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Woman authorship in pre-print versus peer-reviewed oral health-related publications: A two-year observational study

Objectives

Women in oral health science face similar societal issues and challenges as those in other STEMM careers, and gender disparities continue to exist as evidenced by fewer women represented as first and last authors in scientific publications. Pre-prints may serve as a conduit to immediately disseminating one’s work, bypassing the arduous peer review process and its associated inherent biases. Therefore, the purpose of this study was to 1] compare the gender of first and last authors in pre-print versus peer reviewed publications, 2] examine the composition of first and last author pairs as stratified by publication type, and 3] examine the correlation between woman authorship and institutional geographic location and publication metrics stratified by publication type.

Methods

The keyword “oral health” was used to search for publications in BioRxiv and Pubmed in the years 2018 and 2019. Gender of first and last authors were determined, and its frequency was considered as the primary outcome. Additionally, the geographic location of the author’s associated institution and publication metrics measured by Altmetrics score were extracted. Data was descriptively summarized by frequencies and percentages. Chi-square analysis was conducted for categorical variables which included the relationship between gender and publication type as well as gender and region of author’s associated institution. Binomial regression analysis was conducted to analyze the relationship between gender and Altmetrics.

Results

Woman first authors comprised 40.3% of pre-prints and 64.5% of peer reviewed publications [p<0.05]. Woman last authors comprised 31.3% of pre-prints and 61.5% of peer reviewed publications [p<0.05]. When analyzing the relationships between first and last author, the Man-Man pairing represented 47.7% of the pre-print publications and the Woman-Woman pairing comprised a majority of the of the peer review publications at 47.5%. All results were statistically significant with a p-value <0.05. No significant correlation was found between region of institution or Altmetrics and gender of first or last authors [p>0.05].

Conclusion

For the first time in oral health science, it was found that women show higher representation as first and last author positions in peer reviewed publications versus pre-prints.

fiddle: a tool to combat publication bias by getting research out of the file drawer and into the scientific community

Statistically significant findings are more likely to be published than non-significant or null findings, leaving scientists and healthcare personnel to make decisions based on distorted scientific evidence. Continuously expanding ´file drawers' of unpublished data from well-designed experiments waste resources creates problems for researchers, the scientific community and the public. There is limited awareness of the negative impact that publication bias and selective reporting have on the scientific literature. Alternative publication formats have recently been introduced that make it easier to publish research that is difficult to publish in traditional peer reviewed journals. These include micropublications, data repositories, data journals, preprints, publishing platforms, and journals focusing on null or neutral results. While these alternative formats have the potential to reduce publication bias, many scientists are unaware that these formats exist and don't know how to use them. Our open source file drawer data liberation effort (fiddle) tool (RRID:SCR_017327 available at: http://s-quest.bihealth.org/fiddle/) is a match-making Shiny app designed to help biomedical researchers to identify the most appropriate publication format for their data. Users can search for a publication format that meets their needs, compare and contrast different publication formats, and find links to publishing platforms. This tool will assist scientists in getting otherwise inaccessible, hidden data out of the file drawer into the scientific community and literature. We briefly highlight essential details that should be included to ensure reporting quality, which will allow others to use and benefit from research published in these new formats.

Characteristics of academic publications, preprints, and registered clinical trials on the COVID-19 pandemic

The COVID-19 pandemic has unleashed a deluge of publications. For this cross-sectional study we compared the amount and reporting characteristics of COVID-19-related academic articles and preprints and the number of ongoing clinical trials and systematic reviews. To do this, we searched the PubMed database of citations and abstracts for published life science journals by using appropriate combinations of medical subject headings (MeSH terms), and the COVID-19 section of the MedRxiv and BioRxiv archives up to 20 May 2020 (21 weeks). In addition, we searched Clinicaltrial.gov, Chinese Clinical Trial Registry, EU Clinical Trials Register, and 15 other trial registers, as well as PROSPERO, the international prospective register of systematic reviews. The characteristics of each publication were extracted. Regression analyses and Z tests were used to detect publication trends and their relative proportions. A total of 3635 academic publications and 3805 preprints were retrieved. Only 8.6% (n = 329) of the preprints were already published in indexed journals. The number of academic and preprint publications increased significantly over time (p<0.001). Case reports (6% academic vs 0.9% preprints; p<0.001) and letters (17.4% academic vs 0.5% preprints; p<0.001) accounted for a greater share of academic compared to preprint publications. Differently, randomized controlled trials (0.22% vs 0.63%; p<0.001) and systematic reviews (0.08% vs 5%) made up a greater share of the preprints. The relative proportion of clinical studies registered at Clinicaltrials.gov, Chinese Clinical Trial Registry, and EU Clinical Trials Register was 57.9%, 49.5%, and 98.9%, respectively, most of which were still “recruiting”. PROSPERO listed 962 systematic review protocols. Preprints were slightly more prevalent than academic articles but both were increasing in number. The void left by the lack of primary studies was filled by an outpour of immediate opinions (i.e., letters to the editor) published in PubMed-indexed journals. Summarizing, preprints have gained traction as a publishing response to the demand for prompt access to empirical, albeit not peer-reviewed, findings during the present pandemic.

A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern

INTRODUCTION

Epidemic forecasting and prediction tools have the potential to provide actionable information in the midst of emerging epidemics. While numerous predictive studies were published during the 2016-2017 Zika Virus (ZIKV) pandemic, it remains unknown how timely, reproducible, and actionable the information produced by these studies was.

METHODS

To improve the functional use of mathematical modeling in support of future infectious disease outbreaks, we conducted a systematic review of all ZIKV prediction studies published during the recent ZIKV pandemic using the PRISMA guidelines. Using MEDLINE, EMBASE, and grey literature review, we identified studies that forecasted, predicted, or simulated ecological or epidemiological phenomena related to the Zika pandemic that were published as of March 01, 2017. Eligible studies underwent evaluation of objectives, data sources, methods, timeliness, reproducibility, accessibility, and clarity by independent reviewers.

RESULTS

2034 studies were identified, of which n = 73 met the eligibility criteria. Spatial spread, R0 (basic reproductive number), and epidemic dynamics were most commonly predicted, with few studies predicting Guillain-Barré Syndrome burden (4%), sexual transmission risk (4%), and intervention impact (4%). Most studies specifically examined populations in the Americas (52%), with few African-specific studies (4%). Case count (67%), vector (41%), and demographic data (37%) were the most common data sources. Real-time internet data and pathogen genomic information were used in 7% and 0% of studies, respectively, and social science and behavioral data were typically absent in modeling efforts. Deterministic models were favored over stochastic approaches. Forty percent of studies made model data entirely available, 29% provided all relevant model code, 43% presented uncertainty in all predictions, and 54% provided sufficient methodological detail to allow complete reproducibility. Fifty-one percent of predictions were published after the epidemic peak in the Americas. While the use of preprints improved the accessibility of ZIKV predictions by a median of 119 days sooner than journal publication dates, they were used in only 30% of studies.

CONCLUSIONS

Many ZIKV predictions were published during the 2016-2017 pandemic. The accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates there is substantial room for improvement. To enhance the utility of analytical tools for outbreak response it is essential to improve the sharing of model data, code, and preprints for future outbreaks, epidemics, and pandemics.