Questioning the Impact of the Impact Factor. A Brief Review and Future Directions

Purpose: To provide a brief review of literature on the journal impact factors (JIF) and the newer research metrics being proposed or implemented.Methods: The authors performed a PubMed search of articles published in the English language on the journal impact factors. Data captured include historical perspectives, evolution, calculation, criticisms of JIF and their rebuttals, and organized efforts to address JIF issues, alternate research metrics, and future directions. Specific emphasis was laid on evaluating the criticisms, current lacunae, and the changing practice patterns.Results: One of the measures to assess the research impact of an article is the number of citations it receives. Hence, citation-based metrics are commonly used for such purposes. While editors and well-known scholars refrain from attributing article success to the journal's prominence, the same is not true for most authors. JIF is still one of the top factors when deciding on an article submission. JIF is today an acceptable objective and quantifiable measure of knowledge dissemination. However, JIF should not be used as a surrogate measure to assess an individual researcher or an individual article. The reverence to JIF in this regard needs to be questioned. While alternate metrics or altmetrics have their advantages and limitations, they nevertheless augur well an era where scientometrics are complementary to one another without undue reliance on a sole parameter.Conclusion: While there is no need to demonize the JIF, its role in the scholarly assessment should be scaled down. The over-reliance and undue hype surrounding it should be discouraged at multiple scientific levels.

Science deserves to be judged by its contents, not by its wrapping: Revisiting Seglen's work on journal impact and research evaluation

The scientific foundation for the criticism on the use of the Journal Impact Factor (JIF) in evaluations of individual researchers and their publications was laid between 1989 and 1997 in a series of articles by Per O. Seglen. His basic work has since influenced initiatives such as the San Francisco Declaration on Research Assessment (DORA), the Leiden Manifesto for research metrics, and The Metric Tide review on the role of metrics in research assessment and management. Seglen studied the publications of only 16 senior biomedical scientists. We investigate whether Seglen’s main findings still hold when using the same methods for a much larger group of Norwegian biomedical scientists with more than 18,000 publications. Our results support and add new insights to Seglen’s basic work.

The Journal Impact Factor is under attack - use the CAPCI factor instead

The uses and misuses of the Journal Impact Factor (JIF) have been thoroughly discussed in the literature. A few years ago, I predicted that JIF would soon be replaced, while another colleague argued the opposite. Over the past few months, attacks on JIF have intensified, with some publishing organizations gradually removing the indicator from their journals' websites. Here, I argue that most, if not all of the misuses of JIF are related to its name. The word "impact" should be removed, since it implies an influential attribute, either for the journals, their published papers, or their authors. I propose instead the use of a new name, the "CAPCI factor", standing for Citation Average Per Citable Item, which accurately describes what is represented by this measure.

Radiological research activity 1998-2007: relationship to gross domestic product, health expenditure and public expenditure on education

OBJECTIVE: The purpose of this study was to evaluate the relationship of the radiological research activity from 1998 to 2007 to the gross domestic product (GDP), health expenditure and public expenditure on education. METHODS: The population-adjusted research activity determined by the number of articles published, the cumulative impact factor (IF) and the cumulative IF per capita were correlated with per capita values of the GDP, health expenditure and public education expenditure. Linear regression analysis and multiple regression analysis were used for statistical analysis. RESULTS: The cumulative IF per capita correlated with the GDP per capita (R = 0.94, P < 0.0001), health expenditure per capita (R = 0.93, P < 0.0001) and public expenditure on education per capita (R = 0.93, P < 0.0001). Multiple regression analysis demonstrated that public expenditure on education was an independent predictor of radiological research activity (P < 0.001), whereas the year, GDP and health expenditure did not reach statistical significance (P > 0.05). CONCLUSION: Radiological research activity demonstrates a close relationship to the GDP, health expenditure and public expenditure on education. The last factor independently predicts research activity.