I Wouldn’t Search That With My Mobile Phone: Credibility and Trust in OHIRs Among Lower-Income Black Older Adults

Online health information resources (OHIRs) such as conversational assistants and smart devices that provide access to consumer health information in the home are promoted as viable options for older adults to independently manage health. However, there is question as to how well these devices are perceived to meet the needs of marginalized populations such as lower-income Black older adults who often experience lower digital literacy or technology proficiency. We examined the experiences of 34 lower-income Black older adults aged 65-83 from Chicago and Detroit with various OHIRs and explored whether conversational resources were perceived to better support health information seeking compared to traditional online web searching. In a three-phase study, participants tracked their experiences with various OHIRs and documented health-related questions in a health diary. Participants were then interviewed about their diaries in focus groups and semi-structured interviews, followed by a technology critique and co-design session to re-envision a more usable and engaging conversational device. We present preliminary results of the themes that emerged from our analysis: cultural variables in health information seeking practices, perceptions of credibility, likelihood of use, and system accessibility. Participants indicated that their trust of different resources depended on the type of information sought, and that conversational assistants would be a useful resource that require less technology proficiency, even among those with lower e-health literacy. Although our findings indicate that familiarity and trust were salient constructs associated with perceptions of OHIRs, these devices may address digital literacy and technology familiarity with certain design considerations.

Comparative Conceptual Analysis in a Legal Translation Classroom: Where Do the Pitfalls Lie

It is a well-acknowledged fact in legal translation studies that when searching for terminological equivalents, translators should make use of comparative conceptual analysis (e.g. Sandrini 1996; Chromá 2014; Engberg 2015). Thus, legal translation trainees should be equipped with the necessary tools to carry out such analysis, but the question remains: are they? This paper is a follow-up to a study published in 2017 (Klabal, Knap-Dlouhá and Kubánek 2017), where modified think aloud protocols were used to explore the following research question: to what degree are university students doing a course in legal and economic translation able to apply the methods of comparative conceptual analysis to translation of terms not accounted for sufficiently in legal dictionaries or terms with no straightforward equivalents. The results showed that major issues involve non-linearity of the analysis carried out and insufficient use of the resources available. The present study involves a different group of 29 BA students of the same course two years later, who were assigned the same task. As the retrospective protocols fail to simulate real-life conditions, this study uses screen recording and keystroke logging to track the processes leading to the identification of the conceptual equivalent in a more detailed and less subject-dependent manner. The results suggest that the steps most challenging for students include identification of relevant (essential) features defining the source and target language concepts, comparison of these features and selection, or creation, of an equivalent term reflecting the results of the analysis. Students also frequently show Google-driven searching, which influences the order of the steps performed in their analyses and the sources used. To address these challenges, translation training should include a range of tailor-made exercises focusing on the critical steps of the analysis as well as on improving web searching skills.

Probabilistic Thinking: A Principle-Based Concept Analysis in the Context of Uncertainty in Chronic Illness

Background and PurposeThe Reconceptualized Uncertainty in Illness Theory (RUIT) includes the concept of “probabilistic thinking” intending to explain the positive reappraisal of uncertainty in chronic illness. However, the description of the concept is vague, thereby limiting the understanding of the theory. Thus, the aim was to develop a theoretical definition of probabilistic thinking in order to increase the explanatory value of RUIT.MethodsWe conducted a principle-based concept analysis by means of a conceptually driven literature search. Methods consisted of database, dictionary, lexicon, and free web searching as well as citation tracking. We analyzed the concept in terms of (a) epistemology, (b) pragmatics, (c) logic, and (d) linguistics.ResultsThe final data set included 27 publications, 14 of them from nursing. (a) Probabilistic thinking is a coping strategy to handle uncertainty. It involves a focus on either possibilities (in nursing) or probabilities (in other disciplines). (b) There is a lack of operationalization in nursing, though three measurements focusing the handling of probabilities are offered in psychology. (c) Nursing authors interpreting probabilistic thinking as accepted uncertainty lacked logical appropriateness, since probability negotiates uncertainty. (d) Probabilistic thinking is used synonymously with positive thinking and probabilistic reasoning.Implications for PracticeNurses working with chronically ill patients should consider the findings for the application of RUIT. They should recognize whether uncertainty is perceived as a danger and encourage probabilistic thinking. Efforts are necessary to achieve a common language between nursing and other disciplines in order to avoid misunderstandings in clinical practice and research.

