The Cooper Rowan Medical Journal (CRMJ), a new open-access, peer-reviewed biomedical science journal from Cooper Medical School of Rowan University (CMSRU), has published its first manuscripts. The announcement was made by Annette C. Reboli, dean and professor of medicine at CMSRU.
The new scholarly journal is student-driven, partially student-run and faculty-supervised. Its peer-reviewed articles include up-to-date research first-authored by current medical students, allied healthcare students, and medical residents and fellows.
CMSRU is committed to educating students who understand the importance of evidence-based medicine, scholarly research and lifelong learning, explains Reboli.
The journal is one of only a handful of peer-reviewed student medical journals nationwide. It was initiated last year by clinical faculty and medical students – led by fourth-year student Kristopher Hendershot - who sought to create a legitimate, peer-reviewed journal that could publish student research from around the globe. CMSRU medical librarian Benjamin Saracco serves as the journal’s managing editor. He along with Dr. R. Philip Dellinger, professor of medicine at CMSRU and one of the school’s most widely-published researchers, provided guidance and leadership to make the project a reality.
Mirroring the mission and vision of CMSRU and its focus on serving the community, CRMJ prioritises publishing research that addresses medical conditions and healthcare access issues that impact medically underserved patients and communities. To date, CRMJ has received 20 submissions from more than 10 medical schools across the country and has accepted 10 percent of them. CRMJ is indexed in Google Scholar and the journal team has the goal of eventually being indexed in PubMed Central.
According to Saracco, the CRMJ Editorial Board includes defined student and faculty roles for strategic, educational reasons.
Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting & Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment & Entity Extraction.
