Organisation and content of supervised group exercise for people with axial spondyloarthritis in The Netherlands
Bibliographic record
Abstract
Supervised group exercise (SGE) is recommended for people with axial spondyloarthritis (axSpA). Recent literature suggests that its contents and dosage must probably be revised. As a first step towards renewal, this study examined the current SGE organisation and content for people with axSpA in The Netherlands. A pen-and-paper survey was sent to the boards of the 82 local patient associations affiliated with the Dutch Arthritis Society in 2016. One member of each board was asked to complete questions on the nature and organisation of SGE and one of the supervising therapists to complete questions on the SGE supervision and contents. The questionnaire was returned by representatives of 67/82 (82%) local patient associations, of which 17 (25%) provided axSpA-specific SGE (16/17 SGE programmes with both land-based exercise and hydrotherapy and 1/17 with only hydrotherapy). These involved in total 56 groups with 684 participants and 59 supervisors, of whom 54 were physical therapists and 21 had had postgraduate education on rheumatic and musculoskeletal diseases (RMDs). Besides mobility and strengthening exercises and sports (17/17), most programmes included aerobic exercise (10/17), but rarely with heart rate monitoring (1/17), patient education (8/17), periodic assessments (2/17), or exercise personalisation (1/17). In the Netherlands, a quarter of local patient associations organised axSpA-specific SGE, mostly containing land-based exercises combined with sports and hydrotherapy. Most supervisors lacked postgraduate education on RMDs and most programmes lacked intensity monitoring, patient education, periodic assessments, and personalisation, which are needed for optimising exercise programmes according to current scientific insights.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".