Internet-based Sources Research Articles

School entry examinations in the former German Democratic Republic (GDR) from 1949 to 1989 - An overview of formal and content-related implementation

Summarising the formal and substantive enrolment practice of school entry examinations (SEU) in the German Democratic Republic (GDR). Through a systematic literature review using a conventional as well as internet-based sources, specialised literature on specific topics and original documents were made available following selected search terms to capture essential characteristics of SEU in the GDR and to present them in a general context. In the GDR, regular school enrolment took place at the age of 6, although SEU implementation practice during the 1950s and 1960s was fundamentally inconsistent in terms of form and content. On the basis of mandatory annual screening examinations for children, the medical screening examination at pre-school age of 5-6 years was formally valid as a SEU. On a case-by-case basis, the responsible paediatricians carried out supplementary, but non-standardised developmental tests. From the 1970s onwards, the increasing density of kindergarten in the GDR led to their specialist staff getting more involved in the assessment of pre-school children's competences relevant to schooling. In addition, screening at the age of 4-5 years also became more relevant for developmental diagnostic purposes. While various examination procedures were initially used, a standardised inventory of instruments for assessing learning ability, intellectual development and language development gradually emerged during the 1970s. These two staggered SEUs between the age of 4 and 6 years enabled preschool children to be supported if necessary, so that children with developmental delays could be given adequate developmental and educational opportunities. This concept also enabled an intensifying, partly informal cooperation between the specialist staff in the kindergartens, paediatricians, parents and school headmasters. Overall, the SEU in the GDR was based on a professionally and a well thought-out concept from the 1970s onwards. At this time, the standardised, staggered and multidisciplinary approach was methodologically superior to school enrolment practice in West Germany.

Parental Inflammatory Bowel Disease with Child Autism: A Comprehensive Review and Meta-Analysis.

Inflammatory bowel disease (IBD) has been shown to be connected to a greater possibility of neurologically developed problems, such as autism spectrum disorders (ASDs). However, the proof linking parental IBD with ASD in offspring is inconclusive. Thus, we carried out a meta-analysis and comprehensive review to elucidate such linking. Prior research was identified through reviewing multiple internet-based sources, including Cochrane, Web of Knowledge, Embase, CINAHL, PubMed, and PsycINFO, from 1960 to December 2022. Pooled relative risks (RRs) and corresponding 95% confidence intervals (CIs) were determined employing random-effects models, in spite of the I2 statistic measurement of heterogeneity. Prediction intervals (PIs) have been presented to allow for more useful inferences and to indicate the range of genuine effects that might be predicted in future scenarios. Six studies (two case-control studies and four cohort studies) involving 3,200,199 participants were incorporated into the meta-analysis. The pooled RRs of ASDs among offspring of IBD parents were 1.15 (95% CI, 0.92 to 1.45, P = 0.226; I2 = 81.4%, P = 0.003; PI, 0.53-2.62), indicating no significant connection between parental IBD and the likelihood of ASDs in children. Type of IBD, and sex both also yielded no statistically significant results according to subgroup analysis. Our meta-analysis does not provide evidence that parental IBD is connected with the elevated likelihood of ASDs in their children. To confirm these results and understand their underlying mechanisms, additional research with larger sample sizes and improved study designs is required.

Training Background and Demographic Characteristics of Primary Care Team Physicians in Professional Sports.

