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ACADEMIC RESEARCH PROJECTS List of Publications
eHealth Literacy and Information Search Behaviors
As everyday users heavily rely on search engines to access health information, not everyone has the same skills to search for health information online. There have been scales developed to measure people's electronic health (eHealth) literacy. However, there have not been many studies that investigated the relationship between perceived eHealth literacy and health consumers' actual information search behaviors. My dissertation study aims to bridge this research gap. The results from my study can facilitate the measurement of eHealth literacy from a more objective perspective.
Question: How do health consumers' perceived skills to search health information affect their actual information search behaviors and search outcomes?
Methods: In-lab within-subject experimental design, pretest-posttest design, eye- tracking, retrospective think-aloud
Analysis: Content analysis, nonparametric statistic, Beta regression, Poisson regression, generalized linear mixed model, mediation analysis
Consumer Longitudinal Health Information Needs and Search Behavior
Searching for health information is one of the most frequent internet activities. Most health concerns tend to last for a period of time. Yet, the study of consumer online health information search (OHIS) has been primarily based on session-based observations generated in labs or search engine logs. Thus far, we know little about how people search for health information over time. This project addresses this gap by studying consumers’ OHIS in natural settings over a 3-month period. The project will generate much-lacked knowledge about consumer longitudinal OHIS behavior to inform personalized health information search experience design and guide future large-scale search log analyses.
This is a Google Faculty Research Award Project (PI: Dr. Yan Zhang; CO-PI: Dr. Jacek Gwizdka)
Question: How do health consumers, especially those dealing with chronic health issues, seek and search for health information in their everyday life?
Methods: Longitudinal study, interview, diary study, log data
Analysis: Working progress
Consumers’ Evaluation of the Quality of Online Health Information: A Mixed Method study
Instead of passively receiving health information from healthcare providers, health consumers now are taking a more active role in seeking health information online. With numerous online sources available on the interest, it is essential to understand how health consumers evaluate online health information from different types of sources. In this study users evaluated health information derived from governmental, commercial, and user-generated sources. Eye-tracking device and retrospective think-aloud were employed to interpret how participants evaluate the quality of online health information. The results of the study can inform the design of better web spaces to support health consumers' experience in seeking online health information.
Question: How do eHealth literacy and information source affect credibility evaluation?
Methods: In-lab within-subject experimental design, Graeco-Latin Square design, eye-tracking, retrospective think-aloud
Analysis: Content analysis, mixed-effects logistic regression, generalized linear mixed models, negative binomial mixed model, nonparametric statistic
Relevance Mining and Detection System
The internet has changed the ways in which people seek news. With the development of technology, nowadays news readers are more likely to access news online. During the information searching process, search engine result pages (SERPs) are usually the first stage of online news selection and evaluation. Hence, in this study participants were asked to conduct open web search. We employed eye-tracking to interpret participants' visual attention as relevance criteria judgment. Retrospective think-aloud was also conducted to understand the criteria news seekers employed in selecting relevant news on SERPs and the process of how these criteria are prioritized and aggregated.
Question: How do users evaluate information relevance on Google SERPs?
Methods: In-lab within-subject experimental design, eye-tracking, retrospective think-aloud
Analysis: Content analysis, Kruskal-Wallis nonparametric test
A System and Service Design to Enhance Individual's Motivation to Participate in Road-Running Races
With the use of mobile devices, many people turned to mobile application to manage their health, wellness, and physical activities. Besides keeping records of one's health and exercising condition, some mobile applications could also share personal information with friends and family; thus forming an online community to support and motivate one's health and exercising goal. Nevertheless, currently most of the physical activity applications put emphasis only on active users and do not consider people from the online community as potential users. This research project aims to use road-running as an example and design a physical activity social platform so that users (active users and online community) with various motivations and needs could all be part of an exercise event.
Question: How does the design of a physical activity social platform motivate users to participate in exercise events?
Methods: Survey
Analysis: Path analysis
Development of Wearable Real-Time Sensing Technology for Detecting Acute Heart Disease
As people started to age, especially in the era of an aging society, their physical and mental health conditions would start to degenerate, which is one of the major causes of chronic diseases such as heart disease. With the development of technology, wireless and sensor technologies provide a method to continuously record people’s biomedical signals (e.g., heart rate). By developing a wearable device, it may enhance the diagnosis and treatment of users’ everyday health conditions. In this study, we developed and examined a smart clothing system that targeted clinically high-risk patients such as older adults and older adults with chronic diseases. Through research, we were able to understand potential users' perceptions and willingness to utilize wearable technologies to monitor their daily health conditions.
Question: What are older adults' and patients' perceptions and acceptance of wearing smart clothing that can monitor their health conditions?
Methods: Survey, scenarios, interview
Analysis: Structural equation modeling
Determinants of User Acceptance of a Specific Social Platform for Older Adults
The use of the Internet and social applications has many benefits for the elderly, but numerous investigations have shown that the elderly do not perceive online social networks as a friendly social environment. Therefore, TreeIt, a social application specifically designed for the elderly, was developed for this study. In the TreeIt application, seven mechanisms promoting social interaction were designed to allow older adults to use social networking sites to increase social connection, maintain the intensity of social connections, and strengthen the social experience. This study’s main objective was to investigate how user interface design affects older people’s intentions and attitude related to using social networking sites.
Question: How does user interface design affect older people’s intention and attitude related to using SNSs?
Methods: Survey
Analysis: Structural equation modeling
Usability Testing of Smartphone Gestures on Various Smartphone Sizes by Different Age Group Users
The touch panel has been widely used in various devices and has brought about convenient and novel human-computer interactions. Among all devices, smartphones are the most widely used touch-screen products. In addition to the high usage, smartphones vary in display sizes to meet the needs of users of different age groups. Hence, the focus of this study is to test the usability of 3 different sizes of smartphones by children, adults, and the elderly. Three existing gestures used by the Android system were evaluated: drag, pinch, and double-touch drag. Additionally, two re-design gestures were tested: multi-long press and slide down. The users' performances were measured based on their overall time, success time, accuracy, Fitts' Law values, and a subjective questionnaire.
Question: How do users from different age groups perform gestures on different smartphone sizes?
Methods: Two-way mixed-design ANOVA, usability testing, Fitts' Law, usability satisfaction questionnaire
Analysis: ANOVA
Ergonomic Study on 3D Animation Film Design
When 3D object starts from different locations and moves in different velocities, it would affect the viewers’ perception of the naturalness and harmony of the object and the whole image. Hence, in this project, we used a 50-inch stereoscopic display and investigated how 3D objects with different moving locations and moving velocities affected viewers' perception of the 3D image quality. The subjective visual comfort and image quality were measured to understand the optimal velocity and started moving disparity combination that could bring out the best subjective visual comfort and image quality.
Question: What is the optimal parameters combination to provide users the best subjective visual comfort and image quality when viewing 3D videos?
Methods: Taguchi experimental design, objective and subjective measurements
Analysis: ANOVA, nonparametric test
Fundamental Attribution Error in Conceptual and Perceptional Difficulties
In this research, we investigated whether concept and perception have an influence on each other, especially causing fundamental attribution errors. The experiment was a two-factor between-subjects design. Participants were asked to read an article, in which the font and order of the sentences were manipulated. The font (perceptional factor) was either easy or difficult to read. As for the order of the sentences, it was either in normal order or randomized, which would affect the reader’s understanding (conceptual factor) of the article. The result showed that concept and perception have an effect on each other and cause fundamental attribution error.
Question: How do concept and perception affect fundamental attribution errors?
Methods: Between-subject experimental design
Analysis: ANOVA
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