Adherence to Physiotherapy-Guided Web-Based Exercise for Persons with Moderate-to-Severe Multiple Sclerosis
Bibliographic record
Abstract
Abstract Background: Options to support adherence to physical activity in moderate-to-severe multiple sclerosis (MS) are needed. The primary aim was to evaluate adherence to a Web-based, individualized exercise program in moderate-to-severe MS. Secondary aims explored changes in 29-item Multiple Sclerosis Impact Scale, Hospital Anxiety and Depression Scale (HADS), grip strength, Timed 25-Foot Walk test, and Timed Up and Go (TUG) results. Methods: Participants were randomized (2:1) to a physiotherapist-guided Web-based home exercise program or a physiotherapist-prescribed written home exercise program. The primary outcome was adherence (number of exercise sessions over 26 weeks). Secondary outcomes were described in terms of means and effect sizes. Results: There were 48 participants: mean ± SD age, 54.3 ± 11.9 years; disease duration, 19.5 ± 11.0 years; and Patient-Determined Disease Steps scale score, 4.4 ± 1.6. There was no significant difference in mean ± SD adherence in the Web-based group (38.9 ± 28.1) versus the comparator group (34.6 ± 40.8; U = 198.5, P = .208, Hedges’ g = 0.13). Nearly 50% of participants (23 of 48) exercised at least twice per week for at least 13 of the 26 weeks. Adherence was highest in the Web-based subgroup of wheelchair users. Medium effect sizes were found for the HADS anxiety subscale and in ambulatory participants for TUG. There were no adverse events. Conclusions: There was no difference in exercise adherence between the Web-based and active comparator groups. There was no worsening of secondary outcomes or adverse events, supporting the safety of Web-based physiotherapy. More research is needed to determine whether wheelchair users might be most likely to benefit from Web-based physiotherapy.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".