Previous studies have shown that most professional head and orthopaedic team physicians are men, and most orthopaedic team physicians are fellowship-trained. It is unknown whether this holds true for primary care team physicians. To evaluate the residency and fellowship training background as well as the demographic characteristics of primary care team physicians in professional sports. Cross-sectional study. Publicly available information was used to determine the lead and supporting primary care team physicians for every US-based team in Major League Baseball, Major League Soccer, National Basketball Association, National Football League, National Hockey League, National Women's Soccer League, and Women's National Basketball Association. Data regarding training background and sex were obtained using internet-based sources. We identified 310 primary care team physicians from all 165 US-based teams in the 7 leagues included in the study. Female physicians comprised 11.5% (19/165) of the lead primary care team physicians and 14.2% (44/310) of all primary care team physicians. Overall, 66.7% (110/165) of lead primary care team physicians and 75.5% (234/310) of all primary care team physicians were sports medicine fellowship-trained. There was a higher proportion of female (37.5%) and fellowship-trained (93.8%) physicians in women's professional sports leagues. Most primary care team physicians (244/310 [78.7%]) were trained in family medicine or internal medicine. Women constituted a small minority of primary care team physicians in professional sports. Most primary care team physicians were residency trained in family medicine or internal medicine and were sports medicine fellowship-trained. The proportion of female and fellowship-trained primary care team physicians was highest in the National Women's Soccer League and the Women's National Basketball Association.

NARRATIVE OF IDENTITY POLITICS IN THE 2024 PRESIDENTIAL ELECTIONS OF THE REPUBLIC OF INDONESIA: CRITICAL DISCOURSE ANALYSIS

Objective: This research investigates the effects of social media on the quality and functioning of democracy in Indonesia, especially in relation to the 2017 DKI Governor Election and the upcoming 2024 presidential election. Social media is a vital platform for political participation, mobilization and expression, as it enables citizens to access information, voice their opinions and engage with diverse perspectives. However, social media also poses risks and challenges for democracy, as it can be used to manipulate public opinion, spread misinformation and incite violence. Theoritical framework: The influence of negative campaigns on voting behavior and political participation has also been a focus of research, with studies analyzing the impact of campaign narratives and media attention on election outcomes. In this context, many studies have highlighted how campaigns dominated by negative narratives can influence voters' opinions and attitudes. Negative campaigns tend to focus attention on the weaknesses and defects of political opponents, often leading to polarization and dissatisfaction with the political process as a whole. Apart from that, the role of the media in strengthening or balancing the campaign narrative is also an important aspect to be researched. The mass media has great power in strengthening the narratives conveyed by candidates and political parties through the coverage, analysis and opinions they convey to the public. In this case, media attention to certain campaign narratives can influence voter perceptions and preferences. Methods: The research examines how social media was used by different political actors and groups to support or oppose Anies Baswedan, who was a candidate for the governor of DKI Jakarta in 2017 and is now a presidential candidate backed by the Nasdem Party, PKB and PKS. The research also analyzes the impact of social media on the political culture and values of the Indonesian society, as well as the opportunities and limitations for enhancing democratic accountability and transparency through social media. The data collection methods include interviews, document analysis and internet-based sources and social media from 2016 to 2017 Result & Conclusion: The research findings show that social media has both positive and negative effects on democracy, as it can foster civic engagement, deliberation and pluralism, but also create polarization, distrust and intolerance. Social media is the third most popular medium for spreading campaign content, after television and newspapers. The campaign content in the 2017 DKI Governor election was then used in a national context to undermine Anies Baswedan as a presidential candidate, who was backed by the Nasdem Party and PKB, who were his political adversaries in the 2017 DKI Jakarta Governor election. Research Implications: Highlights the importance of responsible social media strategies to support democracy, recommending enhanced digital literacy and content regulation. Originality/Value: Provides a unique analysis of the impact of social media on political elections in Indonesia, offering insights into changing campaign strategies and socio-political interactions.

A case study on generative learning approaches in a studio and flipped class-room setting for increased learning outcomes

Teaching and learning during Covid-19 have been strongly affected by lockdowns, isolated online learning, and the sudden requirement to alternatively assess students while considering the effect internet-based information sources. Here, we present outcomes on the learning outcome of students returning from distance learning into the face-to-face mode, studying the subject “Embedded Mechatronic Systems” employing increasingly methods of Generative Learning Theory (GLT) in a flipped classroom environment, using studio and project-based learning approaches. By introducing a group project component, the formerly disconnected laboratory components become strongly connected with students being exposed to practical aspects and teamwork, generating reflected reports and videos of their practical work. To overcome the effects of Covi-d19, tighter assessments, and in-person engagements is emphasised. Viva-voces have been introduced and AI invigilated final exams have been altered to in-class room quizzes, while monitoring the cohort’s performance over 3 sessions. Our data indicate that face-to-face learning and hands-on practice with peers using self-testing and self-explaining strategies enacts higher outcomes, opposed to remote modes of teaching. Our results exemplify on how to move back into face-to-face teaching with future steps to increase learning outcomes using the flipped classroom, GLT, and a studio setting being discussed.

