Application of theory of planned behavior in identifying factors affecting online health information seeking intention and behavior of women

Purpose

Today, the Internet has become an attractive source for obtaining health information. Since women play an important role in maintaining the health of the family and community and since they are active seekers of health information through the Internet, it is essential to examine their online health information seeking behavior. Therefore, the main purpose of this article is to identify the factors affecting the online health information seeking intention and behavior of women.

Design/methodology/approach

The theoretical framework of this quantitative study was based on the theory of planned behavior. A total of five hypothesized relationships were formulated to develop a conceptual model. The study approach was quantitative. Using simple random sampling, 400 women referred to specialized and sub-specialized clinics of Hamadan University of Medical Sciences, Iran participated in the study and responded to the survey. Descriptive and inferential data analysis was performed using SPSS 21 and Smart PLS 3 software.

Findings

The results showed that the intention to find health information online is a function of psychological variables. These variables include attitude, subjective norms and perceived behavioral control. Findings showed that attitude is the most important factor affecting online health information seeking intention. It was also found that online health information seeking intention has a positive and significant effect on women's information seeking behavior.

Originality/value

This study is the first attempt to use an important and universally accepted theory to identify the factors affecting the online health information seeking behavior of women referring to specialized and sub-specialized clinics and provides important practical concepts for health officials and managers to improve and develop online health information seeking behavior.

COVID-19 Medical Research in Oman: A Bibliometric and Visualization Study

Objectives

To study the quantum and pattern of the COVID-19-related medical research publications that had contributions from researchers in Oman, using bibliometric analysis.

Methods

Data on the COVID-19-related medical research publications with contributions from authors in Oman were sourced from the Scopus database. The main search keywords were ‘COVID-19’ and ‘Oman’. The search included data from 1 December 2019 till 21 August 2021. A bibliometric method utilizing citation analysis and science mapping was applied to the selected data. VOSviewer software was used for constructing and visualizing various bibliometric networks.

Results

The search query returned 360 documents which included those by authors from Oman. After excluding 83 of these due to irrelevance, 277 documents were finally selected for analysis. Three macro research themes emerged: treatment of COVID-19 cases, epidemiology and impact of COVID-19, and etiology and clinical manifestations of COVID-19. A total of 4533 sources were cited in the selected 277 documents. Most articles were published in the International Journal of Infectious Diseases (IJID), followed by Oman Medical Journal, and Sultan Qaboos University Medical Journal. The most cited references included the Lancet, followed by the New England Journal of Medicine, and the Journal of the American Medical Association. The largest number of papers were authored by researchers from Sultan Qaboos University followed by the Oman Ministry of Health. Regarding the number of citations received per paper, the top rank went to the Ministry of Health, followed by Sultan Qaboos University Hospital and Khoula Hospital.

Conclusions

Oman has significantly contributed to the COVID-19-related medical knowledge despite the challenges of conducting research amidst the increased workload during the pandemic. Most publications in Oman were collaborative projects. Based on the evaluated literature, further research focusing on vaccines and therapeutics is warranted.

An Altmetrics Analysis of the Articles Published in the Medical Journal of the Islamic Republic of Iran (1987-2020)

Background: As a newly-emerged metric for evaluating scientific research, altmetrics captures the online activity regarding individual scientific items and is increasingly used in disseminating scientific information in a real-time span. This study aimed to conduct an altmetrics analysis of articles published in the Medical Journal of the Islamic Republic of Iran (MJIRI) during 1987-2020.

Methods: Using the archives of MJIRI's articles (during 1987-2020) and the four databases of Google Scholar, Scopus, Dimensions, and Altmetrics needed data on received citations as well as altmetric indicators and altmetric attention scores of these articles were extracted manually in December 2020. Data analysis was done in Excell and SPSS-25.

