Effect of Self-Care Education by Face-to-Face Method on the Quality of Life in Hemodialysis Patients (Relying on Ferrans and Powers Questionnaire)
Bibliographic record
Abstract
INTRODUTION: One of the most common methods to control chronic renal failure, Hemodialysis creates numerous changes in the style and the quality of life in patients. Educating patients is one of effective factors to improve the quality of life. The present study aims to investigate influences of self-care education by face-to-face method on determining quality of life in hemodialysis patients in Jahrom, Iran, during 2014-2015. METHODS: This is a quasi-experimental, single-blind study in which 50 patients undergoing hemodialysis at Shahaid Mottahari Hospital, Jahrom. The patients were placed in two groups of 25 individuals: the face to face educational group and the control group. The control group received only routine care in hemodialysis unit. The face to face educational group received 8 instruction sessions of 60 minutes before starting dialysis and received an instruction booklet. Data collection tools were a questionnaire consisting of demographic characteristics, a checklist of needs assessment for hemodialysis patients and a quality of life questionnaire, whose reliability and validity were previously approved. The questionnaires were completed face to face, before and after the intervention. RESULTS: The results show that the research units did not have any significant difference in terms of demographic variables. Also increase in various aspects of the quality of life compared with the control group is observed after the intervention in the face to face educational group (p<0.001). DISCUSSION & CONCLUSION: Given the results, representation of adequate training in hemodialysis ward can cause improve in physical function, mental health and thus increase the quality of life in hemodialysis patients, through raising the awareness level.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".