Falls prevention in community-dwelling older adults and implementation of world falls guidelines: a call for action across Europe by the European Geriatric Medicine Society Special Interest Group on Falls and Fractures
Bibliographic record
Abstract
Falls among older adults represent a significant public health challenge due to their consequences, including serious injuries, increased morbidity and mortality, decreased quality of life, and heightened healthcare costs. The World Falls Guidelines (WFG), published in 2022, offer a robust framework for evidence-based interventions; however, the uptake of these guidelines into clinical practice across Europe remains inconsistent. Key barriers to implementation include insufficient resources, a lack of trained healthcare professionals, and limited integration into existing healthcare systems. This position paper by the EuGMS Special Interest Group (SIG) on Falls and Fractures addresses the implementation of the WFG among community-dwelling older adults and falls prevention across Europe by providing an overview of the current status of WFG adoption in Europe and discusses the challenges and opportunities for implementation. We provide an overview of the current resources to support the clinical practice of falls prevention, implementation guides, and educational programs. Additionally, we discuss what is necessary for the future development of these resources and for advancing research. The EuGMS SIG on Falls and Fractures advocates for a commitment of healthcare providers as well as insurers, policymakers, and other stakeholders to collaborative European initiatives-such as developing a standardised falls prevention strategy, promoting evidence-based implementation plans, establishing a European-wide research agenda, and creating under- and postgraduate curricula-which are essential for advancing falls prevention efforts across Europe.
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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 | 0.060 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".