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Fahimeh Mohammadi, Maryam Shekofteh, Maryam Kazerani,
Volume 18, Issue 3 (7-2024)
Volume 18, Issue 3 (7-2024)
Abstract
Background and Aim: The growth and development of scientific fields depends on correct and accurate planning and a general and comprehensive understanding of the structure of these fields. Scientific maps are a type of scientometric methods that help to understand the current state of scientific fields and reveal their internal structure. The aim of the present study is to analyze co-authorship and word co-occurrence maps of scientific publications of Iran in the field of endocrinology and metabolism.
Materials and Methods: This is a cross-sectional scientometrics study. The research population is all scientific publications of Iran in the field of Endocrinology and Metabolism on the Web of Science. The co-authorship and co-word maps were analyzed using VOSviewer, Gephi, and NodeXL software. Network analysis was done using social network analysis indicators. Thematic clusters and emerging subjects were also identified through the examination of word co-occurrence networks.
Results: The total scientific publications of Iran in the field of endocrinology and metabolism on the Web of Science was 4847 documents. The co-authorship network is a type of sparse network. The value of the cluster coefficient of this network was 0.212 and its diameter was 11. The average degree of the co-authorship network (6.62) shows that each node is connected with about 6 other nodes on average. The diameter of the co-authorship network is 11. The most productive and influential outhors are Azizi F and Larijani B. Six thematic clusters were identified in the word co-occurrence network, the largest one is oxidative stress and gene expression, followed by the obesity and diabetes cluster. The word “autoimmunity” is one of the emerging words in this field.
Conclusion: Iran’s research in the field of Endocrinology and Metabolism shows an increasing trend, but there is little cooperation between the authors of the field. Their co-authorship networks are sparse, and the authors’ tendency to form clusters is low. Therefore, planning is needed to increase scientific cooperation and the density of networks. It is suggested that the researchers of this field pay attention to the thematic clusters of the co-word network and emerging subjects in the design of their future research.
Materials and Methods: This is a cross-sectional scientometrics study. The research population is all scientific publications of Iran in the field of Endocrinology and Metabolism on the Web of Science. The co-authorship and co-word maps were analyzed using VOSviewer, Gephi, and NodeXL software. Network analysis was done using social network analysis indicators. Thematic clusters and emerging subjects were also identified through the examination of word co-occurrence networks.
Results: The total scientific publications of Iran in the field of endocrinology and metabolism on the Web of Science was 4847 documents. The co-authorship network is a type of sparse network. The value of the cluster coefficient of this network was 0.212 and its diameter was 11. The average degree of the co-authorship network (6.62) shows that each node is connected with about 6 other nodes on average. The diameter of the co-authorship network is 11. The most productive and influential outhors are Azizi F and Larijani B. Six thematic clusters were identified in the word co-occurrence network, the largest one is oxidative stress and gene expression, followed by the obesity and diabetes cluster. The word “autoimmunity” is one of the emerging words in this field.
Conclusion: Iran’s research in the field of Endocrinology and Metabolism shows an increasing trend, but there is little cooperation between the authors of the field. Their co-authorship networks are sparse, and the authors’ tendency to form clusters is low. Therefore, planning is needed to increase scientific cooperation and the density of networks. It is suggested that the researchers of this field pay attention to the thematic clusters of the co-word network and emerging subjects in the design of their future research.
Zahra Karbasi, Michaeel Motaghi Niko, Maryam Zahmatkeshan,
Volume 18, Issue 3 (7-2024)
Volume 18, Issue 3 (7-2024)
Abstract
Background and Aim: Cataracts are recognized as the cause of 51% of blindness worldwide. Following the promising initial results of artificial intelligence systems in eye diseases, AI algorithms have been applied in the diagnosis of cataracts, grading the severity of cataracts, intraocular lens calculations, and even as an assistive tool in cataract surgery. This study presents a systematic review of AI techniques in the management of cataract disease.
Materials and Methods: This systematic review study was conducted to investigate artificial intelligence techniques to manage cataract disease until November 11, 2023, and based on PRISMA guidelines. We retrieved all relevant articles published in English through a systematic search of PubMed, Scopus, and Web of Science online databases.