Research on Music Teachers' Competitions in Brazil

This article presents a state-of-the-art investigation concerning research related to public competitions for music teachers in Brazil. Data collection focused on research conducted and published until the year 2021, with no specific start date, based on internet-based sources. After collection, the data underwent content analysis. The results revealed four articles, each published in a different journal, with three related to Music and one to Education

Epidemic intelligence data of Crimean-Congo haemorrhagic fever, European Region, 2012 to 2022: a new opportunity for risk mapping of neglected diseases.

BackgroundThe Epidemic Intelligence from Open Sources (EIOS) system, jointly developed by the World Health Organisation (WHO), the Joint Research Centre (JRC) of the European Commission and various partners, is a web-based platform that facilitate the monitoring of information on public health threats in near real-time from thousands of online sources.AimsTo assess the capacity of the EIOS system to strengthen data collection for neglected diseases of public health importance, and to evaluate the use of EIOS data for improving the understanding of the geographic extents of diseases and their level of risk.MethodsA Bayesian additive regression trees (BART) model was implemented to map the risk of Crimean-Congo haemorrhagic fever (CCHF) occurrence in 52 countries and territories within the European Region between January 2012 and March 2022 using data on CCHF occurrence retrieved from the EIOS system.ResultsThe model found a positive association between all temperature-related variables and the probability of CCHF occurrence, with an increased risk in warmer and drier areas. The highest risk of CCHF was found in the Mediterranean basin and in areas bordering the Black Sea. There was a general decreasing risk trend from south to north across the entire European Region.ConclusionThe study highlights that the information gathered by public health intelligence can be used to build a disease risk map. Internet-based sources could aid in the assessment of new or changing risks and planning effective actions in target areas.

Allocation of U.S. Biomass Production to Food, Feed, Fiber, Fuel and Exports

This paper analyzes the end uses—food, feed, fiber, fuel, and exports—of biomass production in the U.S. in 1997, 2002, 2007, and 2012. They are also analyzed at the state level in 2012. Biomass production is measured as human appropriation of net primary production (HANPP), an ecological footprint measured as carbon fixed through photosynthesis, derived from data on crop, timber and grazing yields. HANPP was allocated to end uses using publicly available sources from the U.S. Department of Agriculture and internet-based sources publishing data on agricultural trade. HANPP was 717–834 megatons (MT) of carbon per year, which comprised 515–615 MT of crop-based, 105–149 MT timber-based, and 64–76 MT of grazed HANPP. Livestock feed commanded the largest proportion, but decreased from 395 (50%) to 305 MT (42%) of all HANPP and 320 to 240 MT (58–44%) of crop-based HANPP. The proportion allocated to exports was stable at 118–141 MT (17–18%) of total HANPP and 112–133 MT (21–23%) of crop-based HANPP. Biofiber decreased from 141 MT (18%) to 97 MT (13%) of all HANPP. Biofuel increased strongly from 11 MT to 98 MT, from 1% to 14% of all HANPP and 2% to 18% of crop-based HANPP, surpassing food and biofiber by 2012. Direct food commanded 89–105 MT, the lowest proportion at 12–13% of all HANPP, and 17–18% of crop-based HANPP. The highly fertile Midwest and the drought-prone Intermountain West stand out as regions where a very small percentage of biomass is allocated to direct human food. The high proportions of biomass production allocated to nonfood uses is consistent with the tragedy of ecosystem services and commodification of nature frameworks. Reducing these proportions presents opportunities for improving ecosystem services, food security, and human well-being.

