Associations between cognitive function and long‐term cognitive enhancement therapy: Insights from a 5‐year follow‐up, case study
Bibliographic record
Abstract
Abstract Background A 69‐year‐old retired businessman, born in 1954, with 12 years of education, had been participating in cognitive enhancement sessions for the past 5 years. His medical history included two ischemic strokes, left hemiplegia, as well as disturbances in the left visual field. This study aimed to examine the individual’s cognitive performance over the course of these 5 years, including the COVID‐19 pandemic period. Methods Bi‐weekly, 45‐minute cognitive remediation sessions were performed for 1.5 years, transitioning to once weekly later on. Exercises included orientation (e.g., use of calendar, news, articles), language (e.g., repetition, fluency, fill the gaps), visuospatial (e.g., pattern completion, object localisation, tracking of moving objects), memory (e.g., stories/words/images, learning, consolidation and recall of information, reminiscence and old songs), executive (e.g., dual tasks, categorisation) and motor tasks (e.g., ball games). Results At baseline (July 2018), the person scored 11/30 in the Montreal Cognitive Assessment (MoCA) with significant visuospatial, memory recall, and orientation difficulties. In October 2019 (after 59 sessions), the MoCA score improved to 15/30, with better performance in visuospatial tasks, calculation, delayed recall, and orientation. However, a re‐evaluation in May 2020, following the first wave of COVID‐19, during which sessions were paused, resulted in a score of 11/30. The lowest points were noted in orientation and delayed recall. Sessions continued at a reduced frequency due to COVID‐19 restrictions and medical complications (flu, serious respiratory and urinary tract infections, and hospitalisation) which also affected the fine motor skills of the right hand. Last evaluation, in September 2023, yielded a score of 12/30 points, showing a regain of orientation and calculation scores, but losses in visuospatial skills, naming and delayed recall compared to the 2019 evaluation. Discussion Our findings suggest a connection between cognitive functionality and cognitive enhancement therapy, particularly in orientation, memory recall, and calculation tasks. Achieving impact appears to require sustained and long‐term engagement in personalised enhancement sessions, which can be significantly hindered by external obstacles, such as COVID‐19 restrictions and other health issues.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".