A spatial-institutional analysis of researchers with multiple affiliations.
Ontology highlight
ABSTRACT:
SUBMITTER: Yegros-Yegros A
PROVIDER: S-EPMC8241029 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background:The institutional affiliations and associated collaborative networks that scientists foster during their research careers are salient in the production of high-quality science. The phenomenon of multiple institutional affiliations and its relationship to research output remains relatively unexplored in the literature. Methods:We examined 27,612 scientific articles, modelling the normalized citation counts received against the number of authors and affiliations held. Results:In agreement with previous research, we found that teamwork is an important factor in high impact papers, with average citations received increasing concordant with the number of co-authors listed. For articles with more than five co-authors, we noted an increase in average citations received when authors with more than one institutional affiliation contributed to the research. Discussion:Multiple author affiliations may play a positive role in the production of high-impact science. This increased researcher mobility should be viewed by institutional boards as meritorious in the pursuit of scientific discovery.
| S-EPMC6160819 | biostudies-literature
Project description:INTRODUCTION:University ranking systems and the publish-or-perish dictum, among other factors, are driving universities and researchers around the world to increase their research productivity. Authors frequently report multiple affiliations in published articles. It is not known if the reported institutional affiliations are real affiliations, which is when the universities have contributed substantially to the research conducted and to the published manuscript. This study aims to establish whether there is an empirical basis for author affiliation misrepresentation in authors with multiple institutional affiliations. METHODS AND ANALYSIS:This individual secondary data exploratory analysis on Scopus-indexed articles for 2016 will search all authors who report multiple institutional affiliations in which at least one of the affiliations is to a Chilean university. We will consider that misrepresentation of an affiliation is more likely when it is not possible to verify objectively a link between the author and the mentioned institution through institutional websites. If we cannot corroborate the author affiliation, we will consider this a finding of potential misrepresentation of the affiliation. We will summarise results with descriptive statistics. ETHICS AND DISSEMINATION:The study protocol was approved by the institutional ethics committee of Universidad de Santiago de Chile, Resolution No. 261, and dated January 15, 2018. Results will be submitted to the World Conference on Research Integrity, among other meetings on publication ethics and research integrity, and will be published in scientific, peer-reviewed journals.
| S-EPMC6398759 | biostudies-literature
Project description:Informed consent is crucial in research, but potential participants may not all speak the same language, posing questions that have not been examined concerning decisions by institutional review boards (IRBs) and research ethics committees' (RECs) about the need for researchers to translate consent forms and other study materials. Sixty US IRBs (every fourth one in the list of the top 240 institutions by The National Institutes of Health funding) were contacted, and leaders (eg, chairs) from 34 (response rate=57%) and an additional 12 members and administrators were interviewed. IRBs face a range of problems about translation of informed consent documents, questionnaires and manuals-what, when and how to translate (eg, for how many or what proportion of potential subjects), why to do so and how to decide. Difficulties can arise about translation of specific words and of broader cultural concepts regarding processes of informed consent and research, especially in the developing world. In these decisions, IRBs weigh the need for autonomy (through informed consent) and justice (to ensure fair distribution of benefits and burdens of research) against practical concerns about costs to researchers. At times IRBs may have to compromise between these competing goals. These data, the first to examine when and how IRBs/RECs require researchers to translate materials, thus highlight a range of problems with which these committees struggle, suggesting a need for further normative and empirical investigation of these domains, and consideration of guidelines to help IRBs deal with these tensions.
