Beyond supervised therapy: Promoting behavioral changes in people with MS
Bibliographic record
Abstract
A critical aspect of many rehabilitation interventions for people with multiple sclerosis (MS) is incorporating strategies that support behavior change. The main purpose of this topical review was to summarize recent randomized clinical trials (RCTs) of rehabilitation interventions in which participants learn and apply skills or engage in healthy behaviors. The Capability, Opportunity, Motivation, and Behavior (COM-B) framework was used to broadly classify behavior-change strategies. The included RCTs varied widely in terms of dosing, delivery format, and types of interventionist. Commonly used behavior-change strategies include education, persuasion, and training. We recommend that researchers and clinicians use frameworks like Behavior Change Wheel and Behavior Change Technique Taxonomy to describe and classify intervention strategies used to promote behavior change. We also recommend more sophisticated RCTs be conducted (e.g. sequential multiple assignment randomized trial and three-arm RCTs) to better understand ways of promoting behavior change in rehabilitation interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 teacher head, 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".