Journal of Medical Library and Information Science

Introduction: Disaster management refers to preparedness, response, and recovery from disasters, encompassing a broad spectrum of activities, including risk assessment, emergency planning, communication, and resource management. Artificial intelligence (AI) can potentially enhance our disaster management capabilities, ranging from prediction and detection to impact assessment and recovery monitoring. This study aims to provide an overview of the role and application of AI in disaster management in Iran.

Methods: This study adopts a narrative review approach. Full-text articles and reports were retrieved from databases SID and Magiran, ScienceDirect, PubMed, and Google Scholar, using the keywords “Iran,” “Disaster Management,” and “Artificial Intelligence.” Selection criteria focused on relevance to the study objective and the timeframe of 2020-2023. Then, the articles underwent a review process that evaluated their title, abstract, introduction, methodology, results, discussion, and references.

Results: Out of the 314 retrieved studies, seven articles met the inclusion criteria for the study. The most commonly utilized algorithms were artificial neural networks (ANN) and random forests (RF), and the performance of the AI-based algorithms was reported to be satisfactory.

Conclusion: The occurrence of disasters is inevitable, and it may be impossible to prevent events such as earthquakes, floods, and other disasters. However, studies have shown that AI can be utilized for more efficient disaster management, reducing and minimizing damages and enabling more effective responses to such incidents.

Introduction: Scientific collaboration at the national and international levels influences papers' quality and quantity improvement. Accordingly, this research was designed to analyze the model of scientific collaboration among researchers in medical ethics.

Methods: The research was scientometric and conducted using scientific analysis and drawing indicators. The study population included 14333 documents indexed in the Web of Science (WoS) from 1975 to 2020. Therefore, BibExcel, SPSS, and VOSviewer software were used to analyze and draw the data. In addition, Pearson’s correlation coefficient statistical test was utilized to answer the research hypotheses.

Results: The coefficient of collaboration (CC), degree of collaboration (DC), and collaboration index (CI) were obtained to be 0.40, 0.59, and 2.32, respectively. In the last decade, authors have indicated more inclination toward the multiple authorship model; however, most of this type of collaboration is domestic (national), and only 17.8% is international. The highest co-authorship and international collaboration rates belong to the United States (US) among the 152 countries. Furthermore, Pearson’s correlation test between the number of papers and international collaboration at the significance level of (0.000) suggests a positive direct relationship (p-value< 0.05).

Conclusion: The dominant authorship pattern has been single authorship during the studied period. The tendency of researchers concerning co-authorship occurs within an average and growing level and is not in a favorable situation in terms of international collaboration.

Introduction: Health information is a basis for connecting societies with health and treatment systems. People with a correct understanding of diseases can manage their health conditions. The study aims to investigate the health information-seeking behavior of nursing and pre-hospital emergency students in Abhar, Iran.

Methods: The present research used a survey descriptive method and a quantitative approach. Of all Faculty of Nursing and Pre-Hospital Emergencies students in Abhar, Iran, 450 were chosen. Using Morgan’s table, 208 people were chosen as the statistical population. A questionnaire was distributed to all students to collect data, and finally, 210 questionnaires were completed and collected. The collected information was analyzed using SPSS version 2021 and Excel 2016 software.

Results: The findings showed that 95.2% of the students have a bachelor’s degree. The smartphone is primarily used to search and access health information. Among printed sources, medical books were used more than other sources. Among the most important information channels for obtaining health information from the student’s point of view are TV/radio, the internet, social networks, physicians, colleagues, and universities or hospitals. Influential factors in evaluating health information acquisition channels include fresh and innovative content, up-to-date information and etc.

Conclusion: Students use print sources and health information acquisition channels (digital media, individuals, and organizations) to meet their needs to provide health information, and in this way, they face obstacles and problems. Therefore, paying attention to the quality, validation, trust, and up-to-dateness of information can help students find the right way to seek information.