Results: In our initial search, 192 records were identified in the databases, and eventually, 23 articles were selected for review. The results indicated that convolutional neural network algorithms (6 articles), recurrent neural networks (1 article), deep convolutional networks (1 article), support vector machines (2 articles), transfer learning (1 article), decision trees (4 articles), random forests (4 articles), logistic regression (3 articles), Bayesian algorithms (3 articles), XGBoost (3 articles), and K-nearest neighbors clustering algorithms (2 articles) were the artificial neural network and machine learning techniques and algorithms utilized. These techniques were employed in the studies for the diagnosis (70%), management (17%), and prediction (13%) of cataract disease.
Conclusion: Various artificial intelligence and machine learning techniques and algorithms can be effective and efficient in diagnosing, grading, managing, and predicting cataracts with high accuracy. In this study, deep learning techniques and convolutional neural networks have made the greatest contribution to cataract diagnosis. Deep learning techniques, decision trees, and Bayesian algorithms were involved in cataract management. Machine learning algorithms such as logistic regression, random forest, artificial neural network, decision tree, K1-nearest neighbor, XGBoost, and adaptive boosting also played a role in cataract prediction. Just as early prediction, diagnosis, and timely referral can reduce future complications of the disease, the use of systems based on artificial intelligence models that have acceptable accuracy can be effective in supporting the decision-making process of physicians and managing this disease.
Materials and Methods: This systematic review study was conducted to investigate artificial intelligence techniques to manage cataract disease until November 11, 2023, and based on PRISMA guidelines. We retrieved all relevant articles published in English through a systematic search of PubMed, Scopus, and Web of Science online databases.
Results: In our initial search, 192 records were identified in the databases, and eventually, 23 articles were selected for review. The results indicated that convolutional neural network algorithms (6 articles), recurrent neural networks (1 article), deep convolutional networks (1 article), support vector machines (2 articles), transfer learning (1 article), decision trees (4 articles), random forests (4 articles), logistic regression (3 articles), Bayesian algorithms (3 articles), XGBoost (3 articles), and K-nearest neighbors clustering algorithms (2 articles) were the artificial neural network and machine learning techniques and algorithms utilized. These techniques were employed in the studies for the diagnosis (70%), management (17%), and prediction (13%) of cataract disease.
Conclusion: Various artificial intelligence and machine learning techniques and algorithms can be effective and efficient in diagnosing, grading, managing, and predicting cataracts with high accuracy. In this study, deep learning techniques and convolutional neural networks have made the greatest contribution to cataract diagnosis. Deep learning techniques, decision trees, and Bayesian algorithms were involved in cataract management. Machine learning algorithms such as logistic regression, random forest, artificial neural network, decision tree, K1-nearest neighbor, XGBoost, and adaptive boosting also played a role in cataract prediction. Just as early prediction, diagnosis, and timely referral can reduce future complications of the disease, the use of systems based on artificial intelligence models that have acceptable accuracy can be effective in supporting the decision-making process of physicians and managing this disease.
Fatemeh Soofiabadi, Alireza Shahraki, Mohebali Rahdar,
Volume 18, Issue 3 (7-2024)
Volume 18, Issue 3 (7-2024)
Abstract
Background and Aim: Given the high sensitivity of the medical field, a mistake can cause irreparable damage to human society. For this reason, finding the symptoms of the disease and the relationships between them to facilitate the improvement of diseases is inevitable. Therefore, the aim of the present study was to first identify the symptoms of neurofibromatosis type 1 by specialists, then determine the relationship between the symptoms and the degree of their impact on each other in order to determine the most important criterion in improving the disease.
Materials and Methods: The present study is of a developmental-applied type in terms of its purpose and of a descriptive-survey type in terms of its data collection method. The case study of the present study is spinal disorders, of which neurofibromatosis type 1 has been diagnosed as one of them based on the opinion of experts. Neurofibromatosis type 1 is a genetic disorder that causes tumors in the nervous tissue. Accordingly, in the present study, the criteria, which are the symptoms of the disease, were first determined using the opinion of a group of experts and the implementation of the fuzzy Delphi method. In the next step, a model for the causal relationships between the symptoms of the disease is presented. For this purpose, a fuzzy cognitive map is drawn using MATLAB, FCMapper and Pajek software, then backward and forward scenarios are presented for neurofibromatosis type 1 and the disease improvement scenario is determined.
