Publications by authors named "Emily M He"
Games Health J
August 2024
Article Synopsis
- Hospitalized children and their caregivers often face anxiety, and using virtual reality (VR) can help reduce this stress, but the effectiveness of different software design elements remains unclear.
- A study involving 202 participants evaluated how aspects like fictional environments and graphics quality influence feelings of awe and overall engagement with a custom VR application.
- Results showed that fictional settings increased awe in pediatric patients, while high-quality graphics were more effective for adult caregivers, and all measures of awe positively correlated with engagement. Future research will look into additional VR design elements.
Article Synopsis
- - Pediatric patients often experience anxiety during mask induction for general anesthesia, and augmented reality (AR) headsets are being explored as a potential way to help reduce this anxiety.
- - In a study involving 50 children using AR for mask induction compared to 150 controls receiving standard care, those using AR showed significantly lower mask rejection rates (4% vs. 19.3%) and high levels of cooperation (98% vs. 91.3%).
- - The study concluded that AR improves mask acceptance without affecting cooperation or the incidence of emergent delirium, suggesting it could be a helpful non-pharmacological option in clinical settings.
J Occup Environ Hyg
January 2022
Article Synopsis
- Face masks are effective in reducing SARS-CoV-2 transmission, but people often avoid wearing them due to discomfort.
- A study identified key factors affecting mask comfort: air resistance, water vapor permeability, and face temperature change, using surveys and physiological experiments.
- Machine learning models, particularly a multiple linear regression model, were developed to predict mask comfort scores, aiming to enhance user experience and encourage higher compliance with mask-wearing during the pandemic.
J Occup Environ Hyg
December 2021
Article Synopsis
- The COVID-19 pandemic pushed universities to adopt remote or hybrid learning, raising the need for effective risk assessments for reopening spaces safely.
- A quantitative model was developed to calculate infection probabilities based on parameters like viral shedding rates, room capacity, and air exchange, enabling universities to evaluate risks in various environments.
- The model, which has shown low infection risks under certain conditions, was successfully applied to campuses like Harvard and Stanford, and a user-friendly web application was created to help assess infection risks, although validation with real data is still necessary.
