Mixing Patterns in Interdisciplinary Co-Authorship Networks at Multiple Scales

Bibliometric and social network analysis of a Clinical and Translational Resource awardee: An Oklahoma experience 2014-2021

Background

Social Network Analysis is a method of analyzing coauthorship networks or relationships through graph theory. Institutional Development Award (IDeA) Networks for Clinical and Translational Research (IDeA-CTR) was designed to expand the capability for clinical and translational research to enhance National Institutes of Health funding.

Methods

All publications from a cohort of clinical and translational scientists in Oklahoma were collected through a PubMed search for 2014 through 2021 in October 2022. For this study's bibliometric portion, we pulled the citations from iCite in November of 2022.

Results

There were 2,391 articles published in 1,019 journals. The number of papers published by year increased from 56 in 2014 to 448 in 2021. The network had an average of 6.4 authors per paper, with this increasing by year from 5.3 in 2014 to 6.9 in 2021. The average journal impact factor for the overall network was 7.19, with a range from 0.08 to 202.73. The Oklahoma Shared Clinical and Translational Resources (OSCTR) network is a small world network with relatively weak ties.

Conclusions

This study provides an overview of coauthorship in an IDeA-CTR collaboration. We show the growth and structure of coauthorship in OSCTR, highlighting the importance of understanding and fostering collaboration within research networks.

Author multidisciplinarity and disciplinary roles in field of study networks

When studying large research corpora, "distant reading" methods are vital to understand the topics and trends in the corresponding research space. In particular, given the recognised benefits of multidisciplinary research, it may be important to map schools or communities of diverse research topics, and to understand the multidisciplinary role that topics play within and between these communities. This work proposes Field of Study (FoS) networks as a novel network representation for use in scientometric analysis. We describe the formation of FoS networks, which relate research topics according to the authors who publish in them, from corpora of articles in which fields of study can be identified. FoS networks are particularly useful for the distant reading of large datasets of research papers when analysed through the lens of exploring multidisciplinary science. In an evolving scientific landscape, modular communities in FoS networks offer an alternative categorisation strategy for research topics and sub-disciplines, when compared to traditional prescribed discipline classification schemes. Furthermore, structural role analysis of FoS networks can highlight important characteristics of topics in such communities. To support this, we present two case studies which explore multidisciplinary research in corpora of varying size and scope; namely, 6323 articles relating to network science research and 4,184,011 articles relating to research on the COVID-19-pandemic.

Academic training of authors publishing in high-impact epidemiology and clinical journals

Background

To inform training program development and curricular initiatives, quantitative descriptions of the disciplinary training of research teams publishing in top-tier clinical and epidemiological journals are needed. Our objective was to assess whether interdisciplinary academic training and teamwork of authors publishing original research in 15 top-tier journals varied by year of publication (2000/2010/2020), type of journal (epidemiological/general clinical/specialty clinical), corresponding author gender, and time since the corresponding author completed formal training relative to the article publication date (<5/≥5 years).

Methods and findings

We invited corresponding authors of original research articles to participate in an online survey (n = 103; response rate = 8.3% of 1240 invited authors). In bivariate analyses, year of publication, type of journal, gender, and recency of training were not significantly associated with interdisciplinary team composition, whether a co-author with epidemiological or biostatistical training was involved in any research stage (design/analysis/interpretation/reporting), or with participants’ confidence in their own or their co-authors epidemiological or biostatistical expertise (p > 0.05 for each comparison). Exceptions were participants with more recent epidemiological training all had co-author(s) with epidemiological training contribute to study design and interpretation, and participants who published in 2020 were more likely to report being extremely confident in their epidemiological abilities.

Conclusions

This study was the first to quantify interdisciplinary training among research teams publishing in epidemiological and clinical journals. Our quantitative results show research published in top-tier journals generally represents interdisciplinary teamwork and that interdisciplinary training may provide publication type options. Our qualitative results show researchers view interdisciplinary training favorably.

An Ethical Exploration of Increased Average Number of Authors Per Publication

This article explores the impact of an Increase in the average Number of Authors per Publication (INAP) on known ethical issues of authorship. For this purpose, the ten most common ethical issues associated with scholarly authorship are used to set up a taxonomy of existing issues and raise awareness among the community to take precautionary measures and adopt best practices to minimize the negative impact of INAP. We confirm that intense international, interdisciplinary and complex collaborations are necessary, and INAP is an expression of this trend. However, perverse incentives aimed to increase institutional and personal publication counts and egregious instances of guest or honorary authorship are problematic. We argue that whether INAP is due to increased complexity and scale of science, perverse incentives or undeserved authorship, it could negatively affect known ethical issues of authorship at some level. In the long run, INAP depreciates the value of authorship status and may disproportionately impact junior researchers and those who contribute to technical and routine tasks. We provide two suggestions that could reduce the long-term impact of INAP on the reward system of science. First, we suggest further refinement of the CRediT taxonomy including better integration into current systems of attribution and acknowledgement, and better harmony with major authorship guidelines such as those suggested by the ICMJE. Second, we propose adjustments to the academic recognition and promotion systems at an institutional level as well as the introduction of best practices.

