Customized virtual reality naturalistic scenarios promoting engagement and relaxation in patients with cognitive impairment: a proof-of-concept mixed-methods study
Bibliographic record
Abstract
Being immersed in a natural context has a beneficial and pervasive impact on well-being. Virtual Reality (VR) is a technology that can help expose people to naturalistic scenarios virtually, overcoming obstacles that prevent them from visiting real natural environments. VR could also increase engagement and relaxation in older adults with and without cognitive impairment. The main aim of this study is to investigate the feasibility of a customized naturalistic VR scenario by assessing motion-sickness effects, engagement, pleasantness, and emotions felt. Twenty-three individuals with a diagnosis of cognitive impairment living in a long-term care home participated in our study. At the end of the entire VR experimental procedure with older adults, five health staff operators took part in a dedicated assessment phase focused on evaluating the VR procedure's usability from their individual perspectives. The tools administered were based on self-reported and observational tools used to obtain information from users and health care staff professionals. Feasibility and acceptance proved to be satisfactory, considering that the VR experience was well-tolerated and no adverse side effects were reported. One of the major advantages emerged was the opportunity to deploy customized environments that users are not able to experience in a real context.Trial Registration: National Institute of Health (NIH) U.S. National Library of Medicine, ClinicalTrials.gov NCT05863065 (17/05/2023).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".