How covid-19 bolstered an already perverse publishing system

How COVID-19 affected academic publishing: a 3-year study of 17 million research papers

BACKGROUND

The COVID-19 pandemic induced an unprecedented response from the scientific research community. Previous studies have described disruption of the norms of academic publishing during this time. This study uses an epidemiological statistical toolkit alongside machine-learning methods to investigate the functioning of the scientific information-generation and -consumption ecosystem throughout the pandemic.

METHODS

A dataset of 17 million scientific research papers that were published between January 2019 and December 2022 was analysed. Data on citations and Altmetrics were harvested, and topic modelling was applied to abstracts. COVID-19-related articles were identified from title text. We investigated publication dynamics, correlations between citation metrics and Altmetrics, rates of publication in preprints, and temporal trends in topics, and compared these metrics in COVID-19 papers vs non-COVID-19 papers.

RESULTS

Throughout 2020-2, 3.7% of English-language research output was on the topic of COVID-19. Journal articles on COVID-19 were published at a consistent rate during this period, while preprints peaked in early 2020 and decreased thereafter. COVID-19 preprints had lower publication rates in the peer-reviewed literature than other preprints, particularly those that were preprinted during early 2020. COVID-19 research received significantly more media and social media attention than non-COVID-19 research, and preprints received more attention, on average, than journal articles, with attention peaking during the initial wave and subsequent peaks corresponding to the emergence of novel variants. COVID-19 articles exhibited a higher correlation between Altmetrics and citation metrics compared with non-COVID-19 publications, suggesting a strong alignment between scientific and public attention.

CONCLUSION

This study provides a comprehensive description of the rapid expansion of COVID-19 research, revealing evolving research areas and waxing and waning public interest across different topics. Preprints played an important role in disseminating scientific findings, but the level of coverage of preprinted findings emphasizes the need for guidelines in handling preprint research in media, particularly during a pandemic.

Using artificial intelligence tools to automate data extraction for living evidence syntheses

Living evidence synthesis (LES) involves repeatedly updating a systematic review or meta-analysis at regular intervals to incorporate new evidence into the summary results. It requires a considerable amount of human time investment in the article search, collection, and data extraction phases. Tools exist to automate the retrieval of relevant journal articles, but pulling data out of those articles is currently still a manual process. In this article, we present a proof-of-concept Python program that leverages artificial intelligence (AI) tools (specifically, ChatGPT) to parse a batch of journal articles and extract relevant results, greatly reducing the human time investment in this action without compromising on accuracy. Our program is tested on a set of journal articles that estimate the mean incubation period for COVID-19, an epidemiological parameter of importance for mathematical modelling. We also discuss important limitations related to the total amount of information and rate at which that information can be sent to the AI engine. This work contributes to the ongoing discussion about the use of AI and the role such tools can have in scientific research.

SIFT-ing Through Misinformation: Reflection Notebooks to Teach Critical Digital Literacy

BACKGROUND

The COVID-19 infodemic revealed nurses are not immune from disseminating health misinformation. Furthermore, the 2021 American Association of Colleges of Nursing (AACN) Essentials require competency in social media literacy. Nurse educators need to prepare students to identify credible information online for safe and ethical practice.

PROBLEM

Vertical reading, a traditional evaluation strategy used in nursing education, is insufficient for identifying online health misinformation.

APPROACH

A librarian and nursing faculty member developed an innovative reflection notebook assignment to teach lateral reading-a professional fact-checking technique-and facilitate critical self-reflection among RN-to-BSN students.

OUTCOMES

Reflection notebook responses demonstrated that students use online information in various ways; online information habits require active, ongoing professional development; and lateral reading can promote a more compassionate approach to patient education.

CONCLUSIONS

The reflection notebooks equip students with critical knowledge, skills, and attitudes to practice safely and ethically while demonstrating some of the AACN Essentials requirements.

Trends in Dehydration in Older People: Identifying Landmark Scientific Contributions

BACKGROUND

Dehydration and low fluid intake cause the most prevalent electrolyte imbalance in older adults and increase their morbi-mortality.

