Work in the picture? The reporting of and effects on work outcomes in exercise therapy trials in people with rheumatoid arthritis or axial spondyloarthritis: a systematic review
Bibliographic record
Abstract
OBJECTIVE: Many people with rheumatoid arthritis (RA) or axial spondyloarthritis (axSpA) face limitations in societal participation, including work. Supervised exercise therapy improves symptoms and physical functioning, but its impact on work outcomes is unclear. This systematic review aims to examine the reporting of and effects on work outcomes in exercise therapy trials. METHOD: Eight databases were searched up to February 2024 for randomized controlled trials (RCTs) evaluating the (cost-)effectiveness of supervised exercise therapy interventions in adults with RA/axSpA. The reporting of work and other social participation outcomes, the content of the exercise therapy intervention, and their effects on work outcomes were extracted. Within- and between-group results on work outcomes were summarized. RESULTS: In total, 41 (22 RA, 19 axSpA) RCTs on supervised exercise therapy were included, none of which was specifically targeted at work. Two RCTs in people with RA included work outcomes (absenteeism and employment hours). None of the RCTs in axSpA reported work outcomes. A work-related item or subscale was reported in 6/22 of the RA and 7/19 of the axSpA trials. Outcomes on societal participation (including work) were reported in 13/22 of the RA and 18/19 of the axSpA trials. Effects on work were reported on different outcomes and results were inconclusive. CONCLUSION: Work outcomes are rarely reported in exercise therapy trials in people with RA/axSpA. To determine the effects of supervised exercise therapy on work, future studies should include work outcomes. International consensus on which outcome to use could increase the comparability of results.
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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 | 0.072 | 0.310 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.011 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".