Journal of Health Information Management
Year:2023 | Volume:20 | Issue:1 (89)|Papers Count:8

In the health communication, information can be considered as an independent unit that has the possibility of getting sick and out of its normal health. From this view, health misinformation can be considered as a type of information disorders (1). Misinformation has always been an important part of human communication,however, today, the spread of general misinformation and especially health misinformation by the traditional and modern media has caused serious concern among citizens, scientists, and government officials. Some concerns are based on the assumption that misinformation has the potential to influence the way individuals think, feel and behave about issues contaminated by misinformation, and endanger public health (2). Swire-Thompson and Lazer define the misinformation as "information contrary to the epistemological consensus of the scientific community about a phenomenon" (3). Therefore, health misinformation is a special type of misinformation that contains one or more health-related claims inconsistent with the scientific consensus of health professionals (4). A suitable example is the use of the Internet and social media to release the misinformation about the vaccine and the spread of anti-vaccine emotions in recent years, which has brought harm to the individual and society (5). Considering the importance of understanding health misinformation prevent it, it seems necessary to identify the types of health misinformation and examples of each type and the extent of possible damage so that appropriate solutions can be found to deal with it. Given according to the continuous progresses and changes of science, the information published in the health sciences is in a spectrum in terms of accuracy and accuracy, it is possible to divide the types of common health misinformation into three categories based on the level of its accuracy and precision: 1) Misinformation type 1 (Dissemination of totally incorrect health information): In this case, the sender (individual or media) disseminates health information that is completely medically incorrect and causes an information disorder that can harm the health of the individual and society. 2) Misinformation Type 2 (Propagation of health pseudoscience): In this case, the sender (individual or media) presents irrelevant health information and a person may express correct presuppositions or correct propositions incorrectly or draw incorrect conclusions from them. This case will cause an information disorder and possible damage to the health of the individual and the society. 3) Misinformation Type 3 (Conditional recommendations): In this case, the sender (individual or media) advises and offers health information, which after being reviewed and evaluated by clinical experts or health scientists, their validity and strength are still unknown and is not but it is correctly used in special conditions or situations of each patient. This case, like the previous two cases, has caused information disorders, and although the purpose of these advices is not to harm others, it can unintentionally cause damage to the health of the individual and the society through circulating the relatively correct but marginal health information (6). Figure1 shows this categorizing with an example. . .

Introduction: The purpose of this study is to compile the key components and indicators of the excellence model of information technology management in Isfahan University of Medical Sciences. Methods: This practical and purposeful basic research was carried out using content analysis method and fuzzy Delphi technique. The population included senior and middle managers of information technology in Isfahan University of Medical Sciences and books and articles related to information technology management. The results were presented in the form of a Delphi panel in the form of a questionnaire to the experts and professors, and with the two-stage implementation of the Delphi panel, the agreement coefficient of the experts regarding the mentioned components was obtained through the calculation of CVR and the necessary convergence was achieved. Besides, the members' credibility criterion was used in Newman's validation method. Results: Fourteen dimensions including 142 components were identified as core values, components of the excellence model of information technology management in the University of Medical Sciences. These components were presented to IT experts in the university in the form of a questionnaire, and their agreement coefficient was calculated by performing two steps of the fuzzy Delphi technique. Ultimately, two components were removed and 140 components were confirmed with an agreement coefficient of over 0. 4. Conclusion: It seems that the indicators selected in this research can provide the basis for the development and realization of information technology excellence in organizations. The selected indicators enable them to extract improvement plans and measures along with the comprehensive pathology of their processes and their position in the excellence process to be evaluated in the field of information technology.

Introduction: Blockchain as a distributed, secure, transparent and reliable database shared by a community can also affect sustainable supply chain networks. This research was conducted with the aim of determining the causal relationship of the factors related to the use of blockchain in the sustainable supply chain of the health sector. Methods: The current research is descriptive and was conducted with the participation of 5 experts from Ali Ibn Abi Talib Hospital in Rafsanjan. The experts were selected as a snowball. In order to collect and analyze data, structured interview and fuzzy cognitive mapping method were used. Results: Based on the research literature and expert opinions, fifteen variables related to the use of blockchain in the sustainable health supply chain were identified. The results showed that the data encryption variable was the most effective with a factor of 2. 03 and the scalability variable was the most effective with a factor of 2. 20. Among the 15 factors, the variable of standardization and development of software platforms has the highest degree of centrality with a coefficient of 2. 97. Conclusion: By identifying the effective and efficient factors in the use of blockchain, the officials of Ali Ibn Abitaleb (AS) hospital can use the data encryption that provides a secure environment by implementing blockchain technology, and also an intelligent system for convenience. To make patients communicate with the hospital.

Introduction: With the significant expansion of research, we are witnessing the discrediting of some scientific outputs in the field of medicine. This study endeavored to investigate the dimensions and patterns of cooperation of internationally discredited works in the field of medicine in the Scopus database. Methods: This study is applied in terms of purpose and in terms of conducting research and data analysis, it is quantitative and has been done using bibliometric analysis method and scientometric approach and illustration techniques to draw scientific collaborations. The population is all the discredited medical works available from 2016 to the end of 2020 in the Scopus database which has been done using the network analysis method. Results: The findings showed that during the period, 480 works published in Scopus database were discredited. The Unites States, England, India, and China have the highest index of centrality, intimacy, and crosscontextuality. These countries play an important role in connecting nodes and transmitting information over the network. Conclusion: Discredited articles in the United States and England have high centrality indices, which indicates the greater influence and power of these countries, which, in turn, have a greater influence on other countries in the scientific network.

