Files and links (1)
CC BY-NC-SA V4.0, Open Access
Some early-career biomedical engineering researchers believe in a theory that some research articles are more likely to get published in high-impact journals simply because their research topics are favored. This theory is tested by regressing the journal impact metric against the biomedical engineering research topics across thousands of recent academic journal articles in biomedical engineering. The journal impact metric is operationalized as the CiteScore provided by Scopus, a citation database. To account for the variant spellings of the same topic, the research topics are generated using a research assessment tool named SciVal. The journal articles included in the analysis are also identified using Scopus, because journals indexed in Scopus have assigned subject categories, making it easy to identify journals relevant to biomedical engineering. The inclusion criteria for selecting articles are biomedical engineering journal articles that are (1) peer-reviewed, (2) published in the most recent four years (2018-2021) and (3) in English language. Using each article as an observation, how much more or less CiteScore is linked to the presence of a research topic is tested using linear regression. Several research topics exhibit statistically significant positive slopes, thus supporting the hypothesis that certain research topics have positive correlations with high-impact journals.