Additional External Factors Research Articles

Understanding instructors’ tablet adoption for note-taking in interpreting: insights from the GETAMEL model

With the rise in popularity of tablets, professional interpreters were among the early adopters who integrated them into their workflow. Tablets have also become an indispensable tool for students, including those studying interpreting, who utilize them in the classroom for various purposes, such as note-taking. However, despite this growing trend, the traditional practice of pen-and-paper note-taking remains prevalent. Additionally, current interpreting textbooks primarily focus on teaching pen-and-paper note-taking skills. As interpreting instructors, it is crucial for us to familiarize ourselves with the use of tablets for note-taking in consecutive interpreting (CI). This will enable us to adapt our teaching methods accordingly and cater to the needs of the “iPad Kids” generation. The purpose of this study is to use quantitative method to examine the factors that contribute to the adoption of tablets for note-taking by instructors in the classroom environment. A questionnaire was developed based on the General Extended Technology Acceptance Model for E-learning (GETAMEL) framework. The questionnaire was distributed to teachers at prominent foreign language universities, foreign language faculties in select comprehensive universities and translation training institutions across Chinese Mainland and Macao Special Administrative Region of China. To provide comprehensive insights into the variables under study, descriptive statistics were generated using both SPSS 25.0 and Excel. These tools facilitated the production of detailed data summaries, offering valuable insights into the research variables. The obtained results provide insights into various aspects, including instructors’ knowledge levels and usage of tablet interpreting in university classrooms, their attitudes toward integrating tablet interpreting into teaching, and the key factors that influence their decisions to adopt tablet interpreting in their classroom practices. The findings suggest the existence of additional external factors that could be incorporated into the existing model. The paper concludes with recommendations on how to promote the integration of technology into teaching practices for interpreting instructors.

Impact of Financial Performance and Economic Value Added (EVA) On Stock Returns before and after Covid-19 Pandemic: A Case Study of Telecommunications Companies Listed on IDX

This research aims to investigate the impact of financial performance and Economic Value Added (EVA) on stock returns of telecommunication companies listed in the Indonesia Stock Exchange before and after the COVID-19 pandemic. Financial performance in this research is proxied by Return on Assets (ROA), Return on Equity (ROE), Price-Earnings Ratio (PER), Debt-to-Equity Ratio (DER), Net Profit Margin (NPM), and Earnings per Share (EPS). The study employs a purposive sampling method and selects 10 companies in the telecommunication sub-sector for analysis. The type of research used is a quantitative research design, including Panel Data regression analysis and the Wilcoxon Signed Ranks Test. The findings of this study show that ROA, ROE, and PER significantly impacted stock returns before COVID-19, however, this impact did not exist after the pandemic; DER, NPM, and EPS consistently affect stock returns both before and after the pandemic; and EVA only becomes significant after the pandemic. Simultaneously, ROA, ROE, PER, DER, NPM, EPS, and EVA influenced stock returns before COVID-19, but they did not have any impact after the pandemic. Despite these individual shifts, there are no significant differences in overall financial performance metrics and stock returns between the before and after COVID-19 periods. Future research should consider additional financial metrics or external factors such as market volatility, inflation rates, or industry-specific variables to provide a more comprehensive understanding of stock return determinants.

Pengaruh Sikap, Norma Subjektif, dan Religiusitas Terhadap Preferensi Halal Pada Produk Kosmetik di kalangan Gen Z

The aim of this study is to analyse the influence of attitudes, subjective norms and religiosity on halal preferences for cosmetic products, with a focus on Generation Z. Using a quantitative method with an SEM-PLS approach, this study collected primary data from Generation Z respondents who purchased halal cosmetic products. The analysis shows that attitudes, subjective norms and religiosity together have a significant influence on halal preferences, allowing a deeper understanding of the factors that influence purchasing decisions in this context. The findings of this study provide valuable insights for marketers of halal cosmetic products to develop more targeted and effective marketing strategies to reach Generation Z consumers. Nevertheless, this study has limitations, such as geographical restrictions and not taking into account certain external variables. Therefore, it is recommended for future research to expand the scope and consider additional external factors. To summarise, this study should provide a basis for developing smarter marketing strategies that address halal preferences in cosmetic products in the digital age.

