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Record W4386955776 · doi:10.1136/bmjopen-2022-070566

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

2023· article· en· W4386955776 on OpenAlexaff
Lars Clemmensen, Gry Jørgensen, Kristina Ballestad Gundersen, Lisa Charlotte Smith, Julie Midtgaard, Stéphane Bouchard, Christina Thomsen, Louise Turgut, Louise Birkedal Glenthøj

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsMedicineDistractionStress reductionCoercion (linguistics)EntertainmentVirtual realityReduction (mathematics)Protocol (science)Human–computer interactionPhysical therapyAlternative medicineCognitive psychologyVisual arts

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.842
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.260
GPT teacher head0.504
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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