OBJECTIVE

To analyse the scientific production on dehydration in older adults.

METHODS

A bibliometric analysis was performed using the Web of Science Core Collection database. The data were analysed using two software programs, the Bibliometric package for RStudio version 4.2.2, and VOSviewer 1.6.18 for the analysis of the scientific production, authors, citations, countries and collaborations, journals, research areas, and keywords.

RESULTS

A total of 205 articles were selected. An increase in the number of publications has been observed since 2012, with 2021 being the most productive year. With respect to scientific production, although the USA had the most publications, the two most prolific authors were affiliated with an institution located in the UK, with this country having the most collaborations with other countries in the development of the subject matter. The co-occurrence analysis indicated that the words with the highest occurrence were dehydration (n = 103), hydration (n = 39), prevalence (n = 30), mortality (n = 29), and thirst (n = 29).

CONCLUSIONS

This is the first bibliometric analysis that shows the publication trends on dehydration in older adults. Although the number of publications is limited, they have increased in number in the last few years. The research trends are centred on the prevalence of dehydration and its related factors. More studies are needed that are centred on interventions to correct the problem, to help fight against the electrolyte imbalances that occur, and to reduce the morbi-mortality associated with this condition.

Comparison of journal and top publisher self-citation rates in COVID-19 research

INTRODUCTION

Journal self-citation contributes to the overall citation count of a journal and to some metrics like the impact factor. However, little is known about the extent of journal self-citations in COVID-19 research. This study aimed to determine the journal self-citations in COVID-19 research and to compare them according to the type of publication and publisher.

METHODS

Data in COVID-19 research extracted from the Web of Science Core Collection 2020-2023 was collected and further analyzed with InCites. The journals with the highest self-citation rates and self-citation per publication were identified. Statistical comparisons were made according to the type of publication and publishers, as well as with other major infectious diseases.

RESULTS

The median self-citation rate was 4.0% (IQR 0-11.7%), and the median journal self-citation rate was 5.9% (IQR 0-12.5%). 1,859 journals (13% of total coverage) had self-citation rates at or above 20%, meaning that more than one in five references are journal self-citations. There was a positive and statistically significant correlation of self-citations with the other indicators, including number of publications, citations, and self-citations per publication (p<0.001). Editorial materials contributed more to journal SC with a median self-citation rate of 5%, which was statistically higher than other documents such as articles, letters or reviews (p<0.001). Among the top twelve publishers, the Multidisciplinary Digital Publishing Institute had a median self-citation rate of 8.33% and was statistically higher than the rest (p<0.001). Self-citation rates for COVID-19 were lower than tuberculosis and HIV/AIDS, but self-citations per publication of these diseases were statistically lower than those for COVID-19 (p<0.001).

CONCLUSION

Some journals from the Web of Science Core Collection displayed exorbitant journal self-citation patterns during the period 2020-2023. Approximately, one in every five paper references in COVID-19 is a journal self-citation. Types of publication such as editorials engage in this practice more frequently than others, suggesting that in COVID-19 research, self-citing non-citable items could potentially contribute to inflate journal impact factors during the pandemic.

Global research in schizophrenia and serotonin: a bibliometric analysis

Background

Schizophrenia is a chronic mental illness that affects millions of individuals worldwide. The etiological origin of schizophrenia is heterogeneous, but it has been shown to be associated with dysfunction in serotonin activity, serotonin receptors, and serotonin metabolism in the brain. Bibliometric analysis is a tool used to scrutinise and analyse research activities and evidence in a specific research area. No existing bibliometric analyses have considered both serotonin and schizophrenia.

Methods

We conducted a bibliometric analysis including 12,027 studies related to the schizophrenia-serotonin link published from the inception of the study to 2023 and available in the Scopus database. We used VOSviewer software to identify global trends, analyse the author and editors keywords, the most cited articles and author, as well as the most productive institutes and journals publishing research on schizophrenia-serotonin link.

