Showing 83 results for If
Zahra Ghasemi Aghbolaghi, Fereydoon Azadeh, Fatemeh Sheikhshoaei,
Volume 12, Issue 2 (7-2018)
Abstract
Background and Aim: In the field of scientometrics, little attention has been paid to stem cells. Therefore, the purpose of this study is to draw a Scientific Map of stem cells area (co-word analysis) based on the papers indexed in Web of Science database in selected countries during the years 2011-2013.
Materials and Methods: This study is based on descriptive method, and it was conducted by scientometrics and co-word analysis technique. In this study, 34,142 articles were analyzed from Web of Science database. The search system of Web of Science is a tool for collecting data. Data analysis was done using Web of Science analysis system and CiteSpace software.
Results: Most productions in stem cells are in English and belong to America. Stem cell, cell differentiation, in vitro, gene expression, mesenchymal stem cells, embryonic stem cells and transplantation are the most frequently used words and hot topics in this field.
Conclusion: The growing trend in this area has caused different subject fields to enter stem cells areas. Considering the high frequency of embryonic stem cells in the field, it can be said that different diseases such as spinal cord problems and heart diseases can be treated using these cells.
Mojtaba Ghiasi, Ahmad Sarlak, Hadi Ghafari,
Volume 12, Issue 4 (11-2018)
Abstract
Background and Aim: In the past studies, few researchers have addressed the simultaneous effects of human capital in health and education indicators on the economic growth of the country, and especially, provinces of the country. Therefore, the current study examined the simultaneous effects of human capital in health and education indicators on the economic growth in Iran s’ Provinces
Materials and Methods: This was an applied, analytical, descriptive study, and the research community consisted of the country's provinces. The data were collected through documentary-library research and from the databases of Iran Office for National Statistics, and Central Bank; afterwards, they were analyzed via unit-root and chow tests, using Generalized Method of Moments (GMM) and Eviews 9.
Results: The results showed that each percent of rise in family health expenditure, fertility rate, and life expectancy increased the provincial economic growth by 0.033%, 0.71%, and 1.83% respectively. In addition, 1% rise in mortality rate decreased the provincial economic growth by 0.43%. Educational expenditure influenced the provincial economic growth by a coefficient of 0.08, and credit capital asset acquisition, by a coefficient of 0.048.
Conclusion: Human capital is considered a long-term investment in health and education sectors which should be an important priority on the agenda of provincial policymakers.
Sokaineh Falsafin, Samaneh Khavidaki, Mahdi Mohammadi,
Volume 12, Issue 5 (1-2019)
Abstract
Background and Aim: The purpose of this study is the analysis of articles published about the evaluation of medical scientific products in Web of Science database.
Materials and Methods: This is a quantitative research that is based on literature review. The population of the study consists of 55 articles published in valid national scientific journals on the review of medical scientific products of Iran in Web of Science.
Results: The findings show that during 2006-2016, about 35 articles reviewed the scientific outputs of medical universities and the others examined the scientific outputs of a particular subject area, among which pharmaceutical and surgical fields had the most studies. Some 60.6% of the studies were published by specialists in the field of knowledge and information science, and 39.4% by medical specialists. Among universities, Iran University of Medical Sciences, and among individuals, Hafez Mohammad Hassanzadeh Asfijani were recognized as the most prolific. Most researches have been published using Scientometric Approach, and among scientific software, Pajek has been used more. Among the published articles, those with two and three authors were the most.
Conclusion: The articles have been quantitative, and mentioning various methods indicates a kind of confusion in the choice of vocabulary and terminology.
Reza Safdari, Somaye Mahdavi, Leila Shahmoradi, Khdijeh Adabi, Shahram Tahmasebian, Mahnaz Nazari,
Volume 12, Issue 5 (1-2019)
Abstract
Background and Aim: To provide effective care, health care providers need timely and appropriate information. Electronic records provide quick access and easy management of data. The aim of this study was to develop electronic health records for patients with hydatidiform mole and evaluation of completeness of medical records
Materials and Methods: This applied study was conducted in 2017. After verifying the minimum data set required for the system, data were extracted from patient records using a checklist and entered into SQL server. SQL server 2012 and Visual Studio 2013 to design electronic records and SPSS 20 for data analysis was used. Extent of data completion in patient records was also assesed.
