The effects of educational intervention on self-care behavior and expected clinical outcome in patient undergoing liver transplantation
Bibliographic record
Abstract
Background: Organ transplantation has the potential to rapidly restore the health and wellbeing of individuals experiencing end stage liver disease (ESLD). The aim of the research was to evaluate effects of educational intervention on self-care behaviors and expected clinical outcome in patient undergoing liver transplantation.Methods: A convenience sample of 60 liver patients was assigned for transplantation. The study was conducted in the transplanted Unit in Ain Shams University Hospitals. A quasi-experimental design with pre-post and follow up assessment has been used for this study. Tools were utilized to collect data such a) Self-care practice assessment tool, b) Patient physiological assessment sheet, and c) Demographic and medical health history tool.Results: Improvement in knowledge and self-care behaviors at the post and follow-up tests (p < .0001) after implementation of program compared by pretest evaluation. There are significant improvements in blood pressure (BP) and laboratory results through study stage (p < .001). The pain level improved after intervention and follow up (p < .0001). There are statistically significant between age, job and self-care behaviors at follow up phase.Conclusions: Liver transplantation patients showed a positive improvement in their knowledge, self-care and physiological outcomes after implementing of program. Replication of the study on larger probability sample from different geographical areas to achieve more generalizable results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".