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"Information sources"
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What are primary sources?
An introduction to the concept of primary sources, which are works that provide original information.
Book
The Impact of Health Information Exposure and Source Credibility on COVID-19 Vaccination Intention in Germany
Due to the novelty and high transmission rate of the coronavirus disease 2019 (COVID-19), direct medical countermeasures are urgently needed. Among actions against the further outbreak of COVID-19, vaccination has been considered as a chief candidate. However, the rapid development of COVID-19 vaccines has led to concern about their safety and thus to public vaccine hesitancy. Strategic heath communication channels, which are widely used and highly trusted, can contribute to more effective promotions of vaccination intention and to the reduction of misleading information about COVID-19 vaccines. Therefore, this study examines the relationship between the exposure to and credibility of different health information sources and the COVID-19 vaccination intention among 629 German adults. Descriptive statistical analysis and multiple linear regressions are employed to examine the research questions. Results reveal that, aside from reliable information from experts and health authorities, local newspapers also have a positive impact on COVID-19 vaccination intention. However, this effect diminishes to some extent when age is considered. In addition, alternative information sources pose a noticeable threat to COVID-19 vaccination intention. Therefore, a close cooperation between healthcare experts, health authorities, and mass media with regard to information dissemination is conducive for vaccination campaigns and for the fight against misleading claims about COVID-19 vaccines.
Journal Article
Learning About Primary Sources
\"Introduces readers to primary sources. Includes a hands-on activity related to media literacy\"-- Provided by publisher.
Book
Sources of Health Information and Their Impacts on Medical Knowledge Perception Among the Saudi Arabian Population: Cross-Sectional Study
Having a reliable source for health information is vital to build a strong foundation of knowledge, especially with the current revolution of the internet and social media, which raises many concerns regarding harmful effects on the health of the public. However, there are no studies on how the Saudi Arabian population seeks health information. Details about the most used and trusted sources of health information among the public will help health authorities and public awareness accounts on social media to effectively disseminate health information.
To investigate the types of sources accessed by the Saudi Arabian population while seeking health information, as well as their level of trust in the sources and to assess the impact of these sources on their perception of medical knowledge and health decision-making.
A cross-sectional study was conducted to meet the objectives. The study population included both men and women who were aged 16 years or more and visited primary care clinics at King Khalid University Hospital. Four hundred and thirteen participants were sampled using the simple random method, and a self-administered questionnaire was used to collect data. The data were analyzed using SPSS software (IBM Corp, Armonk, New York, USA).
A total of 413 participants were included in this study, and of these, 99 (24.0%) were males and 206 (49.9%) had a bachelor's degree. Doctors were chosen as the first source of information by 87.6% (283/323) of the participants, and they were completely trusted by most of the population (326/411, 79.3%). The second most commonly used source was pharmacists (112/194, 57.7%), and they were partially trusted by 41.4% (159/384) of the participants. Internet searches, social media, and traditional medicine were not prioritized by most of the participants as the first or second source of health information. The majority of the participants did not trust information obtained from social media, and WhatsApp was the most untrusted source. Almost half of the respondents (197/413, 47.7%) acknowledged that various sources of information can often help them understand their health problems. However, the majority disagreed on substituting a doctor's prescription with information obtained from the internet or a friend or relative.
Although physicians were preferred and highly trusted, internet sources appeared to impact the medical knowledge of the population. The population still preferred to use internet search to obtain health information prior to a doctor's visit.
Journal Article
Using primary sources
In this book, readers will learn how to identify and use primary sources.
Book
Users choose to engage with more partisan news than they are exposed to on Google Search
If popular online platforms systematically expose their users to partisan and unreliable news, they could potentially contribute to societal issues such as rising political polarization
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. This concern is central to the ‘echo chamber’
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and ‘filter bubble’
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debates, which critique the roles that user choice and algorithmic curation play in guiding users to different online information sources
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. These roles can be measured as exposure, defined as the URLs shown to users by online platforms, and engagement, defined as the URLs selected by users. However, owing to the challenges of obtaining ecologically valid exposure data—what real users were shown during their typical platform use—research in this vein typically relies on engagement data
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or estimates of hypothetical exposure
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. Studies involving ecological exposure have therefore been rare, and largely limited to social media platforms
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, leaving open questions about web search engines. To address these gaps, we conducted a two-wave study pairing surveys with ecologically valid measures of both exposure and engagement on Google Search during the 2018 and 2020 US elections. In both waves, we found more identity-congruent and unreliable news sources in participants’ engagement choices, both within Google Search and overall, than they were exposed to in their Google Search results. These results indicate that exposure to and engagement with partisan or unreliable news on Google Search are driven not primarily by algorithmic curation but by users’ own choices.
Ecologically valid data collected during the 2018 and 2020 US elections show that exposure to and engagement with partisan or unreliable news on Google Search are driven not primarily by algorithmic curation but by users’ own choices.
