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Record W2989769862 · doi:10.3389/fgene.2019.01189

Informing Integration of Genomic Medicine Into Primary Care: An Assessment of Current Practice, Attitudes, and Desired Resources

2019· article· en· W2989769862 on OpenAlex
June Carroll, Judith Allanson, Shawna Morrison, Fiona A. Miller, Brenda J. Wilson, Joanne Permaul, Deanna Telner

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFrontiers in Genetics · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsMemorial University of NewfoundlandChildren's Hospital of Eastern OntarioUniversity of TorontoSinai Health System
Fundersnot available
KeywordsReferralGenetic testingGenetic counselingFamily medicineMedicineFamily historyMedical educationPsychologyGeneticsInternal medicineBiology

Abstract

fetched live from OpenAlex

Introduction: Preparing primary care providers (PCP) for genomic medicine (GM) first requires assessment of their educational needs in order to provide clear, purposeful direction and justify educational activities. More understanding is needed about PCPs’ perspectives on their role in newer areas of GM and what resources would be helpful in practice. Our objective was to determine family physicians’ (FP) current involvement and confidence in GM, attitudes regarding its clinical value, suggestions for integration of GM into practice and resources and education required. Methods: A self-complete anonymous questionnaire was mailed to a random sample of 2,000 FPs in Ontario, Canada. Response rate was 26% (361/1,365), mean age 51, 53% male. Results: FPs reported many aspects of traditional GM as part of current practice (eliciting family history: 93%; deciding who to refer to genetics: 94%; but few reported confidence (44%, 32% respectively). Newer areas of GM were not part of most FPs’ current practice and confidence was low (pharmacogenetics: 28% part of practice, 5% confident; direct-to-consumer genetic testing: 14%/2%; whole genome sequencing: 8%/2%). Attitudes were mixed with 59% agreeing that GM would improve patient health outcomes, 41% seeing benefits to genetic testing, but only 36% agreeing it was their responsibility to incorporate GM into practice. Few could identify useful sources of genetic information (22%) or find information about genetic tests (21%). Educational resources participants anticipated would be useful included contact information for local genetics clinics (89%), summaries of genetic disorders (86%) and genetic referral (85%) and testing (86%) criteria. About 58% were interested in learning about new genetic technologies. Most (76%) wanted to learn through in-person teaching (lectures, seminars etc.), 66% wanted contact with a local genetic counselor to answer questions and 59% were interested in a genetics education website. Conclusion: FPs lack confidence in GM skills needed for practice, particularly in emerging areas of GM. They see their role as making appropriate referrals, are somewhat optimistic about the contribution GM may make to patient care, but express caution about its current clinical benefits. There is a need for evidence-based educational resources integrated into primary care and improved communication with genetic specialists.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.439

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.331
Teacher spread0.319 · 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