“Train Your Brain” Cognitive Intervention Group Program for Singaporean Older Adult Patients With Mild Cognitive Impairment: A Pilot Feasibility Study
Bibliographic record
Abstract
The “Train Your Brain” (TYB) cognitive intervention group program was developed based on previous research with the goal of remediating cognitive impairments for elderly Singaporean people with mild cognitive impairment (MCI). This study reports a pilot evaluation of feasibility (defined as participant attendance, retention rate, satisfaction and usefulness) and preliminary efficacy of the TYB program. Nineteen participants with MCI aged ≥ 50 years were recruited from a memory clinic in Singapore, with 14 receiving the TYB intervention. Participants were allocated in order of recruitment into consecutive identical groups for a 9-session program on brain health and cognitive training. Participants received pre- and post-intervention measures of cognition and completed feedback forms reporting on satisfaction with, and utility of, the TYB program. TYB was well attended (85% attendance for the first 6 sessions; 83% for the full 9-session TYB program). Participant satisfaction was high, with positive participant feedback reporting that TYB offered useful cognitive strategies which participants could implement in their daily life. Despite the small sample size and absence of control group, repeated-measures t-tests revealed significant pre- to post-intervention intra-individual improvement in global cognition measured by the Montreal Cognitive Assessment, and in executive function on the Brixton Spatial Anticipation Test. This pilot study provides supportive preliminary evidence for feasibility of TYB, with suggestions of efficacy of this program as a culturally and linguistically appropriate intervention for English-speaking older adults with MCI in Singapore.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".