Hubungan Osteoarthitis dengan Risiko Jatuh pada Lansia
Bibliographic record
Abstract
Osteoarthritis adalah jenis arthritis yang paling sering terjadi pada lansia berusia 60 tahun yang dapat menimbulkan nyeri persendian di tangan, leher, punggung, pinggang, dan sendi lutut. Penelitian ini bertujuan untuk mengetahui hubungan osteoarthritis dengan risiko jatuh pada lansia. Penelitian ini menggunakan desain penelitian deskriptif korelasi dengan pendekatan cross sectional. Sampel penelitian adalah 105 orang responden yang diambil berdasarkan kriteria inklusi menggunakan metode purposive sampling. Analisis yang digunakan analisis univariat untuk melihat distribusi frekuensi dan bivariat menggunakan uji Chi-Square. Alat pengumpulan data yang digunakan adalah kuesioner Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) dan Stopping Elderly Accident, Death, and Injuries (STEADI) yang sudah dilakukan uji validitas dan reliabilitas. Hasil penelitian ini menunjukkan bahwa mayoritas responden mengalami osteoarthritis berat sebanyak 46 orang (43,8%) dan mayoritas responden beresiko jatuh sebanyak 74 orang (70,5%). Hasil penelitian ini menunjukkan adanya hubungan antara osteoarthritis dan risiko jatuh pada lansia di Puskesmas Rejosari dengan p-value (0,002) α (0,05).
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".