The emergence of team science: Understanding the state of adoption research through social network analysis

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.

Barriers and facilitators of conducting research with team science approach: a systematic review

BACKGROUND

The present review aimed to systematically identify and classify barriers and facilitators of conducting research with a team science approach.

METHODS

PubMed, EMBASE, PsycINFO, Scopus, Web of Science, Emerald, and ProQuest databases were searched for primary research studies conducted using quantitative, qualitative, or mixed methods. Studies examining barriers and facilitators of research with a team science approach were included in search. Two independent reviewers screened the texts, extracted and coded the data. Quality assessment was performed for all 35 included articles. The identified barriers and facilitators were categorized within Human, Organization, and Technology model.

RESULTS

A total of 35 studies from 9,381 articles met the inclusion criteria, from which 42 barriers and 148 facilitators were identified. Human barriers were characteristics of the researchers, teaming skills, and time. We consider Human facilitators across nine sub-themes as follows: characteristics of the researchers, roles, goals, communication, trust, conflict, disciplinary distances, academic rank, and collaboration experience. The barriers related to organization were institutional policies, team science integration, and funding. Organizational facilitators were as follows: team science skills training, institutional policies, and evaluation. Facilitators in the field of technology included virtual readiness and data management, and the technology barriers were complexity of techniques and privacy issues.

CONCLUSIONS

We identified major barriers and facilitators for conducting research with team science approach. The findings have important connotations for ongoing and future implementation of this intervention strategy in research. The analysis of this review provides evidence to inform policy-makers, funding providers, researchers, and students on the existing barriers and facilitators of team science research.

TRIAL REGISTRATION

This review was prospectively registered on PROSPERO database (PROSPERO 2021 CRD42021278704).

Current status of neuroimaging research on the effects of acupuncture: a bibliometric and visual analyses

OBJECTIVE

To conduct an inductive analysis of neuroimaging studies following the global popularity surrounding the effects of acupuncture.

METHODS

The relevant works of literature on acupuncture effects-related neuroimaging studies were retrieved from the web of science core collection database from the date of its establishment to 2022. Bibexcel software was used to extract information, such as article numbers, countries, journals, agencies, funding sources and keywords. The VOSviewer software's co-occurrence and clustering module was used for the co-occurrence and cluster analysis of collaborative networks and high frequency keywords, such as authors, institutions and countries.

RESULTS

Neuroimaging research on the effects of acupuncture began in the 1960 s and has since received the extensive attention of scholars. China, The United States and South Korea conduct more neuroimaging research on the effects of acupuncture than other countries. Academic journals such as Evidence-Based Complementary and Alternative Medicine, Journal of Alternative and Complementary Medicine, Neural Regeneration Research and Acupuncture in Medicine have published the highest number of acupuncture-related neuroimaging articles. Moreover, cluster analysis differentiates high-frequency keywords into six clusters. Furthermore, the use of the keyword 'density atlas' reveals that neuroimaging research on the effects of acupuncture surrounding pain and neurofunctional rehabilitation is currently the research focus.

CONCLUSIONS

This bibliometric study identifies six important research hot spots: Static brain functional connectivity analysis of acupuncture analgesic effects, key theories on the scientific problems of acupuncture, acupuncture analgesic effect of the placebo effect, the neuroimaging of acupoint ST-36, the value of acupuncture in regulating the autonomic nerves and acupuncture therapy as complementary medicine.

Fostering interdisciplinary collaboration: A longitudinal social network analysis of the NIH mHealth Training Institutes

BACKGROUND/OBJECTIVE

Growing recognition that collaboration among scientists from diverse disciplines fosters the emergence of solutions to complex scientific problems has spurred initiatives to train researchers to collaborate in interdisciplinary teams. Evaluations of collaboration patterns in these initiatives have tended to be cross-sectional, rather than clarifying temporal changes in collaborative dynamics. Mobile health (mHealth), the science of using mobile, wireless devices to improve health outcomes, is a field whose advancement needs interdisciplinary collaboration. The NIH-supported annual mHealth Training Institute (mHTI) was developed to meet that need and provides a unique testbed.

