Parallel Process Model Research Articles

Method of dynamic updating models of the interaction model of parallel processes in embedded systems

Method of dynamic updating models of the interaction model of parallel processes in embedded systems

Efficacy-focused and autonomy-supportive messaging in social media vaccine campaigns: insights from a Facebook split test

ABSTRACT Background In the context of social media vaccine campaigns, understanding the impact of message framing on audience engagement is crucial. This study examines the efficacy of messages centered on efficacy versus autonomy, informed by theoretical frameworks: the Extended Parallel Process Model (EPPM) and Self Determination Theory (SDT). Methods Utilizing the Facebook A/B Split Test (FBST) feature, an online experiment was conducted to compare the response to two different messages: one emphasizing vaccine efficacy (EPPM-informed) and the other focusing on individual autonomy in making vaccine decisions (SDT-informed). The primary measure of interest was the number of clicks on a link directing to a pro-vaccine website. Results The findings indicated that the autonomy-centered (SDT-informed) message resulted in a significantly higher click-through rate to the pro-vaccine website, particularly among users aged 65 and above. Furthermore, analysis of comments from Facebook users identified factors potentially contributing to vaccine hesitancy, with mistrust being the most dominant. Conclusions The study underscores the importance of tailoring social media vaccine campaigns to address the autonomy needs of the target audience while considering trust-related issues to mitigate vaccine hesitancy. Emphasizing individual autonomy in vaccine decision-making processes can enhance engagement with pro-vaccine content, especially in older demographics.

Women’s preferences for genetic screening in routine care: A qualitative study

ObjectiveExamine decision-making regarding when women would prefer to receive reproductive carrier and cancer predisposition screening and from what clinician. Methods20 women completed in-depth interviews via Zoom exploring their views on the provision of reproductive carrier and cancer predisposition screening. Our analysis identified themes related to what informs women’s preferences for when they would like to receive a genetic screening offer and by which clinician. ResultsParticipants’ responses to questions about when they would be interested in receiving genetic screening were best understood through the lens of the Extended Parallel Process Model. Specifically, personal utility of the information, a woman’s family health history and cost were key factors in decision-making. Women considered their clinician’s knowledge and their trust in and relationship with the clinician when deciding from whom they would prefer to receive an offer of genetic screening. ConclusionOB/GYN clinic patients may accept an offer of genetic screening from a knowledgeable and trusted clinician for carrier and cancer predisposition screening preconceptionally or prenatally. Practice implicationsIntegrating genetic reproductive and cancer predisposition screening into the care provided to reproductive age OB/GYN patients may be acceptable to this population.

A qualitative content analysis based on an extended parallel process model study of daycare center teacher behaviors concerning the eye health of preschool children

Purpose: This study is to explore the antecedent factors of daycare teacher behaviors concerning the eye health of preschool children by applying an extended parallel process model.Methods: Focus group interviews were conducted with ten daycare center teachers on September 4 and 14, 2023. A data analysis was performed according to the content analysis method by clustering the data into the four categories: the two threat factors of severity and susceptibility and the two efficacy factors of self-efficacy and response-efficacy.Results: Daycare center teachers’ perception of the severity of eye health problems in preschool children was high in relation to eye trauma, but it was recognized that viewing the electronic devices were of a less severe because symptoms were not noticed in a short period of time. They also showed low susceptibility because they were not sufficiently interested in the eye health hazard behaviors of preschool children. The self-efficacy of daycare center teachers was low because this was a lack of knowledge about symptoms of eye problems. However, they recognized that eye health activities performed in the preschool age could prevent negative eye health outcomes, thus showing a high response efficacy.Conclusion: In the future, it is necessary to increase the sensitivity and engagement of daycare center teachers concerning with the eye health of preschool children and to increase their self-efficacy. It will also be necessary to develop various interventions to improve eye health for preschool children that can be implemented by daycare center teachers.

Understanding invisible pain in the older adult: a content analysis of social media's representation of herpes zoster vaccine.