Results: The results showed that hormonal changes, flat brown spots on the skin, freckles in the armpit and groin area, soft bumps on the face or under the skin, high blood pressure, respiratory problems, bumps on the iris of the eye (Lish nodules), tumor in the optic nerve-ocular glioma, short stature, bone deformity, learning disabilities-attention deficit hyperactivity disorder (ADHD) and larger than average head size are ranked first to twelfth, respectively. The causal relationships between the symptoms showed that the criterion of hormonal changes has the greatest impact on the criterion of freckles in the armpit or groin area; Therefore, if the hormonal changes criterion improves, neurofibromatosis type 1 will also improve.
Conclusion: The findings of this study have helped the medical community to have a better understanding of the symptoms of the disease so that doctors can improve their prevention and care recommendations based on the severity of the symptoms of the diseases.
Materials and Methods: The present study is of a developmental-applied type in terms of its purpose and of a descriptive-survey type in terms of its data collection method. The case study of the present study is spinal disorders, of which neurofibromatosis type 1 has been diagnosed as one of them based on the opinion of experts. Neurofibromatosis type 1 is a genetic disorder that causes tumors in the nervous tissue. Accordingly, in the present study, the criteria, which are the symptoms of the disease, were first determined using the opinion of a group of experts and the implementation of the fuzzy Delphi method. In the next step, a model for the causal relationships between the symptoms of the disease is presented. For this purpose, a fuzzy cognitive map is drawn using MATLAB, FCMapper and Pajek software, then backward and forward scenarios are presented for neurofibromatosis type 1 and the disease improvement scenario is determined.
Results: The results showed that hormonal changes, flat brown spots on the skin, freckles in the armpit and groin area, soft bumps on the face or under the skin, high blood pressure, respiratory problems, bumps on the iris of the eye (Lish nodules), tumor in the optic nerve-ocular glioma, short stature, bone deformity, learning disabilities-attention deficit hyperactivity disorder (ADHD) and larger than average head size are ranked first to twelfth, respectively. The causal relationships between the symptoms showed that the criterion of hormonal changes has the greatest impact on the criterion of freckles in the armpit or groin area; Therefore, if the hormonal changes criterion improves, neurofibromatosis type 1 will also improve.
Conclusion: The findings of this study have helped the medical community to have a better understanding of the symptoms of the disease so that doctors can improve their prevention and care recommendations based on the severity of the symptoms of the diseases.
Hojjat Rahmani, Sadegh Moradi, Nayeb Fadaei Dehcheshmeh,
Volume 18, Issue 4 (10-2024)
Volume 18, Issue 4 (10-2024)
Abstract
Background and Aim: The fundamental right and most valuable asset for all strata of society is the enjoyment of health. Individuals residing in nomadic settings face geographical, social, cultural, and linguistic barriers when seeking access to essential services. The provision of healthcare services to nomads has become a complex issue due to the nature of the lifestyle. The aim of this study was to assess the challenges in the provision of healthcare services among the nomads in the Khuzestan province.
Materials and Methods: This study uses a qualitative approach, involving seventeen managers and staff from health centers affiliated with Ahvaz University of Medical Sciences. The data collection approach was inductive. Data were gathered through individual interviews, and participants’ opinions were recorded. The data were analyzed using the conventional content analysis method with a mixed approach (deductive and inductive). The credibility and quality of the data were assessed using the Guba and Lincoln method.
Results: The challenges in providing healthcare services in nomads were identified in nine categories and three overarching themes. The themes encompassed the nature and characteristics of the non-sedentary populations, the healthcare system, and the responsibilities of other sectors. The nature and characteristics of the nomads were categorized into five categories: demographic, cultural, climatic-geographic, socio-ethnic-tribal, and lifestyle. The healthcare delivery comprises of two aspects: structural and procedural. Additionally, the duties of other development sectors were categorized into two categories: infrastructures and inter-sectoral collaborations. The results showed that nomads face barriers to receiving healthcare due to the inherent characteristics of them, the healthcare system, and the performance of other organizations. The unstable population, cultural diversity, scattered distribution of the population, and their ethnic and migration-based lifestyle are among the inherent characteristics of nomads that impact the provision of services.
