Original Article
Health Information management
Mohammad Amini; Mansour Esmaeilzadeh; Fatemeh Arabpour
Abstract
Introduction: Telehealth can be a valuable tool for improving access to healthcare, especially during a pandemic. However, certain barriers have limited its widespread adoption. Therefore, this study aims to prioritize the barriers to telehealth services and identify the relationships between them.Methods: ...
Read More
Introduction: Telehealth can be a valuable tool for improving access to healthcare, especially during a pandemic. However, certain barriers have limited its widespread adoption. Therefore, this study aims to prioritize the barriers to telehealth services and identify the relationships between them.Methods: This study is applied in terms of its objective and employs a qualitative-analytical approach for data analysis. First, key barriers were identified through a systematic review of scientific resources and expert opinions. The validity of the barriers was assessed using the Content Validity Ratio (CVR). After validating the barriers, causal relationships between them were extracted and prioritized using the Interpretive Structural Modeling (ISM) method. The research population included university professors, physicians, hospital managers, and health and medical experts, of whom 22 participants were selected through purposive (snowball) sampling. Data collection was conducted using a questionnaire.Results: A review of the literature identified 16 initial barriers related to telehealth. Experts validated and finalized 14 of these barriers. The finalized barriers were classified into a six-level model. The findings indicate that the lack of an appropriate institutional framework to support telehealth and insufficient financial resources are the most fundamental and influential barriers. Addressing these barriers could help mitigate other challenges, such as technological issues and resistance to change. Additionally, barriers such as inconsistencies in insurance reimbursement and increased workload were identified as dependent barriers with less impact.Conclusion: Based on the study results, it is recommended that policymakers, including the Ministry of Health and Medical Education, health insurance organizations, and other relevant institutions, take steps to establish robust legal and institutional frameworks and ensure sufficient financial resources. Furthermore, providing specialized training, developing operational guidelines, and simplifying regulations are key strategies for enhancing the acceptance and efficiency of telehealth services.
Original Article
Health Information management
mohammadreza pourkarim; Shahnaz Nayebzadeh; Seyed Moayed Alavian; Seyed Hassan Hataminasab
Abstract
The creation and introduction of approved influencers in various specialized areas of health requires the knowledge of influential factors as well as indicators that require analysis in each specialty and condition. The primary objective of this research is to identify and evaluate the indicators and ...
Read More
The creation and introduction of approved influencers in various specialized areas of health requires the knowledge of influential factors as well as indicators that require analysis in each specialty and condition. The primary objective of this research is to identify and evaluate the indicators and factors of influencer marketing in the field of health in Iran. In order to achieve the objectives of the research, the research consists of two stages. In the first stage, influencer marketing in the field of health has been identified using the content analysis method. In the second stage, exploratory and confirmatory factor analysis method has been used to group indicators and identify and evaluate influencer marketing factors in the field of health.Methods: In terms of the objectives, this research is applied, while in terms of the research approach, it follows an inductive approach and in terms of its nature, it is exploratory-analytical research.Results: In the first stage, using content analysis method running NVIVO software and reviewing the related articles, influencer marketing indicators in the field of health were addressed and 26 indicators were eventually identified. In the second stage, using exploratory and confirmatory factor analysis and the statistical population of 1126 students and through the questionnaire running AMOS software, 5 final factors including Personality and Charisma Traits, active and skillful characteristics, behavioral characteristics, and indicators of infrastructural measures, and Performance and Engagement Metrics were identified and evaluated.Conclusion: In the vision of today's media activities, audiences are increasingly turning to online communities for media consumption and information exchange about specific interests such as health-related topics.
Original Article
Health Information management
Sara Dakhesh; Shahnaz Khademizadeh; Zeinab Jozi
Abstract
Introduction: Today, the significant application of artificial intelligence (AI) technology in healthcare and medical sciences has brought numerous ethical challenges to the health system. Therefore, the present study analyzes the bibliometrics of all publications related to medical ethics in the application ...
