Citation analysis may severely underestimate the impact of clinical research as compared to basic research (1210.0442v2)

Abstract: Background: Citation analysis has become an important tool for research performance assessment in the medical sciences. However, different areas of medical research may have considerably different citation practices, even within the same medical field. Because of this, it is unclear to what extent citation-based bibliometric indicators allow for valid comparisons between research units active in different areas of medical research. Methodology: A visualization methodology is introduced that reveals differences in citation practices between medical research areas. The methodology extracts terms from the titles and abstracts of a large collection of publications and uses these terms to visualize the structure of a medical field and to indicate how research areas within this field differ from each other in their average citation impact. Results: Visualizations are provided for 32 medical fields, defined based on journal subject categories in the Web of Science database. The analysis focuses on three fields. In each of these fields, there turn out to be large differences in citation practices between research areas. Low-impact research areas tend to focus on clinical intervention research, while high-impact research areas are often more oriented on basic and diagnostic research. Conclusions: Popular bibliometric indicators, such as the h-index and the impact factor, do not correct for differences in citation practices between medical fields. These indicators therefore cannot be used to make accurate between-field comparisons. More sophisticated bibliometric indicators do correct for field differences but still fail to take into account within-field heterogeneity in citation practices. As a consequence, the citation impact of clinical intervention research may be substantially underestimated in comparison with basic and diagnostic research.

Citation Impact Disparities in Clinical Versus Basic Medical Research

This paper investigates the significant variations in citation practices within the medical sciences, highlighting major discrepancies between clinical and basic research areas. Despite the popularity of citation-based bibliometric indicators, such as the h-index and impact factor, these metrics may lead to inaccurate assessments of research performance due to not accounting for heterogeneity within a single medical field. The authors deploy a novel visualization methodology, using term maps, to examine and reveal differences in citation practices across various medical research domains.

Methodological Insights

The authors implement an advanced form of bibliometric mapping to address the challenge of categorizing medical research areas. Using the Web of Science (WoS) database as their primary data source, they define fields based on journal subject categories. They extract terms from publication titles and abstracts and utilize these to construct a two-dimensional term map that characterizes each medical field. The term maps not only visualize the structure of the medical fields but also distinctly color different terms based on their normalized citation scores. These colors serve as an indicator of the citation impact of publications containing those terms. This technique avoids the arbitrariness of explicit boundary drawing and instead provides a flexible, visualization-based exploration of citation impact discrepancies.

Key Findings

The analysis spans 32 medical fields, with particular attention to cardiac & cardiovascular systems, clinical neurology, and surgery. Each term map revealed visible distinctions between research areas, with clinical intervention studies predominantly appearing in low-impact zones and basic as well as diagnostic research appearing in high-impact zones. This pattern suggests that clinical research, particularly surgical interventions, often garners a lower citation impact than basic or diagnostic research, contradicting some prior studies such as Opthof (2011). Importantly, the paper observes that within a single field, citation impacts can vary significantly, often by factors of two to three, underscoring the heterogeneity within medical research domains.

Implications and Future Directions

The findings articulate a critical limitation in current bibliometric indicators: their failure to correct for within-field citation practice variations. This poses a significant risk of underestimating the impact of clinical intervention research, potentially overlooking the valuable contributions made in translating basic research into clinical applications. The paper suggests the necessity for improved normalization processes that adjust for both inter-field and intra-field differences in citation practices. Future developments in AI and bibliometric analysis could leverage machine learning algorithms to dynamically identify and classify research areas, allowing for better-tailored, more accurate bibliometric indicators.

In conclusion, this paper contributes a substantial empirical foundation to the discourse on citation analysis, emphasizing the need for refined metrics that appropriately represent the diversity of research impact within medical fields. By elucidating the biases that current indicators might introduce, this work paves the way for methodological advancements that could lead to more equitable evaluations of scientific research impacts.