bims-evares 2019-10-06 papers

bims-evares

Biomed News

on Evaluation of research

Issue of 2019–10–06
eleven papers selected by
Thomas Krichel, Open Library Society

Highly cited dental articles and their authors: An evaluation of publication and citation characteristics.
Who should you be following? The top 100 social media influencers in orthopaedic surgery.
Altmetric analysis of the contemporary scientific literature in Endodontology.
Evaluating a Center for Interprofessional Education via Social Network Analysis.
A scoping review of simulation models of peer review.
The Archives of Physical Medicine and Rehabilitation at 100 A century of authorship.
Length of Fellowship Training in Population Health Research and Long-term Bibliometric Outcomes.
Research Collaboration in Pediatric Critical Care Randomized Controlled Trials: A Social Network Analysis of Coauthorship.
Characterizing Artificial Intelligence Applications in Cancer Research: A Latent Dirichlet Allocation Analysis.
Academic Review and Perspectives on Robotic Exoskeletons (August 2019).
The 100 most-cited articles on prenatal diagnosis: A bibliometric analysis.

J Investig Clin Dent. 2019 Oct 02. e12462

Highly cited dental articles and their authors: An evaluation of publication and citation characteristics.

Andy Wai Kan Yeung, Yuh-Shan Ho.

   AIM: In the present study, we aimed to identify and analyze the characteristics of highly cited articles in dentistry.
METHODS: All articles belonging to Web of Science category of "dentistry, oral surgery and medicine" published until 2016 were analyzed. The bibliometric data of the highly cited articles were evaluated. The Y-index was applied to assess authors' publication potential. Altmetric scores were recorded from Dimensions, a free online database.
RESULTS: There were 3666 highly cited dentistry articles published in dental journals. Half of them were published in seven leading journals in their specialties. The major contributing countries were the USA, Sweden, the UK, and Switzerland. The highly cited articles were written by 3.7 authors on average. Jan Lindhe had the largest number of highly cited articles, whereas David H. Pashley had the highest potential to publish highly cited articles in dentistry.
CONCLUSIONS: Highly cited articles were distributed among various dental specialties, and the most productive periods were the late 1990s and the early 2000s. The Y-index gave dimensional details of the prolific authors. The current analysis was based on data extracted from Web of Science. Results could be different if data were extracted from other databases, such as Google Scholar.

Keywords:  Web of Science; bibliometric; citation; classic article; implant

DOI:  https://doi.org/10.1111/jicd.12462
World J Orthop. 2019 Sep 18. 10(9): 327-338

Who should you be following? The top 100 social media influencers in orthopaedic surgery.

Nathan H Varady, Akash A Chandawarkar, Willem A Kernkamp, Itai Gans.

   BACKGROUND: Social media has been credited with the potential to transform medicine, and Twitter was recently named "an essential tool" for the academic surgeon. Despite this, peer-to-peer and educational influence on social media has not been studied within orthopaedic surgery. This knowledge is important to identify who is controlling the conversation about orthopaedics to the public. We hypothesized that the plurality of top influencers would be sports medicine surgeons, that social media influence would not be disconnected from academic productivity, and that some of the top social media influencers in orthopaedic surgery would not be orthopaedic surgeons.
AIM: To identify the top 100 social media influencers within orthopaedics, characterize who they are, and relate their social media influence to academic influence.
METHODS: Twitter influence scores for the topic "orthopaedics" were collected in July 2018 using Right Relevance software. The accounts with the top influence scores were linked to individual names, and the account owners were characterized with respect to specialty, subspecialty, practice setting, location, board certification, and academic Hirsch index (h-index).
RESULTS: Seventy-eight percent of top influencers were orthopaedic surgeons. The most common locations included California (13%), Florida (8%), New York (7%), United Kingdom (7%), Colorado (6%), and Minnesota (6%). The mean academic h-index of the top influencers (n = 79) was 13.67 ± 4.12 (mean ± 95%CI) and median 7 (range 1-89) (median reported h-index of academic orthopaedic faculty is 5 and orthopaedic chairpersons is 13). Of the 78 orthopaedic surgeons, the most common subspecialties were sports medicine (54%), hand and upper extremity (18%), and spine (8%). Most influencers worked in private practice (53%), followed by academics (17%), privademics (14%), and hospital-based (9%). All eligible orthopaedic surgeons with publicly-verifiable board certification statuses were board-certified (n = 74).
CONCLUSION: The top orthopaedic social media influencers on Twitter were predominantly board-certified, sports-medicine subspecialists working in private practice in the United States. Social media influence was highly concordant with academic productivity as measured by the academic h-index. Though the majority of influencers are orthopaedic surgeons, 22% of top influencers on Twitter are not, which is important to identify given the potential for these individuals to influence patients' perceptions and expectations. This study also provides the top influencer network for other orthopaedic surgeons to engage with on social media to improve their own social media influence.