Herpes zoster (HZ), a common disease in older adults, affects their quality of life. Therefore, this study aimed to examine the blog posts of HZ-related information on social media platforms to analyze the attitudes and behaviors of residents toward the dissemination of health information. This research used content analysis to focus on Weibo, a representative social media in China, to analyze the content of 1866 blog posts related to herpes zoster (HZ) and herpes zoster vaccine (HZV). According to the consistency test by Cohen's Kappa, four themes were identified: (a) sources, (b) tones, (c) epidemiological information, and (d) extended parallel process model elements. The findings showed that most information on Weibo came from non-professionals, with a neutral tone, and showed the invisible pain of HZ and the effectiveness of HZV through the two largest aspects of prevention and aged protection in epidemiological information. However, current blog posts treat the older adult as invisible individuals, failing to acknowledge them as recipients of the information. Additionally, the cost of the vaccine acts as an invisible economic barrier, contributing to the dissemination of incorrect information about folk remedies. This impacts the older adult's acceptance of health information related to HZV. Thus, the way to share health information with the older adult needs to be improved in the future, and attention should be paid to the transmission of incorrect information to improve their vaccination rates and awareness of health management.

Explainable Spark-based PSO Clustering for Intrusion Detection

Given the exponential growth of available data in large networks, the existence of rapid, transparent and explainable intrusion detection systems has become of high necessity to effectively discover attacks in such huge networks. To deal with this challenge, we propose a novel explainable intrusion detection system based on Spark, Particle Swarm Optimization (PSO) clustering and eXplainable Artificial Intelligence (XAI) techniques. Spark is used as a parallel processing model for the effective processing of large-scale data, PSO is integrated for improving the quality of the intrusion detection system by avoiding sensitive initialization and premature convergence of the clustering algorithm and finally, XAI techniques are used to enhance interpretability and explainability of intrusion recommendations by providing both micro and macro explanations of detected intrusions. Experiments are conducted on several large collections of real datasets to show the effectiveness of the proposed intrusion detection system in terms of explainability, scalability and accuracy. The proposed system has shown high transparency in assisting security experts and decision-makers to understand and interpret attack behavior.

536-P: Characteristics of People with Type 2 Diabetes Based on the Extended Parallel Processing Model (EPPM)

536-P: Characteristics of People with Type 2 Diabetes Based on the Extended Parallel Processing Model (EPPM)

Parallel processing model for low-dose computed tomography image denoising

Low-dose computed tomography (LDCT) has gained increasing attention owing to its crucial role in reducing radiation exposure in patients. However, LDCT-reconstructed images often suffer from significant noise and artifacts, negatively impacting the radiologists’ ability to accurately diagnose. To address this issue, many studies have focused on denoising LDCT images using deep learning (DL) methods. However, these DL-based denoising methods have been hindered by the highly variable feature distribution of LDCT data from different imaging sources, which adversely affects the performance of current denoising models. In this study, we propose a parallel processing model, the multi-encoder deep feature transformation network (MDFTN), which is designed to enhance the performance of LDCT imaging for multisource data. Unlike traditional network structures, which rely on continual learning to process multitask data, the approach can simultaneously handle LDCT images within a unified framework from various imaging sources. The proposed MDFTN consists of multiple encoders and decoders along with a deep feature transformation module (DFTM). During forward propagation in network training, each encoder extracts diverse features from its respective data source in parallel and the DFTM compresses these features into a shared feature space. Subsequently, each decoder performs an inverse operation for multisource loss estimation. Through collaborative training, the proposed MDFTN leverages the complementary advantages of multisource data distribution to enhance its adaptability and generalization. Numerous experiments were conducted on two public datasets and one local dataset, which demonstrated that the proposed network model can simultaneously process multisource data while effectively suppressing noise and preserving fine structures. The source code is available at https://github.com/123456789ey/MDFTN.

Managing Fear Responses: A Qualitative Analysis of Pictorial Warning Labels Five Years Post-Plain Packaging.

Although pictorial warning labels (PWLs) now dominate tobacco packages sold in many countries, few studies have probed how people who smoke respond to the threats presented several years post-plain packaging and larger PWLs. Understanding how people manage the fear and dissonance PWLs arouse, and the strategies they use to rationalize, diminish, and reject risk messages, could inform future PWL design. We undertook 27 in-depth interviews with people aged 18 and over (16 female, 8 Māori, and 13 aged ≤35) who smoked roll-your-own tobacco and lived in Aotearoa New Zealand. We probed participants' views on current PWLs and how they responded to these, then asked them to use alternative images and headlines to create new PWLs. We drew on the extended parallel processing model to interpret the data, which we analyzed using a reflexive thematic analysis approach. People who smoke dislike PWLs, which they think reduce them to diseased body parts. While a minority thought existing PWLs were believable and effective, most reported avoiding PWLs by hiding or cognitively blocking them. Participants used diverse counterarguments to diminish PWLs' relevance and impact, and a minority displayed strong reactance. Several suggested developing PWLs that recognized them as whole people rather than patients in waiting, and recommended greater use of testimonials, particularly from people who had successfully become smoke free. PWLs using more holistic and diverse messages could elicit greater engagement and responsiveness, and motivate cessation more effectively than existing health-oriented warnings. Our findings suggest existing PWLs, which aim to arouse fear of ill health, could be complemented by warnings that emphasize the benefits of quitting. Continuing to use threat-based PWLs could stimulate greater rationalization and reactance. By contrast, PWLs that aim to illustrate how cessation could benefit people who smoke and their families, rather than instill a fear of disease, could avoid message rejection and counter-argument, and may prove a more powerful way of motivating cessation.

