A Preoperative Virtual Reality App for Patients Scheduled for Cardiac Catheterization: Pre–Post Questionnaire Study Examining Feasibility, Usability, and Acceptability
Notice bibliographique
Résumé
BACKGROUND: Pre- and postoperative anxiety is a common phenomenon associated with negative postoperative outcomes. Symptoms of posttraumatic stress disorder, such as fear, nightmares, and sleep deprivation, are prevalent in approximately 30% to 50% of patients following discharge from intensive care units after cardiac surgery. Preliminary evidence suggests a promising role of virtual reality (VR) in preventing stress-related reactions using stress inoculation training. Such training enables cognitive preparation of individuals for stressful situations, thereby becoming more tolerant and resistant to stress, subsequently reducing the risk of potential negative psychological consequences. This study investigated a preoperative VR app-Pre-View-aimed at better informing and preparing patients for cardiac catheterization. OBJECTIVE: This study aims to assess the feasibility, usability, and acceptability of Pre-View in patients undergoing cardiac catheterization. METHODS: Eligible participants were adults scheduled for elective cardiac catheterization. Pre-View comprised an interactive virtual representation of the whole care process related to cardiac catheterization, from entering the hospital for admission to postprocedural stay and discharge. These processes were represented through 360° videos and interactive photos. Self-report questionnaires were completed at baseline (ie, before catheterization and after undergoing the VR experience) and after cardiac catheterization. Outcome measures included user experience and satisfaction, VR presence and immersive tendencies, and user friendliness. The perceived effectiveness was assessed exploratively. RESULTS: A total of 8 individuals, with a mean age of 67 (SD 7.5) years, participated in this study. Half of them underwent the VR experience at the hospital and the other half at home. Participants reported high levels of presence in the virtual environment (Presence Questionnaire score: mean 129.1, SD 13.4). The usability of Pre-View was well evaluated (System Usability Scale score: mean 89.1, SD 12.0), and patient satisfaction was high (Client Satisfaction Questionnaire score: mean 27.1, SD 3.2). Usability and satisfaction scores were higher for participants who underwent Pre-View at home versus those who underwent Pre-View at the hospital, although the latter group was significantly older; 72.8 versus 61.3, respectively. All participants reported Pre-View to be effective in terms of feeling better informed about the care process of cardiac catheterization. Most participants (7/8, 88%) reported Pre-View to be effective in terms of feeling better prepared for cardiac catheterization, acknowledging the potential of Pre-View in reducing negative psychological consequences after catheterization. CONCLUSIONS: The results provide initial support for the feasibility and acceptability of a preoperative VR app, creating a virtual environment that supports patient education and preparation for upcoming cardiac catheterization. More studies are needed to further investigate the effects of VR as a tool to better prepare patients for medical procedures, its effectiveness in reducing negative patient outcomes (eg, anxiety, stress, and postoperative recovery outcomes), and the generalizability of effects across different settings and patient populations.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».