TD‐P‐002: EFFECTS OF ONLINE COMPUTERIZED COGNITIVE TRAINING PROGRAM BEYNEX ON THE COGNITIVE TESTS OF INDIVIDUALS WITH SUBJECTIVE COGNITIVE IMPAIRMENT (SCI)
Bibliographic record
Abstract
Clinical trials conducted on the efficacy of computerized cognitive training have not lead to any important breakthroughs. There is a growing consensus that this can, at least partially, be explained by methodological difficulties. 60 patients with SCI diagnosis, aged 69.90±9.44 on average, were subjected to Montreal Cognitive Assessment (MOCA), Cambridge Cognition (CANTAB tests: MOT, PRM, DMS, SWM, PAL, RTI) and Bayer Activity of Daily Living (ADL) Scale (BAYER). Later the age groups and education levels were normalized to randomly divide the subjects into two groups of 30. The first group was provided with a password to access a web-based program BEYNEX and asked to complete tasks, which included playing 3 varying 5-minute long computer games, on a daily basis; and answering questions on ADL. They were expected to watch and practice a 3-minute physical exercise video as well. All tasks are designed within the parameters used by clinicians and take 15-20 minutes to complete daily. BEYNEX exercises are completely unique and are not in commercial use. Patients' total activity time, ADL and game performances were monitored only by clinicians under 9 different graphics (ADL, Memory, Visual Perception, Speed, Problem-solving, Flexibility, Attention, Language Skills, Arithmetic). After 3 months or at least 1200 minutes of BEYNEX use, the diagnostic tests (MOCA, CANTAB, BAYER) were repeated for both test and control groups. Among the two groups, there are no meaningful differences determined between the beginning and final results of MOCA and BAYER scales; whereas CANTAB results indicated statistically meaningful changes. The results of exercise practicing group showed positive improvement in parameters of Motor screening (MOT Median), Delayed Matching sample (DMS; Percent correct and Percent correct (all delays)), Paired Associated Learning (PAL; Total errors (adjusted) and Total errors (6 shapes, adjusted)). Pattern recognition memory (PRM), Spatial working memory (SWM) and Reaction time (RTI) parameters showed no change.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".