Reader engagement with medical content on Wikipedia

Citation needed? Wikipedia bibliometrics during the first wave of the COVID-19 pandemic

Background

With the COVID-19 pandemic’s outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an “infodemic,” ensuring the quality of information is a crucial vector of public health. Investigating whether and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked which sources informed Wikipedia’s COVID-19–related articles before and during the pandemic’s first wave (January–May 2020).

Results

We found that coronavirus-related articles referenced trusted media outlets and high-quality academic sources. Regarding academic sources, Wikipedia was found to be highly selective in terms of what science was cited. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English-language COVID-19 articles from 2001–2020 revealed a nuanced trade-off between quality and timeliness. It further showed how pre-existing articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this “scientific infrastructure” facilitated contextualization and regulated the influx of new information. Last, we constructed a network of DOI-Wikipedia articles, which showed the landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 drug development.

Conclusions

Understanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its “citizen encyclopedists,” it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts.

Diagnosis of Taenia solium infections based on "mail order" RNA-sequencing of single tapeworm egg isolates from stool samples

Combined community health programs aiming at health education, preventive anti-parasitic chemotherapy, and vaccination of pigs have proven their potential to regionally reduce and even eliminate Taenia solium infections that are associated with a high risk of neurological disease through ingestion of T. solium eggs. Yet it remains challenging to target T. solium endemic regions precisely or to make exact diagnoses in individual patients. One major reason is that the widely available stool microscopy may identify Taenia ssp. eggs in stool samples as such, but fails to distinguish between invasive (T. solium) and less invasive Taenia (T. saginata, T. asiatica, and T. hydatigena) species. The identification of Taenia ssp. eggs in routine stool samples often prompts a time-consuming and frequently unsuccessful epidemiologic workup in remote villages far away from a diagnostic laboratory. Here we present "mail order" single egg RNA-sequencing, a new method allowing the identification of the exact Taenia ssp. based on a few eggs found in routine diagnostic stool samples. We provide first T. solium transcriptome data, which show extremely high mitochondrial DNA (mtDNA) transcript counts that can be used for subspecies classification. "Mail order" RNA-sequencing can be administered by health personnel equipped with basic laboratory tools such as a microscope, a Bunsen burner, and access to an international post office for shipment of samples to a next generation sequencing facility. Our suggested workflow combines traditional stool microscopy, RNA-extraction from single Taenia eggs with mitochondrial RNA-sequencing, followed by bioinformatic processing with a basic laptop computer. The workflow could help to better target preventive healthcare measures and improve diagnostic specificity in individual patients based on incidental findings of Taenia ssp. eggs in diagnostic laboratories with limited resources.

Wikipedia in Health Professional Schools: from an Opponent to an Ally

As an online encyclopedia, Wikipedia is the world's largest reference Web site, with 1.7 billion visits per month. Given how easy it is to access and read, students use Wikipedia globally, despite most faculty members' admonitions. Since 2013, health professional schools worldwide have incorporated Wiki-editing into their formal curricula. These courses impact students by (1) strengthening their ability to evaluate evidence-based content and (2) multiplying their contributions to society through improvements to Wikipedia articles accessed by millions. We showcase several models of incorporating Wikipedia-editing assignments into health professions education worldwide. These successful initiatives can be replicated everywhere.

Developing a scalable framework for partnerships between health agencies and the Wikimedia ecosystem

In this era of information overload and misinformation, it is a challenge to rapidly translate evidence-based health information to the public. Wikipedia is a prominent global source of health information with high traffic, multilingual coverage, and acceptable quality control practices. Viewership data following the Ebola crisis and during the COVID-19 pandemic reveals that a significant number of web users located health guidance through Wikipedia and related projects, including its media repository Wikimedia Commons and structured data complement, Wikidata.

The basic idea discussed in this paper is to increase and expedite health institutions' global reach to the general public, by developing a specific strategy to maximize the availability of focused content into Wikimedia’s public digital knowledge archives. It was conceptualized from the experiences of leading health organizations such as Cochrane, the World Health Organization (WHO) and other United Nations Organizations, Cancer Research UK, National Network of Libraries of Medicine, and Centers for Disease Control and Prevention (CDC)'s National Institute for Occupational Safety and Health (NIOSH). Each has customized strategies to integrate content in Wikipedia and evaluate responses.

We propose the development of an interactive guide on the Wikipedia and Wikidata platforms to support health agencies, health professionals and communicators in quickly distributing key messages during crisis situations. The guide aims to cover basic features of Wikipedia, including adding key health messages to Wikipedia articles, citing expert sources to facilitate fact-checking, staging text for translation into multiple languages; automating metrics reporting; sharing non-text media; anticipating offline reuse of Wikipedia content in apps or virtual assistants; structuring data for querying and reuse through Wikidata, and profiling other flagship projects from major health organizations.