Arctic Greening Trends: Change Points in Satellite-Derived Normalized Difference Vegetation Indexes and Their Correlation with Climate Variables over the Last Two Decades

In this study, we utilized NDVI data from the moderate resolution imaging spectroradiometer (MODIS) alongside climatic variables obtained from a reanalyzed dataset to analyze Arctic greening during the summer months (June–September) of the last two decades. This investigation entailed a detailed analysis of these changes across various temporal scales. The data indicated a continuous trend of Arctic greening, evidenced by a 1.8% per decade increment in the NDVI. Notably, significant change points were identified in June 2012 and September 2013. A comparative assessment of NDVI pre- and post-these inflection points revealed an elongation of the Arctic greening trend. Furthermore, an anomalous increase in NDVI of 2% per decade was observed, suggesting an acceleration in greening. A comprehensive analysis was conducted to decipher the correlation between NDVI, temperature, and energy budget parameters to elucidate the underlying causes of these change points. Although the correlation between these variables was relatively low throughout the summer months, a distinct pattern emerged when these periods were dissected and examined in the context of the identified change points. Preceding the change point, a strong correlation (approximately 0.6) was observed between all variables; however, this correlation significantly diminished after the change point, dropping to less than half. This shift implies an introduction of additional external factors influencing the Arctic greening trend after the change point. Our findings provide foundational data for estimating the tipping point in Arctic terrestrial ecosystems. This is achieved by integrating the observed NDVI change points with their relationship with climatic variables, which are essential in comprehensively understanding the dynamics of Arctic climate change, particularly with alterations in tundra vegetation.

Significance of the regional stage of the All-Russian Olympiad results

The Olympiad movement in domestic pedagogy is perceived simultaneously as a driver of the development of students’ creative abilities and an alternative system for assessing their educational results. The problem of our research is associated with the implementation of Olympiad practices, in particular, with the results of the regional stage of the All-Russian Olympiad for Schoolchildren. The relevance of the study is due to the constantly increasing schoolchildren’s participation and popularity of Olympiads in different subjects. For example, in the 2022-23 academic year, more than 20 million cases of participation were recorded. There is no doubt that the Olympiad movement is important for the development of students’ creativity, however, schoolchildren tend to avoid intellectual competitions. Thus, the aim of the study is to examine additional external motivational factors that may improve the situation. As a theoretical framework of the study, the cultural approach was used along with the cultural theory of the education content. The main research methods are theoretical, including the analysis of scientific and methodological literature, regulatory documentation and tasks of the past years, categorization, induction and deduction. As a result, conclusions were made about the need to reform the Olympiad movement in the area of recognition of the significance of the regional stage results of the All-Russian Olympiad for Schoolchildren. We propose to take into account the effective participation in the Olympiads in the system of state final certification and equate the diploma of the winner and prize-winner of the regional stage with 85 and 75 points of the Unified State Exam, respectively. The article reveals prerequisites for such a reform, indicating a high level of competitions, with the transparency of the procedure for assessing and holding competitions under the direct control of the Ministry of Education. The theoretical significance of the study is refracted in the enrichment of pedagogical science in the field of the implementation of Subject Olympiads for Schoolchildren, its practical significance is the possibility of using the obtained results both to reform the procedure at the federal level and to recognize the significance of the regional stage results by universities when working with applicants.

