Dataset Information

Computational Process of Sharing Emotion: An Authentic Information Perspective.

ABSTRACT: Although results of many psychology studies have shown that sharing emotion achieves dyadic interaction, no report has explained a study of the transmission of authentic information from emotional expressions that can strengthen perceivers. For this study, we used computational modeling, which is a multinomial processing tree, for formal quantification of the process of sharing emotion that emphasizes the perception of authentic information for expressers' feeling states from facial expressions. Results indicated that the ability to perceive authentic information of feeling states from a happy expression has a higher probability than the probability of judging authentic information from anger expressions. Next, happy facial expressions can activate both emotional elicitation and sharing emotion in perceivers, where emotional elicitation alone is working rather than sharing emotion for angry facial expressions. Third, parameters to detect anger experiences were found to be correlated positively with those of happiness. No robust correlation was found between the parameters extracted from this experiment task and questionnaire-measured emotional contagion, empathy, and social anxiety. Results of this study revealed the possibility that a new computational approach contributes to description of emotion sharing processes.

SUBMITTER: Namba S

PROVIDER: S-EPMC9134197 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Computational Process of Sharing Emotion: An Authentic Information Perspective.

Namba Shushi S Sato Wataru W Nakamura Koyo K Watanabe Katsumi K

Frontiers in psychology 20220512

Although results of many psychology studies have shown that sharing emotion achieves dyadic interaction, no report has explained a study of the transmission of authentic information from emotional expressions that can strengthen perceivers. For this study, we used computational modeling, which is a multinomial processing tree, for formal quantification of the process of sharing emotion that emphasizes the perception of authentic information for expressers' feeling states from facial expressions. ...[more]

PMID: 35645906

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Project description:ObjectivePublic crises seriously affect social stability and personal health. When individuals are in a public crisis environment, they will have the impulse and intention to share information, which is a behavioral attitude shown in the face of a crisis. Public crisis information sharing intention will be affected by many factors. This study aims to examine how the process of social presence may influence information sharing intentions during a public crisis and the mediating effects of situational pressure, including risk perception of disease infection and consistency of perception of opinion climate.MethodsThis was a cross-sectional study with 505 youth SNS users. In order to collect as suitable samples as possible, a research website was commissioned to conduct a questionnaire in the early stages of the COVID-19 pandemic in China. This questionnaire was utilized to measure social presence, risk perception of disease infection, consistency of perception of opinion climate and intention to share information about COVID-19. Structural equation modeling was used to examine variable relationships in the research model.ResultsThe results showed that social presence was significantly and positively associated with risk perception of disease infection (B = 0.42, p < 0.001), consistency of perception of opinion climate (B = 0.43, p < 0.001) and intention to share information about COVID-19 (B = 0.48, p < 0.001). Risk perception of disease infection (B = 0.19, p < 0.001) and consistency of perception of opinion climate (B = 0.18, p = 0.002) positively predicted youth SNS users' intention to share information about COVID-19. Risk perception of disease infection and consistency of perception of opinion climate mediated the relationship between social presence and intention to share information about COVID-19 (Z = 2.66, CI: 0.03, 0.15; Z = 2.66, CI: 0.02, 0.16).ConclusionThe study further deepens our understanding of the mechanisms underlying social presence and information sharing intentions. These new findings suggest that some situational cues, including media environment factors (social presence) and perceived stress factors (risk perception of disease infection, consistency of perception of opinion climate) may influence information sharing intention. From the perspective of communication psychology, this study enriched the assessment of information sharing on social media and contributes to understanding of social presence and situation pressure, and it helps to provide specific references for effectively promoting netizens' intention to share information about public crises.