The Usage and Trustworthiness of Various Health Information Sources in the United Arab Emirates: An Online National Cross-Sectional Survey.

Background: The increase in the quality and availability of health information as well as the accessibility of Internet-based sources, has driven growing demand for online health information. Information preferences are influenced by many factors, including information needs, intentions, trustworthiness, and socioeconomic variables. Hence, understanding the interplay of these factors helps stakeholders provide current and relevant health information sources to assist consumers in assessing their healthcare options and making informed medical decisions. Aims: To assess the different sources of health information sought by the UAE population and to investigate the level of trustworthiness of each source. Methods: The study adopted a descriptive online cross-sectional design. A self-administered questionnaire was used to collect data from UAE residents aged 18 years or above between July 2021 and September 2021. Health information sources, their trustworthiness, and health-oriented beliefs were explored through univariate, bivariate, and multivariate analysis in Python. Results: A total of 1083 responses were collected, out of which 683 (63%) were females. Doctors were the first source of health information (67.41%) before COVID-19, whereas websites were the first source (67.22%) during the pandemic. Other sources, such as pharmacists, social media, and friends and family, were not prioritized as primary sources. Overall, doctors had a high trustworthiness of 82.73%, followed by pharmacists with a high trustworthiness of 59.8%. The Internet had a partial trustworthiness of 58.4%. Social media and friends and family had a low trustworthiness of 32.78% and 23.73%, respectively. Age, marital status, occupation, and degree obtained were all significant predictors of Internet usage for health information. Conclusions: The population in the UAE commonly obtains health information from doctors who have been shown to have the highest trustworthiness; this is despite it not being the most common source used.

Analysis of parking traffic in Cologne, Germany, based on an extended Macroscopic transport model and parking API data

While macroscopic transport models are recognised as valuable tools for strategic transport planning, parking is rarely explicitly considered in such models. On the other hand, park-search traffic represents a significant portion of traffic in urban areas, according to many studies. Even if there are already some attempts to integrate parking into transport models, they have not found their way into the practice of modellers.The presented work enhances and combines previous approaches for modelling parking, and proposes a tool for practitioners to analyse common transport problems involving parking. It builds upon existing, even calibrated transport models, using the conventional four-step modeling technique. The approach also explores some emerging, internet-based data sources for transport models. Parking data is accessed from an Application Programming Interface (API) and embedded within the model procedure. Such new data resources resolve some problems from previous model approaches, which see the availability on parking data as problematic. With the combination of a macroscopic transport model and parking data from an API, aspects of parking supply and demand are represented within the model setting, whereas parking choice is calculated via an optimisation of a park-search route.The conceptual approach is demonstrated in the context of an existing macroscopic transport model for Cologne, Germany. This model is extended and refined to represent parking patterns within the study area. As a result, the spatial distribution and the effects of park-search traffic are explicitly shown, indicating some realistic results. It is also shown that the level of detail and the expressiveness of the existing model is increased.

How Well Are Pharmacists Represented in National Institutes of Health R01 Funding to United States Schools of Pharmacy?

Pharmacists are essential healthcare providers but historically are not well represented as principal investigators (PIs) of R01 grants by the United States (US) National Institutes of Health (NIH). Pharmacy organizations have taken steps to provide pharmacists with research training to improve their chances of achieving PI status. We conducted a retrospective cohort study using data from the NIH RePORTER website about R01 grants awarded to PIs affiliated with US Schools of Pharmacy (SOPs) for the fiscal years 2005-2019. Information regarding professional degrees was supplemented using data from the PIs' institutional website profiles and other internet-based sources. Only doctorate degrees obtained within the US were included for clinically related degrees. Data regarding more than one year of funding for the same project, equipment supplements, and diversity supplements were excluded to focus on unique projects in year one of funding. PhDs were the primary unique PIs of R01 grants at US SOPs (>90%). Pharmacist representation as unique PIs increased over the 15 years but was still only 10.1% for the years 2015-2019. There was a higher percentage of female pharmacists as unique PIs than female non-pharmacists. Pharmacists are currently underrepresented as unique PIs for NIH R01 grants. This conclusion is limited by not knowing how many pharmacist R01 applications were submitted.