Application of Technology Acceptance Model (TAM) in Telemedicine Application During Covid-19 Pandemic

The COVID-19 pandemic hit the whole world, including Indonesia, forcing people to limit all activities outside their homes, including treatment activities to hospitals. This study aims to examine the application of the technology acceptance model (TAM) to telemedicine applications during the COVID-19 pandemic. The proposed research model is formulated from the extended technology acceptance model theory with empirical testing using data obtained from telemedicine user surveys. This study analyzed two additional external factors: privacy concerns and trust. Data is processed using SmartPLS software. A total of 406 telemedicine users participated in this study with male, n=206; 51%, female, n=200; 49%. Research respondents habitually used telemedicine applications during the COVID-19 pandemic that hit Indonesia. Among these respondents, 94.7% reported using telemedicine services during the COVID-19 pandemic. The most widely used telemedicine application, with a total of 59.7% of respondents, chose Halodoc. The external variable privacy concern does not affect the perceived usefulness of telemedicine used. However, trust and perceived usefulness are associated with a positive significance in telemedicine used during the COVID-19 pandemic in Indonesia. Privacy concerns have a limited impact on the perception of expediency but influence the ease of use of telemedicine apps. On the other hand, trust plays a vital role in shaping telemedicine's perceived usefulness and ease of use during the COVID-19 pandemic, as telemedicine has become indispensable for accessing healthcare services.

Factors Affecting Market Participant Decision Making in the Spanish Intraday Electricity Market: Auctions vs. Continuous Trading

Intraday markets can be organized as continuous trading or discrete auction sessions. While many studies have attempted to compare the liquidity of these two models, additional external factors specific to each system, such as the balancing market design and number of bidding zones, affect overall market liquidity. In this regard, the Spanish hybrid intraday markets seem like an excellent case study to compare the two market models. Since the two intraday models are implemented in the same system (the Spanish one), the same conditions apply to their implementation. However, a direct comparison of liquidity is still challenging due to two factors: (1) differences exist in market architecture (timing, pricing scheme, bidding formats, etc.) between the two models, which create preferences among market players for one or the other; (2) the opportunistic behavior of market players in the system responding to the market price signals may affect the liquidity dynamics. We demonstrate the relevance of these two factors coming into play in the Spanish intraday markets, first carrying out a qualitative analysis of the market architecture of both models and then empirically analyzing a market manipulation attempt, which we refer to as the 15:10 rush. Our analysis points towards the need for more efficient regulation governing the interaction of the continuous intraday market with intraday auction markets and the potential risks from increased algorithmic trading.

Cybersecurity effectiveness in UK construction firms: an extended McKinsey 7S model approach

PurposeThis study aims to assess the essential elements of internal organisational capability that influence the cybersecurity effectiveness of a construction firm. An extended McKinsey 7S model is used to analyse the relationship between a construction firm's cybersecurity effectiveness and nine internal capability elements: shared values, strategy, structure, systems, staff, style, skills, relationships with third parties and regulatory compliance.Design/methodology/approachBased on a quantitative research strategy, this study collected data through a cross-sectional survey of professionals working in the construction sector in the United Kingdom (UK). The collected data was analysed using descriptive and inferential statistical methods.FindingsThe findings underlined systems, regulatory compliance, staff and third-party relationships as the most significant elements of internal organisational capability influencing a construction firm's cybersecurity effectiveness, organised in order of importance.Research limitations/implicationsFuture research possibilities are proposed including the extension of the proposed diagnostic model to consider additional external factors, examining it under varying industrial relationship conditions and developing a dynamic framework that helps improve cybersecurity capability levels while overseeing execution outcomes to ensure success.Practical implicationsThe extended McKinsey 7S model can be used as a diagnostic tool to assess the organisation's internal capabilities and evaluate the effectiveness of implemented changes. This can provide specific ways for construction firms to enhance their cybersecurity effectiveness.Originality/valueThis study contributes to the field of cybersecurity in the construction industry by empirically assessing the effectiveness of cybersecurity in UK construction firms using an extended McKinsey 7S model. The study highlights the importance of two additional elements, third-party relationships and construction firm regulatory compliance, which were overlooked in the original McKinsey 7S model. By utilising this model, the study develops a concise research model of essential elements of internal organisational capability that influence cybersecurity effectiveness in construction firms.

Endothelial Differentiation of CCM1 Knockout iPSCs Triggers the Establishment of a Specific Gene Expression Signature.

