Individualized Physiotherapy and Activity Coaching in Multiple Sclerosis (IPAC-MS): Results of a Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate if a novel intervention involving individualized behavior change strategies delivered by physiotherapists has an effect on physical activity levels in people with multiple sclerosis (MS) who were previously inactive compared with usual care. DESIGN: Prospective, assessor-blinded, parallel-group, randomized controlled trial. SETTING: Community settings across Saskatchewan, Canada. PARTICIPANTS: Individuals diagnosed with MS, >18 years of age, and able to walk with or without aids were invited to participate from an MS Saskatchewan database. INTERVENTION: The intervention group received individualized physical activity behavioral coaching for 12 months compared with a usual care control group. There were 3 consistent features of the intervention: behavior change techniques, recommendations for physical activity, and ongoing physiotherapist support. However, these components were tailored to each participant. MAIN OUTCOME MEASURES: The primary outcome was change in physical activity levels at 12 months on the Godin Leisure Time Exercise Questionnaire. Secondary measures included MS symptoms (Multiple Sclerosis Impact Scale-29), confidence with managing MS (Multiple Sclerosis Self-Efficacy Scale), and exercise self-efficacy (Exercise Self-Efficacy Scale). RESULTS: A total of 120 participants (mean age 53 years, 78% female, average disease duration 14.7 years) were enrolled and 117 completed primary outcome. At month 12, the mean (95% confidence interval) difference between intervention and control group for Godin Leisure Time Exercise Questionnaire was 15.9 (12.5-28.4). This improvement occurred regardless of age, gender, if on an MS drug, time since relapse, or comorbidity history. In the intervention group, 33.9% were sufficiently active for substantial health benefits compared with 6.9% in the control group at month 12 (P<.001). At baseline, these proportions were 3.4% and 4.9% respectively. Improvement occurred on the Multiple Sclerosis Self-Efficacy Scale and Exercise Self-Efficacy Scale at 12 months in favor of the intervention group. CONCLUSION: Physical activity levels and exercise self-efficacy improved clinically and significantly with neurophysiotherapist led individualized coaching.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".