Evaluating novel methods of outcome assessment following cardiac arrest

IntroductionWe compared novel methods of long-term follow-up after resuscitation from cardiac arrest to a query of the National Death Index (NDI). We hypothesized use of the electronic health record (EHR), and internet-based sources would have high sensitivity for identifying decedents identified by the NDI. MethodsWe performed a retrospective study including patients treated after cardiac arrest at a single academic center from 2010 to 2018. We evaluated two novel methods to ascertain long-term survival and modified Rankin Scale (mRS): 1) a structured chart review of our health system’s EHR; and 2) an internet-based search of: a) local newspapers, b) Ancestry.com, c) Facebook, d) Twitter, e) Instagram, and f) Google. If a patient was not reported deceased by any source, we considered them to be alive. We compared results of these novel methods to the NDI to calculate sensitivity. We queried the NDI for 200 in-hospital decedents to evaluate sensitivity against a true criterion standard. ResultsWe included 1,097 patients, 897 (82%) alive at discharge and 200 known decedents (18%). NDI identified 197/200 (99%) of known decedents. The EHR and local newspapers had highest sensitivity compared to the NDI (87% and 86% sensitivity, respectively). Online sources identified 10 likely decedents not identified by the NDI. Functional status estimated from EHR, and internet sources at follow up agreed in 38% of alive patients. ConclusionsNovel methods of outcome assessment are an alternative to NDI for determining patients’ vital status. These methods are less reliable for estimating functional status.

Training Background and Characteristics of NFL, MLB, and NBA Team Physicians.

An analysis of the demographics and training of head team physicians (HTPs) in professional sports would be valuable for evaluating training programs and as a resource for aspirant HTPs. To outline common characteristics among professional sport HTPs. Cross-sectional study. In June 2021, publicly available directories and news articles were used to identify the head orthopaedic HTPs and primary care HTPs for every team in Major League Baseball (MLB), the National Basketball Association (NBA), and the National Football League (NFL). Data regarding HTP characteristics were collected via internet-based sources. Age, sex, years from fellowship completion to current team role, and years in current team role were compared across sports with chi-square analyses and analyses of variance; comparisons between orthopaedic and primary care HTPs were performed with Fisher exact tests and Student t tests. The most frequently attended residency and fellowship training programs were also calculated. The productivity of fellowship programs was calculated as the number of current HTPs from that institution divided by the number of fellowship positions currently offered. We identified 181 HTPs: 171 (94%) men and 10 (6%) women. The mean age was 55.4 years (range, 33-79 years); the mean time from fellowship training completion to first year in current team role was 9.8 years (range, 0-29 years); and the mean time spent in current team role was 14.1 years (range, 0-39 years). There were 94 orthopaedic HTPs and 87 primary care HTPs. The rate of fellowship training was significantly higher in orthopaedic HTPs (95%) than in primary care HTPs (67%; P < .001). The fellowship programs that produced the largest number of current HTPs were the Hospital for Special Surgery (n = 16; productivity = 2.3), the American Sports Medicine Institute (11; 1.8), and the Kerlan-Jobe Orthopaedic Clinic (11; 1.2). The years from fellowship to HTP varied significantly by sport: 7.2 for MLB, 10.0 for the NFL, and 11.7 for the NBA (P = .048). Almost all orthopaedic HTPs were fellowship trained, as compared with two-thirds of primary care HTPs. Of the 94 orthopaedic HTPs, 62% were trained at 6 specific fellowship programs. Men accounted for a majority of HTPs.