Cerebral cavernous malformation (CCM) is a neurovascular disease that can lead to seizures and stroke-like symptoms. The familial form is caused by a heterozygous germline mutation in either the CCM1, CCM2, or CCM3 gene. While the importance of a second-hit mechanism in CCM development is well established, it is still unclear whether it immediately triggers CCM development or whether additional external factors are required. We here used RNA sequencing to study differential gene expression in CCM1 knockout induced pluripotent stem cells (CCM1-/- iPSCs), early mesoderm progenitor cells (eMPCs), and endothelial-like cells (ECs). Notably, CRISPR/Cas9-mediated inactivation of CCM1 led to hardly any gene expression differences in iPSCs and eMPCs. However, after differentiation into ECs, we found the significant deregulation of signaling pathways well known to be involved in CCM pathogenesis. These data suggest that a microenvironment of proangiogenic cytokines and growth factors can trigger the establishment of a characteristic gene expression signature upon CCM1 inactivation. Consequently, CCM1-/- precursor cells may exist that remain silent until entering the endothelial lineage. Collectively, not only downstream consequences of CCM1 ablation but also supporting factors must be addressed in CCM therapy development.

Temperature responsive hydrogels for biomedical applications

Hydrogel is a three-dimensional communicator for water-insoluble chemicals. The hydrogel can swell structurally with water and contain large amounts of water. Hydrogel is a chemical or physicochemical bond in different polymer chains. Hydrogels are due to their high water content, softness, flexibleness, and biocompatibility. Hydrogels have therefore become increasingly popular. Hydrogels are created by physically or chemically complex natural and human hydrophilic polymers. When an environmentally specific stimulus is specific to the hydrogel, the gel replaces with solutions. Part of the advantage of universal action by thermo-responsive hydrogels is that they show their activity without the charge of any additional external factors. These hydrogels are attractive for specific medical applications because they can swell in place under physiological conditions and facilitate administration. Due to the combination of distinctly different properties of temperature-sensitive durability through joined domains and the high chemical conversion reactivity of nonmaterial, the application of temperature-sensitive hydrogels with the ion-exchange region for nanoscale chemical conversion reactions is an emerging and enticing alternative niche. The protection and direct fabrication of reactive palladium nanoparticles in temperature-responsive hydrogel networks are defined.

The effects of social feedback on private opinions. Empirical evidence from the laboratory.

The question of how people change their opinions through social interactions has been on the agenda of social scientific research for many decades. Now that the Internet has led to an ever greater interconnectedness and new forms of exchange that seem to go hand in hand with increasing political polarization, it is once again gaining in relevance. Most recently, the field of opinion dynamics has been complemented by social feedback theory, which explains opinion polarization phenomena by means of a reinforcement learning mechanism. According to the assumptions, individuals not only evaluate the opinion alternatives available to them based on the social feedback received as a result of expressing an opinion within a certain social environment. Rather, they also internalize the expected and thus rewarded opinion to the point where it becomes their actual private opinion. In order to put the implications of social feedback theory to a test, we conducted a randomized controlled laboratory experiment. The study combined preceding and follow-up opinion measurements via online surveys with a laboratory treatment. Social feedback was found to have longer-term effects on private opinions, even when received in an anonymous and sanction free setting. Interestingly and contrary to our expectations, however, it was the mixture of supportive and rejective social feedback that resulted in the strongest influence. In addition, we observed a high degree of opinion volatility, highlighting the need for further research to help identify additional internal and external factors that might influence whether and how social feedback affects private opinions.

Characteristic study of microplastics distribution and response to human activities in nine highland lakes in Yunnan province

Nine highland lakes in Yunnan Province—Dian Lake, Erhai Lake, Fuxian Lake, Qilu Lake, Yilong Lake, Xingyun Lake, Yangzonghai Lake, Chenghai Lake, and Lugu Lake—were the principal objects of this study. To investigate the microplastic pollution patterns in highland lakes and to identify the most effective microplastic monitoring techniques, the distribution characteristics, abundance, and species of microplastics in the water bodies and sediments of nine highland lakes were scientifically sampled and analyzed in this study. To better understand the relationship between the level of economic development, the intensity of human activity and the level of governmental attention to environmental protection, the strength of the general public's environmental awareness, and the level of microplastic pollution in the Yunnan region, this study also looked into the areas surrounding nine highland lakes. To analyze and study the relationship between the distribution characteristics of microplastics in water bodies and sediments in the nine lakes and external natural conditions, additional external factors, such as geographic location and climatic conditions of the study area of the nine highland lakes, were collected and collated.

