Effect of combined use of transcranial direct current stimulation and cognitive training on executive function and activities of daily living after stroke
Bibliographic record
Abstract
OBJECTIVE: To explore the effects of transcranial direct current stimulation combined with cognitive training on executive function and activities of daily living performance among stroke patients. METHODS: A total of 50 subjects were enrolled and randomly allocated into 2 groups of 25 each. The real-transcranial direct current stimulation group was simultaneously subjected to transcranial direct current stimulation and cognitive training, while the sham-transcranial direct current stimulation group was simultaneously subjected to sham transcranial direct current stimulation and cognitive training. At baseline, and after treatment, each subject was assessed with the Wisconsin Card Sorting Test (WCST), Stroop Color-Word Test (SCWT), Digital Symbol Test (DST), Mini-mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Activities of Daily Living Scale (ADLs). RESULTS: After treatment, the gains in most indices of WCST, SCWT, DST, MMSE, MoCA and ADLs in the real-transcranial direct current stimulation group were significantly higher than those in the sham-transcranial direct current stimulation group (p<0.05). Nonetheless, no significant differences were noted in the gains in SCWT (including only Part A time and error, and Part B time) and activities of daily living (including only basic activities of daily living) between the 2 groups (p>>0.05). CONCLUSION: Transcranial direct current stimulation combined with cognitive training was found to significantly enhance executive function and instrumental activities of daily living performance among stroke patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".