Introduction: Understanding the information seeking behavior of individuals, especially students who are more likely to seek health information than other people, can be seen as an opportunity to provide resources to improve lifestyle or prevent possible health threatening behaviors among students. The main objective of this research is to determine the HISB among students of Tabriz University of Medical Sciences (TUOMS).Material and Methods: This descriptive cross-sectional study was carried out at TUOMS among students in 2017 through using simple random sampling method.Results:  The results showed that most of the students had experience of searching information about prevention of illness (47.8%) and general health knowledge (45.1%). The common outcomes of accessing health information by students were their decision to visit the physician (68.2%) and relieving their concern about their condition or illness (60.2%).Conclusion: The results of this study indicate that most students are searching for information on diet, physical activity and physical health.

Background Road traffic accidents have been one of the leading causes of death. Despite the increasing trend of road traffic apps, there is no comprehensive analysis of their features and no taxonomy for the apps based on traffic safety theories. This study aimed to explore the characteristics of available mobile apps on road traffic health/safety and classify them with emphasis on Haddon’s matrix. Methods The researchers examined the mobile applications related to road traffic health/safety using qualitative content analysis. Google Play was searched using a combination of the keywords. Haddon’s matrix was applied to analyze and classify those mobile apps residing in the categories of Road Traffic health & Safety, and Road Traffic Training. Results Overall, 913 mobile apps met the inclusion criteria and were included in the final analysis. Classification of the apps based on their features resulted in 4 categories and 21 subcategories. A total number of 657 mobile apps were classified based on Haddon’s matrix. About 45.67% of these apps were categorized as the road traffic health & safety group. Conclusions Haddon’s matrix appears to have the potential to reveal the strengths and weaknesses of existing mobile apps in the road traffic accident domain. Future development of mobile apps in this domain should take into account the existing gap.

Background and Objectives: Topic evolutions of scientific and academic disciplines can be clarified by drawing scientific maps and identifies emerging or developed topics of scientific disciplines, sub-topics and the relationship between different topics of a discipline. The purpose of this study is to draw a strategic diagram to analyze the developments of the last twenty years of library and information science field. Material and Methods: This was a Scientometrics study with co-occurrence analysis of words that was conducted on ten journals with the highest impact factor in the field of library and information science. Twenty years (1998-2017) publications were extracted from LISTA database and imported into SciMAT software. After preparing the data, all publications were divided into four time periods, strategic diagrams of each period were drawn and topic clusters were analyzed. Results: The largest clusters of the first two periods were "Information Retrieval" and "Bibliometrics", which in the next period "Citation-Analysis" appeared instead of "Information Retrieval" cluster, but nevertheless the largest node of this cluster was "Information Retrieval". These clusters were the most developed topics in the field of library and information science. Conclusion: Information retrieval and bibliometrics are at the forefront of library and information science. Sentiment analysis and information literacy with a cognitive approach are emerging topics in the field. Also, studies related to information production and related indicators have led to qualitative research.

Background: Road traffic accidents have been one of the main causes of death worldwide. However, most of the crashes are both predictable and preventable. With the widespread use, mobile phone is considered as a major road safety risk. However, varieties of apps have recently been developed for improving the road traffic health and safety. Despite an increasing trend of these apps, there is no comprehensive analysis of their features and no taxonomy or classification of them based on the traffic safety theories or frameworks. The aim of this study was to explore characteristics of available mobile apps on the road traffic health and safety and classify them based on the Haddon's Matrix. Methods: To conduct this research, a comprehensive and systematic review of the mobile applications developed for the road traffic health and safety was carried out through using the qualitative content analysis. Google Play was searched through using a combination of the keywords to retrieve the road traffic apps. In order to extract the app features, their description was examined, and their content was analyzed. Then they were classified in four main categories including Road Traffic Health & safety, Road Traffic Training, Road traffic Navigation, and Other Road Traffic apps. Finally, the Haddon's matrix was applied to analyze and classify those mobile apps residing in two main categories of the traffic health & safety, and the traffic training. Haddon's matrix is a relevant framework for structured analyses of traffic injury events. In the Haddon's matrix, the contributions of human, vehicle/equipment and environmental factors to the injuries in the three phases pre-crash, crash and post-crash has been presented. Results: In this study, 916 mobile apps met the inclusion criteria and were included in the final analysis.19 subcategories were identified for classifying the included apps based on their features and functionalities. In total, 620 of the mobile apps were grouped on the basis of Haddon's matrix. About 61.76% of these apps were categorized as the traffic health & safety group. Among the subcategories of the traffic health & safety group, the highest number of apps (194) was the real-time traffic alerting apps. Behavior based feed-backing subcategory was ranked the second among the traffic health and safety apps with 75 apps. When the researchers applied factors and phases of Haddon's framework for analyzing the apps, it was found that the Haddon's factors have been taken into account in the apps grouped into two main categories of the apps including traffic training and traffic health & safety applications. The highest percentage of Haddon's matrix factor considered for the intervention through the apps was related to the physical & social environment (23.69%) in the traffic training category. The features of 259 apps were classified in the Event/ Driving phase of Haddon's matrix. Most of the apps in this phase was related to the real-time traffic alerting subgroup. These apps performed in real