Using citation tracking for systematic literature searching - study protocol for a scoping review of methodological studies and a Delphi study

Background: Up-to-date guidance on comprehensive study identification for systematic reviews is crucial. According to current recommendations, systematic searching should combine electronic database searching with supplementary search methods. One such supplementary search method is citation tracking. It aims at collecting directly and/or indirectly cited and citing references from "seed references". Tailored and evidence-guided recommendations concerning the use of citation tracking are strongly needed. Objective: We intend to develop recommendations for the use of citation tracking in systematic literature searching for health-related topics. Our study will be guided by the following research questions: What is the benefit of citation tracking for systematic literature searching for health-related topics? Which methods, citation indexes, and other tools are used for citation tracking? What terminology is used for citation tracking methods? Methods: Our study will have two parts: a scoping review and a Delphi study. The scoping review aims at identifying methodological studies on the benefit and use of citation tracking in systematic literature searching for health-related topics with no restrictions on study design, language, and publication date. We will perform database searching in MEDLINE (Ovid), CINAHL (EBSCOhost), Web of Science Core Collection, two information science databases, web searching, and contact experts in the field. Two reviewers will independently perform study selection. We will conduct direct backward and forward citation tracking on included articles. Data from included studies will be extracted using a prespecified extraction sheet and presented in both tabular and narrative form. The results of the scoping review will inform the subsequent Delphi study through which we aim to derive consensus recommendations for the future practice and research of citation tracking.

Securing Hospital Data with Blockchain and AI

In cyber world everything is dependent on data and all Artificial Intelligence algorithms discover knowledge from past data only, With the development of information technologies, the trend of integrating cyber, physical and social (CPS) systems to a highly unified information society, rather than just a digital Internet, is becoming increasing obvious. An increasing amount of personal data, including location information, web-searching behaviour, user calls, user preference, is being silently collected by the built-in sensors inside the products from those big companies, which brings in huge risk on privacy leakage of data owners. In this paper, we aim at securing data by combining blockchain and AI together, and design a Secure Networking architecture (termed as SecNet) to significantly improve the security of data sharing, and then the security of the whole network. In SecNet, to protect data, one of the biggest challenges is where and how to store data, because users have to give their data to service providers if they want to use certain services or applications.

In quest of goldilocks ranges in searching for information on the web

PurposeThe quest to discover optimal conditions or amounts has been carried out in many scientific disciplines and practical fields. In astrophysics, biology, medicine, psychology and education, the quest has resulted in finding the right amount of something, a desirable middle between extremes, a balance between conditions or the optimal state of a system. The results are referred to as the Goldilocks principle, which is based on the idea of being “just right”. The aim of our study was to find out if there are any measures in information search that could be identified as Goldilocks ranges.Design/methodology/approachWe conducted a user experiment in which 68 participants carried out a time-unlimited, topical search task involving finding relevant websites on the basis of which the participants were supposed to prepare a presentation on a given topic. We examined aspects of their search behavior.FindingsWe found that information search Goldilocks ranges can be identified for a length of a search session, number of relevant results, number of queries submitted and number of search engine results pages (SERPs) visited. This preliminary study has resulted in indicating the following dominant ranges: Number of relevant documents found: 5–8; Time spent searching: 21–35 min; Number of queries submitted: 3–7; Number of SERPs viewed: 1–3.Originality/valueTill now, no one has studied Goldilocks ranges in information retrieval. The Goldilocks ranges have some practical implications for improving the effectiveness of web searching.

A Framework to Analyze Business Process Log in XML Format

XML has numerous uses in a wide variety of web pages and applications. Some common uses of XML include tasks for web publishing, web searching and automation, and general application such as for utilize, store, transfer and display business process log data. The amount of information expressed in XML has gone up rapidly. Many works have been done on sensible approaches to address issues related to the handling and review of XML documents. Mining XML documents offera way to understand both the structure and the content of XML documents. A common approach capable of analysing XML documents is frequent subtree mining.Frequent subtree mining is one of the data mining techniques that finds the relationship between transactions in a tree structured database. Due to the structure and the content of XML format, traditional data mining and statistical analysis hardly applied to get accurate result. This paper proposes a framework that can flatten a tree structured data into a flat and structured data, while preserving their structure and content.Enabling these XML documents into relational structured data allows a range of data mining techniques and statistical test can be applied and conducted to extract more information from the business process log.

Datacenter Networks

In today’s society, datacenters play significant roles by providing data storage and computing power needed to carry out a wide variety of tasks, such as web mail, web searching, online transactions, social networking for individuals, and big-data processing tasks at organizational level, including machine learning, and high-performance computing. Datacenters typically consist of a large number of interconnected servers, up to hundreds of thousands of them, hence needing bandwidth-efficient networking between themselves with controlled power operation. Use of optical switching in intra-datacenter networks can significantly improve their overall performance with enhanced speed and reduced power consumption. We present various types of datacenters, using electrical, optical, and hybrid switching. Finally, we present some heuristic methods for designing WRON-based backbone networks for hosting datacenters at suitable locations, and a popularity-based replication strategy of various objects in the selcted datacenters. (136 words)