| S-EPMC3864149 | biostudies-literature
Project description:BackgroundInstitutional delivery is an important indicator in monitoring the progress towards Sustainable Development Goal 3.1 to reduce the global maternal mortality ratio to less than 70 per 100,000 live births. Despite the international focus on reducing maternal mortality, progress has been low, particularly in Sub-Saharan Africa (SSA), with more than 295,000 mothers still dying during pregnancy and childbirth every year. Institutional delivery has been varied across and within the country. Therefore, this study aimed to investigate the individual and community level determinants, and spatial distribution of institutional delivery in Ethiopia.MethodsA secondary data analysis was done based on the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total weighted sample of 11,022 women was included in this study. For spatial analysis, ArcGIS version 10.6 statistical software was used to explore the spatial distribution of institutional delivery, and SaTScan version 9.6 software was used to identify significant hotspot areas of institutional delivery. For the determinants, a multilevel binary logistic regression analysis was fitted to take to account the hierarchical nature of EDHS data. The Intra-class Correlation Coefficient (ICC), Median Odds Ratio (MOR), Proportional Change in Variance (PCV), and deviance (-2LL) were used for model comparison and for checking model fitness. Variables with p-values<0.2 in the bi-variable analysis were fitted in the multivariable multilevel model. Adjusted Odds Ratio (AOR) with a 95% Confidence Interval (CI) were used to declare significant determinant of institutional delivery.ResultsThe spatial analysis showed that the spatial distribution of institutional delivery was significantly varied across the country [global Moran's I = 0.04 (p<0.05)]. The SaTScan analysis identified significant hotspot areas of poor institutional delivery in Harari, south Oromia and most parts of Somali regions. In the multivariable multilevel analysis; having 2-4 births (AOR = 0.48; 95% CI: 0.34-0.68) and >4 births (AOR = 0.48; 95% CI: 0.32-0.74), preceding birth interval ≥ 48 months (AOR = 1.51; 95% CI: 1.03-2.20), being poorer (AOR = 1.59; 95% CI: 1.10-2.30) and richest wealth status (AOR = 2.44; 95% CI: 1.54-3.87), having primary education (AOR = 1.47; 95% CI: 1.16-1.87), secondary and higher education (AOR = 3.44; 95% CI: 2.19-5.42), having 1-3 ANC visits (AOR = 3.88; 95% CI: 2.77-5.43) and >4 ANC visits (AOR = 6.53; 95% CI: 4.69-9.10) were significant individual-level determinants of institutional delivery while being living in Addis Ababa city (AOR = 3.13; 95% CI: 1.77-5.55), higher community media exposure (AOR = 2.01; 95% CI: 1.44-2.79) and being living in urban area (AOR = 4.70; 95% CI: 2.70-8.01) were significant community-level determinants of institutional delivery.ConclusionsInstitutional delivery was low in Ethiopia. The spatial distribution of institutional delivery was significantly varied across the country. Residence, region, maternal education, wealth status, ANC visit, preceding birth interval, and community media exposure were found to be significant determinants of institutional delivery. Therefore, public health interventions should be designed in the hotspot areas where institutional delivery was low to reduce maternal and newborn mortality by enhancing maternal education, ANC visit, and community media exposure.
| S-EPMC7660564 | biostudies-literature
Project description:ImportanceLittle is known about whether a clinician having multiple hospital affiliations (ie, 1 clinician working across multiple teams and organizations) is associated with clinician practice style and cost. The measurement of this association requires adjusting for selection into multihospital affiliations based on both observable and unobservable clinician characteristics.ObjectiveTo evaluate the association of multiple hospital affiliations with clinician service use, breadth of procedures used, and costs.Design, setting, and participantsThis cohort study used Medicare Part B data from 2016 through 2017 in a fixed-effects panel data design to compare service use, procedure breadth, and costs between clinicians with multiple affiliations (treatment group) and clinicians with a single affiliation (control group), with adjustment for volume, patients, and clinician characteristics. The study also controlled for unobserved (time-invariant) clinician characteristics using individual clinician fixed effects. Clinicians with Medicare claims, a reported National Provider Identifier, and affiliation data within Medicare Physician Compare were included for a total sample of 1 073 252 observations (633 552 unique clinicians) for medical services and 358 669 observations (210 260 unique clinicians) for drug prescribing. Statistical analyses were performed from February 1 to October 15, 2021.Main outcomes and measuresService use is the total number of medical (or drug) services that clinicians render to their Medicare beneficiaries within a given year, procedure breadth is the total number of unique Healthcare Common Procedure Coding System codes that are associated with clinicians' medical (or drug) services within a given year, and costs represent the total standardized amount paid by Medicare for the medical (or drug) services. Additional measures were multiple-hospital affiliations, Accountable Care Organization affiliation, and controls across clinician and patient characteristics.ResultsThe medical service sample consisted of 633 552 clinicians (248 359 women [39.2%]; mean [SD] of 19.6 [12.5] years of experience), and the drug service sample consisted of 210 260 clinicians (74 875 women [35.6%]; mean [SD] of 21.6 [12.3] years of experience). For medical services, clinicians with multiple practice affiliations used a mean 8.2% (95% CI, 7.5%-8.9%; P < .001) more medical services per patient, drew on a mean 5.4% (95% CI, 5.1%-5.7%; P < .001) wider set of procedures within their medical care, and incurred a mean 8.6% (95% CI, 7.9%-9.2%; P < .001) more in medical costs. Pertaining to drug services, clinicians with multiple practice affiliations used a mean 2.9% (95% CI, 1.9%-3.9%; P < .001) more drug services per patient, drew on a mean 1.0% (95% CI, 0.5%-1.4%; P < .001) wider set of procedures within their medical care, and incurred a mean 2.7% (95% CI, 1.6%-3.7%; P < .001) more in drug costs. Significant results were also found across extensive and intensive margins of hospital affiliation, and supplemental analysis further indicated heterogenous treatment associations across clinician specialties.Conclusions and relevanceThis cohort study found that a clinician having multihospital affiliations was associated with greater service use, procedure breadth, and costs across both medical and drug services. These findings suggest that clinician affiliations ought to be considered as part of health care delivery design and potential cost-containment strategies.
| S-EPMC8678686 | biostudies-literature
Project description:The institutional environment not only has a great impact on economic development but also has a certain impact on labor agglomeration. This paper explains the phenomenon of labor agglomeration from the perspective of the labor market institutional environment. Taking the labor market institutional environment including social contract environment and labor contract environment as the premise, it is considered that a good labor institutional market can promote labor agglomeration and technological progress can stimulate the agglomeration of highly-skilled talents through theoretical analysis. Based on the provincial panel data from 2001 to 2017, the empirical analysis is conducted to verify the relevant factors through the dynamic spatial Durbin model. The paper finally puts forward some policy suggestions to maintain a good institutional environment of the labor market, including that the local government should continue to improve the labor dispute settlement system, strengthen the protection of labor rights and interests, and enhance the institutional environment of the regional labor market.
| S-EPMC8531718 | biostudies-literature
Project description:Machine learning algorithms are becoming more and more useful in many fields of science, including many areas where computational methods are rarely used. High-performance Computing (HPC) is the most powerful solution to get the best results using these algorithms. HPC requires various skills to use. Acquiring this knowledge might be intimidating and take a long time for a researcher with small or no background in information and communications technologies (ICTs), even if the benefits of such knowledge is evident for the researcher. In this work, we aim to assess how a specific method of introducing HPC to such researchers enables them to start using HPC. We gave talks to two groups of non-ICT researchers that introduced basic concepts focusing on the necessary practical steps needed to use HPC on a specific cluster. We also offered hands-on trainings for one of the groups which aimed to guide participants through the first steps of using HPC. Participants filled out questionnaires partly based on Kirkpatrick's training evaluation model before and after the talk, and after the hands-on training. We found that the talk increased participants' self-reported likelihood of using HPC in their future research, but this was not significant for the group where participation was voluntary. On the contrary, very few researchers participated in the hands-on training, and for these participants neither the talk, nor the hands-on training changed their self-reported likelihood of using HPC in their future research. We argue that our findings show that academia and researchers would benefit from an environment that not only expects researchers to train themselves, but provides structural support for acquiring new skills.