Project description:BackgroundPrecision oncology is one of the fastest-developing domains of personalized medicine and is one of many data-intensive fields. Policy for health information sharing that is informed by patient perspectives can help organizations align practice with patient preferences and expectations, but many patients are largely unaware of the complexities of how and why clinical health information is shared.ObjectiveThis paper evaluates the process of public deliberation as an approach to understanding the values and preferences of current and former patients with cancer regarding the use and sharing of health information collected in the context of precision oncology.MethodsWe conducted public deliberations with patients who had a current or former cancer diagnosis. A total of 61 participants attended 1 of 2 deliberative sessions (session 1, n=28; session 2, n=33). Study team experts led two educational plenary sessions, and trained study team members then facilitated discussions with small groups of participants. Participants completed pre- and postdeliberation surveys measuring knowledge, attitudes, and beliefs about precision oncology and data sharing. Following informational sessions, participants discussed, ranked, and deliberated two policy-related scenarios in small groups and in a plenary session. In the analysis, we evaluate our process of developing the deliberative sessions, the knowledge gained by participants during the process, and the extent to which participants reasoned with complex information to identify policy preferences.ResultsThe deliberation process was rated highly by participants. Participants felt they were listened to by their group facilitator, that their opinions were respected by their group, and that the process that led to the group's decision was fair. Participants demonstrated improved knowledge of health data sharing policies between pre- and postdeliberation surveys, especially regarding the roles of physicians and health departments in health information sharing. Qualitative analysis of reasoning revealed that participants recognized complexity, made compromises, and engaged with trade-offs, considering both individual and societal perspectives related to health data sharing.ConclusionsThe deliberative approach can be valuable for soliciting the input of informed patients on complex issues such as health information sharing policy. Participants in our two public deliberations demonstrated that giving patients information about a complex topic like health data sharing and the opportunity to reason with others and discuss the information can help garner important insights into policy preferences and concerns. Data on public preferences, along with the rationale for information sharing, can help inform policy-making processes. Increasing transparency and patient engagement is critical to ensuring that data-driven health care respects patient autonomy and honors patient values and expectations.

Project description:BackgroundSparse relative effectiveness evidence is a frequent problem in Health Technology Assessment (HTA). Where evidence directly pertaining to the decision problem is sparse, it may be feasible to expand the evidence-base to include studies that relate to the decision problem only indirectly: for instance, when there is no evidence on a comparator, evidence on other treatments of the same molecular class could be used; similarly, a decision on children may borrow-strength from evidence on adults. Usually, in HTA, such indirect evidence is either included by ignoring any differences ('lumping') or not included at all ('splitting'). However, a range of more sophisticated methods exists, primarily in the biostatistics literature. The objective of this study is to identify and classify the breadth of the available information-sharing methods.MethodsForwards and backwards citation-mining techniques were used on a set of seminal papers on the topic of information-sharing. Papers were included if they specified (network) meta-analytic methods for combining information from distinct populations, interventions, outcomes or study-designs.ResultsOverall, 89 papers were included. A plethora of evidence synthesis methods have been used for information-sharing. Most papers (n=79) described methods that shared information on relative treatment effects. Amongst these, there was a strong emphasis on methods for information-sharing across multiple outcomes (n=42) and treatments (n=25), with fewer papers focusing on study-designs (n=23) or populations (n=8). We categorise and discuss the methods under four 'core' relationships of information-sharing: functional, exchangeability-based, prior-based and multivariate relationships, and explain the assumptions made within each of these core approaches.ConclusionsThis study highlights the range of information-sharing methods available. These methods often impose more moderate assumptions than lumping or splitting. Hence, the degree of information-sharing that they impose could potentially be considered more appropriate. Our identification of four 'core' methods of information-sharing allows for an improved understanding of the assumptions underpinning the different methods. Further research is required to understand how the methods differ in terms of the strength of sharing they impose and the implications of this for health care decisions.

Project description:The 2022 Winter Olympics were held in the three competition zones of Beijing, Yanqing and Zhangjiakou, China. The venues of this Winter Olympics were scattered and the terrain was complex. Moreover, the medical resources of Hebei and Beijing were relatively unbalanced. In the medical security of major events, the connection between first aid and in-hospital processes is of the utmost importance to rescue quality. 5th generation mobile network (5G) applications in medical scenarios are on the rise. It would be of great relevance to fully use 5G's low-latency and high-speed features to share the process information of patients, ambulance personnel, and the destination hospital's rescue team at emergency scenes and in transportation, improving rescue efficiency. This paper proposes a system scheme of cross-institutional emergency health information sharing based on 5G and augmented reality wearable devices. It also integrates the construction method of monitoring and other sign data sharing, in addition to testing the proposed scheme's service quality in 5G environments. In the deployment area of the 5G emergency medical rescue information sharing scheme for the Beijing Winter Olympic Games, we selected two designated medical support institutions for testing. The test adopted a combination of fixed-point and driving tests to experiment on the service data, voice service, and streaming media indicators. The 5G signal's coverage rate was close to 100%, the standalone connection's success rate was 100%, and the drop rate was 0. The average downlink rate of multiple scenarios was 620mbps, and the average uplink rate of 5G was over 71.8mbps, which is higher than the average 5G level in China. The downlink rate was more than 20 times larger than the 4th generation mobile network (4G) rate. This study's proposed scheme demonstrates the importance of 5G applications in emergency response and support, in addition to providing a suitable scheme for the integration of 5G networks in the medical scene.

Dataset Information

Computational Process of Sharing Emotion: An Authentic Information Perspective.

Publications

Computational Process of Sharing Emotion: An Authentic Information Perspective.

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