Primary results of a phase-III, randomized controlled trial of the Behavioral Intervention for increasing Physical Activity in Multiple Sclerosis project
Bibliographic record
Abstract
Background We undertook a phase-III, randomized controlled trial (RCT) that examined the effectiveness of a behavioral intervention based on social cognitive theory (SCT) and delivered through the Internet using e-learning approaches for immediate and sustained increases in physical activity among persons with multiple sclerosis (MS). Method The study followed a parallel group RCT design. Persons with MS ( N = 318) were randomized into either behavioral intervention ( n = 159) or attention/social contact control ( n = 159) conditions. The conditions were administered over a 6-month period by persons who were uninvolved in screening, recruitment, random assignment, and outcome assessment. There was a 6-month follow-up period without access of conditions. We collected outcome data every 6 months over the 12-month period. The primary outcome was device-measured minutes/day of moderate-to-vigorous physical activity (MVPA). The data analysis involved a modified intent-to-treat approach (i.e. those who received the allocated conditions) using a linear mixed model. Results There was a significant group by time interaction on the primary outcome of device-measured minutes/day of MVPA ( p < 0.005). MVPA was increased immediately after the 6-month period in the behavioral intervention compared with control, and this difference was sustained over the 6-month follow-up. Conclusion This study provides evidence for the effectiveness of a widely scalable approach for increasing MVPA in persons with MS.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".