The Effect of Direct-to-Consumer Genetic Tests on Anticipated Affect and Health-Seeking Behaviors: A Pilot Survey
Bibliographic record
Abstract
PURPOSE: Numerous websites offer direct-to-consumer (DTC) genetic testing, yet it is unknown how individuals will react to genetic risk profiles online. The objective of this study was to determine the feasibility of using a web-based survey and conjoint methods to elicit individuals' interpretations of genetic risk profiles by their anticipated worry/anxiousness and health-seeking behaviors. METHODS: A web-based survey was developed using conjoint methods. Each survey presented 12 hypothetical genetic risk profiles describing genetic test results for four diseases. Test results were characterized by the type of disease (eight diseases), individual risk (five levels), and research confidence (three levels). After each profile, four questions were asked regarding anticipated worry and health-seeking behaviors. Probabilities of response outcomes based on attribute levels were estimated from logistic regression models, adjusting for covariates. RESULTS: Overall, 319 participants (69%) completed 3828 unique genetic risk profiles. Across all profiles, most participants anticipated making doctor's appointments (63%), lifestyle changes (57%), and accessing screening (57%); 40% anticipated feeling more worried and anxious. Higher levels of disease risk were significantly associated with affirmative responses. CONCLUSION: Conjoint methods may be used to elicit reactions to genetic information online. Preliminary results suggest that genetic information may increase worry/anxiousness and health-seeking behaviors among consumers of DTC tests. Further research is planned to determine the appropriateness of these affects and behaviors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".