Preventing falls and related injuries among seniors in assisted living residences
Bibliographic record
Abstract
Introduction The purpose of this study was to addresses a gap in the fall prevention literature with a focus on Assisted Living Residences (ALRs) – a new community housing option for a rapidly growing number of older persons that are at high risk falls. The result of the 1-year collaborative study was the development of Best Practice Guidelines for integration into routine care. Methods A 6-month prospective, action research intervention was conducted at two ALR sites, with 161 residents. Measures included focus groups, pre/post staff and resident surveys, pre/post measures of balance and gait, and 6-month fall/injury surveillance. Interventions included staff and resident training on fall tracking, fall prevention education for staff and residents, and physical activity interventions. Results Over 6 months, 155 falls were recorded, with 38% (N=73) of residents identified as having at least one fall and 43% (N=72) of falls resulting in injury. There was a statistically significant reduction in the rate of falls per 1000 resident days between the first and second three-month periods (X 2 =11.98; p=0.001). Fall risk reduction was demonstrated by a significant difference (t=3.16, p=.002) in pre/post Timed-Up-and-Go scores. Focus group findings included the need to tailor prevention to joiners and non-joiners of group intervention activities. Conclusion The study demonstrated that fall prevention guidelines can be implemented within routine service delivery in ALRs with a positive effect on fall risk reduction.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".