Multisensory exercise programme improves cognition and functionality in institutionalized older adults: A randomized control trial
Bibliographic record
Abstract
AIM: The aim of this study was to verify the effects of a multisensory exercise programme on the cognition and functionality of institutionalized older adults. METHODS: Forty-five volunteers were randomly allocated to 2 groups, the multisensory exercise programme (n = 24) and the control group that received no treatment (n = 21). The programme consisted of 3 50-min sessions of progressive exercises per week for 16 weeks that challenged their strength, balance, coordination, multisensory stimulation, and flexibility in different tasks. Cognition (Montreal Cognitive Assessment), balance (Berg Scale), mobility (Timed Up and Go), and functional performance (Physical Performance Test) were measured preintervention and postintervention. Statistical analyses were performed using Student's t test and 2-way ANOVA. RESULTS: The multisensory exercise programme showed statistically significant improvements (p < .05) on cognition (effect size [ES]: 0.92), balance (ES: 0.77), mobility (ES: 0.51), and functional performance (ES: 0.86) as compared with the control group, which showed no statistical significant differences at the postintervention time point. CONCLUSIONS: The multisensory exercise programme improved the cognition and functionality of institutionalized older adults. The introduction of a motor and multisensory-based approach in care routines may improve residents' health and engagement to the environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".