Impact of a Virtual Reality Video ("A Walk-Through Dementia") on YouTube Users: Topic Modeling Analysis

• Published in: JMIR formative research Vol. 9; p. e67755
• Main Authors: Li, Xiaoli, Liu, Xiaoyu, Yin, Cheng, Collins, Sandra, Alanazi, Eman
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 16.04.2025
• Subjects: Alzheimer's disease; Application programming interface; Dementia - psychology; Dementia and Cognitive Decline; Extended Reality, Virtual Reality and Virtual Worlds; Female; Formative Evaluation of Digital Health Interventions; Humans; Male; Original Paper; Social Media - statistics & numerical data; Social networks; Usability and Technology Use Studies with Elder Subjects; Virtual Reality; Virtual Reality Interventions in Mental Health; United Kingdom > UK; virtual reality; Alzheimer disease; simulation; topic modeling; digital world; training; ADRD; experiential learning tool; BERT; public awareness; text mining; virtual tour; Bidirectional Encoder Representations from Transformers; YouTube; walk-through dementia; Alzheimer disease and related dementias; older adult; health care student; health care professional; virtual environment; VR video; social media comments; dementia; VR; VR application
• ISSN: 2561-326X; 2561-326X
• DOI: 10.2196/67755

Emerging research has highlighted the potential of virtual reality (VR) as a tool for training health care students and professionals in care skills for individuals with Alzheimer disease and related dementias (ADRD). However, there is limited research on the use of VR to engage the general public in raising awareness about ADRD. This research aimed to examine the impact of the VR video "A Walk-Through Dementia" on YouTube users by analyzing their posts. We collected 12,754 comments from the VR video series "A Walk-Through Dementia," which simulates the everyday challenges faced by individuals with ADRD, providing viewers with an immersive experience of the condition. Topic modeling was conducted to gauge viewer opinions and reactions to the videos. A pretrained Bidirectional Encoder Representations from Transformers (BERT) model was used to transform the YouTube comments into high-dimensional vector embeddings, allowing for systematic identification and detailed analysis of the principal topics and their thematic structures within the dataset. We identified the top 300 most frequent words in the dataset and categorized them into nouns, verbs, and adjectives or adverbs using a part-of-speech tagging model, fine-tuned for accurate tagging tasks. The topic modeling process identified eight8 initial topics based on the most frequent words. After manually reviewing the 8 topics and the content of the comments, we synthesized them into 5 themes. The predominant theme, represented in 2917 comments, centered on users' personal experiences with the impact of ADRD on patients and caregivers. The remaining themes were categorized into 4 main areas: positive reactions to the VR videos, challenges faced by individuals with ADRD, the role of caregivers, and learning from the VR videos. Using topic modeling, this study demonstrated that VR applications serve as engaging and experiential learning tools, offering the public a deeper understanding of life with ADRD. Future research should explore additional VR applications on social media, as they hold the potential to reach wider audiences and effectively disseminate knowledge about ADRD.