تحلیل کتاب سنجی و متن کاوی طرح های تحقیقاتی مصوب کووید19 ایران

زمینه و اهداف در پاسخ به همه گیری کووید19، پژوهشگران در سراسر جهان اقدام به انجام پژوهش مختلفی در ابعاد مختلف این بیماری نمودند، در همین راستا این پژوهش به بررسی ساختار و موضوعات طرحهای تحقیقاتی مصوب کووید19 در ایران نموده است. مواد و روش ها این پژوهش با استفاده از روش های کتاب سنجی و متن کاوی و با رویکرد تحلیلی انجام شده است. جامعه آماری آن، طرح های تحقیقاتی مصوب کووید19 ایران در سال 2020 است. طرح های تحقیقاتی با جستجو در پایگاه اخلاق در پژوهش های زیست پزشکی ایران (ethics.research.ac.ir) استخراج شده اند. متن کاوی جهت شناسایی موضوعات براساس متن عنوان انگلیسی طرح های تحقیقاتی، و با به کارگیری الگوریتم مدل سازی موضوعی در زبان برنامه نویسی پایتون انجام شده است. یافته ها تعداد 6641 طرح تحقیقاتی مصوب کووید19 ایران استخراج شد که مربوط به 93 دانشگاه و مرکز تحقیقاتی است. دانشگاه علوم پزشکی تهران با 687 مورد، دانشگاه علوم پزشکی شهید بهشتی با تعداد 662 مورد و دانشگاه علوم پزشکی شیراز با 351 مورد بیش ترین طرح تحقیقاتی را دارا بودند. طرح های تحقیقاتی مصوب کووید19 ایران در دوازده موضوع: درمان، نیازهای مراقبتی کادر درمان، عوامل شدت بیماری، سلامت روانی و رفتار پیشگیری، تشخیصی و آزمایشگاهی، مطالعات ایمونولوژی، ویتامین ها و عناصر معدنی، بیماری های قلبی و عروقی، مطالعات واکسن، استرس شغلی و زندگی، تجارب پرستاران، بیماران و خانواده آنان و شیوع و علائم، دسته بندی شده است. نتیجه گیری نتایج این پژوهش به طور شفاف وضعیت ساختاری و موضوعی طرح های تحقیقاتی مصوب کووید19 پژوهشگران در داخل کشور در طول همه گیری کووید19 را نشان داده است.