Introduction: This research investigates the articles' structure and thematic relationships in environmental health. Studying scientific outputs using scientometric indicators is an effective tool for understanding scientific research. Methods: The present research was conducted with a scientometric approach to content analysis of texts using the co-occurrence method of words and social network analysis. The statistical population includes 7438 articles indexed in the Web of Science Core Collection (WOSCC) in the field of environmental health in the period 2011-2020. Data analysis was done using cluster analysis method and strategic diagram. Results: The findings showed that in terms of the frequency of public health keywords, air pollution and climate change were the most frequent in environmental health researches. The findings related to hierarchical clustering led to the formation of 10 clusters in this area, and the clusters of "heavy metals" and "air pollution" were identified as clusters with high centrality and density. Conclusion: According to the abundance of keywords and clusters obtained from the strategic diagram, it was found that the topics of heavy metals and air pollution are emerging fields in this field. Some important issues related to environmental health, such as environmental health management, water quality management, etc., have received less attention.

Introduction: To use the "Resistive Economy" concept effectively, experts believe that we need a shared understanding of its meaning, instances, and requirements. This study endeavors to clarify the concept, provide examples, and identify healthcare sector requirements based on expert opinions. Methods: For this qualitative study, we conducted 4 face-to-face interviews with economists and health economists who were selected through purposive sampling. We transcribed and analyzed the interviews through conventional content analysis. Results: We identified two concepts: "economic resilience" and "comprehensive concept of resistive economy". Then, we determined their instances and requirements. "Anti-shock economy", "oil-free economy", "economic productivity", and "transformation" were identified as instances of "economic resilience". "Justice-oriented", "knowledge-based", "endogenous", "extraversion", "democratized", "jihadi culture", "Islamization of the economy", and "resistive economy" as a political economy were identified as instances of the "comprehensive concept of resistive economy". We also explained the instances and requirements of resistive economy in the healthcare sector. Conclusion: There are various interpretations of resistive economy. Based on expert opinions, resiliency is an important specification of that economy, but other specifications should also be considered to address the comprehensiveness of the concept. To implement and operationalize the resistive economy in various sectors including the health sector, the first step is to reach a common understanding of resistive economy amongst the experts.

Introduction: Due to the encounter of the research community with information and the discussion of distinguishing true from false information that individuals face during a crisis, this study endeavors to determine the relationship between health literacy and e-health literacy with the acceptance of conspiracy beliefs and anxiety. The future in the face of covid-19 among graduate students of Shahid Chamran University of Ahvaz has been conducted. Methods: The population for this correlational survey study of the research was the post-graduate students of Shahid Chamran University of Ahvaz in the academic year 2018-2019, which included 362 individuals in the research sample. The instrumentation included a 32-item questionnaire adopted from Duplaga & Grysztar (2021). The data were analyzed using the Pearson correlation coefficient test. Results: Correlation analysis test was used to measure the relationship between the variables. It was found that health literacy and e-health literacy had an inverse relationship with acceptance of conspiracy belief and future anxiety, and increasing health literacy and e-health literacy decreased acceptance of conspiracy belief and anxiety. Conclusion: According to the findings, students with higher health literacy act more intelligently against false and fake information and future anxiety caused by it, as well as conspiracy theories related to the information. Therefore, increasing health literacy and e-health literacy of students can help to fight against the negative consequences and bad effects of health crisis and information diseases.

Introduction: The fourth industrial revolution or the 0. 4 industry will change our perception of the world around us by benefiting from technologies such as the Internet of Things, the Internet, cloud computing and artificial intelligence. This industry has wide applications in the health sector. As a result, this research was conducted with the aim of identifying and modeling the resulting drivers of the 0. 4 industry in Kashan health and treatment. Methods: This research is a mixed type of research and was done in 2 stages. In the first stage, the outcome drivers are identified and in the second stage, a model for them is presented. The sampling method is purposeful in both stages. The number of participants in stages 1 and 2 is 14 and 10 people, respectively, the data collection tool is semi-structured interviews and a researcher-made questionnaire, and the method of data analysis is thematic analysis and fuzzy total interpretive structural modeling. Results: To identify the outcome drivers of using industry 4. 0 in the health sector, 55 drivers were identified through interviews, which were categorized into 12 categories. Based on the drivers model, it was determined that improving medical science, product and service design, access, and data protection are the most important drivers that can be considered in the country's macro policies, health sector policies, and organizational strategies. Conclusion: To stimulate the health sector to go towards healthcare 0. 4, the three main sides (government, society, and health sector managers) must gain the necessary knowledge in this regard. According to the findings of the research, it is necessary to hold recent developments in the field of medical science, which have been caused by industry 4. 0, in the form of educational workshops for health department managers and government policymakers.