Genetics Adviser: The development and usability testing of a new patient digital health application to support clinical genomic testing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: Increasing demand for genomic testing coupled with genetics workforce shortages has placed unsustainable pressure on standard models of care. Digital tools can offer improved access, efficiency, and cost savings. We created a patient-facing digital health application to support genomic testing. Methods: We developed the digital application through user-centered design, guided by an advisory board. We tested its usability and acceptability with patients, practitioners, and members of the general public using mixed methods; data were analyzed using qualitative description and descriptive statistics. Results: The "Genetics Adviser" delivers pre-test education, counseling, and post-test return of results adaptable to any population, test platform, and setting. Usability testing with 25 patients, the general public, and genetics practitioners (15/25 female; mean age range 40-49 years) demonstrated enthusiasm about the application; users found it easy to navigate and comprehend. Acceptance testing with 19 patients and the public (13/19 female; mean age range 40-49 years) indicated high acceptability of the application and moderate knowledge of genomic sequencing after use. Conclusion: The Genetics Adviser is a comprehensive, interactive, patient-centered application found to have high acceptability and usability for pre- and post-test genomic testing, counseling, and return of results adaptable for multiple testing platforms, populations, and settings.
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.
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 | 0.001 |
| 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 it