Does the regional environment matter in ERP system adoption? Evidence from Russia

PurposeThis paper explores the effect the regional technological environment has on technology-driven performance, measured by enterprise resource planning (ERP).Design/methodology/approachThis study specifies a productivity-based production function driven by ERP system adoption. Employing a quasi-experimental research design, the author disentangles two effects – the average effect of ERP adoption and the moderation effect of the regional technological environment. The novelty of this study is that it merges publicly available information retrieved via text-mining tools and official financial reports published by companies.FindingsThe total effect of technology adoption on productivity varies from almost 3%–9% in different technological environments. Moreover, this study’s results revealed that the regional technological environment could enhance the effect of adopting different ERP systems.Originality/valueWhile some papers investigate the relationship between ERP adoption and firm performance regarding the environmental context of a firm, the effect of the regional technological environment on the relationship between technology adoption and firm performance is understudied. Thus, this research tries to contribute to a deeper understanding of the regional context's impact on technology-driven performance. The authors used automated content analysis to collect data on technology adoption; by doing so, this study contributes to the growing body of research utilising the text-mining approach to extract data stored in Internet-based information sources.

Enhancing COVID-19 Epidemic Forecasting Accuracy by Combining Real-time and Historical Data From Multiple Internet-Based Sources: Analysis of Social Media Data, Online News Articles, and Search Queries.

BackgroundThe SARS-COV-2 virus and its variants pose extraordinary challenges for public health worldwide. Timely and accurate forecasting of the COVID-19 epidemic is key to sustaining interventions and policies and efficient resource allocation. Internet-based data sources have shown great potential to supplement traditional infectious disease surveillance, and the combination of different Internet-based data sources has shown greater power to enhance epidemic forecasting accuracy than using a single Internet-based data source. However, existing methods incorporating multiple Internet-based data sources only used real-time data from these sources as exogenous inputs but did not take all the historical data into account. Moreover, the predictive power of different Internet-based data sources in providing early warning for COVID-19 outbreaks has not been fully explored.ObjectiveThe main aim of our study is to explore whether combining real-time and historical data from multiple Internet-based sources could improve the COVID-19 forecasting accuracy over the existing baseline models. A secondary aim is to explore the COVID-19 forecasting timeliness based on different Internet-based data sources.MethodsWe first used core terms and symptom-related keyword-based methods to extract COVID-19–related Internet-based data from December 21, 2019, to February 29, 2020. The Internet-based data we explored included 90,493,912 online news articles, 37,401,900 microblogs, and all the Baidu search query data during that period. We then proposed an autoregressive model with exogenous inputs, incorporating real-time and historical data from multiple Internet-based sources. Our proposed model was compared with baseline models, and all the models were tested during the first wave of COVID-19 epidemics in Hubei province and the rest of mainland China separately. We also used lagged Pearson correlations for COVID-19 forecasting timeliness analysis.ResultsOur proposed model achieved the highest accuracy in all 5 accuracy measures, compared with all the baseline models of both Hubei province and the rest of mainland China. In mainland China, except for Hubei, the COVID-19 epidemic forecasting accuracy differences between our proposed model (model i) and all the other baseline models were statistically significant (model 1, t198=–8.722, P<.001; model 2, t198=–5.000, P<.001, model 3, t198=–1.882, P=.06; model 4, t198=–4.644, P<.001; model 5, t198=–4.488, P<.001). In Hubei province, our proposed model's forecasting accuracy improved significantly compared with the baseline model using historical new confirmed COVID-19 case counts only (model 1, t198=–1.732, P=.09). Our results also showed that Internet-based sources could provide a 2- to 6-day earlier warning for COVID-19 outbreaks.ConclusionsOur approach incorporating real-time and historical data from multiple Internet-based sources could improve forecasting accuracy for epidemics of COVID-19 and its variants, which may help improve public health agencies' interventions and resource allocation in mitigating and controlling new waves of COVID-19 or other relevant epidemics.