Conclusion: The provision of health services to nomads is influenced by recipients’ and providers’ characteristics. Decision-makers and managers, considering the unique conditions of life in the design and implementation of health programs, decision-makers and managers should prioritize strengthening healthcare networks in hard-to-reach areas. Given the limited resources and infrastructure weaknesses in settlements, inter-sectoral collaboration and the development of resources and infrastructure (applying the One Health approach) are important.
Materials and Methods: This study uses a qualitative approach, involving seventeen managers and staff from health centers affiliated with Ahvaz University of Medical Sciences. The data collection approach was inductive. Data were gathered through individual interviews, and participants’ opinions were recorded. The data were analyzed using the conventional content analysis method with a mixed approach (deductive and inductive). The credibility and quality of the data were assessed using the Guba and Lincoln method.
Results: The challenges in providing healthcare services in nomads were identified in nine categories and three overarching themes. The themes encompassed the nature and characteristics of the non-sedentary populations, the healthcare system, and the responsibilities of other sectors. The nature and characteristics of the nomads were categorized into five categories: demographic, cultural, climatic-geographic, socio-ethnic-tribal, and lifestyle. The healthcare delivery comprises of two aspects: structural and procedural. Additionally, the duties of other development sectors were categorized into two categories: infrastructures and inter-sectoral collaborations. The results showed that nomads face barriers to receiving healthcare due to the inherent characteristics of them, the healthcare system, and the performance of other organizations. The unstable population, cultural diversity, scattered distribution of the population, and their ethnic and migration-based lifestyle are among the inherent characteristics of nomads that impact the provision of services.
Conclusion: The provision of health services to nomads is influenced by recipients’ and providers’ characteristics. Decision-makers and managers, considering the unique conditions of life in the design and implementation of health programs, decision-makers and managers should prioritize strengthening healthcare networks in hard-to-reach areas. Given the limited resources and infrastructure weaknesses in settlements, inter-sectoral collaboration and the development of resources and infrastructure (applying the One Health approach) are important.
Mohammadreza Asghariyan, Farzad Firouzi Jahantigh,
Volume 18, Issue 4 (10-2024)
Volume 18, Issue 4 (10-2024)
Abstract
Background and Aim: The emergency department of the hospital is considered one of its main entrances; which has provided health care and treatment for critical and non-critical patients and faces various health and treatment restrictions, but the main emphasis is always on resource limitations. Many simulation projects were implemented in hospitals and first in emergency departments with the aim of increasing productivity. The present research is a general description of the patient’s movement flow and length of stay in the emergency department of a selected specialized hospital in Zahedan city. The aim of the current research is to prevent care complications, reduce waiting time and patient stay in the emergency department, present a simulation model and improve it based on discrete-event simulation.
Materials and Methods: Using the data bank of the emergency department system based on the required data and also through the in-person observation of the data related to the duration of the patient’s stay in the emergency department, including the arrival time, waiting time, The type of services provided to the patient, the time of service and the time of departure were collected and checked and confirmed by experts related to this field so that it has the highest level of reliability with the facts. The data were designed in Excel software, and then data analysis and simulation model creation were done using Aren V14 software, and according to the results, the effect of the proposed solutions was evaluated.
Results: The findings of the present research showed that the longest queue created in the emergency department of the selected specialized hospital in Zahedan city is related to medical examination and additional tests. By implementing the simulation model and testing different solutions, solution 3, which means adding one nurse to nursing consultation and one person to radiology, has the most optimizing effect on the performance of the system at different levels of the patient admission process. and the cost of its implementation is more than solutions 1 and 2. This solution created a 14% decrease in the average length of stay and a 28% decrease in the average duration of additional tests.
