Virtual reality game-based training for preventing falls among community-dwelling older adults with mild cognitive impairment: a pilot randomized control trial study
Bibliographic record
Abstract
Abstract Using a Virtual Reality (VR) game-based application represents an innovative approach to falls prevention in community aged care service. The study investigated the effects of VR training on falls prevention among community-dwelling older adults with mild cognitive impairment. A pilot randomized controlled trial was conducted to compare the effects of full-immersive VR training with group-based exercise (Baduanjin) training on falls prevention. Eighteen participants were recruited through convenience sampling and were randomly assigned to either the VR group or the non-VR exercise group. Both groups participated in 16 falls prevention training sessions over eight weeks. Participants, identified with mild cognitive impairment (MCI), underwent three fall risk measurements. They had been screened using Montreal Cognitive Assessment (HK-MoCA). The primary outcomes assessed included changes in physical risk factors of falls (i.e. functional mobility, walk speed and postural balance), and the secondary outcomes assessed included changes in executive function and fall efficacy. The measurement of physical outcomes was Time Up and Go test (TUG), Berg balance scale (BBS) and Six-minute Walk Test (6MWT). The participants’ executive function and fear of falling were assessed through the Trail marking test (TMTA and TMTB) and the Fall Efficacy International scale (FES-I). The results showed that the VR group had significantly greater improvement than the non-VR group on measures of cognitive-motor performance, such as global cognition, functional mobility, balance and walk speed over time. However, no significant differences were observed between the two groups in executive functions and the fall efficacy. The study provides potential evidence that VR game-based cognitive-motor training can be effective for fall prevention in community dwelling older adults with MCI. However, the findings do not support significant improvements in secondary outcomes. Despite this, the growing trend of VR research suggests increasing interest and potential for future applications in aged care and rehabilitation services.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".