Use of information sources in Covid-19 pandemic and its relation with knowledge and anxiety

Abstract Introduction. Production of useful information during a pandemic is a key element of outbreak control strategies. Aim. As no study has yet examined what information sources were used in the COVID-19 pandemic and how the use of information sources is related to knowledge and anxiety, this research tries to fill the research gap. Material and methods. We conducted an explorative study among 7,764 Slovenian population to assess the use of information sources, knowledge, and anxiety, and determine the relationship between different information sources and knowledge and anxiety in lay public in Slovenia during the pandemic of COVID-19. Results. A combination of unregulated internet-based information sources and regulated ones were frequently used information sources. The Internet as the main source was more used by younger and more educated individuals. Traditional mass media and religious organizations were more frequently used by older participants, while friends and/or relatives and/or colleagues and natural therapist by younger participants. Results also show that greater anxiety is associated with the greater need for information. Conclusion. Informing people should not primarily be based on the traditional interpersonal communication between a doctor and patients, other face-to-face communication or the use of printed information, but rather on regulated and unregulated websites, social media, and TV.

Social Fröhlich condensation: preserving societal order through sufficiently intensive information pumping

PurposeThis paper aims to present the basic assumptions for creation of social Fröhlich condensate and attract attention of other researchers (both from physics and socio-political science) to the problem of modeling of stability and order preservation in highly energetic society coupled with social energy bath of high temperature.Design/methodology/approachThe model of social Fröhlich condensation and its analysis are based on the mathematical formalism of quantum thermodynamics and field theory (applied outside of physics).FindingsThe presented quantum-like model provides the consistent operational model of such complex socio-political phenomenon as Fröhlich condensation.Research limitations/implicationsThe model of social Fröhlich condensation is heavily based on theory of open quantum systems. Its consistent elaboration needs additional efforts.Practical implicationsEvidence of such phenomenon as social Fröhlich condensation is demonstrated by stability of modern informationally open societies.Social implicationsApproaching the state of Fröhlich condensation is the powerful source of social stability. Understanding its informational structure and origin may help to stabilize the modern society.Originality/valueApplication of the quantum-like model of Fröhlich condensation in social and political sciences is really the novel and original approach to mathematical modeling of social stability in society exposed to powerful information radiation from mass-media and Internet-based sources.

Online Health Information Seeking Behaviors Among Older Adults: Systematic Scoping Review.

BackgroundWith the world’s population aging, more health-conscious older adults are seeking health information to make better-informed health decisions. The rapid growth of the internet has empowered older adults to access web-based health information sources. However, research explicitly exploring older adults’ online health information seeking (OHIS) behavior is still underway.ObjectiveThis systematic scoping review aims to understand older adults’ OHIS and answer four research questions: (1) What types of health information do older adults seek and where do they seek health information on the internet? (2) What are the factors that influence older adults’ OHIS? (3) What are the barriers to older adults’ OHIS? (4) How can we intervene and support older adults’ OHIS?MethodsA comprehensive literature search was performed in November 2020, involving the following academic databases: Web of Science; Cochrane Library database; PubMed; MEDLINE; CINAHL Plus; APA PsycINFO; Library and Information Science Source; Library, Information Science and Technology s; Psychology and Behavioral Sciences Collection; Communication & Mass Media Complete; ABI/INFORM; and ACM Digital Library. The initial search identified 8047 publications through database search strategies. After the removal of duplicates, a data set consisting of 5949 publications was obtained for screening. Among these, 75 articles met the inclusion criteria. Qualitative content analysis was performed to identify themes related to the research questions.ResultsThe results suggest that older adults seek 10 types of health information from 6 types of internet-based information sources and that 2 main categories of influencing factors, individual-related and source-related, impact older adults’ OHIS. Moreover, the results reveal that in their OHIS, older adults confront 3 types of barriers, namely individual, social, and those related to information and communication technologies. Some intervention programs based on educational training workshops have been created to intervene and support older adults’ OHIS.ConclusionsAlthough OHIS has become increasingly common among older adults, the review reveals that older adults’ OHIS behavior is not adequately investigated. The findings suggest that more studies are needed to understand older adults’ OHIS behaviors and better support their medical and health decisions in OHIS. Based on the results, the review proposes multiple objectives for future studies, including (1) more investigations on the OHIS behavior of older adults above 85 years; (2) conducting more longitudinal, action research, and mixed methods studies; (3) elaboration of the mobile context and cross-platform scenario of older adults’ OHIS; (4) facilitating older adults’ OHIS by explicating technology affordance; and (5) promoting and measuring the performance of OHIS interventions for older adults.

