Increasing author counts in neurosurgical journals from 1980 to 2020

OBJECTIVE Scientific productivity, as assessed by publication volume, is a common metric by which the academic neurosurgical field assesses its members. The number of authors per peer-reviewed article has been observed to increase over time across a broad range of medical specialties. This study provides an update to this trend in the neurosurgical literature. METHODS All publications from January 1, 1980, to April 30, 2020, were queried from four neurosurgical journals: Neurosurgery, Journal of Neurosurgery (JNS), JNS: Pediatrics, and JNS: Spine. Publication information was acquired from the National Center for Biotechnology Information Entrez database and reconciled with the Scopus database. Publication type was limited to articles and excluded editorials, letters, and reviews. The number of authors and affiliation counts were determined based on structured abstract fields provided in the two databases. RESULTS Between January 1, 1980, and April 30, 2020, the overall increase in author count for the four neurosurgical journals was 0.12 to 0.18 authors per year (p < 0.001). For Neurosurgery, the mean (SD) author count increased from 2.81 (1.4) in 1980–1985 to 7.97 (4.92) in 2016–2020 (p < 0.001). For the JNS, the mean (SD) author count increased from 2.82 (1.04) in 1980–1985 to 7.6 (3.65) in 2016–2020 (p < 0.001). The percentage of articles with more than 10 authors increased from 0.2% to 22.3% in Neurosurgery and from 1.9% to 17.5% in JNS. Only 28% of the author count variation was explained by an increasing number of institutional or departmental affiliations. CONCLUSIONS Author counts for peer-reviewed articles in neurosurgical academic journals have increased significantly during the past 4 decades, with large increases in the numbers of articles with more than 10 authors in the past 5 years. A total of 28% of the variation in this increase can be explained by an increase in multiinstitutional or multidepartmental studies.

The impact of gender on early scientific publication and long-term career advancement in Israeli medical school graduates

Background Many medical schools and residency programs incorporate research projects into their curriculum, however most remain unpublished. Little is known on the long-term effect of early-career publication, especially in female graduates. Methods We collected data on physicians 15–20 years after graduation (representing a mid-career point), and analysed data on early publication, publication volume and impact according to graduates’ gender and professional characteristics. Physicians were divided into those who never published, early-publishers (EP) who published within 2 years of graduation and late-publishers (LP). We analysed and compared the demographics, publication volume, publication quality as well as current mid-career position. Results Of 532 physicians, 185 were EP (34.8%), 220 were LP (41.3%), 127 (23.9%) never published, 491 (92.2%) became specialists and 122 (22.3%) achieved managerial position. Of the 405 who published, the average number of publications was 20.3 ± 33.0, and median (IQR) 9(19). H-index was significantly higher in EP, males, surgical specialists, and those holding a managerial position. Male gender was associated with higher publication rate (OR = 1.742; 95% CI 1.193–2.544; P = 0.004). Using quantile regression, female gender was negatively associated with the number of publications in Q50-Q95. Surgical specialty and managerial position were positively associated with publications in Q25 to Q75 and early publication in Q25 and Q75. Conclusions We found a strong association between EP and the number, impact, and quality of publications throughout their academic career. This study illuminates the need for further investigations into the causes of gender discrepancies. We should invest in support programs encouraging early high quality research projects for young physicians and female graduates.

Analysis of hot spots in Internet Economy research based on bibliometrics abstract

In this paper, the core journals and CSSCI of CNKI are selected as the database, and the research overview of Internet economy is analyzed through Citespace visual software. The analysis contents mainly include publishing institutions, authors and keywords. The research found that the number of literatures on the topic of Internet economy grew rapidly, and the institutions with large publication volume mainly distributed in Beijing, Shanghai and other places.Research hotspots mainly include Internet finance, artificial intelligence and other hot words closely related to us.

