Alat ukur untuk menilai kemampuan fungsional pasien dengan osteoartritis lutut: tinjauan pustaka
Bibliographic record
Abstract
Background: Osteoarthritis is a common disease that has become one of the main causes of disability and is ranked fourth as a contributing factor of disability. In Indonesia, many healthcare professionals, including physiotherapists, treat patients with various stages of osteoarthritis. Physiotherapists have a crucial role in improving the functional ability of patients with knee osteoarthritis. However, many of them do not use appropriate outcome measures to document patients’ improvements.Objective: This literature review aimed to summarize the available outcome measures that can be used to measure the functional ability of patients with knee osteoarthritis, in order to increase the awareness and knowledge of healthcare professionals, particularly physiotherapists, regarding the use of available outcome measures.Methods: The method used was literature review. Literature search was conducted in PubMed and Google Scholar databases using the main keywords: “outcome measure”, “scale”, “questionnaire”, “knee”, “osteoarthritis”, “functional ability”, “validity” and “reliability”.Result: This review identified 7 outcome measures in the form of questionnaires that can be used to measure the functional ability of patients with knee osteoarthritis. The most commonly used measure is the Western Ontario and McMaster University osteoarthritis index, which has been translated and validated in various languages. All measuring instruments were established in developed countries, except for the Ibadan Knee Osteoarthritis Outcome Measure. None of the 7 outcome measures have been translated and validated into Indonesian.Conclusion: This literature review has summarized measuring tools that can be used to measure the functional ability of patients with knee osteoarthritis. To date, no tools have been translated and validated into Indonesian. In the future, it is hoped that further research can be conducted in the form of cross-cultural adaptations studies on the validity and reliability of these outcome measures into Indonesian to support the effectiveness of using these measures to assess the functional ability of patients with knee osteoarthritis. Latar belakang: Osteoartritis merupakan penyakit umum yang menjadi salah satu penyebab utama kecacatandan menempati urutan keempat untuk faktor penyebab kecacatan. Di Indonesia, banyak tenaga kesehatan, termasuk fisioterapis, yang merawat pasien dengan bebagai stadium osteoartritis. Fisioterapis sangat berperan dalam meningkatkan aspek fungsional pasien dengan osteoartritis lutut. Namun, banyak yang masih belum menggunakan alat ukur yang sesuai untuk mendokumentasikan kemajuan pasien.Tujuan: Tujuan tinjauan pustaka ini adalah untuk merangkum alat ukur yang dapat digunakan untuk mengukur kemampuan fungsional pasien dengan osteoartritis lutut, guna meningkatkan pengetahuan dan kesadaran tenaga kesehatan, terutama fisioterapis, dalam penggunaan alat ukur yang tersedia.Metode: Metode penelitian yang digunakan adalah tinjauan pustaka. Penelusuran artikel dilakukan pada database PubMed dan Google Scholar dengan kata kunci utama: “outcome measure”, “scale”, “questionnaire”, “knee”, “osteoarthritis”, “validity” dan “reliability”. Hasil: Tinjauan pustaka ini menemukan 7 alat ukur dalam bentuk kuisioner yang dapat digunakan untuk mengukur kemampuan fungsional pasien dengan osteoartritis lutut. Alat ukur yang paling sering digunakan adalah Western Ontario and McMaster University osteoarthritis index, yang sudah diterjemahkan dan divalidasi ke dalam berbagai bahasa. Semua instrumen pengukuran dibuat oleh negara maju, kecuali Ibadan Knee Osteoarthritis Outcome Measure. Dari 7 kuisioner, belum ada yang diterjemahkan dan divalidasi ke dalam Bahasa Indonesia.Kesimpulan: Tinjauan pustaka ini telah merangkum alat ukur yang dapat digunakan untuk mengukur kemampuan fungsional pasien dengan osteoartritis lutut. Sampai saat ini, belum ada kuisioner yang sudah diterjemahkan dan divalidasi ke dalam bahasa Indonesia. Diharapkan adanya pengembangan penelitian berupa studi adaptasi lintas budaya terhadap validitas dan realibilitas kuisioner lainnya ke dalam bahasa Indonesia untuk menunjang efektivitas penggunaan alat ukur dalam menilai kemampuan fungsional pasien dengan osteoartritis lutut.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".