A new communication approach to encourage lung cancer screening action in rural eligible populations

ObjectiveThe purpose of this study was to develop an effective communication approach to encourage lung cancer screening action within rural screening-eligible populations. MethodsAn iterative research approach using targeted engagement with the priority population was used. Findings were triangulated through multiple methods, including two surveys and concept testing interviews. The Health Belief Model and the Extended Parallel Process Model served as study frameworks. ResultsInitial findings suggest that threat levels are high in the priority population and an emphasis on barrier mitigation messaging may drive action. Health campaign posters integrating these findings were developed and tested with the priority population. The new health campaign posters were tested against examples of previously used health campaign posters. Findings suggest that the new health campaign posters were more effective in spurring lung cancer screening motivation and intention to act in the priority population compared to current health campaign poster examples. ConclusionMessaging focused on gain-framing, inoculation messaging, and barrier mitigation may be more effective in encouraging lung cancer screening action in rural eligible populations. InnovationThis project outlines a systematic process to developing effective, targeted communication approaches using behavior change and persuasive communication frameworks along with engagement from priority populations.

Examining the Role of Information Behavior in Linking Cancer Risk Perception and Cancer Worry to Cancer Fatalism in China: Cross-Sectional Survey Study.

Reducing cancer fatalism is essential because of its detrimental impact on cancer-related preventive behaviors. However, little is known about factors influencing individuals' cancer fatalism in China. With a general basis of the extended parallel process model, this study aims to examine how distinct cancer-related mental conditions (risk perception and worry) and different information behaviors (information seeking vs avoidance) become associated with cancer fatalism, with an additional assessment of the moderating effect of information usefulness. Data were drawn from the Health Information National Trends Survey in China, which was conducted in 2017 (N=2358). Structural equation modeling and bootstrapping methods were performed to test a moderated mediation model and hypothesized relationships. The results showed that cancer risk perception and cancer worry were positively associated with online health information seeking. In addition, cancer worry was positively related to cancer information avoidance. Moreover, online health information seeking was found to reduce cancer fatalism, while cancer information avoidance was positively associated with cancer fatalism. The results also indicated that the perceived usefulness of cancer information moderated this dual-mediation pathway. The national survey data indicate that cancer mental conditions should not be treated as homogeneous entities, given their varying functions and effects. Apart from disseminating useful cancer information to encourage individuals to adaptively cope with cancer threats, we advocate for health communication programs to reduce cancer information avoidance to alleviate fatalistic beliefs about cancer prevention.

A content analysis of EPPM’s threat and efficacy information in environmental news: The impact of a community of practice and topic

The extended parallel process model summarizes the positive impact of threat and efficacy messages on behavioral intentions. In news contexts, research to date shows national journalists emphasize threat information and neglect efficacious information. Findings show U.S. university student journalists emphasized efficacy rather than threats countering past content analysis research. We also found environmental and sustainability communities of practice did not predict threat and efficacy information, but topics did.

Social Media and Women's Mental Health: The Roles of Information Acquisition in Mediating Appearance Anxiety

Objectives: With the rapid advancement of digital technology, the use of social media has become a significant characteristic of contemporary society. In this context, the continuous portrayal and emphasis on ideal beauty on social media platforms have particularly intensified women's "appearance anxiety." Although previous studies have explored the link between social media and mental health, the mechanism of how women's appearance anxiety, triggered by social media, impacts mental health remains unclear. Methods: In this paper, integrating the Extended Parallel Process Model (EPPM), we establish a research model to analyze how social media affects women's mental health through the mediation of information acquisition patterns. We conducted a cross-sectional survey online with 565 participants from June to August 2023, resulting in 521 valid questionnaires for hypothesis testing.Results: We found that social media is a significant factor influencing women's appearance anxiety. The frequency of accessing beauty and fashion information positively predicts overall appearance anxiety in women. Both active and passive information acquisition modes positively predict women's appearance anxiety and behaviors, influencing perceived risks and efficacy, with perceived risks and efficacy playing a mediating role. Conclusions: Conveying risk-related information (such as the risks of cosmetic surgery and makeup use) enhances women's appearance anxiety, while mitigating risk information (such as skin care methods and natural beauty) reduces it, with perceived risks and efficacy mediating these effects.

