Participation in and outcomes from a 12-month tailored exercise programme for people with multiple sclerosis (MSTEP©): a randomized trial
Bibliographic record
Abstract
Objective: To estimate, among people with multiple sclerosis, the extent to which a personally tailored exercise programme (MSTEP©) resulted in greater improvements in exercise capacity and related outcomes over 12 months in comparison with general exercise guidelines. Design: Two-group randomized trial. Subjects: Ambulatory and sedentary. Interventions: MSTEP©, a personally adapted exercise regimen done on most days including two days of high intensity exercise; guidelines recommending 30 minutes of moderate intensity aerobic and strength training two times per week. Main measures: Primary outcome was peak oxygen consumption (VO 2peak ) at 12 months; secondary outcomes were composite measures of physical function, fatigue, and health-related quality of life. Results: In total, 137 people were randomized, 66 were lost over 12 months leaving 71 with outcome data, 34 in MSTEP© group, and 37 in the Guideline group. Exercise enjoyment and confidence and exercise-induced fatigue predicted retention. There were no differences between groups on the proportion making a 10% increase in VO 2peak (27.1% MSTEP© vs 29.6% Guidelines; OR: 0.83; 95% CI: 0.23–3.08) by the 12 month assessment. The effect on fatigue was larger in the MSTEP© group than the Guideline groups (OR: 1.59; 95% CI: 0.93–2.74), the effect on physical function was more modest (OR: 1.35; 95% CI: 0.80–2.25), and null for health-related quality of life outcomes. Conclusions: The disappointing exercise retention suggests that people with multiple sclerosis may not consider exercise important to their brain health. Either type of exercise resulted in stable exercise capacity over 1 year in those sticking with the programme.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.005 | 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".