Open Access Open Badges Research

Scoliosis: density-equalizing mapping and scientometric analysis

Karin Vitzthum12*, Stefanie Mache1, David Quarcoo1, Cristian Scutaru12, David A Groneberg1 and Norman Schöffel1

Author Affiliations

1 Institute of Occupational Medicine, Charité-Universitätsmedizin Berlin, Free University Berlin and Humboldt-University Berlin, Thielallee 69-73, D-14195 Berlin, Germany

2 Department of Respiratory Medicine, Hanover Medical School, Carl-Neuberg-Straß 1, 30625 Hanover, Germany

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Scoliosis 2009, 4:15  doi:10.1186/1748-7161-4-15

Published: 28 July 2009



Publications related to scoliosis have increased enormously. A differentiation between publications of major and minor importance has become difficult even for experts. Scientometric data on developments and tendencies in scoliosis research has not been available to date. The aim of the current study was to evaluate the scientific efforts of scoliosis research both quantitatively and qualitatively.


Large-scale data analysis, density-equalizing algorithms and scientometric methods were used to evaluate both the quantity and quality of research achievements of scientists studying scoliosis. Density-equalizing algorithms were applied to data retrieved from ISI-Web.


From 1904 to 2007, 8,186 items pertaining to scoliosis were published and included in the database. The studies were published in 76 countries: the USA, the U.K. and Canada being the most productive centers. The Washington University (St. Louis, Missouri) was identified as the most prolific institution during that period, and orthopedics represented by far the most productive medical discipline. "BRADFORD, DS" is the most productive author (146 items), and "DANSEREAU, J" is the author with the highest scientific impact (h-index of 27).


Our results suggest that currently established measures of research output (i.e. impact factor, h-index) should be evaluated critically because phenomena, such as self-citation and co-authorship, distort the results and limit the value of the conclusions that may be drawn from these measures. Qualitative statements are just tractable by the comparison of the parameters with respect to multiple linkages. In order to obtain more objective evaluation tools, new measurements need to be developed.