METHODS

In this study, we applied a longitudinal social network analysis technique to evaluate how well the program fostered communication among the disciplinarily diverse scholars participating in the 2017-2019 mHTIs. By applying separable temporal exponential random graph models, we investigated the formation and persistence of project-based and fun conversations during the mHTIs.

RESULTS

We found that conversations between scholars of different disciplines were just as likely as conversations within disciplines to form or persist in the 2018 and 2019 mHTI, suggesting that the mHTI achieved its goal of fostering interdisciplinary conversations and could be a model for other team science initiatives; this finding is also true for scholars from different career stages. The presence of team and gender homophily effects in certain years suggested that scholars tended to communicate within the same team or gender.

CONCLUSION

Our results demonstrate the usefulness of longitudinal network models in evaluating team science initiatives while clarifying the processes driving interdisciplinary communications during the mHTIs.

Research Progress of Ferroptosis: A Bibliometrics and Visual Analysis Study

Background

Ferroptosis is a type of cell death with major topic of debate under current research and plays an important role in disease regulation.

Objective

In this study, the literature management software Bibexcel and knowledge graph tool VOSviewer were used to summarize and analyze the international research trends and hotspots about ferroptosis in recent years, which highlight the disease mechanism, diagnosis, and treatment related to ferroptosis. Material/Methods. The core collection database of Web of Science was used for retrieving ferroptosis research literature. The information such as the amount of text, the country, the period, the institution, the fund, and the keywords was extracted by the bibliometric tool Bibexcel. The cooccurrence and clustering function of VOSviewer were used to analyze the high-frequency keywords and the cooperative network of the author, institution, and country.

Results

The research of ferroptosis started late and was formally proposed in 2012. It has developed rapidly and presented an “exponential” growth trend. China, the United States, Germany, Japan, and France are the main national forces of ferroptosis research development. The United States and China have a relatively high degree of support and attention to ferroptosis. Exploring oxidative stress, inducers/inhibitors, synergistic antitumor effect, relationships with other cell death types, GSH/GPX4 and iron metabolism imbalance related mechanisms of ferroptosis, and ferroptosis in the nervous system disease, ischemia-reperfusion injury, tumor, inflammation, and age-related diseases are the hot research directions.

Conclusion

Ferroptosis has been a research hotspot in the field of biomedicine in recent years and has attracted the attention of scholars all over the world. The occurrence mechanism of ferroptosis and its application in neurological diseases, ischemia and reperfusion injury, tumors, inflammation, and aging are the hot directions of current research. In the future, ferroptosis can be appropriately considered for strengthening new approaches, new diseases, new inductors, new inhibitors, clinical transformation, and traditional medicine research.

Great minds think alike, or do they often differ? Research topic overlap and the formation of scientific teams

Over the last century scientific research has become an increasingly collaborative endeavor. Commentators have pointed to different factors which contribute to this trend, including the specialization of science and growing need for diversity of interest and expertise areas in a scientific team. Very few studies, however, have precisely evaluated how the diversity of interest topics between researchers is related to the emergence of collaboration. Existing theoretical arguments suggest a curvilinear relationship between topic similarity and collaboration: too little similarity can complicate communication and agreement, yet too much overlap can increase competition and limit the potential for synergy. We test this idea using data on six years of publications across all disciplines at a large U.S. research university (approximately 14,300 articles, 12,500 collaborations, and 3,400 authors). Employing topic modelling and network statistical models, we analyze the relationship between topic overlap and the likelihood of coauthorship between two researchers while controlling for potential confounders. We find an inverted-U relationship in which the probability of collaboration initially increases with topic similarity, then rapidly declines after peaking at a similarity "sweet spot". Collaboration is most likely at low-to-moderate levels of topic overlap, which are substantially lower than the average self-similarity of scientists or research groups. These findings - which we replicate for different units of analysis (individuals and groups), genders of collaborators, disciplines, and collaboration types (intra- and interdisciplinary) - support the notion that researchers seek collaborators to augment their scientific and technical human capital. We discuss implications for theories of scientific collaboration and research policy.