Cognitive Groove Expands Life Space in Older Adults with Mild Cognitive Impairment: A Community‐Based Rehabilitation Approach
Bibliographic record
Abstract
BACKGROUND: Life space mobility - how far and how often someone moves through their environment - is a meaningful marker of physical function, cognitive health, and independence. In older adults with mild cognitive impairment (MCI), life space often becomes restricted and can accelerate functional decline. This study evaluated the impact of Cognitive Groove, brought to you by GERAS DANCE, on life space mobility in older adults with and without MCI. METHOD: Cognitive Groove is a structured, community-based rehabilitation program designed for older adults with early cognitive and/or mobility challenges. The program was delivered across 12 YMCA sites in Southern Ontario, Canada. The program included in-person dance classes (twice weekly, 1 hour each) and at-home balance exercises (10 minutes daily) over 12-weeks. Life space mobility was assessed using the Life Space Assessment (LSA), cognitive function with the Montreal Cognitive Assessment (MoCA), and physical function with the Short Physical Performance Battery (SPPB). MCI was defined as a baseline MoCA score of 18-25. Paired t-tests examined the changes from baseline to 12 weeks, and the chi-square test assessed changes in LSA frequency. Statistical significance was p ≤0.05. RESULT: A total of 106 older adults (age = 76.10(7.0) years; range 61-93) participated in Cognitive Groove. There were 61 older adults classified with MCI and 45 without MCI. Program adherence was high, with an average attendance of 75% (18/24 sessions). By the end of the program, older adults with MCI were moving farther and more often in their daily lives (p ≤0.05). Their life space became similar to those without MCI, whose movement stayed the same during the program (p >0.05). Notably, older adults with MCI reported more frequent travel outside their neighbourhood but within their town (Life Space Level 4, p <0.001). MoCA scores improved by 1.04 points in the MCI group, exceeding the minimal clinically important difference of 1.0, and both groups demonstrated significant improvements in SPPB scores (p <0.001). CONCLUSION: These findings suggest that Cognitive Groove not only enhances physical performance, but also life space mobility, by fostering community re-engagement among older adults with MCI to support functional independence and active aging.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".