Gender Disparities Among Highly Cited Researchers in Biomedicine, 2014-2020.
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ABSTRACT:
SUBMITTER: Shamsi A
PROVIDER: S-EPMC8742200 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: Not available
| S-EPMC10998113 | biostudies-literature
Project description:BackgroundScientific productivity is often evaluated by means of cumulative citation metrics. Different metrics produce different incentives. The H-index assigns full credit from a citation to each coauthor, and thus may encourage multiple collaborations in mid-list author roles. In contrast, the Hm-index assigns only a fraction 1/k of citation credit to each of k coauthors of an article, and thus may encourage research done by smaller teams, and in first or last author roles. Whether H and Hm indices are influenced by different authorship patterns has not been examined.MethodsUsing a publicly available Scopus database, I examined associations between the numbers of research articles published as single, first, mid-list, or last author between 1990 and 2019, and the H-index and the Hm-index, among 18,231 leading researchers in the health sciences.ResultsAdjusting for career duration and other article types, the H-index was negatively associated with the number of single author articles (partial Pearson r -0.06) and first author articles (-0.08), but positively associated with the number of mid-list (0.64) and last author articles (0.21). In contrast, all associations were positive for the Hm-index (0.04 for single author articles, 0.18 for first author articles, 0.24 for mid-list articles, and 0.46 for last author articles).ConclusionThe H-index and the Hm-index do not reflect the same authorship patterns: the full-credit H-index is predominantly associated with mid-list authorship, whereas the partial-credit Hm-index is driven by more balanced publication patterns, and is most strongly associated with last-author articles. Since performance metrics may act as incentives, the selection of a citation metric should receive careful consideration.
| S-EPMC10478343 | biostudies-literature
Project description:In this study, it was investigated whether early tweets counts could differentially benefit female and male (first, last) authors in terms of the later citation counts received. The data for this study comprised 47,961 articles in the research area of Life Sciences & Biomedicine from 2014-2016, retrieved from Web of Science's Medline. For each article, the number of received citations per year was downloaded from WOS, while the number of received tweets per year was obtained from PlumX. Using the hurdle regression model, I compared the number of received citations by female and male (first, last) authored papers and then I investigated whether early tweet counts could predict the later citation counts received by female and male (first, last) authored papers. In the regression models, I controlled for several important factors that were investigated in previous research in relation to citation counts, gender or Altmetrics. These included journal impact (SNIP), number of authors, open access, research funding, topic of an article, international collaboration, lay summary, F1000 Score and mega journal. The findings showed that the percentage of papers with male authors in first or last authorship positions was higher than that for female authors. However, female first and last-authored papers had a small but significant citation advantage of 4.7% and 5.5% compared to male-authored papers. The findings also showed that irrespective of whether the factors were included in regression models or not, early tweet counts had a weak positive and significant association with the later citations counts (3.3%) and the probability of a paper being cited (21.1%). Regarding gender, the findings showed that when all variables were controlled, female (first, last) authored papers had a small citation advantage of 3.7% and 4.2% in comparison to the male authored papers for the same number of tweets.
| S-EPMC7605688 | biostudies-literature
Project description:There has been growing recognition of the popularity of medical crowdfunding and research documenting how crowdfunding arises from, and contributes to, social and health inequities. While many researchers have surmised that racism could well play a role in medical crowdfunding campaign outcomes, research on these dynamics has been limited. No research to date has examined these dynamics among the most successful medical crowdfunding campaigns, focusing instead on average users' experiences or specific patient subpopulations. This paper analyzes key characteristics and demographics of the 827 most successful medical crowdfunding campaigns captured at a point in time in 2020 on the popular site GoFundMe, creating the first demographic archetype of "viral" or highly successful campaigns. We hypothesized that this sample would skew towards whiter, younger populations, more heavily represent men, and reflect critical illnesses and accidents affecting these populations, in addition to having visually appealing, well-crafted storytelling. Analysis supported these hypotheses, showing significant levels of racial and gender disparities among campaigners. While white men had the greatest representation, Black and Asian users, and black women in particular, were highly underrepresented. Like other studies, we find evidence that racial and gender disparities persist in terms of campaign outcomes as well. Alongside this quantitative analysis, a targeted discourse analysis revealed campaign narratives and comments reinforced racist and sexist tropes of selective deservingness. These findings add to growing calls for more health research into the ways that social media technologies shape health inequities for historically marginalized and disenfranchised populations. In particular, we underscore how successful crowdfunding campaigns, as a both a means of raising funds for health and a broader site of public engagement, may deepen and normalize gendered and racialized inequities. In this way, crowdfunding can be seen as a significant technological amplifier of the fundamental social causes of health disparities.
