The psychological well‐being of renal peer support volunteers
Bibliographic record
Abstract
AIM OF THE STUDY: The purpose of this study was to describe the characteristics of renal peer support volunteers (PSVs) and explore the effects on their psychological well-being from helping others. BACKGROUND: Dialysis patients, transplant patients and family members who become renal PSVs receive special training in empathy, listening, self-awareness and problem solving. The trained renal PSVs offer a unique service to others struggling to learn to live with renal failure because they have faced the same struggles. METHODS: This exploratory study utilized a longitudinal design. The first time for data collection was immediately after the volunteers had completed a Kidney Foundation of Canada training programme. Subsequent interviews were at time intervals of 4, 8 and 12 months after the first interview. Information on the psychological well-being of the volunteers was collected at each interview in two different ways: the 38-item Mental Health Inventory (MHI) and open-ended questions. FINDINGS: Thirty-one PSVs completed all four interviews. The average age of the volunteers was 45 years and almost half had a university level of education. They identified themselves as belonging to 12 different ethno-cultural groups. Analysis of the quantitative data from the MHI indicated that the mental health of the PSVs stayed remarkably stable over time. Analysis of the qualitative data from the open-ended questions revealed four major themes which, taken together, showed notable increases in personal growth and well-being for the PSVs over time. CONCLUSION: After participating in a training programme, renal PSVs maintained, and possibly improved, their own well-being by helping others with chronic renal failure.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".