Consumer Perspectives on Access to Direct‐to‐Consumer Genetic Testing: Role of Demographic Factors and the Testing Experience
Bibliographic record
Abstract
Policy Points: The policy context of direct‐to‐consumer personal genomic testing (DTC‐PGT) has been evolving over the last decade, with little empirical data available about consumers’ perspectives. A majority of consumers of DTC‐PGT supported expanded access to services and their integration into the medical context and opposed more governmental regulation. Consumers’ attitudes about access to services and regulation did not vary based on the specific genetic risk information they received from companies, but may vary based on whether consumers perceived their DTC experience negatively. Context While policymakers have been considering the appropriateness of direct‐to‐consumer personal genomic testing (DTC‐PGT) for more than a decade, there is little empirical data on consumers’ views regarding the regulation of these products. No research has assessed whether consumers’ personal experience with testing is related to their views about access to and regulation of DTC tests. Methods Data were analyzed from the PGen Study, a longitudinal prospective cohort of DTC‐PGT customers of 23andMe (n = 564) and Pathway Genomics (n = 377; total N = 941). Consumers were sent an electronic survey before receiving genetic test results and again 6 months after receipt of results. Findings At the 6‐month follow‐up, more than 80% of participants believed that people have a right to access genetic information directly, that parents should be able to get DTC‐PGT testing for their children, and that genetic information should be kept private. Participants supported health insurance coverage of PGT (60%), wider availability of PGT (68%), and inclusion of genetic information in medical records (63%). Participants were less supportive of government regulation (28%) and restricting testing to clinical settings (14%). Conservative political ideology was associated with less support for government regulation (P < 0.001), as was feeling more confident in one's genetic knowledge (P < 0.05). Participants’ level of computed genetic risk for common diseases, as indicated by their actual test results received from companies, showed no relationship with attitudes. However, those who perceived that they had received elevated risk results expressed lower support for expanded availability and incorporation of PGT into health care (P < 0.01). Those who reported being upset by their genetic test results were less likely to endorse access to DTC products without a medical professional (P < 0.01). Conclusions PGT consumers supported expanded access to these services and opposed additional regulation. Users who had a negative personal experience with PGT testing were less supportive of expanded availability without a medical professional.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".