| S-EPMC10916987 | biostudies-literature
Project description:Plant effector biology is a research area that describes how plant-associated organisms modulate host structures and function to promote colonization by using small molecules (effectors). In this article, we analyzed 249 highly cited publications focused on plant pathogen effectors (i.e., Highly Influential studies on plant Pathogen Effectors; thereafter HIPEs) published between 2000 and 2020. This analysis identifies countries, organizations, and journals that contributed HIPEs, and reveals the evolution of research trends, model molecules, and model organisms over the last two decades. We notably show an increasing proportion of studies focused on effectors of biotrophic and hemibiotrophic fungi upon time. Our snapshot of the highly influential plant effector biology papers may help new comers in the field to gain an analytical understanding of this research area.
| S-EPMC9762492 | biostudies-literature
Project description:This paper presents a methodological proposal based on the identification of highly cited papers (HCPs) at domestic-level in the Spanish Public University System (SUPE), in order to find the most outstanding publications in the local context. The principal aim is to detect different activity and impact profiles among Spanish universities and differentiate those institutions that play a more significant role. To determine which and how many are the highly cited papers at the domestic level (HCP-DL) collected in the Web of Science, three citation thresholds (1, 5, and 10%) were established. Thematic classification in Incites/Essential Science Indicators areas is used. The results show a preponderance of HCPs in the field of Space Science, while the polytechnic universities have high visibility in the Computer Science area. It has been observed that the presence of HCPs in a given area is involved with universities specialized in teaching and research activities. In absolute terms, the big non-specialized universities are major producers of HCPs and hold the leading positions in our results. However, when efficiency is analyzed in relative terms, some small, specialized universities reveal themselves to be more efficient at producing HCPs (% of HCPs or citations per HCP). We think that this methodology, due to its simplicity, its ease of calculation, and the knowledge it provides, can be very useful to analyze the national systems of any country, in order to know the impact and visibility of the research carried out in its scientific institutions or research areas.
| S-EPMC8101551 | biostudies-literature
Project description:This bibliometric review is aimed to analyze the top 100 most-cited publications in dentistry and to compare its outcomes. A literature search was performed using Elsevier's Scopus, without any restriction of language, publication year, or study design. Of 336,381 articles, the top 100 were included based on their citation count, which ranged from 638 to 4728 citations (Feijoo et al., 326 to 2050). The most productive decade was the 2000s, with 40 articles on the list (Feijoo et al., 1980s: 26). Marx RE (7%) was the major contributor in this study (Feijoo et al., Socransky SS: 9%), and almost half (48%) of articles were from the USA. Of the top 100 articles, 26% focused on periodontology (Feijoo et al., periodontology: 43%), while 17% of the total were published in the Journal of Dental Research (Feijoo et al., Journal of Clinical Periodontology: 20%). Most of the publications were narrative reviews/expert opinion (36%), (Feijoo et al., case series: 22%), and were within the evidence level V (64%) (Feijoo et al., 54%). The citation count that a paper secures is not necessarily a reflection of research's quality, however, the current analysis provides the latest citation trends in dentistry.
