MétaCan
Menu
Back to cohort
Record W4408514261 · doi:10.2196/66557

Novel Virtual Reality Intervention for Stress Reduction Among Patients With or at Risk for Cardiovascular Disease: Mixed Methods Pilot Study

2025· article· en· W4408514261 on OpenAlexvenueno aff
Katherine Elizabeth Makaroff, Christopher Van, Vincent Grospe, Lynae Edmunds, Marcella Calfon Press, Karol E. Watson, Tamara B. Horwich

Bibliographic record

VenueJMIR Cardio · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintStress reductionIntervention (counseling)DiseaseMedicineVirtual realityReduction (mathematics)Stress (linguistics)GerontologyPsychologyPhysical therapyComputer scienceInternal medicineHuman–computer interactionWorld Wide WebPsychiatryMathematics

Abstract

fetched live from OpenAlex

Background: Virtual reality (VR) has emerged as a promising, low-risk strategy to manage many forms of psychological stress and may be a modality to improve cardiovascular health. Recent scientific statements on the mind-heart-body connection call for better adherence to psychological screening and adoption of more holistic "behavioral cardiology" interventions that improve the overall health of patients with or at risk for cardiovascular disease (CVD). Objective: The aim of this study is to assess safety and preliminarily explore how a VR experience can aid in stress reduction among patients with or at risk for CVD. Methods: A convergent mixed methods approach was used for this single-arm prospective pilot study. In total, 20 patients were recruited from the University of California Los Angeles adult cardiology clinics and cardiac rehabilitation. Surveys and physiologic parameters were collected before, during, and after a 30-minute VR experience aimed at relaxation. The primary outcome was the State-Trait Anxiety Inventory-State (STAI-S) scale. They participated in a 90-minute visit, during which they completed surveys, including the STAI-S scale, before and after a 30-minute VR experience. Physiological parameters were also collected before, during, and after the experience. Visits concluded with semistructured interviews analyzed with inductive thematic analysis to add depth and nuance to our analysis. Results: STAI-S scale scores after the VR experience were significantly decreased from baseline (median 31, IQR 28-38 vs median 24, IQR-29.25; P<.001). Verbal feedback revealed that participants experienced a relaxing sense of "distance from stress" moderated by unexpected, intense audiovisual components. Heart rate significantly decreased (mean 73, SD 8 vs mean 67, SD 6 beats per minute; P<.001), while blood pressure (mean systolic 128, SD 14 vs mean systolic 129, SD 18 mm Hg; P=.75 and mean diastolic 79, SD 9 vs mean diastolic 80, SD 10 mm Hg; P=.60) and galvanic skin response (mean 0.74, SD 0.89 vs mean 0.70, SD 0.57 microsiemens; P=.45) remained the same. Changes in heart rate variability parameters were consistent with increased vagal tone over time but were only statistically significant at certain time points. Survey results and interviews generally indicated safety, tolerability, and openness to using VR again. Conclusions: This sample of patients with CVD or risk of CVD had above-average stress, consistent with epidemiological data; the statistically and clinically significant decrease in subjective perception of stress partially converged with physiologic data. Overall, the VR intervention was a safe and feasible stress reduction method. Future research is needed to evaluate the effectiveness of this immersive therapy in reducing cardiovascular risk profiles.

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)0.003
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.402
Teacher spread0.359 · 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

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJMIR CardioSame topicCardiac Health and Mental HealthFrench-language works237,207