Results: Only 1274 MJIRI articles (about 51%) were present in the Altmetric Institute and had an altmetric attention score. Only 109 papers (8.5%) were shared at least once on online social media. Twitter was the most frequent social medium used for sharing the articles (n=91, 7.14%). These articles were twitted 171 times in total and the mean rate of twitting them was 1.88 per paper. Users from 21 countries in the world tweeted the articles. The top three twitting courtiers/regions were the United States (n=47), the United Kingdom (n=14) and India (n=3), respectively. Regarding twitters' membership status, the top three ranks were dedicated to the members of the public with 137 twits, practitioners (doctors and other healthcare professionals) with 18 twits and scientists with 16 twits. In Mendeley, the top three ranks were dedicated to master students (n=284), bachelor students (n=240) and Ph.D. students (n=155), respectively. The top three disciplines in this regard were medicine and dentistry (n=335), nursing and health profession (n=190), and biochemistry, genetics and molecular biology (n=68). Most of the highly-mentioned articles were review papers. The relationship between the altmetric attention score and citation performance of MJIR articles was not significant (p>0.05).

Conclusion:This study is one of the first studies to investigate the altmetrics indicators of articles published in an Iranian high-prestigious internationally-wide medical journal. Using social media tools can certainly promote medical scholars' scientific interactions and make added value for research published in medical journals. Editorial boards, including that of MJIRI can use altmetrics for detecting research trends and publishing approaches and consequently increased citation counts and research impact.

Global scientific collaboration: A social network analysis and data mining of the co-authorship networks

Co-authorship networks consist of nodes and numerous links indicating scientific collaboration of researchers. These networks could be studied through social networks analysis and data mining techniques. The focus of the article is twofold: the first objective is the analysis of the co-authorship networks of the top 60 countries that had the highest number of scientific publications in the world, and the second one is the discovery of collaboration patterns of highly cited papers of these countries. To do so, all scientific publications of the top 60 countries in all fields as well as their highly cited papers were included in the study period between 2011 and 2015. The research samples in the first part included 10,460,999 documents and in the second part encompassed 711,025 highly cited papers. Required data were extracted from web of science database. To analyse co-authorship networks, centrality indices and clustering coefficient were used. UCINET, Pajek, VOSviewer and BibExcel software were used to map co-authorship networks of the countries and to calculate indices. Finally, the discovery of collaboration patterns in highly cited papers is studied through association rules. The research data indicated that over 95% of documents has been produced by the top 60 countries. In addition, the USA, Germany, England, France and Spain launched the most co-authorship. Quantitatively, there have been the most powerful collaboration links between China and the USA, the USA and England, the USA and Germany, and the USA and Canada. The clustering data indicated that collaborations of the top countries of the world were in three main clusters. The Friedman test showed that there was a significant difference in the priorities of the countries for collaboration; and the USA, China, England, Germany, France, Japan and Italy are in the top priority for collaboration, respectively. The results of collaboration pattern in highly cited papers indicated that the USA participates in more than half of collaboration patterns for producing highly cited papers.

Information-seeking behavior in the digital age: use by faculty members of the internet, scientific databases and social networks

Purpose

The study aims to survey information-seeking behavior of the Iranian medical faculty members and to identify the reasons and obstacles of their usage via the internet, scientific databases and online social networks.

Design/methodology/approach

In this cross-sectional study, a structured questionnaire used to collect data. The research population includes faculty members of four faculties of Hamadan University of Medical Sciences in Iran, including health, nursing – midwifery, paramedicine and rehabilitation. SPSS software was used to analyze data in descriptive and analytical levels.

Findings

Low internet speed, network traffic and lack of time were the main barriers and difficulties. Gender was significantly related with familiarity with databases, problems and barriers to accessing information, barriers to using social network, as well as purpose and motivation of using social network. Search for educational and research resources and use of social network to increase their general information were the main goals of participants to using the internet and databases. A negative significant relationship was observed between usage of social network with age (r = −0.204, P = 0.047) and experience (r = −0.239, P = 0.019).

Originality/value

The usage of faculty members of various digital resources is growing ever more. This study examines the use of faculty members of the internet, scientific databases and online social networks simultaneously.