The Extent of Gender Gap in Citations in Ophthalmology Literature

Purpose

To investigate the severity and causes of gender imbalance in the counts of ophthalmology citations.

Methods

The PubMed database was searched to identify cited papers that were published in four journals (Prog Retin Eye Res, Ophthalmology, JAMA Ophthalmol, and Invest Ophthalmol Vis Sci) between August 2015 and July 2020, and those that referenced these cited papers by 2021 July (i.e., citing papers). The gender category of a given paper is defined by the gender of the first and last author (MM, FM, MF, and FF; M means male and F means female). A generalized additive model to predict the expected proportion was fitted. The difference between the observed proportion and expected proportion of citations of a paper’s gender category was the primary outcome.

Results

The proportion of female-led (MF and FF) papers slightly increased from 27% in 2015 to 30% in 2020. MM, FM, MF, and FF papers were cited as −9.3, −1.5, 13.0, and 23.9% more than expected, respectively. MM papers cited 13.9% more male-led (MM and FM) papers than female-led papers, and FF papers cited 33.5% fewer male-led papers than female-led papers. The difference between the observed proportion and expected proportion of MM citing papers within male-led and female-led cited papers grew at a rate of 0.13 and 0.67% per year.

Conclusion

The high frequency of citations of female-led papers might narrow the gender gap in the citation count within ophthalmology. These findings show that papers by female-led are less common, so the gender gap might still exist even with their high citation count.

Ten ignored questions for stress psychology research

Stress psychology is an interesting and important interdisciplinary research field. In this perspective article, we briefly discuss 10 challenges related to the conceptual definition, research methodology, and translation in the field of stress that do not receive sufficient attention or are ignored entirely. Future research should attempt to integrate a comprehensive stress conceptual framework into a multidimensional comprehensive stress model, incorporating subjective and objective indicators as comprehensive measures. The popularity of machine learning, cognitive neuroscience, and gene epigenetics is a promising approach that brings innovation to the field of stress psychology. The development of wearable devices that precisely record physiological signals to assess stress responses in naturalistic situations, standardize real-life stressors, and measure baselines presents challenges to address in the future. Conducting large individualized and digital intervention studies could be crucial steps in enhancing the translation of research.

Analyzing the Evolution of Interdisciplinary Areas

Recently, various new areas of research have been of great interest to researchers. As these areas are highly based on academic and industrial needs, it is necessary to examine the change and evolution in research. This study proposed a framework for identifying emerging areas and their evolution. The proposed framework suggests that latent Dirichlet allocation is applied to identify emerging topics and their networks in such interdisciplinary areas. The simulation for empirical network analysis was then applied to the identified topic networks to terminate continuous evolution. The proposed framework is applied to a smart city, which is one of the most interdisciplinary and fast-evolving areas. These findings indicate that the evolution of smart transportation and smart grids is likely to be the focus. The findings also indicate that newly emerging research may lack openness and diversity. This study contributes to further investigate research trends and planning research strategies for new and interdisciplinary areas.

Interplay between success and patterns of human collaboration: case study of a Thai Research Institute

Networks of collaboration are notoriously complex and the mechanisms underlying their evolution, although of high interest, are still not fully understood. In particular, collaboration networks can be used to model the interactions between scientists and analyze the circumstances that lead to successful research. This task is not trivial and conventional metrics, based on number of publications and number of citations of individual authors, may not be sufficient to provide a deep insight into the factors driving scientific success. However, network analysis techniques based on centrality measures and measures of the structural properties of the network are promising to that effect. In recent years, it has become evident that most successful research works are achieved by teams rather than individual researchers. Therefore, researchers have developed a keen interest in the dynamics of social groups. In this study, we use real world data from a Thai computer technology research center, where researchers collaborate on different projects and team up to produce a range of artifacts. For each artifact, a score that measures quality of research is available and shared between the researchers that contributed to its creation, according to their percentage of contribution. We identify several measures to quantify productivity and quality of work, as well as centrality measures and structural measures. We find that, at individual level, centrality metrics are linked to high productivity and quality of work, suggesting that researchers who cover strategic positions in the network of collaboration are more successful. At the team level, we show that the evolution in time of structural measures are also linked to high productivity and quality of work. This result suggests that variables such as team size, turnover rate, team compactness and team openness are critical factors that must be taken into account for the success of a team. The key findings of this study indicate that the success of a research institute needs to be assessed in the context of not just researcher or team level, but also on how the researchers engage in collaboration as well as on how teams evolve.