Effect of Occupational Therapy in Patients Receiving Hemodialysis: A Randomized Controlled Study
Bibliographic record
Abstract
Objective: Hemodialysis (HD) treatment may have negative effects on the occupational performance and quality of life of individuals. This study was planned to investigate the effect of client-centered occupational therapy (OT) intervention on occupational performance and quality of life in individuals receiving HD. Materials and Methods: In total, 42 randomly assigned individuals were divided into control (awareness training) and intervention (awareness training and client-centered OT) groups. The Canadian Occupational Performance Measure was utilized to evaluate the occupational performance, and Kidney Disease Quality of Life Short Form was used to assess the quality of life. Results: Improvement in both occupational performance and quality of life was determined in the intervention group after 8 weeks. In the control group, only the improvement was determined in the general health parameter of quality of life (p<0.05). Conclusion: OT interventions can contribute to improving occupational performance and quality of life of individuals receiving HD treatment, and these interventions can play an important role in the treatment process of these individuals. Cite this article as: İnal Ö, Kayıhan H, Karahan S, Üstündağ S. Effect of Occupational Therapy in Patients Receiving Hemodialysis: A Randomized Controlled Study. Turk J Nephrol 2021; 30(1): 63-9.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".