Results

Most publications related to the link between schizophrenia and serotonin are focused on adult humans and examine topics such as antipsychotic agents, depression, and serotonin uptake inhibitors. The Journal of Clinical Psychiatry has published the most papers on the schizophrenia-serotonin relationship. Among nations, the United States is the leader in publications. King's College London is the institution with the highest number of publications, and H. Y. Meltzer is the most influential author. Growing trends in schizophrenia-serotonin research are personalised medicine, alternative medicine, transcranial magnetic stimulation, artificial intelligence, nervous system inflammation, brain-gut axis, and the gut microbiome.

Conclusion

Since 1950, there have been several fluctuations in the number of published studies related to schizophrenia and serotonin. We believe that the development of novel medications and treatments for schizophrenia will be increased in the future, as well as research into genetic risks, psychological factors, and cranial neuroimaging components. Future schizophrenia and serotonin research is likely to focus on personalised medicine, alternative therapies, novel pathogenesis of schizophrenia, and the use of emerging technologies such as artificial intelligence.

COVID-19 Response of the Journal Public Health Reports (PHR), March 2020-March 2023

OBJECTIVE

Publication science is the scholarly study of various aspects of the academic publishing process. Its applications to COVID-19 literature have been limited. Here, we describe COVID-19 submissions to, and resulting articles published by, the journal Public Health Reports (PHR), an important resource for US public health practice.

METHODS

We reviewed PHR's COVID-19 submissions and articles published between March 27, 2020, and March 27, 2023. We coded each article for article type, author affiliation, the categories listed in PHR's call for COVID-19 papers, and the public health emergency preparedness and response capabilities from the Centers for Disease Control and Prevention (CDC).

RESULTS

During the study period, PHR received 1545 COVID-19 submissions and published 190 of those articles in a collection, COVID-19 Response. The COVID-19 Response collection included 102 research articles, 29 case study/practice articles, and 24 commentaries. The corresponding author of more than half (52.1%; n = 99) of the articles was affiliated with academia. By the categories listed in PHR's call for COVID-19 papers, 51 articles addressed health disparities, 38 addressed public health surveillance, and 34 addressed COVID-19 vaccination. By the CDC public health emergency preparedness and response capabilities, 87 articles addressed public health surveillance and epidemiologic investigation, 38 addressed community preparedness, and 32 addressed community recovery. The percentage of articles focused on policy/law was higher early in the pandemic (2020-2021) than later (2022-2023) (9.5% vs <3.0%). During the latter period, articles largely focused on vaccination (12.8%) and contact tracing (10.6%).

CONCLUSIONS

Articles published in PHR's COVID-19 Response collection covered a broad range of topics and were authored by contributors from diverse organizations. Our characterization of the COVID-19 output of a representative US public health practice journal can help academic publishing better address informational needs of public health responders.

Characteristics of retracted research papers before and during the COVID-19 pandemic

Objectives

During the COVID-19 pandemic, a large number of research papers were published, and some of them were retracted. The present study aims to reveal the characteristics of retracted papers before and during the pandemic.

Methods

The study investigated 24,542,394 publications from 1999 to 2022 and analyzed the profiles of retracted papers from the perspectives of year, disease category, country, and journal.

Results

Retraction rates were generally increasing at least until 2019, and were the highest for "Neoplasms." The number of publications for "Infections" and "Respiratory Tract Diseases" dramatically rose during the COVID-19 pandemic; however, the retraction rates in the two categories or of COVID-19-related papers were not especially high compared to other diseases. The association with retraction was strongest for China in most disease categories, whereas for COVID-19 papers, other countries showed higher retraction rates than China. In recent years, retracted papers have become less likely to be published in high-impact journals.

Conclusion

The COVID-19 pandemic does not seem to affect the retractions of research papers much. We should keep monitoring retractions and analyze the effects of pandemics for better science.

