Square-stepping Exercise For Older Adults With Chronic Disease To Improve Cognition and Mobility
Bibliographic record
Abstract
Square-stepping exercise (SSE) is a visuospatial working memory task with a cued stepping response that improves mobility and cognition in older adults. PURPOSE: To determine if a SSE intervention improves cognitive and mobility in older adults with chronic disease (i.e., knee osteoarthritis [KOA]; type 2 diabetes mellitus [T2DM] with self-reported cognitive complaints [sCC]; and dementia), compared to control groups. METHODS: We conducted three pilot randomized controlled trials, with 12- and 24-week intervention periods, compared to wait-list control groups. Assessments focused on: mobility (i.e., 30-second chair stand, and walking speed) for adults with KOA; cognition [i.e., Cambridge Brain Sciences, antisaccade reaction time (RT)] for adults with T2DM with sCC; and mood and behaviours questionnaire (i.e., Neuropsychiatric Inventory Questionnaire; NPIQ) for adults with dementia. RESULTS: KOA participants showed trends toward improved 30-second chair stand at 12-weeks (F=1.8, p=0.12, ηp2=0.16) and 24-weeks (F=3.4, p=0.09, ηp2=0.18), and walking speed at 24-weeks (F=2.4, p=0.14, ηp2=0.14), compared to controls after adjusting for baseline. T2DM with sCC improved on planning change scores from 12 to 24-weeks (F=5.8, p=0.03, ηp2=0.28) compared to controls, and a non-significant improvement in antisaccade RT of 38 ms (SD 16). Adults with dementia improved on NPIQ scores (i.e. symptoms) at 12-weeks (total: F=7.3, p=0.01, ηp2=0.25; frequency: F=9.4, p=0.01, ηp2=0.30; and severity: F=7.0, p=0.02, ηp2=0.24), compared to controls. CONCLUSIONS: In our pilot trials, SSE showed promise for improving mobility and cognition in adults with chronic disease and demonstrates the potential for its use in adults with diverse mobility and cognitive impairments. Funding: Supported by the Department of Family Medicine, University of Western Ontario, Mitacs Accelerate, Ontario Graduate Scholarship, and Schlegel - University of Waterloo Research Institute for 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".