K-Means clustering of dermatology journals: comparing the distribution of "free-to-publish" and "pay-to-publish" models.

This study investigates the impact of Free-to-Publish (F2P) versus Pay-to-Publish (P2P) models in dermatology journals, focusing on their differences in terms of journal metrics, Article Processing Charges (APCs), and Open Access (OA) status. Utilizing k-means clustering, the research evaluates dermatology journals based on SCImago Journal Rankings (SJR), H-Index, and Impact Factor (IF), and examines the correlation between these metrics, APCs, and OA status (Full or Hybrid). Data from the SCImago Journal Rank and Journal Citation Report databases were used, and metrics from 106 journals were normalized and grouped into three tiers.The study reveals a higher proportion of F2P journals, especially in higher-tier journals, indicating a preference for quality-driven research acceptance. Conversely, a rising proportion of P2P journals in lower tiers suggests potential bias towards the ability to pay. This disparity poses challenges for researchers from less-funded institutions or those early in their careers. The study also finds significant differences in APCs between F2P and P2P journals, with hybrid OA being more common in F2P.Conclusively, the study highlights the disparities in dermatology journals between F2P and P2P models and underscores the need for further research into authorship demographics and institutional affiliations in these journals. It also establishes the effectiveness of k-means clustering as a standardized method for assessing journal quality, which can reduce reliance on potentially biased individual metrics.