Yadigar KASTAMONİ, Kenan ÖZTÜRK, İhsan HIZ, Hanife ERTÜRK, Soner ALBAY
Süleyman Demirel Üniversitesi Tıp Fakültesi Dergisi - 2026;33(2):162-173
Objective This study aimed to examine the bibliometric overview of articles published in the Medical Journal of Süleyman Demirel University between 2020 and 2025, and thereby to reveal the journal's current publication profile and developmental trends. Material and Method All articles published in the journal between January 2020 and December 2025 were retrieved from the DergiPark archive and cross-checked with Google Scholar. Data were independently extracted by two researchers using a pre-specified coding form; disagreements were resolved by consensus. Citations were retrieved on a single reference date (15 December 2025). Analyses were structured as a primary stream restricted to regular issues (n=438) and a supplementary stream including special issues (n=482). Departmental and institutional collaboration networks, as well as a keyword co-occurrence network, were constructed in Python (NetworkX). Group differences were tested with Pearson's chi-square, Kruskal-Wallis and Mann-Whitney U tests, and Spearman correlations (alpha=0.05). Results In regular issues (n=438), 84.93% of articles were research articles, 7.53% case reports, 6.39% reviews, and 1.14% other. In the two special issues (n=44), reviews dominated (81.82%). The article-type mix, publication language, and study-design distribution all shifted significantly across 2020-2025 (all p<0.05); notably, the English-language share rose from 33.8% in 2020 to 100% in 2025. A total of 176 articles (36.51%) received at least one Google Scholar citation. The departmental collaboration network revealed Pathology, General Surgery, Radiology, and Orthopedics & Traumatology as the most central nodes, forming a densely connected core of co-authoring clinical disciplines. The institutional network was dominated by Süleyman Demirel University as the central hub, with Isparta City Hospital and Mehmet Akif Ersoy University as its strongest collaborators. The keyword co-occurrence network identified three clusters centred on (i) COVID-19/pandemic, (ii) oxidative stress/apoptosis/inflammation, and (iii) quality of life / nursing / psychosocial topics.