The relationship between social responsibility and public libraries accountability: The mediating role of professional ethics and conscientiousness

Public libraries are powerful social institutions whose services have a positive contribution to civil society. As one of the most important and most visited social institutions, such libraries are responsible to the community. Promoting social responsibility in public libraries requires addressing issues such as librarians’ accountability, professional ethics, and conscientiousness. Accordingly, this study strives to address this research gap by examining the relationship between organizational social responsibility and accountability perceived by staff in public libraries. Based on theoretical foundations, librarians’ professional ethics and conscientiousness were considered as mediating variables. Quantitative research method was used for this study and six hypothesized relationships were formulated to develop a conceptual model. Study data were collected through a questionnaire. Data obtained from 362 librarians of Iranian public libraries were analyzed running SPSS software and Smart PLS 3.0. The results revealed that perceived social responsibility of public libraries directly contributes to their perceived responsiveness. Furthermore, the implementation of social responsibility by public libraries reinforces the professional ethics and conscientiousness of librarians. As a result, the professional ethics and conscientiousness will lead to improving the accountability of public libraries. Accordingly, this study can help public library administrators, policymakers, and librarians to develop more comprehensive strategies for providing services to citizens by focusing on their social responsibilities, thereby establishing their place in society.

Iranian researchers' contributions to research on COVID-19: A bibliometric analysis and visualization

Background: COVID-19 pandemic crisis motivated researchers worldwide to deeply investigate it from different perspectives. As Iran is one of the highly-affected countries by Covid-19, Iranian researchers have focused on studying it. This study aimed at analyzing and visualizing Iranian researchers' papers on COVID-19 from a bibliometric perspective. Methods: By searching MeSH-selected keywords related to COVID-19 in Scopus, Iranian researchers' papers on COVID-19 were extracted in a CSV format and underwent bibliometric techniques, such as coauthorship analysis, citation, and co-citation analysis, keyword and term co-occurrence mapping and etc. in the Microsoft Excel and VOSviewer software package. Results: A total of 405 papers were authored by Iranian researchers on COVID-19 during the study period, with the average number of citations per paper of 2.60 and a mean h-index of 15. The majority of papers were original articles in English. Archives of Clinical Infectious Diseases and Archives of Iranian Medicine and Medical Hypotheses were highly ranked publishing journals, respectively. The most productive institute and author were Tehran University of Medical Sciences with 119 papers and Rezaei, N. with 12 papers. Iranian researchers collaborated with the researchers of 73 countries, with the USA ranking first in Covid-19 research, followed by Italy, Canada, and United Kingdom. In publishing papers on COVID-19, Iran ranked first among the Middle Eastern countries and thirteenth internationally. Conclusion: Iranian researchers were active in 5 main areas of COVID-19 research, including epidemiology, diagnosis, treatment, virology, and systematic review.

Developing a model to identify the antecedents and consequences of user satisfaction with digital libraries

Purpose

The primary objective of the present study was to design and develop a model to identify the antecedents and consequences of user satisfaction with digital libraries.

Design/methodology/approach

The theoretical framework of this study was based on information system success theory, technology acceptance model (TAM), media affinity theory, satisfaction-loyalty theory and engagement theory. In so doing, eight hypothesized relationships were formulated to develop the conceptual model. The study approach was quantitative. Using simple random sampling technique, a total of 409 Iranian students participated in the study and responded to the survey. Descriptive and inferential data analysis was also performed using SPSS and SmartPLS3 software.

Findings

The results showed that the generic usability of digital library and the quality of digital resources could be used as a functional theoretical framework to predict and understand the factors contributing to user satisfaction in the domain of digital library. Increasing user satisfaction with digital library may have implications including recommending the digital library to others, the digital library reusing as well as the digital library engaging and integrating with them. It should be noted that system quality, service quality, and information quality are important factors in the formation of perceived usefulness, perceived ease of use, and digital libraries' affinity.

Originality/value

This study is the first attempt to empirically evaluate the antecedents and consequences of the user satisfaction with digital library presenting a new model. The model presented in this study can be used in future research as well. Also, this study has eloquently expanded the theories of user satisfaction with digital libraries.

