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Taiwan has been promoting its national health insurance (NHI), which provides people with appropriate medical resources; however, health insurance education is missing from schools, and teachers lack relevant teaching abilities. This study describes the development of the health insurance education empowerment program (HIEEP) to promote effective teaching on educators. A two-group parallel-controlled trial was conducted with health education teachers, in which participants learned to discuss its importance through demonstration and practice. The questionnaire measured their teaching effectiveness in HIEEP using a baseline measurement and a one-week follow-up measurement. Of 196 people that started the trial, 186 completed it. The intervention effects were evaluated using the Johnson-Neyman method. The results showed that in the experimental group, the program raised all teachers' variable scores, which evaluated health insurance meaning, teaching competence, self-determination, and impact. The empowerment program can provide teachers will allow for more effective health insurance education.

In practice, it is often necessary to add retarders to β-hemihydrate phosphogypsum (β-HPG) to prolong its setting time. In this paper, the effects of modified amino acid (XK) on physical and mechanical properties, hydration characteristics, and microstructure of β-HPG were investigated using various methods including fluidity, setting time, strength, hydration heat, X-ray diffraction (XRD), scanning electron microscope (SEM), mercury intrusion porosimetry (MIP), and X-ray photoelectron spectroscopy (XPS). The findings indicate that the addition of XK enhances the fluidity of β-HPG, and as the content of XK increases, there is an occurrence of prolonged setting time but a concurrent decrease in both the compressive and flexural strength. In addition, the incorporation of XK hampers the hydration process of β-HPG, resulting in a reduction in the hydration exothermic rate. Microscopic analysis reveals that while XK does not alter the final hydration products, it does affect the growth pattern of dihydrate gypsum crystals because of surface adsorption, and specifically, the crystals become short and columnar, with a looser crystal structure. Furthermore, XK leads to larger pores and deterioration of the pore structure of β-HPG.

Abstract The unknownness and dread potential of a risk event shapes its perceived risk. A public health emergency of international concern (PHEIC) declaration by the World Health Organisation (WHO) is a signal for such an event. Understanding perceived risk then shapes risk-avoiding behaviours, important for health prevention. The review aims to consolidate the determinants of risk perception during a PHEIC, underscoring the need for grounding in context and theory. Studies published from 2010 until end-2020, searching PubMed, PsycINFO, MedlinePlus, PubPsych, and CINAHL, were included. Studies with only biological conceptualisations of risk, or no association to risk perception, were excluded. A total of 65 studies were included. Quality of the cross-sectional studies was assessed using Newcastle Ottawa Scale (NOS), yielding an average of 5.4 stars (out of 10). Factors were classified into three broad categories – individual, contextual, and media. Individual risk factors include emotions; beliefs, trust, and perceptions; immutable physical traits (sex, age, ethnicity); mutable traits (education, income, etc.); and knowledge, with no definitive correlation to risk perception. Contextual traits include pandemic experience, time, and location, with only time negatively correlated to risk perception. Media traits include exposure, attention, and framing of media, with no clear association to risk perception. One limitation is excluding a portion of COVID-19 studies due to censoring. Still, this lack of consensus highlights the need to better conceptualise “risk perception”. Specifying the context and timing is also important since jurisdictions experience different outbreaks depending on outbreak histories. Using theories to ground risk perception research assists with these tasks.

Abstract Background This study investigates the potential of diffusion tensor imaging (DTI) in identifying penumbral volume (PV) compared to the standard gadolinium-required perfusion–diffusion mismatch (PDM), utilizing a stack-based ensemble machine learning (ML) approach with enhanced explainability. Methods Sixteen male rats were subjected to middle cerebral artery occlusion. The penumbra was identified using PDM at 30 and 90 min after occlusion. We used 11 DTI-derived metrics and 14 distance-based features to train five voxel-wise ML models. The model predictions were integrated using stack-based ensemble techniques. ML-estimated and PDM-defined PVs were compared to evaluate model performance through volume similarity assessment, the Pearson correlation analysis, and Bland–Altman analysis. Feature importance was determined for explainability. Results In the test rats, the ML-estimated median PV was 106.4 mL (interquartile range 44.6–157.3 mL), whereas the PDM-defined median PV was 102.0 mL (52.1–144.9 mL). These PVs had a volume similarity of 0.88 (0.79–0.96), a Pearson correlation coefficient of 0.93 (p

BackgroundVaccine hesitancy is a growing global health threat that is increasingly studied through the monitoring and analysis of social media platforms. One understudied area is the impact of echo chambers and influential users on disseminating vaccine information in social networks. Assessing the temporal development of echo chambers and the influence of key users on their growth provides valuable insights into effective communication strategies to prevent increases in vaccine hesitancy. This also aligns with the World Health Organization’s (WHO) infodemiology research agenda, which aims to propose new methods for social listening. ObjectiveUsing data from a Taiwanese forum, this study aims to examine how engagement patterns of influential users, both within and across different COVID-19 stances, contribute to the formation of echo chambers over time. MethodsData for this study come from a Taiwanese forum called PTT. All vaccine-related posts on the “Gossiping” subforum were scraped from January 2021 to December 2022 using the keyword “vaccine.” A multilayer network model was constructed to assess the existence of echo chambers. Each layer represents either provaccination, vaccine hesitant, or antivaccination posts based on specific criteria. Layer-level metrics, such as average diversity and Spearman rank correlations, were used to measure chambering. To understand the behavior of influential users—or key nodes—in the network, the activity of high-diversity and hardliner nodes was analyzed. ResultsOverall, the provaccination and antivaccination layers are strongly polarized. This trend is temporal and becomes more apparent after November 2021. Diverse nodes primarily participate in discussions related to provaccination topics, both receiving comments and contributing to them. Interactions with the antivaccination layer are comparatively minimal, likely due to its smaller size, suggesting that the forum is a “healthy community.” Overall, diverse nodes exhibit cross-cutting engagement. By contrast, hardliners in the vaccine hesitant and antivaccination layers are more active in commenting within their own communities. This trend is temporal, showing an increase during the Omicron outbreak. Hardliner activity potentially reinforces their stances over time. Thus, there are opposing forces of chambering and cross-cutting. ConclusionsEfforts should be made to moderate hardliner and influential nodes in the antivaccination layer and to support provaccination users engaged in cross-cutting exchanges. There are several limitations to this study. One is the bias of the platform used, and another is the lack of a comprehensive definition of “influence.” To address these issues, comparative studies across different platforms can be conducted, and various metrics of influence should be explored. Additionally, examining the impact of influential users on network structure and chambering through network simulations and regression analysis provides more robust insights. The study also lacks an explanation for the reasons behind chambering trends. Conducting content analysis can help to understand the nature of engagement and inform interventions to address echo chambers. These approaches align with and further the WHO infodemic research agenda.