Testing Extended Parallel Processing Model in the Korean COVID-19 Context: Effect of Moral Intuitions as Moderators

Despite the possible social implications of the coronavirus disease 2019 (COVID-19), previous studies of the extended parallel processing model (EPPM) in the context of COVID-19 overlooked the emotional aspects when processing fear-inducing COVID-19-related messages. Drawing upon the moral foundation theory (MFT), this study aimed to (a) apply EPPM in the Korean COVID-19 context, (b) introduce MFT and explain why moral intuitions can be related to the processing of COVID-19 messages, and (c) examine the moderating role of moral intuitions in the EPPM model. Based on the theoretical backgrounds, this study tested EPPM hypotheses and also tested whether moral intuition can moderate the relationship between perceived self-efficacy, perceived threat, fear of COVID-19, and health compliance behavioral intention. This study conducted an online survey using measurements of perceived self-efficacy, perceived threat, MFQ-20, fear of COVID, and health compliance. Our study showed three main findings. First, our study found the main effects of (a) self-efficacy on health compliance behavioral intention and (b) perceived threat on health compliance behavioral intention. Second, our study found that morality moderated the main effects of self-efficacy or perceived threat and also moderated EPPM interaction on fear of COVID. Third, the moderation of morality in the relationship between self-efficacy and health compliance behavioral intention showed that health compliance intention decreased as morality increased. Our findings suggest that people can consider COVID-19 as a social and moral issue that involves protecting others.

Testing Messages on Facebook to Promote Use of an HPV Educational Web-Intervention

In the US, the human papillomavirus (HPV) vaccine remains underutilized leading to disparities in HPV-related diseases. Latinx have some of the highest rates of cancer caused by HPV. In a previous study, we developed a tailored-messaging based online educational intervention (CHICOS) that was found to increase HPV vaccination intention among Latinx participants. The current research uses Facebook Advertising to test the comparative effectiveness of messages designed using the Extended Parallel Processing Model (EPPM) to promote the use of CHICOS among Latinx young adults and parents of adolescents. We also looked at differences in the effectiveness of messages that highlighted HPV-related cancers, genital warts, or a control condition as well as differences in Spanish vs. English messages. Results found Latinx young adults and parents, were more likely to click on Facebook Advertisements containing messages in Spanish and those that mention cancer risks pertinent to this population compared to those in English or messages that discuss genital warts. Thus, findings suggest that Facebook Advertising has the potential to be a useful tool for motivating information seeking online about HPV vaccination.

HETEROGENEOUS COMPUTING TO ACCELERATE THE SEARCH OF SUPER K-MERS BASED ON MINIMIZERS

The k-mers processing techniques based on partitioning of the data set on the disk using minimizer-type seeds have led to a significant reduction in memory requirements; however, it has added processes (search and distribution of super k-mers) that can be intensive given the large volume of data. This paper presents a massive parallel processing model in order to enable the efficient use of heterogeneous computation to accelerate the search of super k-mers based on seeds (minimizers or signatures). The model includes three main contributions: a new data structure called CISK for representing the super k-mers, their minimizers and two massive parallelization patterns in an indexed and compact way: one for obtaining the canonical m-mers of a set of reads and another for searching for super k-mers based on minimizers. The model was implemented through two OpenCL kernels. The evaluation of the kernels shows favorable results in terms of execution times and memory requirements to use the model for constructing heterogeneous solutions with simultaneous execution (workload distribution), which perform co-processing using the current search methods of super k -mers on the CPU and the methods presented herein on GPU. The model implementation code is available in the repository: https://github.com/BioinfUD/K-mersCL.