Effectiveness of multifaceted fall-prevention programs for the elderly in residential care
Bibliographic record
Abstract
BACKGROUND: Unintentional falls are particularly prevalent among older people and constitute a public health concern. Not much is known about the implications of multifaceted intervention programs implemented in residential care settings. OBJECTIVES: To evaluate the effectiveness of multifaceted intervention programs in reducing the number of falls, fallers, recurrent fallers, and injurious falls among older people living in residential care facilities. SEARCH STRATEGY: Comprehensive searches of Medline, PubMed, and EMBASE up to July 2007, the cited literature lists of each included study, and the internet engines Google Scholar, Yahoo, and Dogpile were performed to identify eligible studies. SELECTION CRITERIA: Eligible studies for this review were those that had randomized, controlled trials with adequate follow-up study components in their design. Studies that included elderly people in residential care who participated in multifaceted falls-prevention programs were included. DATA COLLECTION AND ANALYSIS: Two authors independently extracted the necessary data. Studies were assessed for quality by the criteria of Downs and Black. The results of the included studies have been reviewed narratively. MAIN RESULTS: From 21 articles potentially relevant to the topic, five studies met the inclusion criteria and all were reasonably well conducted. Three reported significant reductions in the number of recurrent fallers, two reported significant reductions in the number of falls, and one reported significant reductions in the number of fallers. One other reported a reduction in the number of injurious falls in those who received the multifaceted prevention program compared with the control group. However, the analyses of this specific study were not based on intent-to-treat, so the effect of intervention on the number of injurious falls remains inconclusive. No study reported on adverse events, costs, or sustainability of the interventions. CONCLUSIONS: Multifaceted programs that encompass a wide range of intervention strategies have shown some evidence of efficacy. However, more well-designed research is required that assesses effects on injurious falls, quality of life, cost-effectiveness, and sustainability.
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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".