and post-test genetic counselling and results disclosure in conjunction with their clinician. Participants randomised into the control arm will receive usual care, that is, clinician-delivered pretest and post-test genetic counselling, and results disclosure. The primary outcome is participant distress 2 weeks after test results disclosure. Secondary outcomes include knowledge, decisional conflict, anxiety, empowerment, quality of life, satisfaction, acceptability, digital health literacy and health resource use. Quantitative data will be analysed using statistical hypothesis tests and regression models. A subset of participants will be interviewed to explore user experience; data will be analysed using interpretive description. A cost-effectiveness analysis will examine the incremental cost of the Navigator compared with usual care per unit reduction in distress or unit improvement in quality of life from public payer and societal perspectives. ETHICS AND DISSEMINATION: This study was approved by Clinical Trials Ontario. Results will be shared through stakeholder workshops, national and international conferences and peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT06455384.

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)0.045
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.989
Threshold uncertainty score0.304

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.050
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0110.006
Bibliometrics0.0040.005
Science and technology studies0.0040.004
Scholarly communication0.0060.004
Open science0.0040.002
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0910.010

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 head0.072
GPT teacher head0.487
Teacher spread0.415 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations2
Published2024
Admission routes3
Has abstractyes

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