Risk Factors Associated with Falls in Older Adults with Dementia: A Systematic Review
Bibliographic record
Abstract
Purpose: People with dementia fall more often than cognitively healthy older adults, but their risk factors are not well understood. A review is needed to determine a fall risk profile for this population. The objective was to critically evaluate the literature and identify the factors associated with fall risk in older adults with dementia. Methods: Articles published between January 1988 and October 2014 in EMBASE, PubMed, PsycINFO, and CINAHL were searched. Inclusion criteria were participants aged 55 years or older with dementia or cognitive impairment, prospective cohort design, detailed fall definition, falls as the primary outcome, and multi-variable regression analysis. Two authors independently reviewed and extracted data on study characteristics, quality assessment, and outcomes. Adjusted risk estimates were extracted from the articles. Results: A total of 17 studies met the inclusion criteria. Risk factors were categorized into demographic, balance, gait, vision, functional status, medications, psychosocial, severity of dementia, and other. Risk factors varied with living setting and were not consistent across all studies within a setting. Conclusion: Falls in older adults with dementia are associated with multiple intrinsic and extrinsic risk factors, some shared with older adults in general and others unique to the disease. Risk factors vary between community- and institution-dwelling samples of adults with dementia or cognitive impairment.
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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".