Keywords:  Impact; Influence; Orthopaedics; Orthopedics; Social media; Twitter

DOI:  https://doi.org/10.5312/wjo.v10.i9.327
Int Endod J. 2019 Sep 30.

Altmetric analysis of the contemporary scientific literature in Endodontology.

J Kolahi, S Khazaei, P Iranmanesh, A Khademi, M H Nekoofar, Pm H Dummer.

   AIM: To analyze and visualize the knowledge structure of scientific articles in the field of Endodontology with high altmetric attention scores to discover hot topics, active researchers and which journals were involved.
METHODOLOGY: On 5 June 2019 the altmetric database (Altmetric LLP, London, UK) was searched using the titles of 11 endodontic journals. Bibliometric data from endodontic articles and journals with an altmetric score>5 (top 5%) were retrieved from PubMed and analyzed using the VOSviewer. Science mapping of articles with an altmetric score>5 at two levels was created: author keywords co-occurrence and co-authorship network analysis.
RESULTS: Of the 2197 articles in the field of Endodontology identified with altmetrics, 192 had altmetric scores>5 (top 5%). Considering the total mentions among all altmetric resources, the Journal of Endodontics had the highest rank followed by the International Endodontic Journal and Australian Endodontic Journal. Twitter was the most popular altmetric data resource followed by patents andFacebook. Meta-analysis, systematic review and pulpitiswere the hot topics. At the author level, Dummer P.M.H had the greatest influence on the network. There was no significant correlation between altmetric score and citations count (P>0.05). Mendeley mentions correlated with citations (P<0.05).
CONCLUSIONS: Overall, the altmetric scores of topics within Endodontology were low, possibly due to the specific and specialized nature of the specialty, as well as the difficulty members of the public probably have in understanding endodontic research. Journals and researchers with a focus on Endodontology would have more influence if they were to set-up their own social media profiles and thus enhance their visibility and social impact by immediately sharing research findings and communicating with their network and audience.

Keywords:  Facebook; Twitter; altmetrics; endodontology; social media

DOI:  https://doi.org/10.1111/iej.13226
Acad Med. 2019 Oct 01.

Evaluating a Center for Interprofessional Education via Social Network Analysis.

Alan W Dow, Daniel K Sewell, Kelly S Lockeman, Elizabeth A Micalizzi.

Centers and institutes are created to support interdisciplinary collaboration. However, all centers and institutes face the challenge of how best to evaluate their impact since traditional counts of productivity may not fully capture the interdisciplinary nature of this work. The authors applied techniques from social network analysis (SNA) to evaluate the impact of a center for interprofessional education (IPE), a growing area for centers because of the global emphasis on IPE.The authors created networks based on the connections between faculty involved in programs supported by an IPE center at Virginia Commonwealth University from 2014 to 2017. They used mathematical techniques to describe these networks and the change in the networks over time. The results of these analyses demonstrated that, while the number of programs and involved faculty grew, the faculty maintained a similar amount of connection between members. Additional faculty clusters emerged, and certain key faculty were important connectors between clusters. The analysis also confirmed the interprofessional nature of faculty collaboration within the network.SNA added important evaluation data beyond typical metrics such as counts of learners or faculty. This approach demonstrated how a center was evolving and what strategies might be needed to support further growth. With further development of benchmarks, SNA could be used to evaluate the effectiveness of centers and institutes relative to each other. SNA should guide strategic decisions about the future of centers and institutes as they strive to meet their overarching goal of tackling a social challenge through interdisciplinary collaboration.

