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Record W4416124076 · doi:10.2196/87619

Virtual Fresh Air Breaks in Locked Psychiatric Units: Pre–Post Study of Mood, Distress, and Anxiety With Evaluation of Feasibility and Acceptability (Preprint)

2025· article· en· W4416124076 on OpenAlexvenueno aff
Khalid Obaid Alshaibani, Eduardo Vargas, Joshua Van Alfen, Jesse Martinez-Kratz, Wen-Ki Fong, S. Nassir Ghaemi

Bibliographic record

VenueJMIR Mental Health · 2025
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsUsabilityAnxietyDistressHeadsetVirtual realityChecklistSession (web analytics)Cronbach's alpha

Abstract

fetched live from OpenAlex

BACKGROUND Supervised fresh-air breaks (FABs) were shown to be a promising method that can support individual health. Nevertheless, labor shortage, as well as other concerns related to safety and environment, can hinder its application in many healthcare settings. Virtual reality (VR) may offer an indoor, immersive alternative that replicates natural environments and supports emotional regulation in confined settings. OBJECTIVE To evaluate the immediate and short-term effects of a brief, nature-based virtual fresh-air break (VFAB) on mood, anxiety, and subjective distress, and to assess feasibility, acceptability, usability, presence, cybersickness, and safety among adult psychiatric inpatients. METHODS A prospective, single-arm pilot study was conducted on a 20-bed locked medical–surgical psychiatric unit at Tufts Medical Center between July and August 2025. Eligible adults were English-speaking, able to provide informed consent, and deemed by the treating team to be suitable for participation without any acute behavioral or safety concerns. Participants completed one 15-minute VFAB session using a standalone Meta Quest 2 headset (Nature Treks VR, Greener Games Ltd; Pine Vesta environment) while seated in a monitored private room. Mood, anxiety, and subjective distress were rated using 0–10 numeric scales before, immediately after, and 48 hours after the session. Post-session questionnaires assessed presence (modified Igroup Presence Questionnaire), usability (System Usability Scale [SUS]), and cybersickness (Virtual Reality Sickness Questionnaire [VRSQ]). Acceptability and feedback were collected post-session, and records were reviewed for safety outcomes within 48 hours. Data were analyzed using Friedman tests for repeated measures and Wilcoxon signed-rank tests with Bonferroni correction, with P < .05 considered statistically significant. RESULTS Of 64 patients screened, 39 (60.9 %) were eligible and 26 (66.7 % of eligible) participated. Most participants (19/26, 73.1 %) were restricted from physical FABs. Median anxiety scores decreased from 5.0 (pre-VR) to 2.0 (post-VR; P = .018) and median distress from 5.0 to 1.0 (P = .001), both returning toward baseline by 48 hours (P = .011 and P = .007). Mood increased non significantly from 5.0 to 7.0 (P = .052; overall P = .066). Usability was high (median SUS 80.0, IQR 72.5–86.9) and cybersickness low (median VRSQ 2.0, IQR 0–6). Presence ratings indicated strong immersion (general presence median 2.0). Nearly all sessions were completed (23/26, 88.5 %), and 69.2 % of participants strongly recommended the experience; 76.9 % wished to repeat it. No adverse events, including seizures, agitation, or restraints, occurred within 48 hours. CONCLUSIONS VFAB was feasible, acceptable, and safe in an acute psychiatric unit and produced immediate reductions in anxiety and distress. While effects were not sustained at 48 hours, the intervention was well tolerated with minimal cybersickness and high usability. Findings support evaluation of repeated sessions and comparative trials against supervised outdoor breaks.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.350
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations0
Published2025
Admission routes1
Has abstractyes

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