A Novel Virtual Reality-Based Nature Meditation Program for Older Adults’ Mental Health: Results from a Pilot Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVES: The rapid aging of the global population necessitates innovative interventions to address older adults' mental health. This pilot study evaluated the feasibility, acceptability, and preliminary efficacy of a 4-week, 8-session nature-mindfulness-compassion program using immersive virtual reality (Embodied-and-Embedded-Mindfulness-Compassion-Framework - Virtual-Reality (EEMCF-VR)) for older adults' mental health. METHODS: = 12). Participants completed self-report assessments of stress, positive and negative emotions, coping self-efficacy, psychosocial well-being, mindfulness, and nature connectedness at baseline (T1), midpoint (T2), post-intervention (T3), and 4-week follow-up (T4). Additionally, the EEMCF-VR group completed program feedback (T3) and simulator sickness (T1-T3) questionnaires. RESULTS: EEMCF-VR met feasibility benchmarks (recruitment targets achieved, attrition < 15%) and was well-tolerated (minimal simulator sickness). Participant feedback indicated high acceptability. The EEMCF-VR group reported significantly lower stress and negative emotions at T2 and T4 compared to controls. Qualitative analysis highlighted perceived benefits and components to retain (e.g. video content) or refine (e.g. headset weight). CONCLUSIONS: EEMCF-VR demonstrated feasibility and acceptability, with promising effects on stress and mood, warranting investigation in larger trials. CLINICAL IMPLICATIONS: EEMCF-VR shows potential as a scalable intervention to reduce older adults' emotional distress.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".