Group-based exercice training programs for military members presenting musculoskeletal disorders – protocol for a pragmatic randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Musculoskeletal disorders are a leading cause of morbidity and the most prevalent source of disability among soldiers. Their high prevalence in armed forces and limited ressources have led to problems related to access to physical rehabilitation care. To increase access, supervised group-based exercise programs for the most prevalent musculoskeletal disorders (low back pain, patellofemoral pain, rotator cuff-related shoulder pain or lateral ankle sprain) have been developed at a Canadian Armed forces (CAF) base, but their effectiveness has not been evaluated. The primary objective of this randomized controlled trial is to evaluate the mid- and long-term effects of these group-based training programs on pain severity and functional limitations, in comparison with usual individual physiotherapy care. Secondary objectives include comparing both interventions in terms of health-related quality of life, pain-related fear, and patients' satisfaction. METHODS: One hundred and twenty soldiers with a new medical referral for physiotherapy services for one of the four targeted musculoskeletal disorders will be consecutively recruited. They will be randomly assigned to either group-based training program or usual individual physiotherapy care, and will take part in the assigned 12-week intervention. There will be four evaluation sessions over 26 weeks (baseline, week 6, 12 and 26). At each follow-up, functional limitations, pain severity, health-related quality of life and pain-related fears will be assessed. Patients satisfaction with treatment will also be evaluated at the end of the intervention period. Either two-way repeated measures ANOVA will be used to analyse and compare the effects of the interventions. DISCUSSION: This RCT will determine the effectiveness of group-based training programs compared to usual individual physiotherapy care. This new intervention model could represent an efficient, and more pro-active approach to manage a higher number of soldiers with musculoskeletal disorders. It could improve access to physical rehabilitation care and improve the health of soldiers. TRIAL REGISTRATION: ClinicalTrials.gov ( NCT05235152 ), February 11th 2022.
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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 | 0.044 | 0.037 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.060 | 0.009 |
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".