Predicting dengue incidence leveraging internet-based data sources. A case study in 20 cities in Brazil.

The dengue virus affects millions of people every year worldwide, causing large epidemic outbreaks that disrupt people’s lives and severely strain healthcare systems. In the absence of a reliable vaccine against dengue or an effective treatment to manage the illness in humans, most efforts to combat dengue infections have focused on preventing its vectors, mainly the Aedes aegypti mosquito, from flourishing across the world. These mosquito-control strategies need reliable disease activity surveillance systems to be deployed. Despite significant efforts to estimate dengue incidence using a variety of data sources and methods, little work has been done to understand the relative contribution of the different data sources to improved prediction. Additionally, scholarship on the topic had initially focused on prediction systems at the national- and state-levels, and much remains to be done at the finer spatial resolutions at which health policy interventions often occur. We develop a methodological framework to assess and compare dengue incidence estimates at the city level, and evaluate the performance of a collection of models on 20 different cities in Brazil. The data sources we use towards this end are weekly incidence counts from prior years (seasonal autoregressive terms), weekly-aggregated weather variables, and real-time internet search data. We find that both random forest-based models and LASSO regression-based models effectively leverage these multiple data sources to produce accurate predictions, and that while the performance between them is comparable on average, the former method produces fewer extreme outliers, and can thus be considered more robust. For real-time predictions that assume long delays (6–8 weeks) in the availability of epidemiological data, we find that real-time internet search data are the strongest predictors of dengue incidence, whereas for predictions that assume short delays (1–3 weeks), in which the error rate is halved (as measured by relative RMSE), short-term and seasonal autocorrelation are the dominant predictors. Despite the difficulties inherent to city-level prediction, our framework achieves meaningful and actionable estimates across cities with different demographic, geographic and epidemic characteristics.

Indonesian Defense Diplomacy Strategy in Trilatel Cooperative Arrangement (Port visit Indomalphi 2017-2019)

The Sulu-Sulawesi Sea is a strategic trade route so that it becomes one of the policy priorities. Strategic value does not necessarily bring benefits, but also brings security threats such as piracy, piracy and kidnapping with a ransom demand. In an effort to overcome this, since 2017 the Trilateral Cooperative Arrangement in the Port Visit scheme has been built between the three countries of Indonesia, Malaysia, and the Philippines. The purpose of this study is to analyze the form of Port Visit cooperation and to analyze the Indonesian Defense Diplomacy Strategy in this cooperation. This research uses defense theory, strategy theory, and defense diplomacy theory. This study uses a qualitative descriptive analysis research method. The data collection carried out in this study used primary data through interviews and secondary data from a literature review of journals, books, reports, and internet-based sources. The Trilateral Port Visit Indomalphi cooperation is a response in dealing with transnational crimes in the Sulu-Sulawesi Sea area. With various series of activities, this cooperation plays an important role in efforts to maintain regional security and stability and provides the authority to maintain the safety of all Indonesian citizens as mandated by the law. The Indonesian Defense Diplomacy Strategy in the Indomalphi Port Visit is aimed at increasing mutual trust and military capacity in terms of coordination, communication and piracy capture training. Therefore, the defense diplomacy strategy in this study can be said to have fulfilled the two main characters of defense diplomacy, namely; defense diplomacy to build mutual trust (CBMs) and defense diplomacy to build defense capacity (CB).&#x0D;