Using a 360° Virtual Reality or 2D Video to Learn History Taking and Physical Examination Skills for Undergraduate Medical Students: Pilot Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Learning through a 360° virtual reality (VR) or 2D video represents an alternative way to learn a complex medical education task. However, there is currently no consensus on how best to assess the effects of different learning materials on cognitive load estimates, heart rate variability (HRV), outcomes, and experience in learning history taking and physical examination (H&P) skills. OBJECTIVE: The aim of this study was to investigate how learning materials (ie, VR or 2D video) impact learning outcomes and experience through changes in cognitive load estimates and HRV for learning H&P skills. METHODS: This pilot system-design study included 32 undergraduate medical students at an academic teaching hospital. The students were randomly assigned, with a 1:1 allocation, to a 360° VR video group or a 2D video group, matched by age, sex, and cognitive style. The contents of both videos were different with regard to visual angle and self-determination. Learning outcomes were evaluated using the Milestone reporting form. Subjective and objective cognitive loads were estimated using the Paas Cognitive Load Scale, the National Aeronautics and Space Administration Task Load Index, and secondary-task reaction time. Cardiac autonomic function was assessed using HRV measurements. Learning experience was assessed using the AttrakDiff2 questionnaire and qualitative feedback. Statistical significance was accepted at a two-sided P value of <.01. RESULTS: All 32 participants received the intended intervention. The sample consisted of 20 (63%) males and 12 (38%) females, with a median age of 24 (IQR 23-25) years. The 360° VR video group seemed to have a higher Milestone level than the 2D video group (P=.04). The reaction time at the 10th minute in the 360° VR video group was significantly higher than that in the 2D video group (P<.001). Multiple logistic regression models of the overall cohort showed that the 360° VR video module was independently and positively associated with a reaction time at the 10th minute of ≥3.6 seconds (exp B=18.8, 95% CI 3.2-110.8; P=.001) and a Milestone level of ≥3 (exp B=15.0, 95% CI 2.3-99.6; P=.005). However, a reaction time at the 10th minute of ≥3.6 seconds was not related to a Milestone level of ≥3. A low-frequency to high-frequency ratio between the 5th and 10th minute of ≥1.43 seemed to be inversely associated with a hedonic stimulation score of ≥2.0 (exp B=0.14, 95% CI 0.03-0.68; P=.015) after adjusting for video module. The main qualitative feedback indicated that the 360° VR video module was fun but caused mild dizziness, whereas the 2D video module was easy to follow but tedious. CONCLUSIONS: Our preliminary results showed that 360° VR video learning may be associated with a better Milestone level than 2D video learning, and that this did not seem to be related to cognitive load estimates or HRV indexes in the novice learners. Of note, an increase in sympathovagal balance may have been associated with a lower hedonic stimulation score, which may have met the learners' needs and prompted learning through the different video modules. TRIAL REGISTRATION: ClinicalTrials.gov NCT03501641; https://clinicaltrials.gov/ct2/show/NCT03501641.
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 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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,001 |
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 ».