Virtual Reality Therapy in Palliative Care: A Case Series
Bibliographic record
Abstract
Objectives Virtual reality (VR) opens a variety of therapeutic options to improve symptom burden in patients with advanced disease. Until to date, only few studies have evaluated the use of VR therapy in the context of palliative care. This case series aims to evaluate the feasibility and acceptability of VR therapy in a population of palliative care patients. Methods In this single-site case series, we report on six palliative care patients undergoing VR therapy. The VR therapy consisted of a one-time session ranging between 20 to 60 minutes depending on the patient's needs and the content chosen for the VR sessions. A semi-structured survey was conducted and the Edmonton Symptom Assessment System (ESAS) and the Distress Thermometer were performed pre- and post-intervention. Results Overall, VR therapy was well accepted by all patients. Five out of six patients reported having appreciated VR therapy. There were individual differences of perceived effects using VR therapy. The semi-structured survey revealed that some patients felt a temporary detachment from their body and that patients were able to experience the VR session as a break from omnipresent worries and the hospital environment (“I completely forgot where I am”). There was a considerable reduction in the total ESAS score post-treatment (T0 ESAS Tot = 27.2; T1 ESAS Tot = 18.8) and a slightly reduction in distress (T0 DT Tot = 4.4; T1 DT Tot = 3.8). However, two patients were more tired after the intervention. Significance of Results: Our preliminary results demonstrate that VR therapy is acceptable, feasible and safe for use within a palliative care population and appears to be a viable treatment option. Clinical trials are both warranted and necessary to confirm any therapeutic effects of VR therapy, as is the need to tailor VR systems better for use in palliative care settings.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".