Online occupational therapy in the caregivers of people with Multiple sclerosis: a randomized control trial
Bibliographic record
Abstract
PURPOSE: Caregivers of people with Multiple sclerosis (MS) face various challenges in the occupations of daily lives. We investigated the effect of an online occupational therapy program on the mastery and performance in caregivers of people with MS. METHOD: In a single-blind randomized controlled trial twenty-four eligible caregivers of people with MS participated in the control and an occupational therapy group program. Caregivers completed The Canadian Occupational Performance Measure (COPM) and the Relative Mastery Scale (RMS) before and after the intervention and one-month later. FINDINGS: <.001). IMPLICATIONS: Online Occupational therapy shows promising results in facilitating the adaptation process and improving caregivers' performance and satisfaction levels.IMPLICATIONS FOR REHABILITATIONCaregivers of people with multiple sclerosis face various challenges when engaging in their daily occupations.Managing the challenges faced by caregivers as essential members of the treatment team contributes to improving their performance level in daily occupations and can finally enhance the quality of treatment interventions for patients.Online delivery can overcome caregivers' time constraints for attendance in the treatment centers for training.Online occupational therapy can enhance mastery, occupational performance level, and satisfaction, and is recommended for caregivers of people with multiple sclerosis.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".