Qin Hu

Ms. Qin Hu

University of Hyogo

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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QHQin Hu
Qin Hu
MUMaki Umeda
Maki Umeda
The coronavirus disease 2019 (COVID-19) has profoundly affected the psychological well-being of foreign residents. This study examines stress, anxiety, and depression levels in Chinese residents in Japan during the COVID-19 pandemic. It identifies risk factors and the roles of disaster preparedness and social support. An online survey among Chinese residents in Japan was conducted from 22 June to 14 July 2020. The Depression, Anxiety and Stress Scale, Disaster Preparedness for Resilience Checklist, and Social Support Rate Scale were used to measure psychological symptoms. Multivariable linear regressions identified the risk factors and positive effects of disaster preparedness and social support. Of the total 497 participants, 45.3%, 66.6%, and 54.3% reported severe stress, anxiety, and depressive symptoms, respectively. People with a lower level of education, a higher level of economic influence, the presence of COVID-19 symptoms, and confirmed or suspected family or friends in China were associated with higher levels of stress, anxiety, and depression. This study, to the best of our knowledge, is the first survey to reveal the protective role of disaster preparedness in reducing psychological symptoms during the pandemic. It offers unique data for further research on how to promote the mental health of vulnerable populations including foreign residents.

17 March 2025 in CIN: Computers, Informatics, Nursing
Verified
Journal Article
Open access
QHQin Hu
Qin Hu
HCHeyu Chen
Heyu Chen
CWCong Wang
Cong Wang
SLSimin Li
Simin Li
HCHua Cao
Hua Cao
YJYan Jiang
Yan Jiang
Technological advancements have fueled the integration of virtual reality into nursing education, presenting innovative teaching modalities. Nonetheless, a conspicuous gap exists in understanding the influencing factors that impact the quality of virtual reality experiences, thereby challenging educators in creating optimal learning ecosystems tailored to nursing curricula. Adopting the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines, a comprehensive search of electronic databases including PubMed, Embase, CINAHL, Web of Science, and the Cochrane Library was performed. Forty-five studies met the inclusion criteria, revealing a broad spectrum of factors affecting virtual reality experience quality. Human-centric factors encompassed cybersickness, accommodation for individuals who wear glasses, and left-handed, elderly, and women users. System-centric issues are mainly limited immersion and inadequate interaction. The synthesis of existing literature underscores the multifaceted nature of factors influencing virtual reality experience quality in nursing education. Recommendations include enhancing immersion and interaction, considering user diversity in design, and fostering international collaborations for content standardization.

29 March 2025 in Health Emergency and Disaster Nursing
Verified
Journal Article
Open access
PDF file
QHQin Hu
Qin Hu
YJYan Jiang
Yan Jiang
Introduction and Purpose/Objectives: Amidst escalating climate change and disasters, disaster nursing proficiency is vital for gauging public health emergency responses. Traditional training faces resource scarcity, safety issues, and struggles to replicate complex scenarios, hindering skill development. Cave Automatic Virtual Environment (CAVE) systems, with their high levels of immersion and interactivity, presents a novel solution for disaster nursing education. This study aims to leverage the ADDIE instructional design model (comprising Analysis, Design, Development, Implementation, and Evaluation) to develop a CAVE-based virtual reality scenario tailored for disaster nursing, with the objective of augmenting nurses’ abilities in nursing competence within disaster contexts.Approaches/Methods: The study comprised a systematic literature review for need benchmarking, practitioner interviews for real-world requirements, and expert panels for design refinement. Following content curation, scripting, and technical realization via 3D modeling and C# coding, exhaustive testing guaranteed functionality and user fit, resulting in a tailored, immersive VR platform for disaster nursing education.Results/Findings: By employing the ADDIE framework, this work generated a CAVE-based virtual reality simulation for disaster nursing, achieving striking fidelity through advanced visualization techniques and physics emulation, thereby significantly enhancing the authenticity and interactive dimensions of the learning experience. Further augmented with an integrated Learning Management System (LMS), the solution enables tailored tracking and evaluation mechanisms, forming a cornerstone for personalized training advancement in the realm of disaster nursing education.Discussion/Implication: The research enables personalized, high-stress scenario training in a safe space, bridging the theory-practice gap. It introduces innovative teaching methods for future healthcare workers, readying them for dynamic disaster challenges, ensuring real-world relevance and individual learner fit, enhancing crisis response preparedness and resilience.