The cognitive and motor effects of immersive virtual reality in individuals with neurocognitive disorder: randomized controlled trial protocol
Bibliographic record
Abstract
OBJECTIVE: To assess the cognitive and motor effects of an intervention utilizing commercial immersive virtual reality (IVR) games in older adults diagnosed with mild neurocognitive disorder (mild NCD) or mild major neurocognitive disorder and compare these effects with those of a motor-cognitive integrated exercise program. METHODS: This randomized controlled trial will include volunteers aged 60 years and older diagnosed with mild NCD or mild major NCD. Participants will be randomly assigned to two groups, each undergoing two 45-minute sessions weekly for seven weeks. The Virtual Reality Group (VRG) will engage in six IVR games, while the Exercise Group (EG) will perform integrated motor-cognitive exercises. Outcomes will be measured using the mini-BESTest, Dynamic Gait Index, Box and Block Test, 1-minute sit-to-stand test, Grip Strength Test, Neurocognitive Battery, Word Accentuation Test, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Montreal Cognitive Assessment, and Functional Activities Questionnaire. Sample size calculation indicates 32 participants (16 per group) to achieve 80 % power with α = 0.05, accounting for 20 % attrition. The trial is registered at the Brazilian Clinical Trials Registry (RBR-2kk9vnh). RESULTS: It is hypothesized that participants in the VRG will demonstrate greater improvements in cognitive and motor performance compared to the EG. CONCLUSIONS: This study aims to determine whether commercial IVR games can serve as effective cognitive and motor interventions for individuals with mild NCD or mild major NCD.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.006 |
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".