Ph.D Candidate | Research Assistant
Mixed Method Researcher: Eye Tracking, Usable Security, Privacy, Accessibility
EQUI-Tech Lab
Research Goal
Recent Publication
I am conducting research to understand the interaction between individuals with mild dementia and healthy older adults with digital health information. My approach involves using eye-tracking and facial recognition technology to evaluate cognitive load, emotional reactions, and trust. Furthermore, my investigation delves into the aspects of privacy and trust concerning online health information, aiming to enhance the availability of dependable online health resources.
“Training Adults with Mild to Moderate Dementia in ChatGPT: Exploring Best Practices”
Recent Projects
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This study explores Nomophobia, examining smartphone usage among older adults and individuals with dementia to understand its impact on digital well-being. Additionally, the research aims to assess the extent of reliance on smartphones within these demographics, shedding light on the implications of this dependency.
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We examine how individuals with mild dementia engage with digital health information, focusing on cognitive load, emotional responses, and trust. Using eye-tracking and facial expression analysis, we assess their interaction with different online dementia information sources, investigating how they process challenging content and their level of trust in these sources.
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Mobile phone usage has become ubiquitous in recent decades, including among older adults and those with age-related cognitive changes. The research reveal common interaction patterns, app preferences, and privacy/security measures among these groups, offering insights for developing apps tailored to their needs and suggesting future research directions.
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Our study aimed to comprehensively analyze digital dementia information by exploring its readability, linguistic, psychological, and emotional aspects, as well as identifying its intended target audiences. To achieve this, we performed an in-depth textual analysis encompassing three distinct categories of text- based digital dementia information available in English: a dataset consisting of 300 medical articles, 35 websites, and 50 blogs.