Results: Data on the completion of paper records indicated that in 100% of cases, “address” item was filled in. The less completed data was related to carotene deficiency (%1.1). Our findings also showed that the eight most important items like age of first menstruation, first gestational age, interval between pregnancies, number of sexual partners, menstruation between pregnancies, contraceptive methods, social habits and radiotherapy, were not completed in all records.
Conclusion: Many of the important minimum data set for hydatidiform mole disease were either not completed or completed in limited numbers in paper records. By developing such health records, we can ensure better prevention and treatment, and regular follow-up for the patients and help them to save their time and costs.
Maryam Emami, Nosrat Riahinia, Faramarz Soheili,
Volume 12, Issue 6 (3-2019)
Abstract
Background and Aim: The purpose of this study was to analyze the co-occurrence of the terms of medical and laboratory equipment patents in the United States Patent and Trademark Office between 1984 and 2014.
Materials and Methods: This research was an applied study using scientometrics and co-word analyses. The statistical population of the present study included all patents of medical and laboratory equipment registered in the United States Patent and Trademark Office database between 1984 and 2014. As a result, a total of 13424 patents were retrieved.
Results: The results revealed that in terms of frequency, the keyword "Menstrual Fluid" and in terms of co-occurrence, two keywords (Menstrual Fluid and Magnetic Resonance Image Apparatus) were the most frequent ones in medical and laboratory equipment studies. The results of hierarchical clustering with "Ward's method" led to the formation of eight clusters in this area including the following: General Equipment, Rehabilitation Equipment, Dental Equipment, Therapeutic Equipment, Emergency Equipment, Laboratory Equipment, Diagnostic Equipment, and Medical Consumables.
Conclusion: The analysis of the co-occurrence of words revealed the scientific structure of medical and laboratory equipment well. Accordingly, the scientific issues were extracted and the relationship between them was discovered. The maps of co-word analysis showed several changes, sustainability of concepts, and terms related to this field of science.
Hamideh Sadat Atyabi, Sima Rasti, Maryam Niyyati, Zahra Eslamirad, Mahdi Delavari, Gholam Abbass Moosavi,
Volume 13, Issue 3 (9-2019)
Abstract
Background and Aim: Vermamoeba vermiformis is an opportunistic free living amoeba(FLA) that is ubiquitous in different environmental sources. This Amoeba can cause Amoebic Keratitis(AK) and Granulomatous Amoebic Encephlitis (GAE) in immunocompromised patients. This study was conducted to determine the rate of Vermamoeba vermiformis in stagnant water and soil in Arak.
Materials and Methods: In this Cross-Sectional study, stagnant water(60) and soil samples(36) were collected from Arak parks. The samples were filtered in 0.45µm nitrocellulose paper and cultured on to 1.5% NNA for the presence of free living amoeba(FLA). After DNA extraction, Vermamoeba vermiformis was identified by Polymerase Chain Reaction(PCR) using primers NA1 and NA2. Eight isolates of Vermamoeba vermiformis were sequenced blasted and after confirmation, recorded in the Gene Bank. The data were recorded in SPSS.16 and analyzed using X2 and Fischer Exact test.
Results: Out of 96 environmental sources, 29.2% were positive for free living amoeba. The rate of FLA pollution in stagnant water and soil were 28.3 and 30.6% respectively(P<0.001). The contamination rate of stagnant water and soil with Vermamoeba vermiformis were 10% and 16.7%, respectively(P<0.001).
Conclusion: The results of the present study revealed ,that stagnant water and soil resources were contaminated to FLA and Vermamoeba. Due to the Pathogenic ability of this amoeba and the possibility of endosymbian pathogens in it, health education is recommended for controlling and preventing the disease, especially in susceptible patients, including those who use contact lenses.
