The Effect of Frailty on Quality of Life in Older Patients Receiving Hemodialysis and Associations With Fear of Falling
Bibliographic record
Abstract
PURPOSE: This study investigated the effect of frailty and avoidance behavior due to fear of falling on the quality of life in older patients receiving hemodialysis treatment. METHODS: This study is cross-sectional and descriptive. The study was conducted between January 2 and 31, 2022, with 154 individuals aged 65 years and over receiving treatment in dialysis centers. The study data were collected using the Patient Information Form, Edmonton Frail Scale, Fear of Falling Avoidance-Behavior Questionnaire, and Quality of Life Scale (SF-12). RESULTS: The Mean Edmonton Frail Scale score was found to be 8.7 ± 3.36, the mean Fear of Falling Avoidance-Behavior Questionnaire score was found to be 33.17 ± 9.11, the mean SF-12 physical component score was found to be 34.32 ± 8.51, and the mean mental component score was seen as 41.77 ± 8.35. The Fear of Falling Avoidance-Behavior Questionnaire was an associated factor in the effect of the Edmonton Frail Scale on quality of life. It strengthened the negative impact of the Edmonton Frail Scale on quality of life. The predictive effect of these two variables in explaining quality of life was 59.3%. CONCLUSION: It was found that the participants had moderate levels of frailty, moderate levels of activity limitation, and participation restriction due to fear of falling, and low levels of physical and mental quality of life. It was determined that frailty had a direct impact on quality of life. Also, the indirect effect of frailty on quality of life was determined through the role of avoidance behavior due to fear of falling.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".