Prolonged QT Interval in Cirrhosis: Twisting Time?

Approximately 30% to 70% of patients with cirrhosis have QT interval prolongation. In patients without cirrhosis, QT prolongation is associated with an increased risk of ventricular arrhythmias, such as torsade de pointes (TdP). In cirrhotic patients, there is likely a significant association between the corrected QT (QTc) interval and the severity of liver disease, and possibly with increased mortality. We present a stepwise overview of the pathophysiology and management of acquired long QT syndrome in cirrhosis. The QT interval is mainly determined by ventricular repolarization. To compare the QT interval in time it should be corrected for heart rate (QTc), preferably by the Fridericia method. A QTc interval >450 ms in males and >470 ms in females is considered prolonged. The pathophysiological mechanism remains incompletely understood, but may include metabolic, autonomic or hormonal imbalances, cirrhotic heart failure and/or genetic predisposition. Additional external risk factors for QTc prolongation include medication (IKr blockade and altered cytochrome P450 activity), bradycardia, electrolyte abnormalities, underlying cardiomyopathy and acute illness. In patients with cirrhosis, multiple hits and cardiac-hepatic interactions are often required to sufficiently erode the repolarization reserve before long QT syndrome and TdP can occur. While some risk factors are unavoidable, overall risk can be mitigated by electrocardiogram monitoring and avoiding drug interactions and electrolyte and acidbase disturbances. In cirrhotic patients with prolonged QTc interval, a joint effort by cardiologists and hepatologists may be useful and significantly improve the clinical course and outcome.

An empirical study of e-learning post-acceptance after the spread of COVID-19

There are various reasons why vaccine fear has resulted in public rejection. Students have raised concerns about vaccine effectiveness, leading to hesitation when it comes to vaccination. Vaccination apprehension impacts students' perceptions, which has an impact on the acceptability of an e-learning platform. As a result, the goal of this study is to look at the post-acceptance of an e-learning platform using a conceptual model with several factors. Every variable makes a unique contribution to the e-learning platform's post-acceptance. In the current study, TAM variables were combined with additional external factors such as fear of vaccination, perceived routine use, perceived enjoyment, perceived critical mass, and self- efficacy, all of which are directly associated with post-acceptance of an e-learning platform. Here, a hybrid conceptual model was used to evaluate the newly widespread use of e-learning platforms in this area in this study in the UAE. In the past, empirical investigations primarily used Structural Equation Modeling (SEM) analysis; however, this study used a developing hybrid analysis approach that combines SEM with deep learning–based Artificial Neural Networks (ANN). This study also employed the Importance–Performance Map Analysis (IPMA) to determine the significance and performance of each element. Through the findings, it was found that fear of vaccination, perceived ease of use, perceived usefulness, perceived routine use, perceived enjoyment, perceived critical mass, and self-efficiency all had a significant impact on students' behavioral intention to use the e-learning platform for educational purposes. It was also shown in the analysis of ANN as well as IPMA that the perceived ease of use of the e-learning platform is the most important indicator of post-acceptance. The proposed model, in theory, provides appropriate explanations for the elements that influence post-acceptance of the e-learning platform in terms of internet service factors at the individual level. In the practical sense, these findings will help decision-makers and practitioners in higher education institutions identify the factors that should be given extra care and plan their policies accordingly. The ability of the deep ANN architecture to identify the non-linear relationships between the factors involved in the theoretical model has been determined in this research. The implication offers extensive information about taking effective steps to decrease the fear of vaccination among people and increase vaccination confidence among teachers and educators and students, consequently impacting society.