The Need for the Establishment of Biomedical Engineering (BME) as an Academic and Professional Discipline in the Philippines — A Quantitative Argument

<p><b>Background: </b>This article quantitatively presents the relationship between volume of BME publications produced from 1990 to 2019 in the member states of the ASEAN and 12 indicators of overall and physical health. The objective was to show that ASEAN states that recognize BME as an academic and professional discipline have been successful in producing research in the field, and thus, have advanced the provision of high-quality healthcare for their people. </p> <p><b>Results: </b><i>Acceptable</i> relationships [Pearson correlation coefficients (PCC) > 0.6000] were found between BME publication volume and all indicators. Stronger relationships (PCC > 0.7000) were found between BME publication volume and the natural logarithm of the indicators. Brunei data behaved anomalously and was removed to check for any improvements in PCC. Indeed, PCCs for all indicators improved significantly upon exclusion of Brunei data [PCC > 0.8000 for six indicators (linear scale), PCC > 0.9000 for five indicators (log scale)]. These PCCs signify especially strong relationships between BME research yield and healthcare quality in a country. To visualize the relationships, BME publication volume was plotted against GDP per capita, while the remaining 11 indicators were each plotted against BME publication volume. Linear, logarithmic, and exponential regression curves were overlaid on the datapoints. Coefficients of determination (R²) were calculated to measure the aptness of the fits. R² > 0.9000 for two indicators, R² > 0.8000 for five indicators, R² > 0.7000 for four indicators, and R² < 0.7000 for only one indicator were calculated from the curve fits overlaid on the datapoints excluding Brunei data. </p> <p><b>Conclusion:</b> We believe that it is time for the Philippines to adopt BME as an academic and professional discipline, so that it may one day enjoy the benefits brought about by advancements in the provision of healthcare, which are experienced by its neighbors that have gone ahead with movements to cultivate the highly essential discipline.</p>

The Need for the Establishment of Biomedical Engineering (BME) as an Academic and Professional Discipline in the Philippines — A Quantitative Argument

<p><b>Background: </b>This article quantitatively presents the relationship between volume of BME publications produced from 1990 to 2019 in the member states of the ASEAN and 12 indicators of overall and physical health. The objective was to show that ASEAN states that recognize BME as an academic and professional discipline have been successful in producing research in the field, and thus, have advanced the provision of high-quality healthcare for their people. </p> <p><b>Results: </b><i>Acceptable</i> relationships [Pearson correlation coefficients (PCC) > 0.6000] were found between BME publication volume and all indicators. Stronger relationships (PCC > 0.7000) were found between BME publication volume and the natural logarithm of the indicators. Brunei data behaved anomalously and was removed to check for any improvements in PCC. Indeed, PCCs for all indicators improved significantly upon exclusion of Brunei data [PCC > 0.8000 for six indicators (linear scale), PCC > 0.9000 for five indicators (log scale)]. These PCCs signify especially strong relationships between BME research yield and healthcare quality in a country. To visualize the relationships, BME publication volume was plotted against GDP per capita, while the remaining 11 indicators were each plotted against BME publication volume. Linear, logarithmic, and exponential regression curves were overlaid on the datapoints. Coefficients of determination (R²) were calculated to measure the aptness of the fits. R² > 0.9000 for two indicators, R² > 0.8000 for five indicators, R² > 0.7000 for four indicators, and R² < 0.7000 for only one indicator were calculated from the curve fits overlaid on the datapoints excluding Brunei data. </p> <p><b>Conclusion:</b> We believe that it is time for the Philippines to adopt BME as an academic and professional discipline, so that it may one day enjoy the benefits brought about by advancements in the provision of healthcare, which are experienced by its neighbors that have gone ahead with movements to cultivate the highly essential discipline.</p>

The Need for the Establishment of Biomedical Engineering (BME) as an Academic and Professional Discipline in the Philippines — A Quantitative Argument

<p><b>Background: </b>This article quantitatively presents the relationship between volume of BME publications produced from 1990 to 2019 in the member states of the ASEAN and 12 indicators of overall and physical health. The objective was to show that ASEAN states that recognize BME as an academic and professional discipline have been successful in producing research in the field, and thus, have advanced the provision of high-quality healthcare for their people. </p> <p><b>Results: </b><i>Acceptable</i> relationships [Pearson correlation coefficients (PCC) > 0.6000] were found between BME publication volume and all indicators. Stronger relationships (PCC > 0.7000) were found between BME publication volume and the natural logarithm of the indicators. Brunei data behaved anomalously and was removed to check for any improvements in PCC. Indeed, PCCs for all indicators improved significantly upon exclusion of Brunei data [PCC > 0.8000 for six indicators (linear scale), PCC > 0.9000 for five indicators (log scale)]. These PCCs signify especially strong relationships between BME research yield and healthcare quality in a country. To visualize the relationships, BME publication volume was plotted against GDP per capita, while the remaining 11 indicators were each plotted against BME publication volume. Linear, logarithmic, and exponential regression curves were overlaid on the datapoints. Coefficients of determination (R²) were calculated to measure the aptness of the fits. R² > 0.9000 for two indicators, R² > 0.8000 for five indicators, R² > 0.7000 for four indicators, and R² < 0.7000 for only one indicator were calculated from the curve fits overlaid on the datapoints excluding Brunei data. </p> <p><b>Conclusion:</b> We believe that it is time for the Philippines to adopt BME as an academic and professional discipline, so that it may one day enjoy the benefits brought about by advancements in the provision of healthcare, which are experienced by its neighbors that have gone ahead with movements to cultivate the highly essential discipline.</p>