Bibliometric and Text Mining Analysis on COVID19 Research Projects in Iran

Background and Objectives In response to the COVID19 epidemic, researchers around the world conducted various studies on different dimensions of the disease. Accordingly, this study aimed at investigating the structure and topics of COVID19 research projects approved in Iran.Material and Methods This applied research, adopting an analytical approach, was conducted using bibliometric and text mining methods. The statistical population was the COVID19 research projects approved in Iran in 2020. These research projects were extracted from the database of Iran national committee for ethics in biomedical research (ethics.research.ac.ir). To identify the topics of the research projects on COVID19 for text mining the English Language titles of the projects were used, topic modeling algorithms was done by the Python programming language. Results We selected a total of 6641 COVID19 research projects approved and conducted in 93 different Iranian universities and research centers. .of the main bulk of the research in this area had been conducted by Tehran University of Medical Sciences, Shahid Beheshti University of Medical Sciences, and Shiraz University of Medical Sciences including 687,662, and 351 cases respectively. COVID19 Research projects fell into 12 topical categories including Treatment, Care needs of medical staff, Factors affecting disease severity, Mental health and preventive, Diagnostic and laboratory measures, Immunology studies, Vitamins and minerals, Cardiovascular disease, Vaccine studies, Job and life stress, Experiences of nurses, patients and their families and Prevalence and symptoms. Conclusion The results of this study clearly show the structural and topic status of research COVID19 projects approved in Iran during the COVID19 epidemic. Extended Abstract Background and Objectives In response to the COVID19 epidemic, researchers around the world have conducted various studies on different dimensions of the disease. The researchers and various research teams have designed and conducted an extensive range of studies related to COVID19 including epidemiology, disease surveillance, consequences of the disease, and clinical trials. In Iran, different ongoing or completed research projects have also been approved to identify various aspects of the disease. Research project proposals are documents prepared by researchers to carry out research projects and are formulated according to particular demands for research in the society on various subjects such as disease burden, epidemics, threats and natural factors. Therefore, this study investigated the structure and topics of COVID19 research projects approved in Iran. Material and Methods This applied research, adopting an analytical approach, was conducted using bibliometric and text mining methods. The statistical population was the COVID19 research projects approved in Iran in 2020. These research projects were extracted from the database of Iran national committee for ethics in biomedical research (ethics.research.ac.ir). To identify the topics of the research projects on COVID19bytheir English titles, topic modeling algorithms were used in the Python programming language.This database, includes the bibliographic data of all research projects which have been approved by the medical sciences, received implementation ethics license. The projects related to medical sciences are registered in this database to receive an ethics code before implementation; thus, all Iranian projects within COVID19 topical area are registered in this database before being implemented, and their bibliographic data can be retrieved and accessed. After extracting data related to the approved COVID19 research projects from the mentioned database, a topical modeling algorithm named Latent Dirichlet Allocation (LDA) was employed to identify the topics of research projects by the English titles of COVID19 approved research projects in Iran, using text mining techniques. Text mining process employed in this study includes three stages; (1) data preprocessing (2) implementation of text mining and visualization techniques, and (3) the analysis of results and knowledge extraction. In the present investigation, Python programming language and its libraries related to text mining, such as Gensim, NLTK, and Spacy, were used to implement text mining algorithms. Results We selected a total of 6641 COVID19 research projects approved and conducted in 93 different Iranian universities and research centers. .of the main bulk of the research in this area had been conducted by Tehran University of Medical Sciences, Shahid Beheshti University of Medical Sciences, and Shiraz University of Medical Sciences including 687,662, and 351 cases respectively. The highest number of research projects approved in Iran included 1238, 796, 796 cases in April, May, and March, respectively. The results also revealed that the researchers to contribute most, as the main executor, to the approved research projects included Amir Vahedian Azimi from Baqiyatallah University of Medical Sciences, Jamshid Yazdani Charati from Mazandaran University of Medical Sciences, Ramin Sami from Isfahan University of Medical Sciences and Hossein Sheybani from Shahroud University of Medical Sciences each of whom had had 12 research projects approved. The results of text mining techniques also indicated that the terms COVID, patients, evaluation, hospital, and disease were among the most frequent words used in the titles of COVID19 research projects approved in Iran.The results obtained from topical modeling have identified 12 distinct themes for the research projects in this area, including treatment, care needs of medical staff, factors of disease severity, mental health and preventive behavior, diagnostic and laboratory studies, Immunology studies, vitamins and minerals, cardiovascular diseases, vaccine studies, job and life stress, experiences of nurses, patients and their families and prevalence and symptoms. Conclusion In the present study, bibliometric and text mining techniques were applied to identify the topical structure of COVID19 research projects approved in Iran. The results of this study clearly depicted the structural and topic status of research COVID19 projects approved in Iran during the COVID19 epidemic. The results seem to be useful for planners and policymakers in research and medical organizations to identify topics that are understudied by researchers and also to formulate new research priorities and requirements in this field. Practical Implications of Research This research has used bibliometric and text mining techniques to identify the thematic structure of research projects approved by Covid19 in Iran. The results of this study can be useful for planners and policy makers in research and medical organizations in order to identify topics that are less frequently considered by researchers and also to formulate new research priorities and requirements in this field. Ethical Considerations The present study was extracted from a research project approved by the Vice Chancellor for Research andTechnology of Gonabad University of Medical Sciences with the code A1012635. Conflict of Interest The authors state that there is no conflict of interest in the present study. Aknowledgment Researchers express their gratitude to the Vice Chancellor for Research, Technology and Infectious Diseases Research Center of Gonabad University of Medical Sciences for their financial and spiritual support of this research.