Challenges in Media Attention toward COVID-19-Preventive Behaviors: Dual Roles of Threat and Perceived Capability for Information Systems and Health Care.

Based on the extended parallel process model, this study investigated the relationship between young adults' media exposure to COVID-19 and their adoption of protective behaviors. This study surveyed 141 college students and found that increased risk perceptions led to greater intentions to engage in COVID-19-preventive behaviors and that these intentions were mediated by normative beliefs. There was no significant difference in risk perceptions between traditional media and social media. The results showed that college students took precautions against COVID-19 because they perceived themselves to be both vulnerable and capable.

An efficient parallel approach for quad-constellation GNSS real-time precise orbit determination enabling 5-second intervals updating

Real-time Global Navigation Satellite System (GNSS) precise orbits are essential prerequisites for real-time GNSS-based applications. However, the high computational demands of filter-based real-time multi-GNSS POD methods present a significant challenge for practical utilization. This study introduces an efficient parallel approach for quad-constellation GNSS real-time POD using the square root information filter (SRIF). In the proposed approach, parallel QR factorization algorithms are implemented to expedite parameter estimation based on SRIF, while parallel processing model is designed for real-time POD to enhance its computational efficiency. Validation experiments show that the computation time for measurement and time update in SRIF can be reduced by 78.5% and 80.5%, respectively, compared to the traditional serial approach. Additionally, parallel computing improves the computational efficiency of GNSS processing algorithms in real-time POD by approximately 70%. The proposed approach enables the completion of quad-system real-time POD solutions with 90 stations within 5 s, representing an impressive 73.0% reduction.

Listen to the Scientists: Effects of Exposure to Scientists and General Media Consumption on Cognitive, Affective, and Behavioral Mechanisms During the COVID-19 Pandemic

Throughout the COVID-19 crisis, scientists around the globe have engaged in science communication to an unprecedented degree to convey first-hand epidemiological knowledge and information on preventive measures. The present work is aimed at empirically investigating the impact of direct exposure to scientists as compared to general COVID-19-related media consumption (N=698) on central cognitive, affective, and behavioral variables, based on the extended parallel process model (EPPM) and its adaptations. A segment of the sample comprises individuals recruited independently, while others were sourced from an online panel. Importantly, this study sample was conducted at the outset of the COVID-19 pandemic. The results revealed that direct exposure to scientists positively affected recipients’ knowledge and self-efficacy. General media consumption, by contrast, positively affected perceived threat as well as fear and uncertainty. Both sources positively affected the adherence to protective measures.

Communicating particulate matter risk: the effects of empoweredness and trust in government information on protective behaviour

ABSTRACT In response to increasing concerns about the health risks associated with air pollution, air quality information and behavioural recommendations are more available to the public through risk communication. However, not all people are willing to change their behaviours; even when they do, the level of action varies. This study investigated how empoweredness (self-efficacy, individual response efficacy, collective response efficacy, hope, and values) and trust in government information affect the protective actions citizens take against particulate matter (PM) risk, by expanding on the extended parallel process model (EPPM). We analyzed the case of Seoul, South Korea, where nationwide environmental concern in regard to PM pollution recently led to intense policy measures and public communication efforts. To test our conceptual model, we conducted an online survey with 513 Seoul citizens on their perception of PM risk and their behaviour during high PM episodes. Our regression results revealed two key findings. First, perceived risk, self-efficacy, individual response efficacy, and trust in government information were positively associated with protective behaviours, supporting our hypotheses. Second and more importantly, trust in government information was found to be moderate the effects of self-efficacy, individual response efficacy, collective response efficacy, and hope on protective behaviour against PM pollution. This suggests trust can be a boundary condition that allows an individual’s empoweredness to be fully extended to behavioural change. Our study demonstrates the possibility of expanding EPPM applications in pro-environmental behaviour studies by adding new variables that can be factored into future risk communication. HIGHLIGHTS We explore the effects of empoweredness and trust in government information on protective behaviour against particulate matter in Korea. Empoweredness is measured by three types of efficacies, hope, and values. Survey responses are statistically analyzed to capture the associations between variables. Self-efficacy, values, and trust are positively associated with protective behaviour. Trust in government moderates some associations between empoweredness and protective action.