Predicting intention to share information on commercial websites based on personality traits

Purpose

The growing popularity of e-commerce, in recent years, has led to an increase in sharing information in cyberspace. Personality traits are one of the most effective personal factors in sharing information on business websites. This study aims to investigate the relationship between personality traits and intention to share information on commercial websites.

Design/methodology/approach

In this survey study, structural equation modeling was used. The statistical population of this study consisted of 385 Iranian students. Two questionnaires, i.e. personality traits and intention to share information, were used to collect the required data. The validity of the research instruments was estimated by calculating the average variance extracted. Furthermore, the reliability was assessed and confirmed by Cronbach’s alpha coefficient and composite reliability. Data analysis was performed with AMOS and partial least squares statistical software.

Findings

The results indicated that the components of personality traits including authoritarianism, self-esteem, locus of control and adaptation had a significant positive effect on intention to share information.

Originality/value

In this study, the authors designed a model to examine the effect of personality traits on intention to share information on commercial websites.

Do altmetrics correlate with citations? A study based on the 1,000 most-cited articles

Purpose

The purpose of this paper is to study the presence of highly cited papers of Nature in social media websites and tools. It also tries to examine the correlation between altmetric and bibliometric indicators.

Design/methodology/approach

This descriptive study was carried out using altmetric indicators. The research sample consisted of 1,000 most-cited articles in Nature. In February 2019, the bibliographic information of these articles was extracted from the Scopus database. Then, the titles of all articles were manually searched on Google, and by referring to the article in the journal website and altmetric institution, the data related to social media presence and altmetric score of articles were collected. The data were analyzed using Microsoft Excel and SPSS.

Findings

According to the results of the study, from 1,000 articles, 989 of them (98.9 per cent) were mentioned at least once in different social media websites and tools. The most used altmetric source in highly cited articles was Mendeley (98.9 per cent), followed by Citeulike (79.8 per cent) and Wikipedia (69.4 per cent). Most Tweets, blog posts, Facebook posts, news stories, readers in Mendeley, Citeulike and Connotea and Wikipedia citations belonged to the article titled “Mastering the game of Go with deep neural networks and tree search”. The highest altmetric score was 3,135 which belonged to this paper. Most tweeters and articles’ readers were from the USA. The membership type of the tweeters was public membership. In terms of fields of study, most readers were PhD students in Agricultural and Biological Sciences. Finally, the results of Spearman’s Correlation revealed positive significant statistical correlation between all altmetric indicators and received citations of highly cited articles (p-value = 0.0001).

Practical implications

The results of this study can help researchers, editors and editorial boards of journals better understand the importance and benefits of using social media and tools to publish articles.

Originality/value

Altmetrics is a relatively new field, and in particular, there are not many studies related to the presence of articles in various social media until now. Accordingly, in this study, a comprehensive altmetric analysis was carried out on 1000 most-cited articles of one of the world's most reliable journals.

Usage, captures, mentions, social media and citations of LIS highly cited papers: an altmetrics study

Purpose

The purpose of this paper is to investigate the usage, captures, mentions, social media and citations of highly cited papers of Library and information science (LIS).

Design/methodology/approach

This study is quantitative research that was conducted using scientometrics and altmetrics indicators. The research sample consists of LIS classic papers. The papers contain highly cited papers of LIS that are introduced by Google Scholar. The research data have been gathered from Google Scholar, Scopus and Plum Analytics Categories. The data analysis has been done by Excel and SPSS applications.

Findings

The data indicate that among the highly cited articles of LIS, the highest score regarding the usage, captures, mentions and social media and the most abundance of citations belong to “Citation advantage of open access articles” and “Usage patterns of collaborative tagging systems.” Based on the results of Spearman statistical tests, there is a positive significant correlation between Google Scholar Citations and all studied indicators. However, only the correlation between Google Scholar Citations with capture metrics (p-value = 0.047) and citation metrics (p-value = 0.0001) was statistically significant.

Originality/value

Altmetrics indicators can be used as complement traditional indicators of Scientometrics to study the impact of papers. Therefore, the Altmetrics knowledge of LIS researchers and experts and practicing new studies in this field will be very important.