Yearlong Evaluation of Fall Risk Determinants Among 40 Older Adults in Two Residential Assisted Living Facilities
Bibliographic record
Abstract
BACKGROUND Falls among the elderly, the second leading cause of death from unintentional injury globally, represent significant social and economic challenges. We evaluated the relationship between physical activity, physical performance, falls, and cognitive functioning at 1 year in 40 older adults living in 2 residential assisted living facilities in 2 communities in Wisconsin, USA. MATERIAL AND METHODS Forty participants took part in the study, including 25 women and 15 men, with a mean age of 86.6 (±6.3) years. The Montreal Cognitive Assessment (MoCA) assessed cognitive functions, Hospital Anxiety and Depression Scale assessed depression, and Fall Efficacy Scale (FES) assessed fear of falling. Physical performance tests included the 10-meter walking test, 2-minute step test (2MST), and lower extremity strength and hand grip strength using a dynamometer. Additionally, posturography, using a portable Wii platform, Timed Up and Go test (TUG) test, and Performance Oriented Mobility Assessment (POMA) assessed balance. RESULTS As many as 40% participants had at least 1 fall in 6 months. Significant deterioration in gait speed (P<0.0001) and mood (P=0.0137) over 1 year was noted. A significant correlation was found between number of falls and the 2MST (rho=-0.48), POMA and gait speed (rho=0.63), and the TUG (rho=-0.62), FES, and 2MST (rho=-0.54). The 2MST was the only significant parameter affecting the risk of falls in the study group (P=0.0118). CONCLUSIONS Among assisted living facility residents, a higher risk of falling was associated with decreased gait speed, impaired balance, decreased mood, increased fear of falling, and fewer repetitions performed in the 2MST.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".