The Conversion to Telegenetics Through the COVID-19 Pandemic Impact on the Accessibility to Genetic Counseling for Remote Indigenous Communities
Bibliographic record
Abstract
Indigenous populations in Canada, particularly those in remote locations, have historically been and continue to be underserved in health care services for multiple reasons, including but not limited to, accessibility due to the distance these remote communities are relative to their nearest healthcare centers and systematic racism. In addition to general health care services, remote Indigenous populations in Canada also have limited access to genetic counseling services. During the COVID-19 pandemic, many health care services in Canada pivoted to remote models to limit patient-provider exposure. Genetic counseling services were included in this switch, with many appointments transitioning into phone or web-based (telegenetics) appointment styles. This study surveyed 44 Canadian genetic counselors on their experiences during the pandemic and how this switch to remote counseling affected access to remote Indigenous patients. The majority of respondents identified travel costs, internet access, privacy concerns, culture, language, and health/genetic literacy as access barriers before the pandemic. Distance and the associated travel time/cost to genetic counseling appointments were identified as the greatest barrier by our participants, and the remote telegenetics model was expected to alleviate travel time and cost. Many respondents are doubtful that other identified barriers, including healthcare access and systemic discrimination, will be alleviated solely by offering telegenetics appointments. The next steps for the Canadian genetic counseling community are to work to address accessibility issues to healthcare and infrastructure (i.e.internet, clinical space) in general for remote Indigenous populations, and work to improve relationships between communities. Future research should include surveying remote Indigenous patients and Indigenous community leaders directly to design the next steps to improve access to health care services including genetic counseling.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.012 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".