Comparative efficacy of vision-restricted vs. conventional cognitive-motor dual-task training for cognition improvement in type 2 diabetes: A randomized controlled trial
Bibliographic record
Abstract
Background Cognitive disorder is caused by hyperglycemia and insulin resistance in type 2 diabetes. Elevated glycemic levels contribute to neural damage and exacerbate cognitive decline, strict glucose control is required to maintain cognition. Vision-Feedback Restricted Cognitive motor dual-task training (VFR-CMDT) improves brain areas associated to memory and motor skills. Methods In this randomized controlled experiment, 80 Type 2 Diabetes Mellitus adults (mean age 52 years; duration of diabetes more then 5 years) were randomized into two groups, Vision-Feedback Restricted Cognitive-Motor Dual Training (VFR-CMDT;(n = 40)) and Conventional Cognitive-Motor Dual Task Training (CV-CMT; (n = 40)) . The Primary outcome measure were the Montreal Cognitive Assessment (MoCA) and Trail Making Test - Part B (TMT-B) and Secondary was Subjective Cognitive Complaints (SSCs). Evaluated at baseline, Week 4 (post-intervention), and Week 8 (follow-up). Results Significant improvements were observed in all measures over time ( p < 0.001). By Week 4, both groups’ MoCA ratings increased from 19 to 27, and by Week 8, they were unchanged. By Week 8, SCCs showed improvement from 58 to 30 in VFR-CMDT and 33 in CV-CMT, while TMT-B times improved from 210–215 s to 80–88s. Although VFR-CMDT demonstrated numerically greater improvements, the group x time interaction effects were not statistically significant (all p > 0.05), indicating no superiority of either intervention. Gains within the group were very significant ( p < 0.001), however comparisons between groups were not ( p > 0.15). At Week 8, the effect sizes for SCCs (d ≈ 0.65) and MoCA (d ≈ 0.50) were modest to moderate, while those for TMT B (d ≈ 0.53) were moderate. Conclusion Both cognitive training programs produced improvements in global cognition (MoCA), executive function (TMT-B), and subjective cognitive complaints (SCCs) among adults with T2DM over eight weeks. Outcomes appeared directly consistent with potential benefits, the differences were not statistically significant, even though VFR-CMDT showed numerically greater than CV-CMT. To draw more definitive conclusions about the comparative efficacy of VFR-CMDT, future research should use larger, stratified samples and extend follow-up periods to evaluate durability and generalizability of cohnitive improvements.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".