DOI: https://doi.org/10.1097/ACM.0000000000003010
Scientometrics. 2019 ;121(1): 555-594

A scoping review of simulation models of peer review.

Thomas Feliciani, Junwen Luo, Lai Ma, Pablo Lucas, Flaminio Squazzoni, Ana Marušić, Kalpana Shankar.

  Peer review is a process used in the selection of manuscripts for journal publication and proposals for research grant funding. Though widely used, peer review is not without flaws and critics. Performing large-scale experiments to evaluate and test correctives and alternatives is difficult, if not impossible. Thus, many researchers have turned to simulation studies to overcome these difficulties. In the last 10 years this field of research has grown significantly but with only limited attempts to integrate disparate models or build on previous work. Thus, the resulting body of literature consists of a large variety of models, hinging on incompatible assumptions, which have not been compared, and whose predictions have rarely been empirically tested. This scoping review is an attempt to understand the current state of simulation studies of peer review. Based on 46 articles identified through literature searching, we develop a proposed taxonomy of model features that include model type (e.g. formal models vs. ABMs or other) and the type of modeled peer review system (e.g. peer review in grants vs. in journals or other). We classify the models by their features (including some core assumptions) to help distinguish between the modeling approaches. Finally, we summarize the models' findings around six general themes: decision-making, matching submissions/reviewers, editorial strategies; reviewer behaviors, comparisons of alternative peer review systems, and the identification and addressing of biases. We conclude with some open challenges and promising avenues for future modeling work.

Keywords:  Agent-based modeling; Journal editing; Peer review; Research funding; Simulation

DOI:  https://doi.org/10.1007/s11192-019-03205-w
Arch Phys Med Rehabil. 2019 Sep 26. pii: S0003-9993(19)31116-5. [Epub ahead of print]

The Archives of Physical Medicine and Rehabilitation at 100 A century of authorship.

Marcel P J M Dijkers.

   OBJECTIVE: To describe the authors who have contributed papers to the Archives of Physical Medicine and Rehabilitation (APM&R) over the 100 years of its existence.
DESIGN: Extraction of relevant information from a sample of APM&R papers; SETTING: N/A; PARTICIPANTS: 4933 authors contributing to 1787 articles; MAIN OUTCOME MEASURES: number of authors, their gender, professional education and country of residence RESULTS: The number of authors per article increased from 1.1 average in 1922 to 5.8 in 2017. The percentage women among authors grew from under 5% to about 40%. In 1922 the majority of authors had an MD degree (85%); this declined to less than 30% by 2017, while the percentage of authors with a PhD grew from about 10% to about 30%. Contributors with a Bachelors degree initially were about 1%, grew to 13%, and then declined again. While over 90% of authors were from the United States in APM&R's early years, this percentage went into a steep decline beginning in about 1997, and now is around 35% CONCLUSIONS: The APM&R has seen major transformations in the nature of its contributors over a century of publication; many of these parallel the changes seen in other areas of health care and medical science, but some characteristics and shifts (especially in gender and level of training of its authors) appear unique.

Keywords:  Bibliometrics; International cooperation; Publishing; Rehabilitation; Scholarly communication

DOI:  https://doi.org/10.1016/j.apmr.2019.08.484
Epidemiology. 2019 Nov;30 Suppl 2 S85-S93

Length of Fellowship Training in Population Health Research and Long-term Bibliometric Outcomes.

Tiffany L Holland, Keewan Kim, Carrie J Nobles, Ya-Ling Lu, Indulaxmi Seeni, Sunni L Mumford, Stephen E Gilman, Lindsay D Levine, Victoria C Andriessen, Enrique F Schisterman.

