Matching Items (2)
Description
Beliefs about change reflect how we understand phenomena and what kind of predictions we make for the future. Cyclical beliefs about change state that events are in a constant flux, and change is inevitable. Linear beliefs about change state that events happen in a non-fluctuating pattern and change is not commonplace. Cultural differences in beliefs about change have been documented across various domains, but research has yet to investigate how these differences may affect health status predictions. The present study addresses this gap by inducing different beliefs about change in a European-American college sample. Health status predictions were measured in terms of predicted likelihood of exposure to the flu virus, of contraction of the flu, and of receiving a flu vaccine. Most differences were observed among those who have a recent history of suffering from the flu. Among them, cyclical thinkers tended to rate their likelihood for exposure and contraction to be higher than linear thinkers. However, linear thinkers indicated that they were more likely to receive a flu vaccine. The different patterns suggest the possibility that cyclical beliefs may activate concepts related to cautionary behaviors or pessimistic biases, while linear beliefs may activate concepts related to taking action and exercising control over the environment. Future studies should examine the interplay between beliefs about change and the nature of the predicted outcome.
ContributorsKim, Summer Hyo Yeon (Author) / Kwan, Virginia S. Y. (Thesis advisor) / Neuberg, Steven L. (Committee member) / Cohen, Adam B. (Committee member) / Arizona State University (Publisher)
Created2012
Description
The 2017-2018 Influenza season was marked by the death of 80,000 Americans: the highest flu-related death toll in a decade. Further, the yearly economic toll to the US healthcare system and society is on the order of tens of billions of dollars. It is vital that we gain a better understanding of the dynamics of influenza transmission in order to prevent its spread. Viral DNA sequences examined using bioinformatics methods offer a rich framework with which to monitor the evolution and spread of influenza for public health surveillance. To better understand the influenza epidemic during the severe 2017-2018 season, we established a passive surveillance system at Arizona State University’s Tempe Campus Health Services beginning in January 2018. From this system, nasopharyngeal samples screening positive for influenza were collected. Using these samples, molecular DNA sequences will be generated using a combined multiplex RT-PCR and NGS approach. Phylogenetic analysis will be used to infer the severity and temporal course of the 2017-2018 influenza outbreak on campus as well as the 2018-2019 flu season. Through this surveillance system, we will gain knowledge of the dynamics of influenza spread in a university setting and will use this information to inform public health strategies.
ContributorsMendoza, Lydia Marie (Author) / Scotch, Matthew (Thesis director) / Hogue, Brenda (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05