A Bayesian Inference Model for Sustainable Crowd Source Logistics for Small and Medium Scale Enterprises (SME) in Africa

Trade in Africa is likely to increase and alter significantly during the next decade. Intra-African trade has shown significant potential to reinvigorate African commerce. Logistics and distribution are critical, acting as a catalyst for private sector development and growth. However, little attention has been given to the association crowd logistis platforms and SME’s in Africa. This study applies an Extended Technology Acceptance Model (ETAM) to explore the implications of crowd-sourcing logistics for small and medium-sized enterprises (SMEs) in the African market. A survey was conducted to obtain the necessary primary data from 130 SME owners across Africa. To provide further insight, this study adopts a Bayesian inference model to analyze the data obtained. This research also considers perceived risk as an additional external factor of the TAM as a vehicle to test the hypotheses and relationships and explain users’ willingness to adopt a web-based logistical platform. Empirical results show that in the adoption of new Technology; it is worth noting that for SME owners external factors (i.e. subjective norms, perceived risk, perceived experience) have more effect on the perceived usefulness of crowd logistics platforms than intrinsic factors (i.e. perceived enjoyment, computer anxiety and self efficacy).The analysis also showed that crowd logistics platforms provide a competitive advantage for SMEs but the perceived risks associated with crowd logistics platforms should be regulated.

Machine Learning Outperforms Classical Forecasting on Horticultural Sales Predictions

Forecasting future demand is of high importance for many companies as it affects operational decisions. This is especially relevant for products with a short shelf life due to the potential disposal of unsold items. Horticultural products are highly influenced by this, however with limited attention in forecasting research so far. Beyond that, many forecasting competitions show a competitive performance of classical forecasting methods. For the first time, we empirically compared the performance of nine state-of-the-art machine learning and three classical forecasting algorithms for horticultural sales predictions. We show that machine learning methods were superior in all our experiments, with the gradient boosted ensemble learner XGBoost being the top performer in 14 out of 15 comparisons. This advantage over classical forecasting approaches increased for datasets with multiple seasons. Further, we show that including additional external factors, such as weather and holiday information, as well as meta-features led to a boost in predictive performance. In addition, we investigated whether the algorithms can capture the sudden increase in demand of horticultural products during the SARS-CoV-2 pandemic in 2020. For this special case, XGBoost was also superior. All code and data is publicly available on GitHub: https://github.com/grimmlab/HorticulturalSalesPredictions.

Identification of residual force in static load tests on instrumented screw displacement piles

Abstract Occurrence of the so-called residual force of an unknown value significantly disturbs interpretation of static load tests performed on piles equipped with additional measuring instruments. Screw displacement piles are the piling technology in which the residual force phenomenon is very common. Its formation mechanism is closely related to the installation method of this type of piles, which initiates generation of negative pile skin friction without any additional external factors. Knowledge of the value and distribution of a residual force (trapped in a pile shaft before starting the load test) is a necessary condition for the proper interpretation of instrumented pile test results. In this article, a clear and easy-to-use method of residual force identification, based on the analysis of shaft deformations recorded during pile unloading is presented. The method was successfully verified on two pile examples and proved to be effective and practical.

Mental Model of Malaysian Pig Farmers in Implementing Disease Prevention and Control Practices.

The 1998 Nipah virus outbreak in Malaysia resulted in major financial losses to the multi-million-dollar swine industry. While productivity and biosecurity of pig farms have improved since, biosecurity in some farms remains substandard with farmers struggling to adapt to current national pig farming policies. Farm viability and animal health depends on farmers' role as decision-makers in managing disease threats and other aspects of farm management. This study aimed to describe the mental model of farmers in making decisions about disease prevention and control measures during the 1998 Nipah virus outbreak, and in 2019, 20 years after the last reported Nipah case. Using a qualitative approach, in-depth, semi-structured interviews with 12 pig farmers (mostly small-scale or medium-scale farms) were conducted in three states in Malaysia. Data were analyzed via inductive content analysis. Thirty-six unique dimensions in the mental model were identified, representing six interrelated themes corresponding to participants' decision making related to disease prevention and control: drivers of action to prevent and control disease; perception of practice options; individual determinants of familiar practices; external social factors; external economic factors; and additional external factors. Key drivers of disease control and prevention responses during the Nipah outbreak included heightened perception of risk, emotions, perceived economic loss, and subjective norms whereas key drivers in 2019 included perception of risk, perceived effectiveness, perceived benefits, and other dimensions such as perception of the future, perceived economic cost, barriers, and loss. An unfavorable future outlook, perceived economic factors, and socio-political and personal factors currently hinders farm improvement and adoption of Pig Farming Areas (PFAs) and Modern Pig Farming (MPF) systems. Private sector service providers and veterinarians are highly influential in advocating for good biosecurity, herd health, and animal health intervention practices. Insights gained can inform the development of strategic policies and interventions.

Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study.

BackgroundAn increasing number of mobile health (mHealth) apps are becoming available for download and use on mobile devices. Even with the increase in availability and use of mHealth apps, there has still not been a lot of research into understanding the intention to use this kind of apps.ObjectiveThe purpose of this study was to investigate a technology acceptance model (TAM) that has been specially designed for primary health care applications.MethodsThe proposed model is an extension of the TAM, and was empirically tested using data obtained from a survey of mHealth app users (n=310). The research analyzed 2 additional external factors: promotion of health and health benefits. Data were analyzed with a PLS–SEM software and confirmed that gender moderates the adoption of mHealth apps in Spain. The explanatory capacity (R2 for behavioral intention to use) of the proposed model was 76.4%. Likewise, the relationships of the external constructs of the extended TAM were found to be significant.ResultsThe results show the importance of healthy habits developed by using mHealth apps. In addition, communication campaigns for these apps should be aimed at transferring the usefulness of eHealth as an agent for transforming attitudes; additionally, as more health benefits are obtained, ease of use becomes greater. Perceived usefulness (PU; β=.415, t0.001;4999=3.442, P=.001), attitude toward using (β=.301, t0.01;499=2.299, P=.02), and promotion of health (β=.210, t0.05;499=2.108, P=.03) were found to have a statistically significant impact on behavior intention to use eHealth apps (R2=76.4%). Perceived ease of use (PEOU; β=.179, t0.01;499=2.623, P=.009) and PU (β=.755, t0.001;499=12.888, P<.001) were found to have a statistically significant impact on attitude toward using (R2>=78.2%). Furthermore, PEOU (β=.203, t0.01;499=2.810, P=.005), health benefits (β=.448, t0.001;499=4.010, P<.001), and promotion of health (β=.281, t0.01;499=2.393, P=.01) exerted a significant impact on PU (R2=72.7%). Finally, health benefits (β=.640, t0.001;499=14.948, P<.001) had a statistically significant impact on PEOU (R2=40.9%), while promotion of health (β=.865, t0.001;499=29.943, P<.001) significantly influenced health benefits (R2=74.7%).ConclusionsmHealth apps could be used to predict the behavior of patients in the face of recommendations to prevent pandemics, such as COVID-19 or SARS, and to track users’ symptoms while they stay at home. Gender is a determining factor that influences the intention to use mHealth apps, so perhaps different interfaces and utilities could be designed according to gender.

Orthodox military clergy in World War I

The article is devoted to the consideration of the role of military priests during World War I. The starting points are the assertions that with the arrival of Christianity on the territory of Russia, the state power received a powerful tool of patriotic education, motivation and stimulation for the processes of defending a civil position during hostilities during various years in opposition to an external enemy, a mechanism for calling not only military intelligentsia, but also ordinary citizens and ordinary soldiers to fight for the Motherland, family, and Russian land. However, today among modern researchers there is no single point of view regarding the role of military clergy in World War I, and the opinions of researchers about the importance of the military clergy in this historical period differ dramatically. On the basis of the analysis, it was found that the participation of the military clergy in the context of World War I had both positive and negative factors of influence on maintaining the fighting spirit, patriotic mood, dedication and desire to protect the Motherland at all costs among members of the army of the Russian Empire. Despite the presence of a complex of negative tendencies in the influence of the clergy during World War I, which was due to a combination of additional external and internal factors of the disintegration of the institution of the clergy at that time, one cannot deny the invaluable contribution of the military clergy to Russia’s achievements in World War I.