Azita Yazdani, Ali Asghar Safaei, Reza Safdari, Maryam Zahmatkeshan,
Volume 13, Issue 3 (9-2019)
Abstract
Background and Aim: Breast cancer is the most common type of cancer and the main cause of death from cancer in women worldwide. Technologies such as data mining, have enabled experts in this area to improve decision making in the early diagnosis of the disease. Therefore, the purpose of this research is to develop an automatic diagnostic model for breast cancer by employing data mining methods and selecting the model with the highest accuracy of diagnosis.
Materials and Methods: In this study, 654 available patient records of Motahari breast cancer Clinic in Shiraz" were used as the sample. The number of records was reduced to 621 after the pre-processing operation. These samples had 22 features that ultimately used ten were used as effective features in the design of the model. Three types of Decision tree, Naive Bayes and Artificial neural network were used for diagnosis of breast cancer and 10-fold cross-validation method for constructing and evaluating the model on the collected data set.
Results: The results of the three techniques mentioned all three models showed promising results in detecting breast cancer. Finally, the artificial neural network accounted for the highest accuracy of 94/49%(sensitivity 96/19%, specificity 86/36%) in the diagnosis of breast cancer.
Conclusion: Based on the results of the decision tree, the risk factors such as age, weight, Age of menstruation, menopause, OCP of records duration, and the age of the first pregnancy were among the factors affecting the incidence of breast cancer in women.
Mohsen Rezaei, Nazanin Zahra Jafari, Hossein Ghaffarian, Masoud Khosravi Farmad3, Iman Zabbah, Parvaneh Dehghan,
Volume 13, Issue 5 (1-2020)
Abstract
Background and Aim: Timely diagnosis and treatment of abnormal thyroid function can reduce the mortality associated with this disease. However, lack of timely diagnosis will have irreversible complications for the patient. Using data mining techniques, the aim of this study is to determine the status of the thyroid gland in terms of normality, hyperthyroidism or hypothyroidism.
Materials and Methods: Using supervised and unsupervised methods after data preprocessing, predictive modeling was performed to classify thyroid disease. This is an analytical study and its dataset contains 215 independent records based on 5 continuous features retrieved from the UCI machine learning data reference.
Results: In supervised method, multilayer perception(MLP), learning vector quantization(LVQ), and fuzzy neural network(FNN) were used; and in unsupervised method, fuzzy clustering was employed. Besides, these precision figures(0.055, 0.274, 0.012 and 1.031) were obtained by root mean square error(RMSE) method, respectively.
Conclusion: Reducing the diagnosis error of thyroid disease was one of the goals of researchers. Using data mining techniques can help reduce this error. In this study, thyroid disease was diagnosed by different pattern recognition methods. The results show that the fuzzy neural network(FNN) has the least error rate and the highest accuracy.
Nastaran Abbasi Hasanabadi, Farzad Firouzi Jahantigh, Payam Tabarsi,
Volume 13, Issue 6 (2-2020)
Abstract
Background and Aim: Despite the implementation of effective preventive and therapeutic programs, no significant success has been achieved in the reduction of tuberculosis. One of the reasons is the delay in diagnosis. Therefore, the creation of a diagnostic aid system can help to diagnose early Tuberculosis. The purpose of this research was to evaluate the role of the Naive Bayes algorithm as a tool for the diagnosis of pulmonary Tuberculosis.
Materials and Methods: In this practical study, the study population included Patients with TB symptoms, the study sample is recorded data of 582 individuals with primary Tuberculosis symptoms in Tehran's Masih Daneshvari Hospital. The data of samples were investigated in two classes of pulmonary Tuberculosis and non-Tuberculosis. A Naive Bayes algorithm for screening pulmonary Tuberculosis using primary symptoms of patients has been used in Python software version 3.7.
Results: Accuracy, sensitivity and specificity after the implementation of the Naive Bayes algorithm for diagnosis of pulmonary Tuberculosis were %95.89, %93.59 and %98.53, respectively, and the Area under curve was calculated %98.91.
