Experiences of living kidney donors: A synthesis of unsolicited patient narratives
Bibliographic record
Abstract
INTRODUCTION: Despite the lauded benefits of living kidney donation, there is growing evidence of the challenges that living kidney donors (LKD) encounter in their donation trajectory and gaps in healthcare service provision. However, most of the evidence is derived from research conducted by clinicians or academic investigators. Significantly less attention has been devoted to analyzing unsolicited accounts of LKDs' experiences. METHODS: We conducted a review and synthesis of published unsolicited first-person narratives of LKDs and aimed to synthesize their experiences and identify care needs. Four electronic databases were searched and 27 LKD narratives were included in our final analysis. Thematic synthesis was used to generate themes inductively. RESULTS: Although the majority of LKDs reported the act of donation to be a fulfilling experience, almost 48% reported encountering challenges in the care that they received. Also, 29% of LKDs reported experiencing an adverse clinical event. Five distinct themes emerged surrounding the donation experience and healthcare needs: 1) Educational needs due to perceived lack of transparency and compensating for knowledge gaps; 2) Respect for donor autonomy due to coercive influences from family or healthcare providers, lack of respect for donor preferences and loopholes in the consent process; 3) Unmet care needs related to poor communication with healthcare providers, coordination issues and inconsistent and inadequate long-term care; 4) Unanticipated outcomes due to economic costs and the emotional burden of donation; and 5) Contributing beyond the donation event by advocating for a balanced view of donation and generating support mechanisms. CONCLUSION: In this synthesis of LKDs narratives, important care gaps and the need to advocate for a balanced perspective on living kidney donation were highlighted. Our review underscores the value of patients' own stories as critical evidence that can inform improvement in healthcare service delivery.
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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 | 0.030 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".