The influence of a virtual reality entertainment program on depressive symptoms and sedentary behaviour in inpatient stroke survivors: a research protocol for a pilot randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Sedentary behaviour among stroke inpatients may be due to high rates of depressive symptoms after stroke. Thus, efforts to address depressive symptoms among stroke inpatients are warranted to in turn lessen sedentary behaviour. Despite evidence that virtual reality (VR) is emerging as a method to help with depression, the use of VR to improve depression among inpatient stroke survivors has yet to be studied. In this paper, we report on the protocol investigating the feasibility of a VR entertainment system at improving depressive symptoms among stroke survivors receiving inpatient rehabilitation. METHODS: In this single-blind randomized controlled trial, 30 inpatient stroke survivors from the rehabilitation unit at Kelowna General Hospital will be randomized to either (1) intervention: 3 times per week of VR entertainment for duration of inpatient rehabilitation or (2) control: usual care. Individuals will be included if they have a confirmed diagnosis of stroke, are 19 years of age or older, able to provide informed consent, have physician clearance to participate in the study (medically stable or fit), or are able to understand English. Outcome measures to address depressive symptoms (primary outcome), sedentary behaviour, motivation, anxiety, stress, and happiness (secondary outcome) will be administered at two timepoints: (1) baseline (T1) and (2) post-intervention (T2). Study analyses will consider study feasibility indicators and clinical (statistical) outcomes. Means and standard deviations (for continuous variables) and frequencies and proportions (for categorical variables) will be used to summarize the variables. Feasibility indicators will be dichotomized into either 'success' if they meet the a priori criteria, or 'revise' if they do not meet the criteria. Intervention effects post-intervention (T2) for the primary and secondary clinical outcomes will be estimated using linear regression including baseline (T1) controlling for age and sex. DISCUSSION: The results of this trial will add to our understanding of depression and sedentary behaviour among individuals receiving inpatient stroke rehabilitation as well as the feasibility of a VR entertainment program to improve depressive symptoms, which will in turn may lessen sedentary behaviour in inpatient stroke survivors. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04011202 . First posted July 8, 2019 (study postponed from March 2020 to July 2021 due to COVID-19).
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".