Impact on activities of daily living using a functional electrical stimulation device to improve dropped foot in people with multiple sclerosis, measured by the Canadian Occupational Performance Measure
Bibliographic record
Abstract
BACKGROUND: Dropped foot is a common problem following multiple sclerosis. Functional electrical stimulation can elicit an active muscle contraction providing dorsiflexion and eversion. OBJECTIVE: To determine if the Odstock dropped foot stimulator (ODFS), improved activities of daily living for people with multiple sclerosis. METHOD: 64 people with unilateral dropped foot due to secondary progressive multiple sclerosis took part in a randomized controlled trial. Research volunteers were assigned to a group using the ODFS or a group who received physiotherapy exercises for 18 weeks. Outcome measures were the Canadian Occupational Performance Measure (COPM) and a falls diary. RESULTS: Results of 53 research volunteers are reported. Improvements in performance and satisfaction scores were greater in the ODFS group than the exercise group; (p < 0.05). Use of the ODFS was also perceived as effective in reducing tripping and increasing walking distance. The median number of falls were 5 in the ODFS group and 18 in the exercise group (p = 0.036) over the study period. CONCLUSION: The study shows that people with multiple sclerosis using the ODFS increased their COPM performance and satisfaction scores of their identified problems of activities of daily living more than a matched group who received physiotherapy exercises. ODFS users also experienced fewer falls.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".