A Conceptual Approach to Comprehensive Interdisciplinary Cognitive Rehabilitation: A description using the TIDieR-Rehab Framework
Bibliographic record
Abstract
Abstract Cognitive impairment is highly prevalent in people with progressive multiple sclerosis. Computerized cognitive training techniques have demonstrated some success at targeting core cognitive processes but are criticized for lack of transfer to real-world tasks. Research in physical rehabilitation has demonstrated the efficacy of high volume, moderate intensity task-specific training (TST) that is monitored, progressed and ideally practiced in real-world environments to enhance learning, transferability and support neurorecovery of motor functions. Findings demonstrate that TST influences activity and participation outcomes, leads to improved cortical reorganization, and focuses on activities that align with a person’s daily life and specific goals. Our MSCanRehab group adapted the same principles to develop a novel comprehensive interdisciplinary approach to cognitive rehabilitation that combines core cognitive process training (CCPT), TST and a modified Cognitive Orientation to Daily Occupational Performance (CO-OP) approach. The cognitive TST was individualized to participant goals identified using the Canadian Occupational Performance Measure and further tailored based on their areas of cognitive weakness. A modified CO-OP process was utilized that incorporated CCPT and cognitive TST personalized to meet meaningful participant goals and improve occupational performance. Cognitive TST utilized goal-directed practice and repetition focused on cognitive skills (vs. impairments) using real-world tasks. Task complexity and challenge was gradually increased and progressively adapted with emphasis on active participation and problem solving. A case example demonstrates how the intervention was implemented. Components of the intervention are described using the TIDieR-Rehab checklist to ensure a comprehensive description, with emphasis on essential elements and dosage parameters. Highlights - Computerized cognitive training alone can lack generalizability to real-world settings - The task-specific training approach used in physical rehabilitation can be adapted to address cognitive rehabilitation goals - A modified Cognitive Orientation to Daily Occupational Performance (CO-OP) process that incorporates core cognitive processes training with cognitive task-specific training provides a personalized and adaptable approach to cognitive rehabilitation in people with progressive 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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".