An exploration of delegation practices regarding the utilization of genetic counseling assistants for disclosure of genetic testing results
Bibliographic record
Abstract
Genetic counselors (GCs) play a crucial role in the healthcare system, providing education, support and guidance regarding genetic risk assessment, testing and results interpretation. To help GCs practice at the highest level of their expertise, the role of the genetic counseling assistant (GCA) was introduced, focusing on tasks like administrative support and patient care coordination. Although GCs typically handle the disclosure of test results, there is limited research on the delegation of results disclosure to GCAs. This study explores GCs' perspectives on delegating negative and variant of uncertain significance (VUS) genetic test results disclosures to GCAs. A quantitative survey was conducted among GCs practicing in the United States and Canada. Results revealed that while the majority of GCs were willing to delegate both negative and VUS results, few currently do so. Oncology GCs exhibited greater willingness and actual delegation of VUS disclosures relative to other specialties. Effective communication skills, level of genetics knowledge, and willingness to seek help were identified as the most influential attributes on GCs' confidence in GCAs' abilities to disclose test results. The most frequent concern about GCAs disclosing negative and VUS results was remaining suspicion for an underlying genetic etiology. Additionally, GCs were concerned about delegating VUS disclosures since patients more frequently struggle to understand those results. A triaging system to determine suitable results for a GCA to disclose and extensive shadowing of GCs disclosing results were proposed as methods of building GCs' confidence in the ability of a GCA to disclose test results. Ultimately, a better understanding of the discrepancy between GCs' willingness to delegate results disclosures and actual delegation practices is essential if the GCA scope of practice were to include results disclosure.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".