Perception of illness by patients treated with haemodialysis
Bibliographic record
Abstract
Introduction: Perception of illness is the way in which a condition is perceived, which reflects the patient’s attitude towards illness and treatment. Aim: The aim of the research was to understand the perception of illness among patients treated with haemodialysis. The specific goal was to determine the factors affecting the perception of the illness and their interrelationships. Material and methods: The study included 98 people treated with haemodialysis as part of the international project “Health, coping, and quality of life in people with chronic kidney disease and in their families”. As research tools the following were used: the Barthel Index, Instrumental Activities of Daily Living Scale (IADL), Edmonton Symptom Assessment Scale – Revised (ESAS – R), and the Brief Illness Perception Questionnaire (Brief IPQ) Scoring Instructions. Results: The perception of illness in the study group was significantly influenced by the intensity of physical symptoms (p = 0.007), especially dyspnoea or fatigue. Whereas, the following areas of the perception of illness: Consequences, Treatment control, Timeline, Illness concern, and Comprehensibility were mainly affected by functional efficiency, age, and education level. A worse perception of illness was observed with the increase in IADL dependency, younger age, and lower education level. Conclusions: 1. Perception of illness in the study group was at a moderate level. 2. Perception of illness in the study group was most strongly influenced by the intensity of symptoms, especially dyspnoea and fatigue. 3. Functional efficiency, age, and education significantly affected the perception of illness.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".