Read More
Introduction: Today, the significant application of artificial intelligence (AI) technology in healthcare and medical sciences has brought numerous ethical challenges to the health system. Therefore, the present study analyzes the bibliometrics of all publications related to medical ethics in the application of AI tools.Methods: This study is descriptive-analytical and was conducted using a scientometrics approach. The research population includes all publications related to medical ethics in AI studies indexed in the Web of Science core collection.Results: By implementing a search strategy, 354 scientific works related to the concept of medical ethics in the application of artificial intelligence tools were identified. Most of these documents were research articles (70.05%). From 2019 to the search date (December 4, 2024), the years 2024, 2023, and 2021 saw significant growth in scientific publications on artificial intelligence related to medical ethics. It was also reported that the United States, Germany, and the United Kingdom, with 89, 41, and 36 works respectively, contributed the most to the publication of studies in this field. Additionally, citation analysis of these works revealed that research from these three countries—the United States (with 1,312 received citations), Germany (with 927 received citations), and the United Kingdom (with 893 received citations)—received the highest number of citations in this area of study.Conclusion: It can be inferred that research related to the implementation of artificial intelligence technology with a medical-ethical perspective is growing. Therefore, it is necessary that, through purposeful and principled development of these publications, broader awareness and dissemination of medical ethics standards—especially in the age of artificial intelligence—be promoted.
Original Article
Health Information management
Roghaye Khasha; Nasrin Taherkhani
Abstract
Introduction: Asthma is a health hazard for all societies. Scientific research on asthma can make a significant contribution to offering new therapeutic approaches to improve patients’ conditions. The aim of this study is to examine the structure of Iranian researchers’ co-authorship network ...
Read More
Introduction: Asthma is a health hazard for all societies. Scientific research on asthma can make a significant contribution to offering new therapeutic approaches to improve patients’ conditions. The aim of this study is to examine the structure of Iranian researchers’ co-authorship network in the field of asthma.Methods: The study was conducted in three stages. In the first stage, PubMed-indexed articles published by Iranian researchers in the field of asthma between 2015 and 2025 were collected. In the second stage, the co-authorship network was drawn based on the extracted information. In the third stage, both macro- and micro-level indicators were used to analyze the authors’ co-authorship networks. NetworkX and Gephi were utilized for analysis.Results: The results indicate a density of 0.01002, a clustering coefficient of 0.916, a modularity of 0.735, and a network diameter of 14. Based on micro-level indicators, Masjedi had the highest degree centrality and Katz centrality. Masjedi and Mahdaviani had the highest betweenness centrality, Ansarian had the highest eigenvector centrality.Conclusion: The low density, high clustering coefficient, and high modularity suggest that within this dispersed network, researchers in small, interconnected groups collaborate with one another.
بیان دیدگاه
Health Information management
Mohammadhiwa Abdekhoda
Abstract
With the growing emphasis on data-driven research, especially i n fields like medical sciences, Research Data Management (RDM) has become an essential part of the academic research cycle. RDM encompasses the processes of collecting, storing, organizing, documenting, sharing, and preserving research data ...
Read More
With the growing emphasis on data-driven research, especially i n fields like medical sciences, Research Data Management (RDM) has become an essential part of the academic research cycle. RDM encompasses the processes of collecting, storing, organizing, documenting, sharing, and preserving research data to ensure its long-term accessibility and reusability. Medical librarians, as information organization specialists, are emerging as key players in this field by leveraging their professional expertise and technological competencies. They support researchers in developing Data Management Plans (DMPs), offer guidance on metadata standards such as FAIR, advise on data storage formats and ethical practices, and participate in managing data repositories. Furthermore, medical librarians play an active role in educating researchers about open data principles, Creative Commons licenses, and ethical and legal considerations, especially regarding sensitive health data and regulations like HIPAA and GDPR. Despite facing challenges such as organizational constraints, lack of policies, limited resources, and insufficient training, medical librarians can overcome these obstacles by acquiring new skills in data analysis, programming languages like Python, and cloud-based storage solutions. Their involvement in RDM not only redefines the academic library’s role but also enhances its strategic value in knowledge production. In the future, medical librarians may serve functions similar to data scientists, aiding in the analysis and visualization of big medical data. To realize this potential, institutional investment in medical librarian training, policy development, and infrastructure is essential. Ultimately, medical librarians are well-positioned to become future research data managers and vital contributors to sustainable open science practices.
)
