Adapting a Self-Management Tool (My Kidneys My Health) to Meet the Needs of Diverse Canadian Populations: Program Report
Bibliographic record
Abstract
Purpose of Program: Our team co-developed My Kidneys My Health , an online platform designed with patients with non-dialysis-dependent chronic kidney disease and care partners to provide tailored education and self-management support. While My Kidneys My Health has seen increased use and positive user feedback since its development and launch in 2021, there are opportunities to improve its cultural relevance, accessibility, and usefulness for diverse populations. In this report, we describe our approach to addressing these elements by adapting My Kidneys My Health content and knowledge mobilization strategies. Sources of Information: Patients and care partners in Canada have identified the lack of accessible, person-centered resources as a major barrier to effective self-management for non-dialysis-dependent chronic kidney disease. Digital heath tools can meet this need by delivering consistent, evidence-based education and support in a user-friendly format. Through our program of research with Canadians Seeking Solutions and Innovations to Overcome Chronic Kidney Disease (Can-SOLVE CKD), we have co-developed My Kidneys My Health through a series of patient-oriented research studies. Methods: Our program objectives are to (1) understand and address gaps in sexual health support for individuals with non-dialysis-dependent chronic kidney disease; (2) build relationships with Indigenous communities in Alberta to understand and share self-management learnings; and (3) improve accessibility to My Kidneys My Health content for diverse populations. To guide the adaptation and implementation of My Kidneys My Health , our team adopted the following Can-SOLVE CKD phase 2 pillars: (1) Implementation Science and Knowledge Mobilization, (2) Indigenous Cultural Competency, (3) Incorporation of Equity, Diversity, and Inclusion principles in Knowledge Mobilization and Implementation Efforts, and (4) Patient Engagement and Capacity Building. We used the Can-SOLVE CKD Pathway to Implementation and applied the Map2Adapt framework. Key Findings: Primary care and nephrology providers expressed readiness to integrate My Kidneys My Health into clinical workflows, and collaborative partnerships with initiatives like Kidney Check enhanced knowledge sharing. We initiated relationship building with the Stoney Nakoda Tsuut’ina Tribal Council Ltd. Health Department (G4 Health), including in-person meetings with the health directors, and co-development of engagement packages and communications designed to reflect our culturally safe methodologies. We addressed accessibility barriers by updating website features and new printable materials on key self-management topics, with French translations. Results from our mixed methods sexual health study underscored the need for tailored, credible resources for people with non-dialysis-dependent chronic kidney disease. Findings from our ongoing environmental scan will inform a sexual health resource inventory for integration into My Kidneys My Health . Patient partners reported meaningful involvement that shaped project priorities, design, and knowledge mobilization. Limitations: Significant time and resources are required to support meaningful Indigenous engagement, which contributed to delays in the project timeline. In Alberta, we have had ongoing healthcare restructuring disrupting relationship building with key decision-makers and creating uncertainty around partner roles. Finally, a permanent solution to accommodate and maintain My Kidneys My Health will be needed after the research is completed. Implications: Our work exemplifies an integrated, patient-oriented approach that emphasizes implementation science, equity, cultural competency, and capacity-building. As we move forward, our focus will remain on enhancing accessibility, relevance, and sustainability to ensure that all people living with non-dialysis-dependent chronic kidney disease can access trusted, evidence-based support to live well with kidney disease.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".