Mehdi Dadkhah

Objectives: The integrity of research and science is increasingly under threat from questionable journals. In particular, hijacked journals rapidly expand, propagating scam-based, non-peer-reviewed publications. While the academic literature offers discussions, developed methodologies, and block lists to combat these fraudulent journals, the most prevalent hijacked journals and their primary distribution channels remain ambiguous. Methods: To bridge this knowledge gap, the current study utilized a list of 380 previously detected hijacked journals and the web analytics platform Semrush to identify the most visited hijacked journals and their primary channels for attracting web traffic. This research first analyzes hijacked journals across various fields and then focuses specifically on hijacked medical journals. Results: Our findings demonstrate that over 50 % of previously detected hijacked journals are active, primarily attracting researchers via email, search engines, and artificial intelligence (AI) tools. Furthermore, the majority of visitors to these journal websites originate from India. The results for medical journals align with these overall trends. Conclusions: Addressing the significant problem these questionable journals pose necessitates implementing legal action and technological solutions.

Purpose: The negative impact of potential predatory journals has been widely discussed, primarily within academic contexts. However, their influence beyond academia remains underexplored. This study aims to address that gap. Methods: The current editorial utilised a sample list of 8 potential predatory medical journals. We compiled a list of potential predatory medical journals using the discontinued titles list in Scopus and the current blocklists. Then their patent-to-paper citations have been examined to understand the dissemination of questionable medical publications outside of academia. Results: This indicates that potential predatory medical journals received 483,848 citations from scholarly works and 4,251 citations from patents. Conclusion: When patents cite papers from predatory journals, flawed information may propagate, or potentially leading to wrongful patent rejections and wasted resources. This serves as a warning for the patent community to take action against potential predatory journals.

Purpose: This study aims to analyze the technological impact of papers that Advanced Pharmaceutical Bulletin has published through patent-to-paper citations analysis. Methods: Current research uses a Scientometric approach to analyze patent citations to published papers by the Advanced Pharmaceutical Bulletin. The Lens has been used for collecting patents that cited related papers. Some of the data analysis was conducted using the Lens analytical tool. Results: Results show that APB’s patent-to-paper citation rate is 32.39%, above the toxicology field average (6.15%) but below pharmacology (46.33%), indicating significant technological influence. APB contributes to both science and technology, attracting global inventors. Conclusion: The patent citations metric can be used to understand how a journal contributes to technological progress. However, these methods need to be standardized and promoted to understand a journal's real value in technology contribution.

Objectives: The challenges posed by questionable journals to academia are very real, and being able to detect hijacked journals would be valuable to the research community. Using an artificial intelligence (AI) chatbot may be a promising approach to early detection. The purpose of this research is to analyze and benchmark the performance of different AI chatbots in identifying hijacked medical journals. Methods: This study utilized a dataset comprising 21 previously identified hijacked journals and 10 newly detected hijacked journals, alongside their respective legitimate versions. ChatGPT, Gemini, Copilot, DeepSeek, Qwen, Perplexity, and Claude were selected for benchmarking. Three question types were developed to assess AI chatbots’ performance in providing information about hijacked journals, identifying hijacked websites, and verifying legitimate ones. Results: The results show that current AI chatbots can provide general information about hijacked journals, but cannot reliably identify either real or hijacked journal titles. While Copilot performed better than others, it was not error-free. Conclusions: Current AI chatbots are not yet reliable for detecting hijacked journals and may inadvertently promote them.

Purpose: Hijacked journals are fraudulent websites that mimic legitimate journals and, by charging authors, publish manuscripts. The current editorial endeavors to provide a close view of current literature. This editorial piece analyzes 10 years of research on hijacked journals and endeavors to shed light on future trends. Methods: Current research uses a bibliometric approach to analyze data and discuss results. The OpenAlex has been used for data collection. Some of the data analysis was conducted using OpenAlex. The other study was done using Bibliometrix, and the date is limited to publication between 2014 and 2024. Results: The findings provide a close view of the published literature in terms of access type, growth, topics, most frequent words, country contribution, top publishers, and alignment of literature with sustainable development goals. Conclusion: The gap in current literature is the limitation in easily usable methods to be accessible by all researchers for hijacked journal detection and data analysis. The use of artificial intelligence can be promising.

Purpose: Hijacked journals are journals managed by cybercriminals that mimic the original journal and publish manuscripts without peer review, charging a fee to the author. Although there is literature on hijacked journals, there is a gap in the content of published papers in the hijacked journals. This study aims to analyze the content of published papers in hijacked journals to assess their alignment with various Sustainable Development Goals (SDGs). Methods: About 21 medicine journals have been investigated and about 3300 published manuscripts in them analyzed in terms of SDGs using the text-based analyzing method. Results: The findings indicated that published manuscripts fit in the categories of SDG 01, SDG 03, SDG 11, and SDG 16 where SDG-03 is most dominant. Conclusion: The awareness about the problem of hijacked journals is critical, especially for developing countries, to eliminate the negative effects of these journals. It is the first research that discusses the negative effect of hijacked journals by considering SDGs and sheds light on the phenomenon.