Effect of Group Counseling Plus Tailored Exercise on Mobility Function in Multiple Sclerosis
Bibliographic record
Abstract
BACKGROUND: Multiple sclerosis (MS) impairs muscular function and limits individuals' ability to perform everyday activities requiring mobility. People with MS frequently exhibit mobility problems (ie, slower walking speed, shorter strides). General exercise training (eg, resistance, aerobic) provides modest physiological and walking mobility benefits. However, researchers suggest tailoring of interventions to address mobility specifically. We conducted a phase 2a pre-post intervention development study (Obesity-Related Behavioral Intervention Trials [ORBIT] intervention development model) of mobility exercise plus cognitive behavioral counseling to improve function and social cognitions known to encourage exercise. METHODS: The intervention was conducted twice per week for 8 weeks followed by 1 month of self-managed mobility exercise. Participants (N = 29; mean ± SD age = 52.24 ± 11.36 years, mean time since MS diagnosis ≥11 years) were assessed at baseline and after follow-up for mobility function, social cognitions, and intervention fidelity indicators. RESULTS: Results indicated significant improvements in a variety of valid measures of mobility function (eg, 400-m walk), self-regulatory efficacy for mobility exercise and symptom control, and fidelity measures with small to medium effect sizes. CONCLUSIONS: Positive findings suggest that the intervention seems to merit testing as a randomized pilot study following the ORBIT model.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".