Canadian health care professionals' knowledge, attitudes and perceptions of nutritional genomics
Bibliographic record
Abstract
Nutritional genomics has reached the public through applications of the Human Genome Project offered direct to consumers (DTC). The ability to pursue nutrigenetic testing without the involvement of a health care professional has received considerable attention from academic and policy commentators. To better understand the knowledge and attitudes of Canadian health care professionals regarding nutritional genomics and nutrigenetic testing, qualitative research in the form of focus group discussions was undertaken. Four key themes emerged: (1) concerns over DTC testing; (2) lack of health care professional competency; (3) genetic scepticism and inevitability; (4) expectation of regulation. Together, they indicate that health care professionals have little knowledge about nutritional genomics and hold contradictory attitudes towards genomics in general, and to nutritional genomics in particular. Respondents argue in favour of a delivery model where health care professionals act as intermediaries. They are also aware of their lack of competency to provide such services. To ensure greater public protection, respondents cite the importance of more stringent regulatory oversight of DTC genetic testing. Whether such an approach is necessary to address the various ethical and social issues raised by nutrigenetic testing remains an open debate.
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 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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".