Personalised virtual reality in palliative care: clinically meaningful symptom improvement for some
Bibliographic record
Abstract
OBJECTIVES: This study examined the effects of virtual reality (VR) among palliative care patients at an acute ward. Objectives included evaluating VR therapy benefits across three sessions, assessing its differential impact on emotional versus physical symptoms and determining the proportion of patients experiencing clinically meaningful improvements after each session. METHODS: A mixed-methods design was employed. Sixteen palliative inpatients completed three personalised 20 min VR sessions. Symptom burden was assessed using the Edmonton Symptom Assessment Scale-Revised and quality of life with the Functional Assessment of Chronic Illness Therapy (FACIT-Pal-14). Standardised criteria assessed clinically meaningful changes. Quantitative data were analysed using linear mixed models. RESULTS: Quality of life improved significantly pre-VR to post-VR with a large effect size (Cohen's d: 0.98). Total symptom burden decreased after 20 min VR sessions (Cohen's d: 0.75), with similar effect sizes for emotional (Cohen's d: 0.67) and physical symptoms (Cohen's d: 0.63). Over 50% of patients experienced clinically meaningful improvements per session, though substantial individual variability occurred. CONCLUSIONS: This study reveals the nuanced efficacy of personalised VR therapy in palliative care, with over half of the patients experiencing meaningful benefits in emotional and physical symptoms. The marked variability in responses underscores the need for realistic expectations when implementing VR therapy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".