BACKGROUND: The length of research fellowships, the number of doctorates pursuing them, and the academic job market have changed dramatically in recent years. However, there is limited investigation on attributes of fellowships most relevant to future scientific achievement. We analyzed the association of a modifiable aspect of research training, fellowship length, with future achievement and differences across research discipline in the Division of Intramural Population Health Research (DIPHR), Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health.
METHODS: Demographics of 88 DIPHR trainees from 1998 to 2016 were collected from publicly available annual reports. Research performance metrics, including total publication count and H index through 2016, were collected via Scopus. We used linear regression models for associations between fellowship length, including both total exposure to research training and duration of postdoctoral training alone, and research performance adjusted for start year, publications at entry, branch (e.g., Biostatistics and Bioinformatics, Epidemiology, and Health Behavior), and mentor seniority.
RESULTS: Each additional year of research training in DIPHR was associated with a 15% increase in H index (95% confidence interval [CI] = 3.0, 28.4) and 21% more lifetime publications (95% CI = 3.0, 41.9). Results were similar, although attenuated, when evaluating postdoctoral training alone. Differences by discipline were observed, with the strongest positive associations in the Biostatistics and Bioinformatics and Epidemiology Branches.
CONCLUSIONS: Longer training at DIPHR was associated with improved measures of research performance, though this relationship varied by discipline. Additional research is needed to tailor training programs to optimize success of trainees.

DOI: https://doi.org/10.1097/EDE.0000000000001093
Pediatr Crit Care Med. 2019 Oct 02.

Research Collaboration in Pediatric Critical Care Randomized Controlled Trials: A Social Network Analysis of Coauthorship.

Mark Duffett, Melissa Brouwers, Maureen O Meade, Grace M Xu, Deborah J Cook.

OBJECTIVES: Clinical research is a collaborative enterprise; researchers benefit from the expertise, experience, and resources of their collaborators. We sought to describe the extent and patterns of collaboration among pediatric critical care trialists, and to identify the most influential individuals, centers, and countries.
DESIGN: Social network analysis of coauthorship.
DATA SOURCES: Publications of pediatric critical care randomized controlled trials (1986-2018).
DATA EXTRACTION: We manually extracted the names of all authors and their affiliations. We used productivity (number of randomized controlled trials), influence (number of citations), and four measures of prominence in the social network (degree, betweenness, closeness, and eigenvector centrality) to identify the most influential individuals.
MEASUREMENTS AND MAIN RESULTS: From 415 randomized controlled trials in pediatric critical care, we identified 2,176 trialists from 377 centers in 43 countries. The coauthorship network is highly disconnected and dominated by a single large cluster of trialists publishing 142 (34%) of the randomized controlled trials. However, 119 (29%) of the randomized controlled trials were published by 28 smaller clusters-a median (interquartile range) of 3 (2-4) randomized controlled trials each. The remaining 154 (37%) randomized controlled trials were coauthored by researchers publishing a single randomized controlled trial each. This overall structure has remained constant with the publication of new randomized controlled trials over 33 years. The most influential trialists and centers varied according to the metric we used; only one trialist and three centers ranked in the top 10 for all measures of influence. Thirty-five of the 40 trialists (88%) ranking in the top 10 of any of the measures were from the United States, the United Kingdom, and Canada.
CONCLUSIONS: Pediatric critical care has made considerable progress in the number of trialists and randomized controlled trials, but the research enterprise remains highly clustered and fragmented, particularly geographically. Efforts to further increase the quantity and quality of research in the field should include steps to increase the level and range of collaboration.

DOI: https://doi.org/10.1097/PCC.0000000000002120
JMIR Med Inform. 2019 Sep 15. 7(4): e14401

Characterizing Artificial Intelligence Applications in Cancer Research: A Latent Dirichlet Allocation Analysis.

Bach Xuan Tran, Carl A Latkin, Noha Sharafeldin, Katherina Nguyen, Giang Thu Vu, Wilson W S Tam, Ngai-Man Cheung, Huong Lan Thi Nguyen, Cyrus S H Ho, Roger C M Ho.

