Post-Traumatic Growth among Patients after Living and Cadaveric Donor Kidney Transplantation: The Role of Resilience and Alexithymia
Bibliographic record
Abstract
The aim of this study was to determine the role of resilience and alexithymia in the post-traumatic growth as a response to extreme stress in patients after kidney transplantation and to determine whether there are differences in the level of posttraumatic growth in patients after living and cadaveric donor kidney transplantation. The relationships between these variables were also evaluated. The questionnaire survey of 91 kidney recipients took place in 2018 and 2019. The following tools were used: authorial post-transplant questionnaire for recipients and validated questionnaires, Post Traumatic Growth Inventory (PTGI-R), Resilience Coping Scale Questionnaire, and Toronto Alexithymia Scale Questionnaire (TAS20). The results obtained showed significant differences between the group of kidney recipients from living donors and recipients from cadaveric donors, in terms of overall post-traumatic growth, as well as changes in self-perception and a greater appreciation for life. Post-traumatic growth in both groups was related to the level of resilience and the level of alexithymia. Resilience is an accurate predictor of posttraumatic growth in general and for each of the groups of recipients separately.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".