Virtual Reality for Workplace Violence Training of Health Care Workers: Pilot Mixed Methods Usability Study
Notice bibliographique
Résumé
Background: Workplace violence (WPV) is a growing concern in health care, adversely impacting frontline providers, patients, and visitors. Traditional training programs have demonstrated limited long-term effectiveness in equipping health care professionals with de-escalation and crisis management skills. Virtual reality (VR) may offer an opportunity to create an innovative, immersive, and engaging platform for WPV training that could address the limitation of conventional methods. Objective: The aim of this pilot usability study was to assess the user experience of a prototype VR training course designed to prepare frontline health care staff for WPV scenarios. We evaluated the VR system's practicality, engagement, and perceived value and identified areas for improvement. Methods: A cross-sectional, mixed methods study was conducted with 13 frontline health care providers. Four pilot-training modules were developed and deployed in a VR environment on stand-alone headsets to address a variety of topics around WPV: Situational Awareness, Self-Awareness and Self-Regulation, Team Dynamics, and Evasive Maneuvers. Participants engaged with each module while providing qualitative feedback during the training. Qualitative feedback was analyzed using a rapid qualitative analysis technique. After completing the pilot training courses, participants completed surveys on usability (System Usability Scale) and user experience (mini Player Experience Inventory) and shared first impressions via Reaction Cards. Results: Participants found the pilot VR training to be engaging (mini Player Experience Inventory; mean 5.23, SD 1.34), with 89% of Reaction Card responses reflecting positive impressions such as "valuable," "creative," and "accessible." However, the overall System Usability Scale score (mean 63.30, SD 9.53) indicated room for improvement in usability. Although participants identified the VR system as manageable and intuitive, first-time users experienced challenges navigating the virtual environment. We identified four themes from qualitative feedback: (1) Perceived Value, (2) Technical and Navigational Barriers, (3) User Preferences, and (4) Vision. Participants described the VR training modules as refreshing due to the immersion in complex environments and noted areas for improvements in the tone and emotional expressiveness of nonplayer characters. Conclusions: Despite reported limitations, VR training has the potential to be a useful WPV training tool. It offers an immersive, hands-on, and safe environment for health care professionals to practice but may present challenges in engaging learners with the training objectives initially. While overall engagement and value in the training were high, refining dialogue realism and technical usability will support wider adoption. Future iterations of the pilot material may benefit from exploring role-specific content, multiplayer functionality, and integration of artificial intelligence-driven interactions to enhance responsiveness. Further research should compare VR WPV trainings with traditional trainings to evaluate differences in short- and long-term training effectiveness.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».