Abstract
The word ‘growth’ represents an increase in actual size, implying a change of state. In science and technology, growth may imply an increase in number of institutions, scientists, or publications, etc. The present study demonstrates the growth of neurology literature for the period 1961-2010. A total of 291,702 records were extracted from the Science Direct Database for fifty years. The Relative Growth Rate (RGR) and Doubling Time (Dt.) of neurology literature have been calculated, supplementing with different growth patterns to check whether neurology literature fits exponential, linear, or logistic models. The results of the study indicate that the growth of literature in neurology does not follow the linear, or logistic growth model. However, it follows closely the exponential growth model. The study concludes that there has been a consistent trend towards increased growth of literature in the field of neurology.
Highlights
One of the features of modern research in recent years has been the spectacular development of scientific discoveries and growth of knowledge, say Gupta et al (2002)
The results show that the power model (α>0, γ>1) followed by logistic models are best describing the cumulative growth of publications in all sub-disciplines
The results show that the linear growth model provides better fits to the observed data, whereas the exponential model provided the poorest fit
Summary
One of the features of modern research in recent years has been the spectacular development of scientific discoveries and growth of knowledge, say Gupta et al (2002). This has caused an unprecedented accumulation of information and has become a major concern for scientists and researchers (Meera & Sangam, 2010). All JISTaP content is Open Access, meaning it is accessible online to everyone, without fee and authors’ permission. Redistribution, or reproduction of a work, users must clarify the license terms under which the work was produced
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