The Effect of Exercise on Falls in People Living with Dementia: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: People living with dementia (PWD) are at a heightened risk for falls. However, the effects of exercise on falls in PWD are unclear. OBJECTIVE: To conduct a systematic review of randomized controlled trials (RCTs) examining the efficacy of exercise to reduce falls, recurrent falls, and injurious falls relative to usual care among PWD. METHODS: We included peer-reviewed RCTs evaluating any exercise mode on falls and related injuries among medically diagnosed PWD aged ≥55years (international prospective register of systematic reviews (PROSPERO) ID:CRD42021254637). We excluded studies that did not solely involve PWD and were not the primary publication examining falls. We searched the Cochrane Dementia and Cognitive Improvement Group's Specialized Register and grey literature on 08/19/2020 and 04/11/2022; topical categories included dementia, exercise, RCTs, and falls. We evaluated the risk of bias (ROB) using the Cochrane ROB Tool-2 and study quality using the Consolidated Standards of Reporting Trials. RESULTS: Twelve studies were included (n = 1,827; age = 81.3±7.0 years; female = 59.3%; Mini-Mental State Examination = 20.1±4.3 points; intervention duration = 27.8±18.5 weeks; adherence = 75.5±16.2%; attrition = 21.0±12.4%). Exercise reduced falls in two studies [Incidence Rate Ratio (IRR) range = 0.16 to 0.66; fall rate range: intervention = 1.35-3.76 falls/year, control = 3.07-12.21 falls/year]; all other studies (n = 10) reported null findings. Exercise did not reduce recurrent falls (n = 0/2) or injurious falls (n = 0/5). The RoB assessment ranged from some concerns (n = 9) to high RoB (n = 3); no studies were powered for falls. The quality of reporting was good (78.8±11.4%). CONCLUSION: There was insufficient evidence to suggest that exercise reduces falls, recurrent falls, or injurious falls among PWD. Well-designed studies powered for falls are needed.
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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 | 0.007 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".