| S-EPMC8003932 | biostudies-literature
Project description:Measuring gender inequality and women's empowerment is essential to understand the determinants of gender gaps, evaluate policies and monitor countries' progress. With this aim, over the past two decades, research has mainly been directed towards the development of composite indices. The purpose of this paper is to introduce a new and interdisciplinary perspective to the current debate on measuring gender inequality in human development. As a starting point, we develop a simple macroeconomic model of the interdependence between human development and gender inequality. We then introduce a biometric indicator, based on the ratio of female to male body mass index, to measure women's empowerment at the country level. Finally, by using the latest available data, we examine the ability of this biometric indicator to capture countries' performance in achieving gender equality. We obtain five main results: 1) we provide a theoretical framework to explain the joint determination of human development and gender inequality; 2) we show how to use this framework to simulate the impact of exogenous shocks or policy changes; 3) we demonstrate that exogenous changes have a direct and a multiplier effect on human development and gender inequality; 4) we find that the distribution of obesity between the female and male populations represents a useful proxy variable for measuring gender equality at the country level; 5) finally, we use these results to integrate and develop existing knowledge on the 'ecological' approach to the overweight and obesity pandemic.
| S-EPMC5352805 | biostudies-literature
Project description:Precision Medicine implies a deep understanding of inter-individual differences in health and disease that are due to genetic and environmental factors. To acquire such understanding there is a need for the implementation of different types of technologies based on artificial intelligence (AI) that enable the identification of biomedically relevant patterns, facilitating progress towards individually tailored preventative and therapeutic interventions. Despite the significant scientific advances achieved so far, most of the currently used biomedical AI technologies do not account for bias detection. Furthermore, the design of the majority of algorithms ignore the sex and gender dimension and its contribution to health and disease differences among individuals. Failure in accounting for these differences will generate sub-optimal results and produce mistakes as well as discriminatory outcomes. In this review we examine the current sex and gender gaps in a subset of biomedical technologies used in relation to Precision Medicine. In addition, we provide recommendations to optimize their utilization to improve the global health and disease landscape and decrease inequalities.
| S-EPMC7264169 | biostudies-literature
Project description:ImportanceSince the onset of the COVID-19 outbreak, an extremely high number of studies have been published worldwide, with variable quality. Research trends of highly cited papers may enable identification of influential research, providing insights for new research ideas; it is therefore important to investigate trends and focus on more influential publications in COVID-19-related studies.ObjectiveTo examine research trends of highly cited studies by conducting a bibliometric analysis of highly cited studies in the previous 2 months about COVID-19.Design, setting, and participantsIn this cross-sectional study, Essential Science Indicators (ESI) and Web of Science (WOS) Core Collection were used to find studies with a focus on COVID-19 that were identified as highly cited studies from Clarivate Analytics. Highly cited studies were extracted from the ESI database bimonthly between January 2020 and December 2022. Bibliographic details were extracted from WOS and combined with ESI data using unique accession numbers. The number of highly cited studies was counted based on the fractional counting method. Data were analyzed from January through July 2023.Main outcomes and measuresThe number of publications by research field, country, and institutional affiliation.ResultsThe number of published COVID-19-related highly cited studies was 14 studies in January to February 2020, peaked at 1292 studies in November to December 2021, and showed a downward trend thereafter, reaching 649 studies in November to December 2022. China had the highest number of highly cited studies per 2-month period until July to August 2020 (138.3 studies vs 103.7 studies for the US, the second highest country), and the US had the greatest number of highly cited studies afterward (159.9 studies vs 157.6 studies for China in September to October 2020). Subsequently, the number of highly cited studies per 2-month period published by China declined (decreasing from 179.7 studies in November to December 2020 to 40.7 studies in September to October 2022), and the UK produced the second largest number of such studies in May to June 2021 (171.3 studies). Similarly, the top 5 institutional affiliations in May to June 2020 by highly cited studies per 2-month period were from China (Huazhong University: 14.7 studies; University of Hong Kong: 6.8 studies; Wuhan University: 4.8 studies; Zhejiang University: 4.5 studies; Fudan University: 4.5 studies), while in November to December 2022, the top 5 institutions were in the US and UK (Harvard University: 15.0 studies; University College London: 11.0 studies; University of Oxford: 10.2 studies; University of London: 9.9 studies; Imperial College London: 5.8 studies).Conclusions and relevanceThis study found that the total number of highly cited studies related to COVID-19 peaked at the end of 2021 and showed a downward trend until the end of 2022, while the origin of these studies shifted from China to the US and UK.
| S-EPMC10492181 | biostudies-literature