| S-EPMC7521077 | biostudies-literature
Project description:Kennewick Man, referred to as the Ancient One by Native Americans, is a male human skeleton discovered in Washington state (USA) in 1996 and initially radiocarbon dated to 8,340-9,200 calibrated years before present (BP). His population affinities have been the subject of scientific debate and legal controversy. Based on an initial study of cranial morphology it was asserted that Kennewick Man was neither Native American nor closely related to the claimant Plateau tribes of the Pacific Northwest, who claimed ancestral relationship and requested repatriation under the Native American Graves Protection and Repatriation Act (NAGPRA). The morphological analysis was important to judicial decisions that Kennewick Man was not Native American and that therefore NAGPRA did not apply. Instead of repatriation, additional studies of the remains were permitted. Subsequent craniometric analysis affirmed Kennewick Man to be more closely related to circumpacific groups such as the Ainu and Polynesians than he is to modern Native Americans. In order to resolve Kennewick Man's ancestry and affiliations, we have sequenced his genome to ?1× coverage and compared it to worldwide genomic data including for the Ainu and Polynesians. We find that Kennewick Man is closer to modern Native Americans than to any other population worldwide. Among the Native American groups for whom genome-wide data are available for comparison, several seem to be descended from a population closely related to that of Kennewick Man, including the Confederated Tribes of the Colville Reservation (Colville), one of the five tribes claiming Kennewick Man. We revisit the cranial analyses and find that, as opposed to genome-wide comparisons, it is not possible on that basis to affiliate Kennewick Man to specific contemporary groups. We therefore conclude based on genetic comparisons that Kennewick Man shows continuity with Native North Americans over at least the last eight millennia.
| S-EPMC4878456 | biostudies-literature
Project description:Scientists from nearly all disciplines face the problem of simultaneously evaluating many hypotheses. Conducting multiple comparisons increases the likelihood that a non-negligible proportion of associations will be false positives, clouding real discoveries. Drawing valid conclusions require taking into account the number of performed statistical tests and adjusting the statistical confidence measures. Several strategies exist to overcome the problem of multiple hypothesis testing. We aim to summarize critical statistical concepts and widely used correction approaches while also draw attention to frequently misinterpreted notions of statistical inference. We provide a step-by-step description of each multiple-testing correction method with clear examples and present an easy-to-follow guide for selecting the most suitable correction technique. To facilitate multiple-testing corrections, we developed a fully automated solution not requiring programming skills or the use of a command line. Our registration free online tool is available at www.multipletesting.com and compiles the five most frequently used adjustment tools, including the Bonferroni, the Holm (step-down), the Hochberg (step-up) corrections, allows to calculate False Discovery Rates (FDR) and q-values. The current summary provides a much needed practical synthesis of basic statistical concepts regarding multiple hypothesis testing in a comprehensible language with well-illustrated examples. The web tool will fill the gap for life science researchers by providing a user-friendly substitute for command-line alternatives.
| S-EPMC8189492 | biostudies-literature
Project description:BACKGROUND:Despite extensive literature describing the use of social media in health research, a gap exists around best practices in establishing, implementing, and evaluating an effective social media knowledge translation (KT) and exchange strategies. OBJECTIVE:This study aims to examine successes, challenges, and lessons learned from using social media within health research and to create practical considerations to guide other researchers. METHODS:The Knowledge Translation Platform of the Alberta Strategy for Patient-Oriented Research SUPPORT Unit formed a national working group involving platform staff, academics, and a parent representative with experience using social media for health research. We collected and analyzed 4 case studies that used a variety of social media platforms and evaluation methods. The case studies covered a spectrum of initiatives from participant recruitment and data collection to dissemination, engagement, and evaluation. Methods and findings from each case study as well as barriers and facilitators encountered were summarized. Through iterative discussions, we converged on recommendations and considerations for health researchers planning to use social media for KT. RESULTS:We provide recommendations for elements to consider when developing a social media KT strategy: (1) set a clear goal and identify a theory, framework, or model that aligns with the project goals and objectives; (2) understand the intended audience (use social network mapping to learn what platforms and social influences are available); (3) choose a platform or platforms that meet the needs of the intended audience and align well with the research team's capabilities (can you tap into an existing network, and what mode of communication does it support?); (4) tailor messages to meet user needs and platform requirements (eg, plain language and word restrictions); (5) consider timing, frequency, and duration of messaging as well as the nature of interactions (ie, social filtering and negotiated awareness); (6) ensure adequate resources and personnel are available (eg, content creators, project coordinators, communications experts, and audience stakeholder or patient advocate); (7) develop an evaluation plan a priori driven by goals and types of data available (ie, quantitative and qualitative); and (8) consider ethical approvals needed (driven by evaluation and type of data collection). CONCLUSIONS:In the absence of a comprehensive framework to guide health researchers using social media for KT, we provide several key considerations. Future research will help validate the proposed components and create a body of evidence around best practices for using and evaluating social media as part of a KT strategy.
| S-EPMC7413271 | biostudies-literature