A systematic review on the effects of non-pharmacological interventions for fatigue among people with upper and/or lower limb osteoarthritis
Bibliographic record
Abstract
Objectives: To identify non-pharmacological fatigue interventions and determine the effectiveness of these non-pharmacological interventions in reducing fatigue immediately and over time in OA. Methods: A review protocol (CRD42020163730) was developed and registered with the PROSPERO database. Included studies comprised peer-reviewed randomized controlled trials (RCTs) that examined the effects of conservative interventions on fatigue in people with upper and lower limb OA. Cochrane Collaboration's tool for assessing the risk of bias (ROB-2) was used to assess the quality of evidence of studies. Narrative synthesis was used to summarize the effectiveness of identified fatigue interventions. Results: Out of 2644 citations identified from databases, 32 reports were included after screening for titles, abstracts and full texts. Of these reports, 30 parallel RCTs, one cluster and one cross-over RCT were included. 13 RCTs were of low ROB, 6 had some concerns and 13 had high ROB. The narrative synthesis identified interventions for fatigue including exercise, activity pacing, cognitive behavioural therapy, telerehabilitation and complementary alternative therapies. Exercise interventions showed the most significant beneficial effects on fatigue. Conclusions: Diverse interventions for fatigue management among individuals with upper and lower limb OA were identified. Of these, exercise interventions appear to be the most promising with the majority of these interventions favouring fatigue improvement. While cognitive behavioural therapy has limited evidence of beneficial effects, there is insufficient evidence regarding the effectiveness of other identified interventions, including complementary and alternative therapies, and telerehabilitation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".