A Patient Engagement Council to Support Inclusion and Engagement of the Low German Mennonite Community in Clinical Trial Research and Design
Bibliographic record
Abstract
Background The Low German Mennonite (LGM) community originally migrated from Europe to Canada and now also has communities in Mexico and South America. Because of cultural isolation and practices of endogamy, there is known prevalence of specific genetic diseases in this population. One such disease is CD3δ severe combined immunodeficiency (SCID) caused by a founder C202T variant. Infants present with a complete lack of T cells and nonfunctional B cells, leading to early mortality if not treated with allogeneic hematopoietic cell transplant. Our research team is developing a gene editing clinical trial for CD3δ SCID. We have established an LGM Patient Engagement Council (PEC) to inform the design, development, and implementation of this trial to ensure results are more accessible and appropriate to the LGM community it aims to benefit. Methods After consulting with the Alberta SPOR SUPPORT Unit (AbSPORU) Patient Engagement Team, we connected with multiple groups working with the LGM and members of the community regarding participation in the PEC. Results The LGM PEC is a 12-member group comprised of community members, midwifery students, community health representatives/translators, and researchers. Terms of Reference were co-developed, online meetings are held once a month with additional opportunities for joining specific research training and working group opportunities, a presentation about LGM culture was shared through a teaching hospital, and focus groups in LGM language were held around Alberta. Compensation is offered to PEC members contributing lived experience. Conclusion The LGM PEC was successful in translating knowledge to the LGM community regarding research and consenting processes, creating trusting relationships, breaking down language barriers, and fostering mutual understanding. Future plans include the co-development of videos and podcasts in Low German to help further socialize health research engagement as well as co-development of an informed consent video for the upcoming CD3δ SCID gene therapy trial.
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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 | 0.370 | 0.439 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.006 | 0.025 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.038 | 0.013 |
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".