Conclusion: The use of queuing models and simulation techniques improve the performance of the system and their implementation has significant effects on reducing the waiting time and length of stay of patients in the emergency department, increasing the quality level of the process of monitoring patients. It leads to optimal management of resources and increased productivity.
Afshan Tajbakhsh, Nadjla Hariri, Mohammad Hassanzadeh,
Volume 18, Issue 4 (10-2024)
Volume 18, Issue 4 (10-2024)
Abstract
Background and Aim: The development of the internet and the digitalization of higher education have facilitated the possibility of online course delivery, enabling instructors and students to interact through virtual education. Virtual learning can enhance access to educational resources and services through communication technologies, regardless of time and location. Accordingly, the objective of this study is to design a virtual education model for teaching information literacy skills on the websites of medical university libraries across the country.
Materials and Methods: This research was conducted with a mixed approach (qualitative and quantitative). In the first stage, the meta-combination method and the study of previous researches were used according to the research topic and the components were extracted, and after several checks with experts, the necessary concepts and components for the design of the model were extracted. Then, using the Delphi method, experts’ opinions were applied to the output of the meta-combination stage, and the final questionnaire was designed and made available to the statistical community, and finally, in the fourth stage, modeling and validation and fitting of the model took place.
Results: The final model was developed using meta-synthesis and validated by experts, comprising 7 main categories, 14 subcategories, and 102 indicators. The main categories include technical factors, strategic factors, instructor-related components, structural factors, educational factors, content-related factors, and assessment and evaluation factors. From the users’ perspective, the content-related subcategory recorded the lowest value, with a score of 0.518 for users and 0.533 for instructors. Conversely, the assessment and evaluation subcategory achieved the highest scores, with 0.916 from the instructors’ perspective, 0.953 jointly from both users and instructors, and 0.842 for structural factors from the users’ perspective.
Conclusion: The results of the research showed that there is a significant relationship between the virtual training of information literacy skills on the website of the libraries of medical sciences universities of the country and the mentioned factors. Therefore, the model obtained in this study can be a basis for designing and compiling a framework for electronic learning of information literacy. Acquiring information literacy skills and fostering an information-literate society is a crucial necessity in the information age, particularly for graduate students whose work and activities are inherently tied to research and problem-solving.
Materials and Methods: This research was conducted with a mixed approach (qualitative and quantitative). In the first stage, the meta-combination method and the study of previous researches were used according to the research topic and the components were extracted, and after several checks with experts, the necessary concepts and components for the design of the model were extracted. Then, using the Delphi method, experts’ opinions were applied to the output of the meta-combination stage, and the final questionnaire was designed and made available to the statistical community, and finally, in the fourth stage, modeling and validation and fitting of the model took place.
Results: The final model was developed using meta-synthesis and validated by experts, comprising 7 main categories, 14 subcategories, and 102 indicators. The main categories include technical factors, strategic factors, instructor-related components, structural factors, educational factors, content-related factors, and assessment and evaluation factors. From the users’ perspective, the content-related subcategory recorded the lowest value, with a score of 0.518 for users and 0.533 for instructors. Conversely, the assessment and evaluation subcategory achieved the highest scores, with 0.916 from the instructors’ perspective, 0.953 jointly from both users and instructors, and 0.842 for structural factors from the users’ perspective.
Conclusion: The results of the research showed that there is a significant relationship between the virtual training of information literacy skills on the website of the libraries of medical sciences universities of the country and the mentioned factors. Therefore, the model obtained in this study can be a basis for designing and compiling a framework for electronic learning of information literacy. Acquiring information literacy skills and fostering an information-literate society is a crucial necessity in the information age, particularly for graduate students whose work and activities are inherently tied to research and problem-solving.
Leila Keikha, Fatemeh Sheikhshoaei, Abdolahad Nabiolahi, Mahnaz Khosravi,
Volume 18, Issue 4 (10-2024)
Volume 18, Issue 4 (10-2024)
Abstract
Background and Aim: Health librarians can play an important role in meeting the information needs of the clinical team and improving the quality of medical cares. Increasing clinical health literacy and use of Evidence-based medicine among ophthalmology residents is of great importance due to the importance of patients’ health in this field and appropriate decision-making about the individual’s health status. The present study aimed to evaluate the effect of an educational intervention by clinical librarians on the skills of ophthalmology residents in using of evidence-based information at Zahedan University of Medical Sciences.