   BACKGROUND: Artificial intelligence (AI)-based therapeutics, devices, and systems are vital innovations in cancer control; particularly, they allow for diagnosis, screening, precise estimation of survival, informing therapy selection, and scaling up treatment services in a timely manner.
OBJECTIVE: The aim of this study was to analyze the global trends, patterns, and development of interdisciplinary landscapes in AI and cancer research.
METHODS: An exploratory factor analysis was conducted to identify research domains emerging from abstract contents. The Jaccard similarity index was utilized to identify the most frequently co-occurring terms. Latent Dirichlet Allocation was used for classifying papers into corresponding topics.
RESULTS: From 1991 to 2018, the number of studies examining the application of AI in cancer care has grown to 3555 papers covering therapeutics, capacities, and factors associated with outcomes. Topics with the highest volume of publications include (1) machine learning, (2) comparative effectiveness evaluation of AI-assisted medical therapies, and (3) AI-based prediction. Noticeably, this classification has revealed topics examining the incremental effectiveness of AI applications, the quality of life, and functioning of patients receiving these innovations. The growing research productivity and expansion of multidisciplinary approaches are largely driven by machine learning, artificial neural networks, and AI in various clinical practices.
CONCLUSIONS: The research landscapes show that the development of AI in cancer care is focused on not only improving prediction in cancer screening and AI-assisted therapeutics but also on improving other corresponding areas such as precision and personalized medicine and patient-reported outcomes.

Keywords:  artificial intelligence; cancer; global; mapping; scientometrics

DOI:  https://doi.org/10.2196/14401
IEEE Trans Neural Syst Rehabil Eng. 2019 Sep 30.

Academic Review and Perspectives on Robotic Exoskeletons (August 2019).

Guanjun Bao, Lufeng Pan, Hui Fang, Xinyu Wu, Haoyong Yu, Shibo Cai, Bingqing Yu, Yuehua Wan.

Since the first robotic exoskeleton was developed in 1960, this research field has attracted much interest from both the academic and industrial communities resulting in scientific publications, prototype developments and commercialized products. In this article, to document the progress in and current status of this field, we performed a bibliometric analysis. This analysis evaluated the publications in the field of robotic exoskeletons from 1990 to July 2019 that were retrieved from the Science Citation Index Expanded database. The bibliometric analyses were presented in terms of author keywords, year, country, institution, journal, author, and the citation. Results show that currently the United States has taken the leading position in this field and has built the largest collaborative network with other countries. The Massachusetts Institute of Technology (MIT) made the greatest contribution to the field of robotic exoskeleton investigations in terms of the number of publications, average citations per publication and the h-index. In addition, the Journal of NeuroEngineering and Rehabilitation ranks first among the top 20 academic journals in terms of the number of publications related to robotic exoskeletons during the period investigated. Author keyword analysis indicates that most research has focused on rehabilitation robotics. Biomedical engineering, rehabilitation and the neurosciences are the most common disciplines conducting research in this area according to the Web of Science (WoS). Our study comprehensively assesses the current research status and collaboration network of robotic exoskeletons, thus helping researchers steer their projects or locate potential collaborators.

DOI: https://doi.org/10.1109/TNSRE.2019.2944655
Medicine (Baltimore). 2019 Sep;98(38): e17236

The 100 most-cited articles on prenatal diagnosis: A bibliometric analysis.

Meilian Zhang, Yu Zhou, Yanfang Lu, Suhui He, Min Liu.

BACKGROUND: The number of citations a published article receives can be used to demonstrate its impact on a field of study. The objective of this study was to identify and characterize the 100 most-cited research articles (T100) published on prenatal diagnosis.
METHODS: The Web of Science (WOS) database was searched for papers on prenatal diagnosis published between 1900 and 2018. The 100 most-cited original articles and reviews were recorded. Each eligible paper was reviewed for authors, journal name, year of publication, country, institution, total citations, citation density, H-index, research field, article type, and keywords.
RESULTS: The T100 were published between 1972 and 2015 with a mean of 332.7 citations per paper (range: 196-1254). Most of the T100 were published between 1990 and 2005, in 35 journals led by New England Journal of Medicine (n = 14) followed by Lancet (n = 10), and Proceedings of The National Academy of Sciences of the United States of America (n = 8). Studies on method application, which promotes field development, were the majority article type. The team of Lo YM featured prominently in the field, and the United States of America, United Kingdom, and Hong Kong, China were the leading countries/regions. Frequency of cooperation was also highest among these 3 regions. Hierarchical cluster analysis produced 4 groups of keywords.
CONCLUSION: Our analysis provides a historical perspective on scientific progress in prenatal diagnosis and may assist clinicians and researchers in assessing the quality of research over the past 50 years. It also provides concise information to guide future research.

DOI: https://doi.org/10.1097/MD.0000000000017236