Predicting COVID-19 Vaccination Intentions to Inform Evidence-Based Messaging for Building Vaccine Confidence Among Rural Americans.

Examine possible message topics to promote rural vaccination using psychosocial antecedents of vaccination. Cross-sectional survey administered by Research America, Inc. West Virginia (WV). 756 WV adults via convenience sample (n = 370; ∼2% response rate from online panel of ∼20 000 WV residents), and random digit dial of landlines (n = 174; ∼1% response rate from 18 432 numbers) and cellphones (n = 212; ∼1% response rate from 20 486 numbers). Outcome measures included self-reported vaccination intention and behavior. Predictor measures, rooted in theories of social and behavioral science that have been found to be predictive of vaccination outcomes (i.e., Reasoned Action Approach, Extended Parallel Process Model), included perceived severity and susceptibility, negative affect, instrumental and affective attitudes, social norms, self-efficacy, response efficacy, and perceived control. Multivariate linear regression for intention and logistic regression for behavior. Intention was positively predicted by affective attitude, β = .30, P < .05, instrumental attitude, β = .19, P < .05, response efficacy, β = .19, P < .05, negative affect, β = .16, P < .05, self-efficacy, β = .13, P < .05, and subjective norm, β = .13, P < .05, F(10, 267) = 30.12, Adj. R2 = .53. Vaccination status was predicted by instrumental attitude, exp(B) = 2.09, and subjective norm, exp(B) = 2.00, Pseudo R2 = .29, log likelihood = 125.11, χ2(10) = 38.34, P < .05. Promising message targets were instrumental attitude, M = 3.21, SD = 1.46, and subjective norms, M = 3.76, SD = 1.71. COVID-19 vaccine confidence messages should address (1) positive feelings and safety perceptions, (2) vaccination's effectiveness in preventing serious COVID-19, and (3) subjective vaccination norms.

Linguistic agency in disaster messaging: differing strategies for threat and efficacy perceptions

ABSTRACT The purpose of this study was to determine the influence of linguistic assignment of agency on individuals’ perceptions of source credibility; specifically, this study assessed the impact of linguistic assignment of agency when encouraging the public to download a disaster-related mobile app. The experiment was a 2 (human agency and disaster agency) × 3 (low, medium, and high source credibility) between-subjects post-study design. Participants were randomly assigned to one of six messages encouraging them to download the FEMA mobile application. As predicted, high source credibility led to higher perceptions of threat in messages with linguistic agency assigned to disaster. However, when measuring perceptions of efficacy, messages with linguistic agency assigned to humans were more effective. Finally, as predicted by the extended parallel process model, high levels of perception of threat and perception of efficacy predicted a higher likelihood of participants accepting the invitation to download the mobile app.

Hybrid metaheuristic schemes with different configurations and feedback mechanisms for optimal clustering applications

This paper addresses the critical gap in the understanding of the effects of various configurations and feedback mechanisms on the performance of hybrid metaheuristics (HMs) in unsupervised clustering applications. Despite the widespread use of HMs due to their ability to leverage multiple optimization methods, the lack of comprehensive studies on their configuration and feedback mechanisms effects often results in sub-optimal clustering performances and premature convergence. To tackle these issues, we introduce two algorithms for implementing eight distinct HM schemes, focusing on the impacts of parallel and serial processing models along with different feedback mechanisms. Our approach involves selecting candidate metaheuristics based on a mix of evolutionary and swarm-based methods, including the k-means algorithm, to form various HM-based clustering schemes. These schemes were then rigorously evaluated across a range of datasets and feedback mechanisms, further assessing their efficiency in the deployment of smart grid base stations. Performance analysis was based on total fitness evaluations, timing capabilities, and clustering accuracy. The results revealed that parallel HMs with decoupled feedback mechanisms performed best in terms of accuracy but at the cost of slower convergence rates as compared to serial HMs. Our findings further suggest that serial HMs will be best suited for time-sensitive applications where a compromise between speed and accuracy is acceptable, while parallel HMs with decoupled feedback mechanisms are preferable for scenarios where precision is paramount. This research significantly contributes to the field by providing a detailed analysis of HM performance in varying conditions, thereby guiding the selection of appropriate HM schemes for specific clustering tasks.