Materials and Methods: This was a semi-experimental applied study. The research population was ophthalmology residents of Al-Zahra Eye Hospital, Zahedan University of Medical Sciences during the years 2020-2023, who were selected through a census. During a three-month period, 17 combined training sessions (face-to-face and virtual using the Navid system) were held for 18 ophthalmology residents regarding correct search methods from different databases and appropriate use of evidence-based information. To collect data before and after training, a clinical information literacy questionnaire derived from previous studies was used, and data analysis was performed using SPSS software and ANOVA and ANCOVA statistical tests to compare scores before and after training in the intervention group.
Results: The majority of participating residents (55.6%) were female. Before the intervention, 33.3% of the study population had moderate to high levels of knowledge about evidence-based medicine. There was a statistically significant relationship between the total level of knowledge of residents after training and gender (P-value<0.05). Clinical librarian training was effective on the level of basic knowledge of evidence-based medicine, designing clinical questions, searching for clinical evidence, critical evaluation of clinical evidence, and dissemination of evidence-based medical information of residents (P-value<0.05).
Conclusion: Considering the positive impact of clinical librarians’ intervention in improving the level of clinical decision-making knowledge of ophthalmology residents, it is suggested that evidence-based medicine training workshops or courses be held for residents of different disciplines using a variety of educational methods. In addition, it is suggested that evidence-based units be included in the residents’ curriculum and that training be conducted as a team consisting of medical librarians and specialists and ophthalmologist.
Materials and Methods: This was a semi-experimental applied study. The research population was ophthalmology residents of Al-Zahra Eye Hospital, Zahedan University of Medical Sciences during the years 2020-2023, who were selected through a census. During a three-month period, 17 combined training sessions (face-to-face and virtual using the Navid system) were held for 18 ophthalmology residents regarding correct search methods from different databases and appropriate use of evidence-based information. To collect data before and after training, a clinical information literacy questionnaire derived from previous studies was used, and data analysis was performed using SPSS software and ANOVA and ANCOVA statistical tests to compare scores before and after training in the intervention group.
Results: The majority of participating residents (55.6%) were female. Before the intervention, 33.3% of the study population had moderate to high levels of knowledge about evidence-based medicine. There was a statistically significant relationship between the total level of knowledge of residents after training and gender (P-value<0.05). Clinical librarian training was effective on the level of basic knowledge of evidence-based medicine, designing clinical questions, searching for clinical evidence, critical evaluation of clinical evidence, and dissemination of evidence-based medical information of residents (P-value<0.05).
Conclusion: Considering the positive impact of clinical librarians’ intervention in improving the level of clinical decision-making knowledge of ophthalmology residents, it is suggested that evidence-based medicine training workshops or courses be held for residents of different disciplines using a variety of educational methods. In addition, it is suggested that evidence-based units be included in the residents’ curriculum and that training be conducted as a team consisting of medical librarians and specialists and ophthalmologist.
Taleb Khodaveisi, Hamid Bouraghi, Tooba Mehrabi, Javad Faradmal, Mahdiye Shojaei Baghini, Ali Mohammadpour,
Volume 18, Issue 5 (11-2024)
Volume 18, Issue 5 (11-2024)
Abstract
Background and Aim: Identifying the educational needs of health information technology staff is essential before implementing any continuous education programs. This comprehensive study investigates these needs among health information technology personnel working in hospitals in the Hamadan province, considering both the general and specialized aspects of the field.
Materials and Methods: This descriptive cross-sectional study was conducted across 11 hospitals affiliated with Hamadan University of Medical Sciences. The study population comprised staff from the reception, medical records, statistics, and coding departments. Data were gathered using a validated and reliable standardized questionnaire. Collection methods included both in-person and remote approaches. Data analysis was performed using SPSS software, with results reported through descriptive and inferential statistics, specifically utilizing the Kruskal-Wallis test.
