Perbedaan Efektivitas Latihan Core dengan Swissball dan Resistance Band terhadap Peningkatan Endurance Otot Core Remaja Obesitas
Bibliographic record
Abstract
Latar belakang : Otot core berperan penting dalam aktivitas sehari-hari. Individu yang mengalami obesitas cenderung memiliki endurance otot core yang rendah. Remaja adalah masa dimana seseorang banyak melakukan aktivitas fisik seperti naik turun tangga di sekolah dan masa kritis pertumbuhan untuk menjdi dewasa. Remaja obesitas dengan endurance otot core yang rendah berisiko mengalami cedera otot saat aktivitas atau nyeri punggung bawah pada jangka panjang. Endurance otot core dapat ditingkatkan dengan latihan core menggunakan swissball atau resistance band. Tujuan : membuktikan perbedaan efektivitas latihan core dengan swissball dan resistance band terhadap endurance otot core remaja obesitas. Metode : Penelitian ini merupakan randomized controlled trial. Sebanyak 36 remaja obesitas yang memenuhi kriteria inklusi dan eksklusi dirandomisasi dan dibagi kedalam dua kelompok latihan core dengan swissball (n=18) dan resistance band (n=18). Kelompok latihan core dengan swissball dan resistance band masing-masing menjalani latihan selama 6 minggu dengan frekuensi 3 kali per minggu, dengan durasi latihan 40 menit tiap sesi. Endurance otot core dinilai dengan McGill Core Endurance test. Kesimpulan : Latihan core dengan resistance band dapat meningkatkan endurance otot core remaja obesitas lebih tinggi dibandingakan dengan latihan core dengan menggunakan swissball.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".