Conclusion: The performance of a Naive Bayes model for diagnosis of pulmonary Tuberculosis is accurate. This system can be used to help the patient and manage illness in remote areas with limited access to laboratory resources and healthcare professional and cause to diagnose early Tuberculosis. It can also lead to timely and appropriate proceedings to control the transmission of TB to other people and to accelerate the recovery of the disease.
Mina Rezaei, Sedigheh Mehrabian, Kiumars Amini,
Volume 13, Issue 6 (2-2020)
Abstract
Background and Aim: Candida albicans has numerous virulence factors such as the agglutinin-like sequence(ALS) genes which code the large glycoprotein family that has a role in the adherence of Candida. The present study was to observe the synergistic effect of ketoconazole and probiotic composition of Bifidobacterium bifidum on expression of C. albicans als gene biofilm isolated from oral samples.
Materials and Methods: In this cross-sectional study, 12 clinical isolates of C. albicans were collected from oral periodontal infection in patients referred to dental clinic in Kerman. The MIC and FIC values for each treatment(keto and probiotic alone and keto-probiotic composition) were obtained using micro broth dilution method. Finally, a real-time PCR test was performed to evaluate the level of ASL gene expression in the strains and the results were analyzed using the 2-ΔΔct method.
Results: The results showed that the combination of ketoconazole and bifidobacterium bifidum had synergistic effects. The results of this study showed that the effect of Ketoconazole(keto), B.bifidum(probiotic) alone and the effects of ketoconazole+Bifidobacterium(keto+pro) were 1.47, 1.61 and 1.29 times, reduced the als gene, respectively.
Conclusion: The results of this study showed that synergistic effects between ketoconazole and probiotic B. bifidum have been shown to reduce als gene expression(biofilm production). Therefore, it is recommended to administer probiotic supplementation with ketoconazole in the treatment of candidal infections.
Reza Safdari, Seyed Sina Marashi Shooshtari, Marzieh Esmaeili, Fozieh Tahmasbi, Zohreh Javanmard,
Volume 13, Issue 6 (2-2020)
Abstract
Background and Aim: The importance of managing medicines and medical devices as vital resources in healthcare industry cannot be ignored. Therefore, the application of coding systems could be of great help in the control of the required processes. This study aims to develop a coding system for medicines and medical devices in Iran.
Materials & Methods: This descriptive study was planned to be carried out in four phases from September 2018 to August 2019. To identify the requirements of designing a coding system for the classification of medicines and medical devices, library resources were studied, and the existing coding systems in the area of medicines and medical devices came under scrutiny. Then, based on the expert opinion on the results, the initial model of the coding system was designed.
Results: Thirty-five coding systems were identified and investigated. To design the proposed system, two coding systems -- ATC/DDD and UMDNS -- were selected as a core for medicines and medical devices, respectively. Then, based on expert opinion, the axes for the place of consumption and the placement of products and also the application of Quick Response (QR) code for data encoding were added.
Conclusion: The design and development of a comprehensive coding system–which is in compliance with the international protocols and capable of including both medicines and medical devices simultaneously – could be very helpful. Besides, using the location axis in the structure of coding system can improve the management of these products.
Somayeh Ghavidel, Nosrat Riahinia, Samira Daniali,
Volume 13, Issue 6 (2-2020)
Abstract
Background & Aim: studying scientific outputs by using scientific indices is a useful tool for understanding scientific research. The purpose of this study is to visualize the international research outputs of the SMA subject Area.
Materials & Method: This study is an applied one with an analytical approach and using scientometric indices. The population present in this study includes 4217 WOS records all in the SMA area from 1946 until the end of 2018. The MeSH have been used to identify keywords and Ravar PreMap software for words’ homogenization, VOSviewer, HistCite, and Excel used also.
Conclusion: Ninety-one countries involved in scientific production outputs of this subject area, were among the most influential countries in scientific collaboration. The USA has most of its collaborations with other countries. Of the 946 essential journals identified, HUMAN MOLECULAR GENETICS SMA has got the highest number of citations. Articles in SMA Subject Area with the total number of 6097 keywords have got the 1st rank, of which the “Spinal Muscular Atrophy” has got the highest frequency and the core subject among the nine influential countries. The total number of articles in this area is 8505. Worthy of mentioning, Iran with 58% of the total scientific output ranked nine on the list.