The Need for the Establishment of Biomedical Engineering (BME) as an Academic and Professional Discipline in the Philippines — A Quantitative Argument

This article quantitatively presents the relationship that exists between research endeavors in BME, which was measured in terms of the volume of publications produced in the field of BME from 1990 to 2019 in the 10 member states of the ASEAN, and 12 indicators of the overall and physical health of populations (†) — GDP per capita, HDI value, HAQ index, life expectancy at birth, healthy life expectancy at birth, maternal mortality ratio, neonatal mortality rate, probability of dying from noncommunicable diseases, and incidences of death due to stroke, diabetes mellitus, congenital birth defects, and leukemia. The objective was to show that ASEAN states that recognize BME as an academic and professional discipline have been successful in producing research in the field, and thus, have advanced the provision of high-quality healthcare for their people. The Pearson correlation coefficients (PCCs) between BME publication volume and the 12 healthcare indicators were calculated and were reported in the order previously listed (see †) to be +0.7555, +0.7398, +0.7297, +0.7563, +0.7879, -0.6286, -0.6810, -0.7245, -0.6683, -0.6893, -0.7645, and -0.6827. The PCCs between BME publication volume and the natural logarithm of the same indicators in the same order were calculated and were reported to be +0.7338, +0.7051, +0.7184, +0.7452, +0.7754, -0.7985, -0.7286, -0.7905, -0.7872, -0.9208, -0.9149, and -0.7038. It was also discovered that data from Brunei Darussalam behaved anomalously, as they did not conform with the observed trends. Hence, it was decided that data from Brunei would be removed to check for any improvements in PCC. Indeed, PCCs for all indicators improved. PCCs between BME publication volume and the 12 indicators excluding data from Brunei were reported in the same order as follows: +0.9279, +0.9072, +0.8659, +0.8598, +0.8800, -0.7313, -0.7783, -0.7919, -0.7726, -0.7073, -0.8133, and -0.6907. PCCs between BME publication volume and the natural logarithms of the 12 indicators excluding data from Brunei were reported in the same order as follows: +0.9042, +0.8707, +0.9599, +0.8519, +0.8726, -0.8822, -0.9318, -0.8430, 0.8510, -0.9234, -0.9390, and -0.7069, respectively. These PCCs, many of them with magnitudes above 0.9000, signify especially strong relationships between BME research yield and healthcare quality in a country.Moreover, to best visualize the relationships quantified above, BME publication volume was plotted against GDP per capita, while the remaining 11 indicators were each plotted against BME publication volume. Linear (Lin), logarithmic (Log), and exponential (Exp) regression curves were then overlaid on the datapoints. Coefficients of determination (R2) were calculated to measure the aptness of the fits. R2 values were reported in the same order as above to be: 0.5161 (Log), 0.5708 (Lin), 0.5473 (Lin), 0.5720 (Lin), 0.6207 (Lin), 0.7457 (Log), 0.7517 (Exp), 0.6249 (Exp), 0.6197 (Exp), 0.8469 (Exp), 0.8095 (Log), and 0.4660 (Lin) [incl. Brunei]; 0.9214 (Log), 0.8612 (Lin), 0.8230 (Lin), 0.7393 (Lin), 0.7745 (Lin), 0.9433 (Log), 0.8682 (Exp), 0.7106 (Exp), 0.7242 (Exp), 0.8527 (Exp), 0.8960 (Log), and 0.4771 (Lin) [excl. Brunei].For this reason, we believe that it is certainly time for the Philippines to adopt BME as an academic and professional discipline in its own right, so that it may one day enjoy the benefits brought about by advancements in the provision of healthcare that are experienced by its ASEAN neighbors that have already gone ahead with movements to cultivate the highly essential discipline.