Objective The significant increase in the number of COVID-19 publications, on the one hand, and t... more Objective The significant increase in the number of COVID-19 publications, on the one hand, and the strategic importance of this subject area for research and treatment systems in the health field, on the other hand, reveals the need for text-mining research more than ever. The main objective of the present paper is to discover country-based publications from international COVID-19 publications with text classification techniques. Methods The present paper is applied research that has been performed using text-mining techniques such as clustering and text classification. The statistical population is all COVID-19 publications from PubMed Central® (PMC), extracted from November 2019 to June 2021. Latent Dirichlet allocation (LDA) was used for clustering, and support vector machine (SVM), scikit-learn library, and Python programming language were used for text classification. Text classification was applied to discover the consistency of Iranian and international topics. Results The f...
PurposeThe present article's primary purpose is the topic modeling of the global coronavirus ... more PurposeThe present article's primary purpose is the topic modeling of the global coronavirus publications in the last 50 years.Design/methodology/approachThe present study is applied research that has been conducted using text mining. The statistical population is the coronavirus publications that have been collected from the Web of Science Core Collection (1970–2020). The main keywords were extracted from the Medical Subject Heading browser to design the search strategy. Latent Dirichlet allocation and Python programming language were applied to analyze the data and implement the text mining algorithms of topic modeling.FindingsThe findings indicated that the SARS, science, protein, MERS, veterinary, cell, human, RNA, medicine and virology are the most important keywords in the global coronavirus publications. Also, eight important topics were identified in the global coronavirus publications by implementing the topic modeling algorithm. The highest number of publications were respectively on the following topics: “structure and proteomics,” “Cell signaling and immune response,” “clinical presentation and detection,” “Gene sequence and genomics,” “Diagnosis tests,” “vaccine and immune response and outbreak,” “Epidemiology and Transmission” and “gastrointestinal tissue.”Originality/valueThe originality of this article can be considered in three ways. First, text mining and Latent Dirichlet allocation were applied to analyzing coronavirus literature for the first time. Second, coronavirus is mentioned as a hot topic of research. Finally, in addition to the retrospective approaches to 50 years of data collection and analysis, the results can be exploited with prospective approaches to strategic planning and macro-policymaking.
مجله مرکز مطالعات و توسعه آموزش علوم پزشکی یزد, Apr 23, 2019
Introduction: Electronic health literacy is the skill to seek, find, understand and evaluate heal... more Introduction: Electronic health literacy is the skill to seek, find, understand and evaluate health information from electronic information sources and utilize this information to determine or resolve specific health problems. This study investigates the level of electronic health literacy in students of Gonabad University of Medical Sciences. Methods: In this descriptive research, 430 students were selected randomly.115 students were from the Faculty of Public Health, 110 from the Faculty of Nursing, 93 from Faculty of Medicineand 112 from the Faculty of Paramedicine were selected and interviwed during six months from August 2018 to March 2019. The data collection tool was the Persian version of the EHEALS questionnaire. The obtained data were analyzed using SPSS-V. 20. Result: The findings indicated that the level of electronic literacy in 45.1% of students was moderate, in 31.6% was good and in 9.1% students was very good. 12.3% of the students had poor health literacy and 1.9% had a very poor level of electronic health literacy (P=0.270). Conclusion: To improve the level of electronic health literacy of students of Gonabad University of Medical Sciences we recommend informing them about having access to online, comprehensive and validated online health information, and training them on web health information
Health technology assessment in action, May 31, 2023
Context: Infodemic in the COVID-19 pandemic is referred to as too much information about this dis... more Context: Infodemic in the COVID-19 pandemic is referred to as too much information about this disease that spreads quickly. This information can cause various psychological consequences for people. This systematic review studied the effect of the infodemic on individuals’ mental health in the COVID-19 pandemic. Methods: The principles of PRISMA were used to conduct this systematic review. Data were selected using a search strategy in the WOS, PubMed, and Scopus databases on December 31, 2021. The inclusion criteria comprised English-language original articles relevant to the study’s purpose. We excluded all short articles, letters to the editor, conference abstracts, review articles, and any articles unavailable in their full texts. Results: Finally, 17 articles were selected. The results showed that the population of these articles was from China, Singapore, Palestine, Romania, Indonesia, Paraguay, Hong Kong, and Iran. These articles also included health professionals and medical staff (two studies), adults (three studies), citizens and the general public aged 16 or over (eight studies), students (one study), teachers (one study), and the elderly (two studies). The sample sizes varied from 126 to 5,203. Also, these articles examined mental health concerning anxiety (13 studies), depression (eight studies), stress (four studies), sleep disorders (two studies), emotions (two studies), panic, social isolation, and mental health in general. Conclusions: People more subjected to COVID-19-related information are more prone to psychological consequences and more exposed to anxiety, depression, and stress.
