Self-management of Elderly Patients with Osteoarthritic Knee on Recovery Outcomes
Bibliographic record
Abstract
Background: Knee osteoarthritis accounts for almost four fifths of the burden of worldwide. It is the leadingcause of mobility impairment, disability and loss of function in older adults. This study aimed to examine theeffectiveness of self-management of elderly patients with osteoarthritic knee on recovery outcomes.Material and methods: A quasi- experimental design was utilized to conduct this study. The study wascarried out at outpatient clinic of Shebin- Elkom University and Educational Hospital, and then they werefollowing up at their homes. 100 elderly patients were selected who met inclusion and exclusion criteria.Aconstructed interviewing questionnaire, arthritis self-efficacy scale, and Western Ontario and McMasterUniversities Osteoarthritis (WOMAC) index were used to collect the data.Results: there was increase in the mean total pain self-efficacy score, and other symptoms self-efficacyscore in study group than control group.There was decrease in the mean total physical function WOMACscore in study group than control group after intervention.Conclusion: Implementation of self-management for elderly patients was effective in managementsymptoms of knee osteoarthritis among study group compared to control group.
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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 | 0.000 |
| 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".