In the first phase, we propose the development of a curriculum for the guide using information from prior case studies. In the second phase, the guide would be tested on select health-related topics as new case studies. In its third phase, the guide would be finalized and disseminated.

Wikipedia citations: A comprehensive data set of citations with identifiers extracted from English Wikipedia

Wikipedia’s content is based on reliable and published sources. To this date, relatively little is known about what sources Wikipedia relies on, in part because extracting citations and identifying cited sources is challenging. To close this gap, we release Wikipedia Citations, a comprehensive data set of citations extracted from Wikipedia. We extracted29.3 million citations from 6.1 million English Wikipedia articles as of May 2020, and classified as being books, journal articles, or Web content. We were thus able to extract 4.0 million citations to scholarly publications with known identifiers—including DOI, PMC, PMID, and ISBN—and further equip an extra 261 thousand citations with DOIs from Crossref. As a result, we find that 6.7% of Wikipedia articles cite at least one journal article with an associated DOI, and that Wikipedia cites just 2% of all articles with a DOI currently indexed in the Web of Science. We release our code to allow the community to extend upon our work and update the data set in the future.

COVID-19 research in Wikipedia

Wikipedia is one of the main sources of free knowledge on the Web. During the first few months of the pandemic, over 5,200 new Wikipedia pages on COVID-19 were created, accumulating over 400 million page views by mid-June 2020. 1 At the same time, an unprecedented amount of scientific articles on COVID-19 and the ongoing pandemic have been published online. Wikipedia’s content is based on reliable sources, such as scientific literature. Given its public function, it is crucial for Wikipedia to rely on representative and reliable scientific results, especially in a time of crisis. We assess the coverage of COVID-19-related research in Wikipedia via citations to a corpus of over 160,000 articles. We find that Wikipedia editors are integrating new research at a fast pace, and have cited close to 2% of the COVID-19 literature under consideration. While doing so, they are able to provide a representative coverage of COVID-19-related research. We show that all the main topics discussed in this literature are proportionally represented from Wikipedia, after accounting for article-level effects. We further use regression analyses to model citations from Wikipedia and show that Wikipedia editors on average rely on literature that is highly cited, widely shared on social media, and peer-reviewed.

Scientometric trends for coronaviruses and other emerging viral infections

BACKGROUND

COVID-19 is the most rapidly expanding coronavirus outbreak in the past 2 decades. To provide a swift response to a novel outbreak, prior knowledge from similar outbreaks is essential.

RESULTS

Here, we study the volume of research conducted on previous coronavirus outbreaks, specifically SARS and MERS, relative to other infectious diseases by analyzing >35 million articles from the past 20 years. Our results demonstrate that previous coronavirus outbreaks have been understudied compared with other viruses. We also show that the research volume of emerging infectious diseases is very high after an outbreak and decreases drastically upon the containment of the disease. This can yield inadequate research and limited investment in gaining a full understanding of novel coronavirus management and prevention.

CONCLUSIONS

Independent of the outcome of the current COVID-19 outbreak, we believe that measures should be taken to encourage sustained research in the field.

Wikipedia: A Medical Student Educational Project to Edit Wikipedia in Preparation for Practicing Evidence-Based Pain Medicine

OBJECTIVE

Wikipedia is commonly used to acquire information about various medical conditions such as chronic pain. Ideally, better online pain management content could reduce the burden of opioid use disorders. Our goal was to improve the quality of the content available on Wikipedia to make it more accurate and applicable to medical students and the general public while training medical students to practice evidence-based medicine and critically assess their sources of information.

METHODS

An elective class in Neuroscience, Pain, and Opioids composed of 10 medical students met biweekly to discuss landmark and practice-changing research articles in the fields of acute pain, chronic pain, and opioid management. The professor chose Wikipedia articles relevant to this course. Three independent viewers analyzed the quality of citations, anecdotal medical content, and content value for both patients and medical professionals. As part of their coursework, students then edited the Wikipedia articles.

RESULTS

Although some of the Wikipedia pain topic content (6.7% ± 2.0) was anecdotal, financially biased, or inconsistent with Western Medical Practice content, overall articles included primarily high-quality citations (85.6% ± 3.1). On a 0-5 Likert scale, students felt content would be moderately helpful for both medical students/professionals (3.4 ± 0.2) and laypersons (3.5 ± 0.2). Editing and adding citations was feasible, but novel material was often reverted.

CONCLUSION

A significant amount of pain medicine content was relevant and amenable to student editing. Therefore, future use of this tactic could provide a unique opportunity to integrate evidence-based medicine into the medical curriculum and have a direct impact on the widely available medical information. Future refinement in the editorial process may also further improve online information.