Joint Protection Programmes for People with Osteoarthritis and Rheumatoid Arthritis of the Hand: An Overview of Systematic Reviews
Bibliographic record
Abstract
Purpose: Joint protection has been introduced as a self-management strategy for people with rheumatoid arthritis (RA) and osteoarthritis (OA) of the hand. The purpose of this study was to conduct an overview of systematic reviews (SRs) and critically appraise the evidence to establish the current effectiveness of joint protection for people with hand RA and OA. Method: A comprehensive search was conducted of six databases from January 2008 to May 2018. SRs that evaluated the effectiveness of joint protection for people with hand arthritis were eligible for inclusion. The A MeaSurement Tool to Assess systematic Reviews (AMSTAR) 2 checklist was used to assess the methodological quality of each SR. Results: Nine SRs were included: two were rated as high quality, and seven were rated as low quality. Seven of the nine did not take into account risk of bias when interpreting or discussing their findings, six did not assess publication bias, and five did not register their protocol. The high-quality reviews found no clinically important benefit of joint protection for pain, hand function, and grip strength levels. The low-quality reviews reported improvements in function, pain, grip strength, fatigue, depression, self-efficacy, joint protection behaviours, and disease symptoms in people with RA. Conclusions: High-quality evidence from high-quality reviews found a lack of any clinically important benefit of joint protection programmes for pain, hand function, and grip strength outcomes, whereas low-quality evidence from low-quality reviews found improvements in these outcomes.
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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 | 0.021 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".