Delivering clinical tutorials to medical students using the Microsoft HoloLens 2: A mixed-methods evaluation.

BACKGROUND: Mixed reality offers potential educational advantages in the delivery of clinical teaching. Holographic artefacts can be rendered within a shared learning environment using devices such as the Microsoft HoloLens 2. In addition to facilitating remote access to clinical events, mixed reality may provide a means of sharing mental models, including the vertical and horizontal integration of curricular elements at the bedside. This study aimed to evaluate the feasibility of delivering clinical tutorials using the Microsoft HoloLens 2 and the learning efficacy achieved. METHODS: Following receipt of institutional ethical approval, tutorials on preoperative anaesthetic history taking and upper airway examination were facilitated by a tutor who wore the HoloLens device. The tutor interacted face to face with a patient and two-way audio-visual interaction was facilitated using the HoloLens 2 and Microsoft Teams with groups of students who were located in a separate tutorial room. Holographic functions were employed by the tutor. The tutor completed the System Usability Scale, the tutor, technical facilitator, patients, and students provided quantitative and qualitative feedback, and three students participated in semi-structured feedback interviews. Students completed pre- and post-tutorial, and end-of-year examinations on the tutorial topics. RESULTS: Twelve patients and 78 students participated across 12 separate tutorials. Five students did not complete the examinations and were excluded from efficacy calculations. Student feedback contained 90 positive comments, including the technology's ability to broadcast the tutor's point-of-vision, and 62 negative comments, where students noted issues with the audio-visual quality, and concerns that the tutorial was not as beneficial as traditional in-person clinical tutorials. The technology and tutorial structure were viewed favourably by the tutor, facilitator and patients. Significant improvement was observed between students' pre- and post-tutorial MCQ scores (mean 59.2% Vs 84.7%, p < 0.001). CONCLUSIONS: This study demonstrates the feasibility of using the HoloLens 2 to facilitate remote bedside tutorials which incorporate holographic learning artefacts. Students' examination performance supports substantial learning of the tutorial topics. The tutorial structure was agreeable to students, patients and tutor. Our results support the feasibility of offering effective clinical teaching and learning opportunities using the HoloLens 2. However, the technical limitations and costs of the device are significant, and further research is required to assess the effectiveness of this tutorial format against in-person tutorials before wider roll out of this technology can be recommended as a result of this study.

Using Normative Data and Unilateral Hopping Tests to Reduce Ambiguity in Return-to-Play Decisions.

CONTEXT: After a lower extremity injury, patients often return to sport (RTS) when the injured limb's performance on unilateral hopping tests is similar to that of the uninjured limb. However, the exact target symmetry value patients must reach before the RTS is unclear. OBJECTIVE: To identify variables that predict limb symmetry index (LSI) values on 6 unilateral hopping tests in healthy, physically active adults. DESIGN: Cross-sectional study. SETTING: Research laboratory. PATIENTS OR OTHER PARTICIPANTS: In total, 275 healthy, physically active adults, consisting of recreational athletes (n = 198), National Collegiate Athletic Association Division I student-athletes (n = 56), and Army Reserve Officer Training Corps cadets (n = 21), volunteered to participate (143 men, 132 women, age = 20.16 ± 2.19 years, height = 172.66 ± 10.22 cm, weight = 72.64 ± 14.29 kg). INTERVENTION(S): Each participant completed 3 speed (6-m crossover-hop, side-hop, figure-8 hop) and 3 distance (triple-crossover-hop, lateral-hop, medial-hop) functional performance tests on both limbs. MAIN OUTCOME MEASURE(S): Mean performance of the dominant and nondominant limbs and LSI values. Two multiple regression models were used to find variables that might help to predict a participant's LSI for each functional performance test. RESULTS: The models helped to predict limb symmetry for 10 of the 12 multiple regressions. Unilateral limb performance was the best predictor of LSI values, as it was statistically significant in 11 of the 12 regression models. Sex and body mass index were significant predictor variables for the side hop and figure-8 hop, respectively. CONCLUSIONS: We found significant predictor variables that clinicians can use in the absence of baseline testing to determine patient-specific LSI values. Individualizing RTS decisions in this way may help to minimize subjectivity in the decision-making process and ensure a safe and timely return to competition.