Determination of Activities of Daily Living Problems in Patients with Lateral Epicondylitis and Investigation of the Relationship between Pain and Perceived Occupational Performance and Satisfaction
Bibliographic record
Abstract
Aim: Lateral epicondylitis is one of the most common diseases in the upper extremity that causes pain in the elbow, negatively affects activities of daily living. This study was planned to determine the activities of daily living in adults with lateral epicondylitis and to examine the relationship between pain and perceived occupational performance and satisfaction in activities of daily living. Materials and methods: A total of 56 individuals with a diagnosis of lateral epicondylitis, 17 males and 39 females, with a mean age of 52,18±5,92 years, completed the study. Visual Analogue Scale (VAS) was used to evaluate pain, and Canadian Occupational Performance Measure (COPM) was used to determine perceived occupational performance and satisfaction level. Results: According to the VAS, the mean pain at rest of the participants was 2,40±0,72, and the mean of pain during activity was 6,14±1,11. According to COPM, the perceived occupational performance mean of the participants in activities of daily living was 4,13±1,04 and the mean satisfaction was 4,07±1,17. When the correlation between pain and activities of daily living was examined, there was no correlation between pain at rest and perceived occupational performance (r=-0,015, p=0,911) and satisfaction (r=-0,064, p=0,639). A moderately strong negative was found between pain during activity and perceived occupational performance (r=-0,729, p
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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 | 0.001 | 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 | 0.000 |
| 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".