Australians’ perspectives on support around use of personal genomic testing: Findings from the Genioz study
Bibliographic record
Abstract
Personal genomic testing using direct-to-consumer and consumer-directed models, with or without involvement of healthcare providers, is increasing internationally, including in Australia. This study forms a sub-set of the Genioz study - Genomics: National Insights of Australians. We aimed to explore Australians' experiences with these types of tests, especially online DNA tests, and their views regarding whom they would seek support from around understanding test results. The study used a mixed methods approach, employing an exploratory quantitative online survey and follow-up qualitative semi-structured interviews. Between May 2016 and May 2017, 2841 Australians responded to the survey. Interviews were conducted with 63 purposively sampled respondents, including 45 who had a genetic test and 18 who had not. Of 571 respondents who had any type of genetic test, 322 had a personal genomic test using criteria defined by the researchers. Testing for ancestry/genealogy was the most common, reported by 267 participants, reflecting the increased advertising of these tests in Australia. Some respondents described downloading their raw data for further interpretation through third party websites for genealogical as well as health related information. Carrier testing, testing for serious and preventable conditions and nutrition and/or wellness were the most common health related tests reported by respondents. Participants generally preferred to seek support from general practitioners (GPs), medical specialists with relevant expertise and independent genetics specialists, although another important preference for non-health information was online forums and networks. There was less preference for seeking support from employees associated with the testing companies. Generally, of those who had a health related PGT, the most common actions were seeking medical advice or doing nothing with the information, while more of those who had a personal genomic test for nutrition and/or wellness sought advice from complementary/alternative health practitioners (eg naturopaths) and integrative GPs, and 60% reported they had changed their diet. As awareness of personal genomic testing increases, publicly funded clinical genetics services may be less inclined to discuss results from personal genomic testing. Genetic counsellors could play an important role in providing this support, both pre-test and post-test, through opportunities for private practice but independent from testing companies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".