Study protocol for virtual leisure investigating the effect of virtual reality-delivered stress reduction, entertainment and distraction on the use of coercion and need-based medication and patient satisfaction at a closed psychiatric intensive care unit - a mixed-methods pilot clinical trial
Bibliographic record
Abstract
INTRODUCTION: The environment at a psychiatric inpatient ward can lead to emotional distress and behavioural deviations in vulnerable individuals potentially resulting in conflicts, increased use of need-based medication and coercive actions, along with low satisfaction with treatment. To accommodate these challenges, recreational and entertaining interventions are recommended. The tested interventions have, however, shown varying effects and demand a high degree of planning and staff involvement while being difficult to adapt to individual needs. Virtual reality (VR) may help overcome these challenges. METHODS AND ANALYSIS: The study is a mixed-methods clinical trial with a target sample of 124 patients hospitalised at a closed psychiatric ward in the capital region of Denmark. Outcomes (eg, coercion, need-based medication and perceived stress) for a 12-month period where all patients are offered VR-based recreational experiences during their hospitalisation will be compared with outcomes for a 12-month period where VR is not offered. Feasibility and acceptability will be explored with qualitative interviews supplemented with non-participant observations and focus groups. The study began on 1 January 2023, and we expect to complete data collection by 31 December 2024. ETHICS AND DISSEMINATION: The study is registered at Danish Data Protection Agency (j.no P-2022-466) and is approved by the Committee on Health Research Ethics of the capital region of Denmark (j.no 22013313). All patients will be required to provide informed consent. Results from this study will be disseminated via peer-reviewed journals and congress/consortium presentations. TRIAL REGISTRATION NUMBER: NCT05654740.
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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 | 0.034 | 0.035 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.119 | 0.026 |
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".