Strength and Aerobic Exercise for the Treatment of Osteoarthritis Symptoms
Bibliographic record
Abstract
Background: Arthritis is a prevalent joint disease characterized by joint inflammation. Osteoarthritis is the most common form of arthritis which causes progressive cartilage breakdown at the ends of bones and may affect surrounding ligaments, menisci and muscles. Osteoarthritis puts individuals at an increased risk of developing comorbid conditions. The use of exercise is growing as a low-risk treatment for symptoms of osteoarthritis. Purpose: The purpose of this narrative review is to examine how strength and aerobic exercise interventions can be used for the management of osteoarthritis symptoms. Methodology: A literature search was conducted utilizing PubMed, Medline, Google Scholar, and UBC Library. Selected literature included quasi-experimental studies, randomized-controlled trials, systematic reviews, narrative reviews, and exercise guidelines. Results: The literature indicates that strength exercise is beneficial to symptom management and physical function among individuals with osteoarthritis. Research specific to quadriceps strengthening showed significant improvements in physical performance, walking self-efficacy, and pain. While aerobic exercise plays a vital role in overall well-being, it also is shown to be as effective as strength exercise for symptom management and physical function. Conclusion: Evidence suggests that strength and aerobic exercise can enhance the quality of life among individuals with osteoarthritis. Greater dissemination of evidence is needed to increase awareness of strength and aerobic exercise as a valuable treatment option for osteoarthritis. Further research is required to determine optimal exercise parameters prescribed for individuals with osteoarthritis. Health & Fitness Journal of Canada 2019;XXX(X):X-XX. https://doi.org/10.14288/hfjc.XXX.XXX Keywords: Physical Activity, Quadricep Strengthening, Exercise Prescription, Randomized-Controlled Trial, Systematic Review, Medications
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".