Search results

Clinical notes typically contain medical jargons and specialized words and phrases that are complicated and technical to most people, which is one of the most challenging obstacles in health information dissemination to consumers by healthcare providers. The authors aim to investigate how to leverage machine learning techniques to transform clinical notes of interest into understandable expressions.

The authors propose a natural language processing pipeline that is capable of extracting relevant information from long unstructured clinical notes and simplifying lexicons by replacing medical jargons and technical terms. Particularly, the authors develop an unsupervised keywords matching method to extract relevant information from clinical notes. To automatically evaluate completeness of the extracted information, the authors perform a multi-label classification task on the relevant texts. To simplify lexicons in the relevant text, the authors identify complex words using a sequence labeler and leverage transformer models to generate candidate words for substitution. The authors validate the proposed pipeline using 58,167 discharge summaries from critical care services.

The results show that the proposed pipeline can identify relevant information with high completeness and simplify complex expressions in clinical notes so that the converted notes have a high level of readability but a low degree of meaning change.

The proposed pipeline can help healthcare consumers well understand their medical information and therefore strengthen communications between healthcare providers and consumers for better care.

An innovative pipeline approach is developed to address the health literacy problem confronted by healthcare providers and consumers in the ongoing digital transformation process in the healthcare industry.

To elaborate the picture of credibility assessment by examining how participants of online discussion evaluate the informational credibility of conspiracy theories.

Descriptive quantitative analysis and qualitative content analysis of 2,663 posts submitted to seven Reddit threads discussing a conspiracy operation, that is, the damage of the Nord Stream gas pipelines in September 2022. It was examined how the participants of online discussion assess the credibility of information constitutive of conspiracy theories speculating about (1) suspected actors responsible for the damage, (2) their motives and (3) the ways in which the damage was made. The credibility assessments focussed on diverse sources offering information about the above three factors.

The participants assessed the credibility of information by drawing on four main criteria: plausibility of arguments, honesty in argumentation, similarity to one's beliefs and provision of evidence. Most assessments were negative and indicated doubt about the informational believability of conspiracy theories about the damage. Of the information sources referred to in the discussion, the posts submitted by fellow participants, television programmes and statements provided by governmental organizations were judged most critically, due to implausible argumentation and advocacy of biased views.

As the study focuses on a sample of posts dealing with conspiracy theories about a particular event, the findings cannot be generalized to concern the informational credibility conspiracy narratives.

The study pioneers by providing an in-depth analysis of the nature of credibility assessments by focussing on information constitutive of conspiracy theories.

Females are underrepresented in Science, Technology, Engineering and Mathematics (STEM), both in the workforce and in universities. Low self-efficacy and limited access to role models are key factors preventing retention of female STEM students enrolled in university degrees. This paper aims to report on one social marketing pilot programme that was co-designed to increase self-efficacy in females currently enrolled in STEM programmes.

The Co-create, Build and Engage (C-B-E) framework was applied. Process and outcome evaluations were conducted using a repeated measure design to assess pilot programme effectiveness.

A significant increase in self-efficacy and high satisfaction rates were observed for STEM students that attended the bias literacy workshop. Social advertisements raised awareness for available STEM specific university services.

This paper outlines the application of the C-B-E framework. To the best of the authors’ knowledge, this study delivers the first scientific paper reporting an outcome evaluation for a social marketing programme seeking to retain women enrolled in university STEM degrees.

Progress toward health equity is necessary to reduce health disparities, and health literacy is key to achieving this goal. Because libraries provide access to knowledge and insights about their communities, they are effective partners in advancing health equity and implementing programs to reduce health disparities. A literature review on library programs and activities that focus on promoting health equity was conducted.

A literature review on library programs and activities concerning health equity and social determinants of health was conducted. Relevant literature was identified from searches of databases, library publications and grey literature.

The authors found 224 eligible sources and many types of libraries advancing health equity. Libraries frame their role in advancing health equity through external programs in three ways: (1) providing access to high-quality health information, (2) delivering health literacy training and resources and (3) connecting their communities with community health services. Libraries also advance health equity by focusing on internal library operations and providing research services focused on cultural humility and competence as they apply to health care.

This literature review will help the National Library of Medicine (NLM) develop a strategy to support libraries advancing health equity through information made available by programs and activities of NLM and the Network of the National Library of Medicine.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

Many of today’s information and technology systems and environments facilitate inquiry, learning, consciousness-raising and knowledge-building. Such platforms include e-learning systems which have learning, education and/or training as explicit goals or objectives. They also include search engines, social media platforms, video-sharing platforms, and knowledge sharing environments deployed for work, leisure, inquiry, and personal and professional productivity. The new journal, Information and Learning Sciences, aims to advance our understanding of human inquiry, learning and knowledge-building across such information, e-learning, and socio-technical system contexts.

This article introduces the journal at its launch under new editorship in January, 2019. The article, authored by the journal co-editors and all associate editors, explores the lineage of scholarly undertakings that have contributed to the journal's new scope and mission, which includes past and ongoing scholarship in the following arenas: Digital Youth, Constructionism, Mutually Constitutive Ties in Information and Learning Sciences, and Searching-as-Learning.

The article offers examples of ways in which the two fields stand to enrich each other towards a greater holistic advancement of scholarship. The article also summarizes the inaugural special issue contents from the following contributors: Caroline Haythornthwaite; Krista Glazewski and Cindy Hmelo-Silver; Stephanie Teasley; Gary Marchionini; Caroline R. Pitt; Adam Bell, Rose Strickman and Katie Davis; Denise Agosto; Nicole Cooke; and Victor Lee.

The article, this special issue, and the journal in full, are among the first formal and ongoing publication outlets to deliberately draw together and facilitate cross-disciplinary scholarship at this integral nexus. We enthusiastically and warmly invite continued engagement along these lines in the journal’s pages, and also welcome related, and wholly contrary points of view, and points of departure that may build upon or debate some of the themes we raise in the introduction and special issue contents.

This paper shares findings from a multi-year literacy professional development partnership between a school district and university (2014–2019). We share this case of a Literacy Cohort initiative as an example of cross-institutional professional development situated within several of NAPDS’ nine essentials, including professional learning and leading, boundary-spanning roles and reflection and innovation (NAPDS, 2021).

We asked, “In what ways did the Cohort initiative create conditions for community and collaboration in the service of meaningful literacy reforms?” Drawing on social design methodology (Gutiérrez & Vossoughi, 2010), we sought to generate and examine the educational change associated with this multi-year initiative. Our data set included programmatic data, interviews (N = 30) and artifacts of literacy teaching, learning and leading.

Our findings reflect the emphasis areas that are important to educators in the partnership: diversity by design, building relationships through collaboration and rooting literacy reforms in teacher leadership. Our discussion explores threads of reciprocity, simultaneous renewal and boundary-spanning leadership and their role in sustaining partnerships over time.

This paper contributes to our understanding of building and sustaining a cohort model of multi-year professional development through the voices, perspectives and experiences of teachers, faculty and district administrators.