Journal Article
Toward spatial humanities : historical GIS and spatial history
\"The application of geo-spatial technologies, especially Geographic Information Systems (GIS), to issues in history is among the most exciting developments in both digital humanities and spatial humanities. The book captures the wide variety of geo-spatial applications to both traditional and non-traditional subjects in history through a series of exemplary essays designed to signal to non-specialists the methodological and substantive implications of a spatial approach to the humanities. The aim of the book is to illustrate how the use of historical GIS is changing our understanding of the geographies of the past, and how it has become the foundation for new approaches to the study of history. The essays are divided into two parts. The first features new approaches to the past by focusing on current developments in the use of historical sources. The second looks at the insights gained by applying GIS to develop historiography. Together the essays form, not a 'how-to' guide for researchers, but a compelling demonstration of how GIS can contribute to our historical understanding\"-- Provided by publisher.
Book
Social media use and influenza vaccine uptake among White and African American adults
Influenza vaccination rates in the U.S. remain low at 41% among adults over 18 years according to the Centers for Disease Control and Prevention’s 2016 data. Reasons for the low rate vary and include factors such as risk perception, vaccine hesitancy, and access to health care. This cross-sectional study sought to examine the relationship between social media use and influenza vaccine uptake among a sample of White and African Americans over 18 years of age. Using bivariate, and unadjusted and adjusted logistic regression tests, this study examined the relationship among social media use, social media as a source of health information, and influenza vaccination status in 2015. Our results indicate that users of Twitter (OR4.41, 95%CI: 1.43–13.60) and Facebook (OR 1.66, 95%CI: 1.01–2.72) as sources of health information were more likely to be vaccinated in comparison to users who do not use Twitter or Facebook as a source of health information. These findings have implications for the potential of using social media platforms to disseminate influenza vaccine information and encourage users to get vaccinated annually.
Journal Article
Parental digital health information seeking behavior in Switzerland: a cross-sectional study
Background
Digital media are increasingly abundant and used to seek health information, however, to date very little is known on parents’ seeking behavior in the context of child’s health and development outside English-speaking and Scandinavian countries. By investigating the prevalence of, and reasons for use, we studied parents’ perception of the Internet as a resource for improving their health-related knowledge.
Methods
The survey was conducted in a random sample of 2573 Swiss-German parents with at least one child aged less-than 2 years old. Parents received a mailed invitation to fill in an online questionnaire. Two reminders were sent, the later with a paper questionnaire attached. The questionnaire included questions on use of print, digital, and personal information sources, as well as different information situations: general health and development or illness. We ran descriptive analyses on information seeking behavior, type of digital media used, reasons of use. We also conducted regression analyses to explore factors associated with parental perceptions with regard to the Internet’s utility as a source for health information.
Results
A total of 769 questionnaires were returned (response rate 30%). Nearly all parents (91%) used digital media for seeking information on their child’s health and development, and the main reason for use was indicated as being the 24/7 availability of information. Search engines (55%) and webpages for parents (47%) were by far the most frequently used digital media. Generally, the internet is perceived as a good resource, especially by fathers (OR = 1.80, 95% CI: 1.03–3.16). However, a large percentage of parents are skeptical about the correctness of online info (91%), are unsure about their interpretive understanding, and ask for guidance from their pediatrician (67%).
Conclusions
The Internet has become a highly frequented source of information for Swiss-German parents on children’s health with largely valuable perceptions of its utility. Digital media are used in addition to and not in replacement of print media and personal contacts. Increasing parental guidance by health and public health professionals could improve parental digital health utilization and empower parents in the new role they adopt.
Journal Article
Fair and green hyperparameter optimization via multi-objective and multiple information source Bayesian optimization
It has been recently remarked that focusing only on accuracy in searching for optimal Machine Learning models amplifies biases contained in the data, leading to unfair predictions and decision supports. Recently, multi-objective hyperparameter optimization has been proposed to search for Machine Learning models which offer equally Pareto-efficient trade-offs between accuracy and fairness. Although these approaches proved to be more versatile than fairness-aware Machine Learning algorithms—which instead optimize accuracy constrained to some threshold on fairness—their carbon footprint could be dramatic, due to the large amount of energy required in the case of large datasets. We propose an approach named FanG-HPO: fair and green hyperparameter optimization (HPO), based on both multi-objective and multiple information source Bayesian optimization. FanG-HPO uses subsets of the large dataset to obtain cheap approximations (aka information sources) of both accuracy and fairness, and multi-objective Bayesian optimization to efficiently identify Pareto-efficient (accurate and fair) Machine Learning models. Experiments consider four benchmark (fairness) datasets and four Machine Learning algorithms, and provide an assessment of FanG-HPO against both fairness-aware Machine Learning approaches and two state-of-the-art Bayesian optimization tools addressing multi-objective and energy-aware optimization.
Journal Article