Results: The upward trend of SMA scientific research trend indicates the increasing importance of this area in the world. Due to the the international growth of research in this area and the importance of the participation of international research, researchers in our country should pay more attention to scientific cooperation.
Abbas Doulani, Zahra Shabani, Roya Baradar,
Volume 14, Issue 1 (3-2020)
Abstract
Background and Aim: The purpose of the present study was to investigate the scientific outputs of the faculty members of the information science and science departments of Iranian state universities in the Science Research Network and its impact on their scientific outputs in databases and search engines.
Materials and Methods: This study was applied in terms of purpose, survey methodology and Altmetrics approach. The statistical population of the study consisted of 118 faculty members in the field of information science and social sciences active in Social- Scientific Network from 29 Governmental universities in the country. Pearson correlation coefficient, independent t-test, Kruskal-Wallis were used for data analysis.
Results: The findings showed that the authors of Isfahan, Tehran University of Medical Siences and Shahid Chamran of Ahvaz Universities are the most active members of the faculty in ResearchGate in terms of Altmetrics characteristics. In terms of RG score, faculty members with associate's degree perform better than the others. There is also a positive correlation between the Altmetrics indicators of ResearchGate network and the scientometric indicators of Scopus citation database and Google Scholar.
Conclusion: Since there was a positive correlation between Altmetrics indexes in ResearchGate with Scinientometrics indexes in Google Scholar and Scopus, so this leads to the visibility of their scientific work and their improvement of citation indexes in databases.
Roghaye Khasha, Mohammad Mahdi Sepehri, Nasrin Taherkhani,
Volume 14, Issue 3 (7-2020)
Abstract
Background and Aim: Asthma is a common and chronic disease of respiratory tracts. The best way to treat Asthma is to control it. Experts of this field suggest the continues monitoring on Asthma symptoms and adjustment of self-care plan with offering the preventive treatment program to have desired control over Asthma. Presenting these plans by the physician is set based on the control level in which the patient is. Therefore, successful recognition and classification of the disease control level can play an important role in presenting the treatment program to the patient and improves the self-care and strengthens the early interventions to alleviate the Asthma symptoms.
Materials and Methods: Based on this objective, we collected the data of 96 Asthma patients within a 9-month period from a specialized hospital for pulmonary diseases in Tehran. Then we classified the Asthma control level by fuzzy clustering and different types of data mining method within a multivariate dataset with the multi-class response variable.
Results: Our best model resulting from the balancing operations and feature selection on data have yielded the accuracy of 88%.
Conclusion: Our proposed model can be applied in electronic Asthma self-care systems to support the decision in real time and personalized warnings on the possible deterioration of Asthma control. Such tools can centralize the Asthma treatment from the current reactive care models into a preventive approach in which the physician’s decisions and therapeutic actions are resulting from the personal patterns of chronic Asthma control and prevention of acute Asthma.
Samira Daniali, Nosrat Riahi,
Volume 14, Issue 4 (10-2020)
Abstract
Background and Aim: The purpose of the present study is to map the coronavirus domain citation network to better understand this domain based on all other citation networks.
Materials and Methods: The present study is applied in terms of purpose, and is descriptive scientometrics in terms of type, which has been done with the all-citation method. In this study, all scientific publications on coronavirus(6980 documents) in the period 1985-2019 AD were studied on April 10, 2020 in the Web of Science database. For analysis and drawing all citation maps, VOSviewer and Excel software were used.
Results: In the field of coronavirus, 6815 documents, 10246 journals, and 40298 authors were identified. Ksiazek(2003) with the acute respiratory syndrome(SARS) topic received 875 citations and won the first place. The most cited documents in the field of coronavirus have 5 clusters; and the first cluster with 201 documents and with the topic of studying the structure of coronavirus is the largest one. Journal of Virology -- with the thematic range of genome structure and replication, virus identification, etc. -- ranked first with 35,383 citations. The most cited journals in the field of coronavirus are 5 thematic clusters, and the first one is the largest cluster with 121 journals and with the thematic domains of health policy, coronavirus, etc. Also, Woo won PCY first place with his specialization in identifying new microbes and emerging infectious diseases, and receiving 1491 citations. The most cited authors in the field of corona virus are in 6 thematic clusters; the first cluster with 195 authors in specialized field of virology and coronavirus is the largest cluster.
