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Record W2799719141 · doi:10.1038/s41431-018-0151-1

Australians’ views on personal genomic testing: focus group findings from the Genioz study

2018· article· en· W2799719141 on OpenAlexaff
Sylvia A. Metcalfe, Chriselle Hickerton, Jacqueline Savard, Bronwyn Terrill, Erin Turbitt, Clara Gaff, Kathleen Gray, Anna Middleton, Brenda J. Wilson, Ainsley J. Newson

Bibliographic record

VenueEuropean Journal of Human Genetics · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of Ottawa
FundersAustralian Research CouncilState Government of VictoriaUniversity of SydneySydney Medical SchoolWellcome Trust
KeywordsGeneticsPersonal genomicsGroup (periodic table)Focus groupFocus (optics)Genetic testingBiologyPsychologyComputational biologyGenomicsSociologyGenomeGeneAnthropology

Abstract

fetched live from OpenAlex

Personal genomic testing provides healthy individuals with access to information about their genetic makeup for purposes including ancestry, paternity, sporting ability and health. Such tests are available commercially and globally, with accessibility expected to continue to grow, including in Australia; yet little is known of the views/expectations of Australians. Focus groups were conducted within a multi-stage, cross-disciplinary project (Genioz) to explore this. In mid-2015, 56 members of the public participated in seven focus groups, allocated into three age groups: 18-24, 25-49, and ≥50 years. Three researchers coded transcripts independently and generated themes. Awareness of personal genomic testing was low, but most could deduce what "personal genomics" might entail. Very few had heard of the term "direct-to-consumer" testing, which has implications for organisations developing information to support individuals in their decision-making. Participants' understanding of genetics was varied and drawn from several sources. There were diverse perceptions of the relative influence of genetics and environment on health, mental health, behavior, talent, or personality. Views about having a personal genomic test were mixed, with greater interest in health-related tests if they believed there was a reason for doing so. However, many expressed scepticisms about the types of tests available, and how the information might be used; concerns were also raised about privacy and the potential for discrimination. These exploratory findings inform subsequent stages of the Genioz study, thereby contributing to strategies of supporting Australians to understand and make meaningful and well-considered decisions about the benefits, harms, and implications of personal genomic tests.

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)0.020
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.026
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0090.006
Scholarly communication0.0030.003
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.308
Teacher spread0.238 · 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 designQualitative
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

Citations22
Published2018
Admission routes1
Has abstractyes

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