Impact of the COVID-19 pandemic on Canadian transplant journeys: a mixed methods study
Bibliographic record
Abstract
Background Navigating the organ donation and transplantation system in Canada can be challenging for individuals on transplant journeys. Although it is likely that the COVID-19 pandemic has further contributed to these challenges, the experiences of individuals during the pandemic in Canada have not been well elicited. Objective To illuminate how the COVID-19 pandemic has impacted individuals on transplant journeys in Canada. Design Convergent parallel mixed-methods study. Setting Canada. Participants Adult patients, caregivers, and donors on transplant journeys across Canada. Data collection Eight focus groups and an online survey between May and November 2021. Focus group transcripts were analysed using an inductive conventional content analysis approach. Survey data were analysed using descriptive statistics. The study was guided by individuals with lived experience of organ donation and transplantation. Results A total of 830 participants completed three COVID-19 related survey questions, with 21 participating in the focus groups.Survey results: over 50% of patients and caregivers reported that the pandemic impacted their access to their healthcare team, their mental health (60% and 65%, respectively) and their comfort going out in public (80% and 75%, respectively). Although many donors reported several factors that impacted their transplant journey, the impact appeared to be greater for patients and caregivers.Qualitative results: three themes emerged from the qualitative data that contextualise participant’s experiences: compounding isolation, disruption amid uncertainty and unforeseen benefits. Conclusion The COVID-19 pandemic has exacerbated many of the challenges that individuals on transplant journeys experience. It will be critical for transplant programmes to consider these factors in future care provision.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".