Bibliometric Indices As Indicators of Research Output: Analyzing Anesthesiologists as a Paradigm for Surgical Disciplines

Anesthesiology is one of the increasingly competitive surgical specialties with a growing emphasis on scholarly activity. A metric of productivity and citation influence, the Hirsch index (h-index), can help identify mentors capable of guiding postgraduate trainees toward successful academic achievements. This study sought to determine associations between h-indices or m-quotients and manuscript publication in anesthesiology. Using the American Society of Anesthesiologists (ASA) website, accepted abstracts from the ASA Annual Meetings from 2019 to 2021 were screened (n=2146). The first author (FAHi) and senior author (SAHi) h-indices, as well as the first author (FAMq) and senior author (SAMq) m-quotients, were collected for each abstract using the Scopus database. Whether an accepted abstract was subsequently published as a manuscript in a peer-reviewed journal was also noted, along with the number of days between ASA presentation and publication date. Linear and logistic regression models were used for statistical analyses. In total, 348 (34.4%) of the 1012 eligible abstracts were published as manuscripts. Mean FAHi, SAHi, FAMq, and SAMq, were significantly higher for accepted ASA abstracts that were later published in peer-reviewed journals compared to accepted abstracts that were not published (p<0.001). FAHi, SAHi, FAMq, and SAMq had significant positive associations with odds of publication (p=0.002; p<0.001; p=0.006; p<0.001, respectively). There was no statistical significance between FAHi, SAHi, FAMq, or SAMq and the number of days between ASA presentation and publication. Our study uniquely demonstrates the positive, direct association between h-indices and m-quotients with the probability of publication in anesthesiology. We propose that bibliometric indices are adapted to provide a refined perspective of a physician-scientist's capabilities. Postgraduate trainees can use these indices to discern research mentors primed to foster academic excellence.

Intervening on Global Emergencies: The Value of Human Interactions for People's Health

Literature about global emergencies and their impact on people's health underlines the need to improve the social cohesion of human community and the availability of tools to support people and foster community interactions. This paper illustrates research aimed at describing and measuring human interactions in the Veneto community and its changing during the COVID-19 pandemic. 50,000 text occurrences from social media and newspapers about these topics were analyzed between December 2021 and January 2022. People present themselves as members of different teams, pursuing conflicting aims, and attributing the decision-making responsibility of emergencies management exclusively to governments, without considering themselves as active parts of the community. This delegation process on citizens' behalf can affect their health: by taking minor responsibility in handling the repercussions of these events on the community and by arguing over the most effective way to deal with them, they risk freezing and waiting for action by third parties, thus leaving mutual interactions and the promotion of their own health at a standstill. Local institutions can use these data to shape prevention policies to manage the community's emergencies and use them as opportunities to promote public health.

New Challenges in Scientific Publications: Referencing, Artificial Intelligence and ChatGPT

The COVID-19 pandemic has led to a surge in scientific publications, some of which have bypassed the usual peer-review processes, leading to an increase in unsupported claims being referenced. Therefore, the need for references in scientific articles is increasingly being questioned. The practice of relying solely on quantitative measures, such as impact factor, is also considered inadequate by many experts. This can lead to researchers choosing research ideas that are likely to generate favourable metrics instead of interesting and important topics. Evaluating the quality and scientific value of articles requires a rethinking of current approaches, with a move away from purely quantitative methods. Artificial intelligence (AI)-based tools are making scientific writing easier and less time-consuming, which is likely to further increase the number of scientific publications, potentially leading to higher quality articles. AI tools for searching, analysing, synthesizing, evaluating and writing scientific literature are increasingly being developed. These tools deeply analyse the content of articles, consider their scientific impact, and prioritize the retrieved literature based on this information, presenting it in simple visual graphs. They also help authors to quickly and easily analyse and synthesize knowledge from the literature, prepare summaries of key information, aid in organizing references, and improve manuscript language. The language model ChatGPT has already greatly changed the way people communicate with computers, bringing it closer to human communication. However, while AI tools are helpful, they must be used carefully and ethically. In summary, AI has already changed the way we write articles, and its use in scientific publishing will continue to enhance and streamline the process.