Objective The significant increase in the number of COVID-19 publications, on the one hand, and t... more Objective The significant increase in the number of COVID-19 publications, on the one hand, and the strategic importance of this subject area for research and treatment systems in the health field, on the other hand, reveals the need for text-mining research more than ever. The main objective of the present paper is to discover country-based publications from international COVID-19 publications with text classification techniques. Methods The present paper is applied research that has been performed using text-mining techniques such as clustering and text classification. The statistical population is all COVID-19 publications from PubMed Central® (PMC), extracted from November 2019 to June 2021. Latent Dirichlet allocation (LDA) was used for clustering, and support vector machine (SVM), scikit-learn library, and Python programming language were used for text classification. Text classification was applied to discover the consistency of Iranian and international topics. Results The f...
PurposeThe present article's primary purpose is the topic modeling of the global coronavirus ... more PurposeThe present article's primary purpose is the topic modeling of the global coronavirus publications in the last 50 years.Design/methodology/approachThe present study is applied research that has been conducted using text mining. The statistical population is the coronavirus publications that have been collected from the Web of Science Core Collection (1970–2020). The main keywords were extracted from the Medical Subject Heading browser to design the search strategy. Latent Dirichlet allocation and Python programming language were applied to analyze the data and implement the text mining algorithms of topic modeling.FindingsThe findings indicated that the SARS, science, protein, MERS, veterinary, cell, human, RNA, medicine and virology are the most important keywords in the global coronavirus publications. Also, eight important topics were identified in the global coronavirus publications by implementing the topic modeling algorithm. The highest number of publications were respectively on the following topics: “structure and proteomics,” “Cell signaling and immune response,” “clinical presentation and detection,” “Gene sequence and genomics,” “Diagnosis tests,” “vaccine and immune response and outbreak,” “Epidemiology and Transmission” and “gastrointestinal tissue.”Originality/valueThe originality of this article can be considered in three ways. First, text mining and Latent Dirichlet allocation were applied to analyzing coronavirus literature for the first time. Second, coronavirus is mentioned as a hot topic of research. Finally, in addition to the retrospective approaches to 50 years of data collection and analysis, the results can be exploited with prospective approaches to strategic planning and macro-policymaking.
مجله مرکز مطالعات و توسعه آموزش علوم پزشکی یزد, Apr 23, 2019
Introduction: Electronic health literacy is the skill to seek, find, understand and evaluate heal... more Introduction: Electronic health literacy is the skill to seek, find, understand and evaluate health information from electronic information sources and utilize this information to determine or resolve specific health problems. This study investigates the level of electronic health literacy in students of Gonabad University of Medical Sciences. Methods: In this descriptive research, 430 students were selected randomly.115 students were from the Faculty of Public Health, 110 from the Faculty of Nursing, 93 from Faculty of Medicineand 112 from the Faculty of Paramedicine were selected and interviwed during six months from August 2018 to March 2019. The data collection tool was the Persian version of the EHEALS questionnaire. The obtained data were analyzed using SPSS-V. 20. Result: The findings indicated that the level of electronic literacy in 45.1% of students was moderate, in 31.6% was good and in 9.1% students was very good. 12.3% of the students had poor health literacy and 1.9% had a very poor level of electronic health literacy (P=0.270). Conclusion: To improve the level of electronic health literacy of students of Gonabad University of Medical Sciences we recommend informing them about having access to online, comprehensive and validated online health information, and training them on web health information
Health technology assessment in action, May 31, 2023
Context: Infodemic in the COVID-19 pandemic is referred to as too much information about this dis... more Context: Infodemic in the COVID-19 pandemic is referred to as too much information about this disease that spreads quickly. This information can cause various psychological consequences for people. This systematic review studied the effect of the infodemic on individuals’ mental health in the COVID-19 pandemic. Methods: The principles of PRISMA were used to conduct this systematic review. Data were selected using a search strategy in the WOS, PubMed, and Scopus databases on December 31, 2021. The inclusion criteria comprised English-language original articles relevant to the study’s purpose. We excluded all short articles, letters to the editor, conference abstracts, review articles, and any articles unavailable in their full texts. Results: Finally, 17 articles were selected. The results showed that the population of these articles was from China, Singapore, Palestine, Romania, Indonesia, Paraguay, Hong Kong, and Iran. These articles also included health professionals and medical staff (two studies), adults (three studies), citizens and the general public aged 16 or over (eight studies), students (one study), teachers (one study), and the elderly (two studies). The sample sizes varied from 126 to 5,203. Also, these articles examined mental health concerning anxiety (13 studies), depression (eight studies), stress (four studies), sleep disorders (two studies), emotions (two studies), panic, social isolation, and mental health in general. Conclusions: People more subjected to COVID-19-related information are more prone to psychological consequences and more exposed to anxiety, depression, and stress.
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Papers by Meisam Dastani