Compliant flooring to prevent fall-related injuries in older adults: A scoping review of biomechanical efficacy, clinical effectiveness, cost-effectiveness, and workplace safety
Bibliographic record
Abstract
BACKGROUND: Compliant flooring, broadly defined as flooring systems or floor coverings with some level of shock absorbency, may reduce the incidence and severity of fall-related injuries in older adults; however, a lack of synthesized evidence may be limiting widespread uptake. METHODS: Informed by the Arksey and O'Malley framework and guided by a Research Advisory Panel of knowledge users, we conducted a scoping review to answer: what is presented about the biomechanical efficacy, clinical effectiveness, cost-effectiveness, and workplace safety associated with compliant flooring systems that aim to prevent fall-related injuries in healthcare settings? We searched academic and grey literature databases. Any record that discussed a compliant flooring system and at least one of biomechanical efficacy, clinical effectiveness, cost-effectiveness, or workplace safety was eligible for inclusion. Two independent reviewers screened and abstracted records, charted data, and summarized results. RESULTS: After screening 3611 titles and abstracts and 166 full-text articles, we included 84 records plus 56 companion (supplementary) reports. Biomechanical efficacy records (n = 50) demonstrate compliant flooring can reduce fall-related impact forces with minimal effects on standing and walking balance. Clinical effectiveness records (n = 20) suggest that compliant flooring may reduce injuries, but may increase risk for falls. Preliminary evidence suggests that compliant flooring may be a cost-effective strategy (n = 12), but may also result in increased physical demands for healthcare workers (n = 17). CONCLUSIONS: In summary, compliant flooring is a promising strategy for preventing fall-related injuries from a biomechanical perspective. Additional research is warranted to confirm whether compliant flooring (i) prevents fall-related injuries in real-world settings, (ii) is a cost-effective intervention strategy, and (iii) can be installed without negatively impacting workplace safety. Avenues for future research are provided, which will help to determine whether compliant flooring is recommended in healthcare environments.
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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 | 0.021 | 0.095 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".