Zahra Kazempour; Hasan Ashrafi-Rizi
Zahra Kazempour; Hasan Ashrafi-Rizi
Hasan Ashrafi-Rizi; Zahra Kazempour; Leila Shahrzadi
Abstract
The outbreak of the coronavirus disease 2019 (COVID-19) has caused many challenges especially in production and dissemination of misinformation among people. Dissemination of incorrect statistics about patients, the dead as well as those who have recovered from this disease, are some examples of misinformation. ...
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The outbreak of the coronavirus disease 2019 (COVID-19) has caused many challenges especially in production and dissemination of misinformation among people. Dissemination of incorrect statistics about patients, the dead as well as those who have recovered from this disease, are some examples of misinformation. It seems that insufficient media literacy, complete trust or distrust of the media, the spread of rumors, fragmentation of information, social context, speed misinformation sharing, lack of ethics, different opinions between experts and authorities, the impact of time, and the neglect of the issue are all factors influencing the misinformation sharing. The causes of misinformation are different. Nevertheless, it seems that the main cause for all people is the lack or low level of media and information literacy among them. The realistic structure of dealing with crises must also be anticipated and institutionalized in society. On the other hand, the media can prevent dissemination of misinformation with transparency, speed and accuracy in disseminating information, and appropriate policymaking. These activities include quick determination of the spokesperson of the crisis headquarters during crises, the avoidance of other official’s opinions to providing information to the public, as well as the effective action of cyber police against the dissemination of misinformation in this condition noted. What has been mentioned as relevant factors in the present study is the view of the authors, and it is necessary to examine it by health researchers more.
Zahra Kazempour; Maryam Nakhoda; Mahdieh Mirzabeigi; Nader Naghshineh
Volume 14, Issue 5 , October 2017, , Pages 217-223
Abstract
Introduction: Due to various factors such as mental models, users apply different methods when searching information retrieval systems. Therefore, this study aimed to determine the relationship between the students of Isfahan University of Medical Sciences (IUMS) mental models and their web searching ...
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Introduction: Due to various factors such as mental models, users apply different methods when searching information retrieval systems. Therefore, this study aimed to determine the relationship between the students of Isfahan University of Medical Sciences (IUMS) mental models and their web searching behavior.Methods: A mixed approach was used in this applied research. In the identification stage (qualitative stage), the components of users’ mental models were determined using qualitative content analysis methods and semi-structured interviews, thinking aloud protocol and observation. Then, the types of mental models were identified. In quantitative stage, transaction log analysis and observation tool were used to investigate web search behavior. Then, the relationship between users' mental models and some variables of their web search behavior was investigated. The study population included all post-graduate students of IUMS among which 60 students were selected using purposeful sampling method. The descriptive and inferential statistics (Kolmogorov–Smirnov and Pearson correlation) was recruited using SPSS software.Results: In this research, 14 mental model components were identified. The majority of students (55%) had structural mental models. A significant association was observed between students’ mental models and web searching behavior in impact search session length, the complexity of query and natural language queries variables.Conclusion: Students’ mental models impact some web searching behavior variables, therefore, research in this field can lead to a better understanding of why users behave in certain ways. It can be a good method for improving information retrieval systems.
