Effectiveness of cognitive rehabilitation on mild cognitive impairment using teleneuropsychology
Bibliographic record
Abstract
The COVID-19 pandemic has affected the continuity of cognitive rehabilitation worldwide. However, the use of teleneuropsychology to provide cognitive rehabilitation has contributed significantly to the continuity of the treatment. Objectives: To measure the effects of cognitive telerehabilitation on cognition, neuropsychiatric symptoms, and memory strategies in a cohort of patients with mild cognitive impairment. Methods: A sample of 60 patients with mild cognitive impairment according to Petersen's criteria was randomly divided into two groups: 30 treatment cases and 30 controls (waiting list group). Subjects were matched by age, sex, and Montreal Cognitive Assessment. The treatment group received ten cognitive telerehabilitation sessions of 45 minutes duration once a week. Pre-treatment (week 0) and post-treatment (week 10) measures were assessed for both groups. Different linear mixed models were estimated to test treatment effect (cognitive telerehabilitation vs. controls) on each outcome of interest over time (pre/post-intervention). Results: A significant group (control/treatment) x time (pre/post) interaction revealed that the treatment group at week 10 had better scores in cognitive variables: memory (RAVLT learning trials p=0.030; RAVLT delayed recall p=0.029), phonological fluency (p=0.001), activities of daily living (FAQ p=0.001), satisfaction with memory performance (MMQ satisfaction p=0.004) and use of memory strategies (MMQ strategy p=0.000), as well as, and a significant reduction of affective symptomatology: depression (GDS p=0.000), neuropsychiatric symptoms (NPI-Q p=0.045), forgetfulness (EDO-10 p=0.000), and stress (DAS stress p=0.000). Conclusions: Our study suggests that CTR is an effective intervention.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".