THE SAFEST REVIEW: THE SHOCK-ABSORBING FLOORING EFFECTIVENESS SYSTEMATIC REVIEW IN CARE SETTINGS
Bibliographic record
Abstract
Abstract Falls in hospitals and care homes are a major issue of international concern. Falls cost the US $34 billion a year, with injurious falls being particularly life-limiting and costly. Shock-absorbing flooring decreases the stiffness of the ground surface to reduce the impact of a fall. There is a growing body of evidence on flooring for fall-related injury prevention, however no systematic review exists to inform practice. We systematically reviewed the evidence on the clinical and cost-effectiveness of shock-absorbing flooring use for fall-related injury prevention in care settings. We searched six databases, clinical trial registries, conference proceedings, theses/dissertations, websites, reference lists, conducted forward citation searches, and liaised with experts in the field. We conducted study selection, data collection, and critical appraisal independently in duplicate. We evaluated the influence of shock-absorbing flooring on fall-related injuries, falls, and staff work-related injuries. We adopted a mixed methods approach considering evidence from randomised, non-randomised, economic, qualitative, and implementation studies. We assessed and reported the quality of outcomes using the GRADE approach and Summary of Findings Tables. This review, conducted over the course of 2019, summarises the certainty of the evidence on whether and which shock-absorbing floors influence injuries from falls, the chance of someone falling over, and work-related injuries in staff (e.g. from manoeuvring equipment across softer floors). Our findings are applicable to health and social care professionals, buildings and facilities managers, carers, older adults, architects, and designers. Funded by National Institute for Health Research, Health Technology Assessment (ref 17/148/11); registered in PROSPERO (CRD42019118834).
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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 | 0.032 | 0.180 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.007 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".