Conclusion: By identifying the highly cited scientific products in the field of coronavirus, efforts have been made to provide a comprehensive view of top documents, top journals, and top authors so that it can be a decision-making tool in the shortest possible time.
Mohammad Zarbi, Reza Safdari, Nahid Einollahi,
Volume 14, Issue 6 (1-2021)
Abstract
Background and Aim: Medical diagnostic laboratories are among the most important centers in the treatment cycle of patients. Today, the conscious choice of such laboratories is one of the challenges that patients face in the treatment process. This study was conducted with the aim of improving the knowledge of software users in the field of laboratory sciences and also facilitating the conscious and intelligent selection of the laboratory required by users.
Materials and Methods: This is a descriptive-developmental research with an applied approach. The steps consisted of library studies, questionnaire-based needs assessment, collection of knowledge and identity data, design through drawing UML diagrams, implementation using Java programming language, and software evaluation.
Results: A comprehensive system of laboratory information and experiments can be performed in all laboratories in Tehran, based on factors such as location access, types of laboratories and types of tests, a system was designed that allows users to access the most appropriate laboratory centers with high speed and less mobility, sufficient information, and in accordance with their needs. The evaluation was done using a researcher-made questionnaire whose validity and reliability were confirmed. The target population consisted of eleven specialists and forty ordinary users. According to the Likert criterion, the results obtained from the answers of all participants in the study to the questions of the questionnaire were higher than 4.05.
Conclusion: The software showed that the factors that had priority in the need assessment significantly increased user satisfaction and also provided ease of use of laboratory services in accordance with users' needs.
Elahe Behmani, Rastegar Hoseini, Ehsan Amiri,
Volume 14, Issue 6 (1-2021)
Abstract
Background and Aim: Multiple sclerosis (MS) is a progressive disease of the central nervous system, of which the symptoms and problems reduce the quality of life. Recent research has identified sport exercises as an important part of healthy lifestyle in reducing the symptoms of the disease and improving the quality of life; however, the most effective type of exercise is not yet clearly known. The aim of this study was to provide information about the beneficial effects of exercise in MS patients and guidelines for prescribing exercise programs for them.
Materials and Methods: This article is an overview of the ways different sport exercises affect MS. To access scientific articles, databases of PubMed, SID, Google Scholar, and Mag Iran, and the keywords including multiple sclerosis (MS), aerobic training, resistance training, and combined training were used.
Results: Recent reports show that different types of sport exercises lead to a significant increase in the improvement of MS symptoms, although there are many discrepancies between researchers in prescribing different exercise programs (various training protocol, duration, and intensity). However, according to the results of studies, regular moderate-intensity exercise training leads to the functional benefits and improvement and control of the disease process without exacerbation of inflammation through various physiological mechanisms. thus, contrary to popular belief, modulated exercise training can have beneficial effects on MS patient.
Conclusion: Based on the findings of the present study, regular exercises (aerobic, resistance and combination) with moderate intensity improve the symptoms of MS and increase the quality of life.
Dr. Afshin Hamdipour, Hashem Atapour, Fatemeh Ghasemzadeh,
Volume 15, Issue 1 (3-2021)
Abstract
Background and Aim: Road injuries are one of the most important public health problems and the leading cause of death and injury all over the world. The aim of this study is to investigate the trend of publication in the domain of road incidents and injuries and to visualize its scientific structure.
Materials and Methods: The present study is of scientometric type, its method is cross-sectional, and it was done during the period of 2005-2018. A total of 6563 records of road accidents and injuries were selected as the statistical population. The data collection tool was the Web of Science database and the HistCite software was used to visualize the scientific structure.
