THE EFFECT OF MINDFULNESS-ORIENTED RECOVERY ENHANCEMENT INTERVENTION ON POSTSTROKE COGNITIVE IMPAIRMENT
Bibliographic record
Abstract
Abstract Background About one-third of stroke patients are affected by cognitive impairment, and there is evidence that Mindfulness-based interventions (MBIs) can improve cognitive function. Objectives This study aimed to examine the effects of cognitive intervention based on Mindfulness-Oriented Recovery Enhancement (MORE) on cognitive function in patients with Post-Stroke Cognitive Impairment (PSCI). Methods A non-randomized controlled trial was conducted. A total of 44 patients with PSCI were enrolled, with 24 in the intervention group and 20 in the control group. The control group received routine rehabilitation therapy (RT), and the intervention group received 45-60 minutes of cognitive intervention based on MORE twice a week for four weeks plus RT. Results In the intervention group, 21 participants reached the standard of active participation. In intervention group, the mean change of global cognitive function (Montreal Cognitive Assessment, MoCA) after intervention compared with before intervention was 2.33 (95%CI: 1.73 – 2.93, p<0.001), while in the control group, the mean change of MoCA was 1.25 (95%CI: 0.77 – 1.72, p<0.001). Using a per- protocol analysis, the score of MoCA in the intervention group improved significantly compared to that in control group. The intervention group also showed significant improvement in attention, depressive symptoms, mindfulness, self-efficacy, resilience, and quality of life compared to the control group (p < 0.05, respectively). Conclusions The cognitive intervention based on MORE is feasible and effective in improving the cognitive function of patients with PSCI, as well as relieving depressive symptoms and quality of life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".