Challenges of End-Stage Renal Disease Patients in Ethiopia
Bibliographic record
Abstract
Affecting all aspects of patients' lives, end-stage renal disease (ESRD) presents significant challenges. Individuals with ESRD face biological, psychological, economic, and social issues. ESRD patients in Ethiopia bear multifaceted burdens of multiple medical conditions, including comorbid hypertension, diabetes, cardiac problems, anemia, gastrointestinal issues, and bone and mineral disorders. The aim of this study was to address the gap in research on patients in Ethiopia with ESRD and examine biopsychosocial and economic challenges. A qualitative hermeneutic phenomenology design was employed. In-depth interviews were held with 10 women and 10 men. Major themes include the physical corollary of ESRD (e.g., fatigue), and psychological (e.g., fear of loss of capacity and/or occupation) and socioeconomic challenges (e.g., difficulty obtaining social and economic support). Along with complications of ESRD and side effects of dialysis, patients face trauma and social and economic repercussions. Social workers are well positioned to help manage associated biopsychosocial and economic challenges. The findings indicate the need for policies that promote multidisciplinary teams in working with patients who are diagnosed with ESRD.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".