Using the Cognitive Orientation to Occupational Performance (CO-OP) with Adults with Executive Dysfunction following Traumatic Brain Injury
Bibliographic record
Abstract
BACKGROUND: Meta-cognitive strategies have a positive effect on the rehabilitation of executive dysfunction. However, achieving generalization to daily life remains a challenge. We believe that providing rehabilitation in the person's own physical environment and using self-identified tasks will enhance the benefits of meta-cognitive training and promote generalization. PURPOSE: This pilot study tested the applicability of the Cognitive Orientation to Occupational Performance (CO-OP) approach for use with adults with executive dysfunction arising from traumatic brain injury (TBI). METHODS: A single-case design was used with 3 adults, 5 to 20 years post-TBI and their self-identified significant others. Assessments included neuropsychological tests and the Canadian Occupational Performance Measure. The intervention entailed guiding participants to use a meta-cognitive problem-solving strategy to perform self-identified daily tasks that they needed and wanted to do and with which they were having difficulties. The intervention occurred over 20 one-hour sessions in participants' environments. FINDINGS: Performance improved to criterion (2-point positive change) on 7 of 9 trained goals and on 4 of 7 untrained goals (self-report). Improvement was maintained at a 3-month follow-up assessment. IMPLICATIONS: The CO-OP approach has the potential to improve performance in daily functioning for adults with executive dysfunction following TBI.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".