Zeynep Altinay
I am an assistant professor of data visualization at University of Nevada, Reno. I teach classes in digital media as applied to professional communications including social media applications.
My research integrates many aspects of science, technology, and society. I pursue research in the areas of risk communication, science/ environmental/ health communication, visual communication, and digital literacy. I study the persuasive role of visual communication, and how digital production techniques in visual media make us think, feel and behave about many pressing environmental issues of our time. I am currently investigating the cognitive and emotional responses to media and strategic use of environmental narratives in digital platforms. My research and teaching interests overlap in the areas of visual communication, digital communication, infographics and visual display of quantitative information. Most recently, I have been studying social media network structures as they relate to science and health communication.
At LSU, I was involved with the Media Effects Lab conducting experimental research to measure human behavior. Examples of coursework include quantitative and qualitative research methods, statistics, digital communication, public opinion, survey methods, and media effects. I took outside courses from LSU’s School of the Coast and Environment that focused on environmental policy, conflict resolution, environmental planning, and environment and energy. My research is closely tied to experimental design, survey design, and focus group discussions.
I have an MS in Environmental Science from Indiana University School of Public and Environmental Affairs and an MA in Journalism. I have taught coastal environmental communication, science writing, visual communication, and public relations.
Supervisors: Amy Reynolds, Meghan Sanders, and Margaret Reams
My research integrates many aspects of science, technology, and society. I pursue research in the areas of risk communication, science/ environmental/ health communication, visual communication, and digital literacy. I study the persuasive role of visual communication, and how digital production techniques in visual media make us think, feel and behave about many pressing environmental issues of our time. I am currently investigating the cognitive and emotional responses to media and strategic use of environmental narratives in digital platforms. My research and teaching interests overlap in the areas of visual communication, digital communication, infographics and visual display of quantitative information. Most recently, I have been studying social media network structures as they relate to science and health communication.
At LSU, I was involved with the Media Effects Lab conducting experimental research to measure human behavior. Examples of coursework include quantitative and qualitative research methods, statistics, digital communication, public opinion, survey methods, and media effects. I took outside courses from LSU’s School of the Coast and Environment that focused on environmental policy, conflict resolution, environmental planning, and environment and energy. My research is closely tied to experimental design, survey design, and focus group discussions.
I have an MS in Environmental Science from Indiana University School of Public and Environmental Affairs and an MA in Journalism. I have taught coastal environmental communication, science writing, visual communication, and public relations.
Supervisors: Amy Reynolds, Meghan Sanders, and Margaret Reams
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Papers by Zeynep Altinay
Purpose
This study aimed to analyze the use of electronic medical records (EMRs) to improve patient engagement with health information. The study examined two distinct behaviors: continued use of EMRs and not using EMRs (non-adoptive behavior).
Methods
Secondary analysis of a cross-sectional national survey was conducted. The data were interpreted within the Unified Theory of Acceptance and Use of Technology (UTAUT) model to assess the factors that influenced patients’ use of EMRs. Logistic regression analyses were also carried out to identify the significant predictors of non-adoptive behavior.
Results
The results of the study showed that the degree to which participants perceived the technology as easy to use, prior experience in accessing health data through technology, frequency of provider visits, and perceived poor health were indicators of continued use of EMRs. Logistic regression analyses revealed that gender, age, race/ethnicity, education, and type of insurance coverage were significant predictors of some of the barriers/preferences of non-adoptive behavior.
Conclusions
The study concluded that the UTAUT model can be effectively applied in healthcare settings to better understand patients’ use of EMRs and improve health information exchange between healthcare providers and patients. Further exploration is needed to differentiate between various behaviors to better meet the needs of patients and improve health outcomes. Overall, the findings highlight the importance of considering patient factors when implementing EMR systems in healthcare settings.
Methods: We test the predictive power of selected components related to the HBM (perceived susceptibility, perceived severity, and cues to action) for intentions to seek information about ambient air quality. We surveyed 325 individuals throughout Nevada where poor air quality
poses a risk for vulnerable populations.
Results: Ordinal logistic regression analyses showed that experiencing mucous membrane symptoms (eye itching, nose irritation, and dry throat/cough), perceived severity to future health threats, and having an at-risk member in the household positively and significantly
predicted intentions to seek air quality information. Experiencing neuropsychological symptoms (fatigue, feeling heavy-headed, and nausea/dizziness), and having a cardiovascular or a respiratory condition did not have significant effects on reported intentions.
Conclusions: We discuss how the results of this study can be integrated into health communication practices to increase public engagement with air quality information as a personal intervention measure.
Full text: https://srhe.tandfonline.com/doi/full/10.1080/14703297.2020.1786432?needAccess=true
KEYWORDS: climate communication, message framing, place attachment, risk perceptions, visual communication
Technical Reports by Zeynep Altinay
Purpose
This study aimed to analyze the use of electronic medical records (EMRs) to improve patient engagement with health information. The study examined two distinct behaviors: continued use of EMRs and not using EMRs (non-adoptive behavior).
Methods
Secondary analysis of a cross-sectional national survey was conducted. The data were interpreted within the Unified Theory of Acceptance and Use of Technology (UTAUT) model to assess the factors that influenced patients’ use of EMRs. Logistic regression analyses were also carried out to identify the significant predictors of non-adoptive behavior.
Results
The results of the study showed that the degree to which participants perceived the technology as easy to use, prior experience in accessing health data through technology, frequency of provider visits, and perceived poor health were indicators of continued use of EMRs. Logistic regression analyses revealed that gender, age, race/ethnicity, education, and type of insurance coverage were significant predictors of some of the barriers/preferences of non-adoptive behavior.
Conclusions
The study concluded that the UTAUT model can be effectively applied in healthcare settings to better understand patients’ use of EMRs and improve health information exchange between healthcare providers and patients. Further exploration is needed to differentiate between various behaviors to better meet the needs of patients and improve health outcomes. Overall, the findings highlight the importance of considering patient factors when implementing EMR systems in healthcare settings.
Methods: We test the predictive power of selected components related to the HBM (perceived susceptibility, perceived severity, and cues to action) for intentions to seek information about ambient air quality. We surveyed 325 individuals throughout Nevada where poor air quality
poses a risk for vulnerable populations.
Results: Ordinal logistic regression analyses showed that experiencing mucous membrane symptoms (eye itching, nose irritation, and dry throat/cough), perceived severity to future health threats, and having an at-risk member in the household positively and significantly
predicted intentions to seek air quality information. Experiencing neuropsychological symptoms (fatigue, feeling heavy-headed, and nausea/dizziness), and having a cardiovascular or a respiratory condition did not have significant effects on reported intentions.
Conclusions: We discuss how the results of this study can be integrated into health communication practices to increase public engagement with air quality information as a personal intervention measure.
Full text: https://srhe.tandfonline.com/doi/full/10.1080/14703297.2020.1786432?needAccess=true
KEYWORDS: climate communication, message framing, place attachment, risk perceptions, visual communication