Results: The United States, Australia, and the United Kingdom ranked first to third with the production of 927, 700, and 651 documents, and the records of these three countries received 26373, 24447, and 23733 citations, respectively. Besides, the rank of road accidents and injuries for these countries were 89, 115, and 132, and the rate of casualties per 100,000 populations was equal to 10.6, 4.5, and 2.9. On the other hand, Libya, Thailand and Malawi (in South-Eastern Africa) are ranked first to third in the areas under study. The number of publications of these three countries was 5, 58 and 18, and their rank in document publications was 100, 34 and 65, respectively.
Conclusion: The relationship between rank in publications and rank in road accidents was negative and significant; countries with higher publications had a lower rank in road accidents and injuries. This indicates an inverse relationship between the number of publications and the number of road injuries; This means that as the number of publications in this field increases, the rank in injuries will improve. It seems that one of the factors that may be effective in reducing injuries and road accidents is the serious intervention of researchers to conduct research in this area in order to raising awareness and create a traffic culture for citizens.
Maryam Azimi, Davoud Haseli, Hossein Dehdarirad, Farzaneh Fazli, Nahid Einollahi,
Volume 15, Issue 4 (10-2021)
Abstract
Background and Aim: Transgenic species are the ones whose genomes are genetically modified. The transgenic field is one of the areas that has a high importance and position in the world. Therefore, the aim of the present research is to draw and analyze the co-authorship network of researchers in transgenic subject area.
Materials and Methods: The type of this research is descriptive and was carried out using scientometric techniques such as co-authorship network and social network analysis indices. In this study, 23,456 articles by transgenic researchers indexed in the Web of Science database during the period 2010-2019 were retrieved. VOSviewer and UCINET software were used to draw the co-authorship map and analyze the network indicators.
Results: The scientific cooperation network of transgenic researchers was studied and analyzed using macro and micro indicators of the social network. The status of macro indicators was not appropriate and the network was poorly cohesive. So that, the network density was 0.027, the clustering coefficient was 0.834, the diameter was 15 and the average distance was 4.155. In terms of micro-indicators, the status of researchers in the network was determined in such a way that David Ayares had the most cooperation with other members and also Nam-Hai Chua played the most important role in communicating with people from different clusters of the network, finally, Yan Zhang had the shortest distance with other members of the network.
Conclusion: Based on the findings, it can be concluded that the co-authorship network of transgenic researchers has low cohesion and information is transmitted among members at a low speed. With respect to this, status of different researchers in this study was determined, the results of this study can be used to guide future collaborations, and encourage universities and scientific institutes to develop their interactions with each other and further strengthen collaborations. It should also be noted that according to the findings of the study in this field, Iranian researchers were not identified as key individuals in this network, which requires research on the status and position of Iranian researchers in the field of transgenics.
Sirous Panahi, Seideh Fakharpour, Shahram Sedghi,
Volume 15, Issue 6 (3-2022)
Abstract
Background and Aim: The open peer review process, which is one of the peer-reviewed methods in journals, has been accepted in scientific forums. The aim of this study was to investigate the points of view of university faculty members about the open peer review process of journal articles.
Materials and Methods: The study used a descriptive survey. The sample size was calculated using the Cochran’s formula of 150 people out of a total of 246 faculty members of Alborz University of Medical Sciences. The research tool was a questionnaire designed based on the existing literature. Data were analyzed by SPSS software using descriptive statistics and paired t-test.
Results: The results showed that the participants’ views on “approaches and processes of open peer review” with 3.48 mean score and “benefits of open peer review” with mean score of 3.70 were relatively desirable. Among the open peer review styles, participants preferred the “open reporting” and “data peer review” styles, respectively. Participants’ views on the “advantages and disadvantages of open peer review” also indicated that participants agreed with most of the components presented in this area. There was also a statistically significant difference between the mean score of participants’ views on the traditional peer review process and open peer review (P<0.05).
Conclusion: Open peer review is relatively accepted among the faculty members of Alborz University of Medical Sciences. As the acceptance of this type of peer review increases among the scientific community, paying attention to the attitudes and views related to the open peer review process can improve the quality of articles and research published in scientific journals.
