The impact of multimodal cognitive rehabilitation on executive functions in older adults with traumatic brain injury (TBI)
Bibliographic record
Abstract
A bstract Objectives This study evaluated the impact of a multimodal cognitive rehabilitation intervention, the Cognitive Enrichment Program (CEP), on executive functioning (EF) and resumption of daily activities following traumatic brain injury (TBI) in older individuals, in comparison to an active control group having received holistic rehabilitation as usual care. Methods The CEP’sexecutive function module included planning, problem solving, and goal management training, as well as strategies focusing on self-awareness. Effectiveness was evaluated by psychometric tests (Modified Six Elements Task-adapted – MSET-A, D-KEFS Sorting test and Stroop four-color version ), while generalization was measured through self-reported questionnaires about daily functioning (Dysexecutive Functioning Questionnaire – DEX, Forsaken daily life activities ). Measures were obtained before and after intervention, and six months later. Results ANCOVA results showed significant group-by-time interactions on Tackling the 6 subtasks and Avoiding rule-breaking measures of the MSET-A, with moderate effect sizes. Despite improvements in Sorting and Stroop scores, there were no group-by-time interaction on these measures. DEX generalization measure showed a significant reduction in patient/significant other difference on the Executive Cognition subscale. There was a reduction in the number of Forsaken daily life activities in the experimental group compared to controls which was not significant immediately after CEP, but that was significant six months later. Conclusions Our study shows that older adults with TBI can improve their executive functioning with a positive impact on everyday activities after receiving multimodal cognitive training compared to an active control group.
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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 | 0.000 | 0.001 |
| 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".