Results: The results of this study showed that among the generally accepted needs, items such as information technology (96.7%), legal aspects of medical records (87.6%), and communication skills (76.7%) had the highest percentage. Additionally, educational needs varied across different units: Coding unit staff required more training in the principles of diagnosis documentation (92.9%), familiarity with the coding guidelines for causes of death (85.7%), and familiarity with the coding guidelines for procedures (85.7%), statistics unit staff needed training in statistical software, and reception and medical records staff required education on relevant regulations. There was also a significant correlation between educational needs and certain individual characteristics such as work experience, education level, gender, and field of study.
Conclusion: The study results indicate that designing effective educational programs for health information technology staff requires consideration of individual characteristics, such as gender, work experience, and education level. Additionally, the training should be continuous, tailored to the distinct needs of each group, and delivered at appropriate intervals.
Materials and Methods: This descriptive cross-sectional study was conducted across 11 hospitals affiliated with Hamadan University of Medical Sciences. The study population comprised staff from the reception, medical records, statistics, and coding departments. Data were gathered using a validated and reliable standardized questionnaire. Collection methods included both in-person and remote approaches. Data analysis was performed using SPSS software, with results reported through descriptive and inferential statistics, specifically utilizing the Kruskal-Wallis test.
Results: The results of this study showed that among the generally accepted needs, items such as information technology (96.7%), legal aspects of medical records (87.6%), and communication skills (76.7%) had the highest percentage. Additionally, educational needs varied across different units: Coding unit staff required more training in the principles of diagnosis documentation (92.9%), familiarity with the coding guidelines for causes of death (85.7%), and familiarity with the coding guidelines for procedures (85.7%), statistics unit staff needed training in statistical software, and reception and medical records staff required education on relevant regulations. There was also a significant correlation between educational needs and certain individual characteristics such as work experience, education level, gender, and field of study.
Conclusion: The study results indicate that designing effective educational programs for health information technology staff requires consideration of individual characteristics, such as gender, work experience, and education level. Additionally, the training should be continuous, tailored to the distinct needs of each group, and delivered at appropriate intervals.
Saeed Pirmoradi,
Volume 18, Issue 5 (11-2024)
Volume 18, Issue 5 (11-2024)
Abstract
Background and Aim: One of the ways to control high blood pressure is to deactivate the renin-angiotensinogen-aldosterone RAAS system. Renin, also known as angiotensinogenase,It is a type of enzyme that is produced in the afferent arterioles of the kidney by special cells called juxtaglomerular cells and secreted into the bloodstream and converts angiotensinogen protein into angiotensin type 1, which is very effective in causing high blood pressure. Inhibition of renin as the rate-limiting step of this cycle is an effective way to stop it, which plays a role in the treatment of some diseases related to the heart and blood vessels and blood pressure. The purpose of this study is to use new and different methods based on software to discover newer medicinal compounds with less side effects and cost and in a shorter time to discover based on a reference drug for the treatment and control of blood pressure disease.
Materials and Methods: By selecting the inhibitory reference compound of renin enzyme by bioinformatics tools such as PHARMIT, ZINCPHARMER during virtual search through the structural and pharmacophoretic properties of the reference inhibitory compound, a number of new ligands were obtained. Then the docking process was performed and the selected top ligands in terms of toxicity, allergy, toxicity and ADME prediction were examined with the help of tools such as molsoft, PKCSM, way2drug and swiss ADME.
Results: Among the four final top ligands obtained, one of the ligands had the most interaction with different residues and with a higher docking binding energy (vina score=-9.7) than the others, and then the other two ligands had a favorable binding energy.Among the effective interacting residues, Asp215, Asp32 and Leu114 were bound to renin enzyme in superior ligands, such as the reference compound.
Conclusion: In general, the selected inhibitory ligands showed a good ability to interact with residues involved in substrate selectivity and catalytic activity and inhibition of renin enzyme activity according to the analysis of bioinformatics tools and their confirmation requires clinical studies.
Materials and Methods: By selecting the inhibitory reference compound of renin enzyme by bioinformatics tools such as PHARMIT, ZINCPHARMER during virtual search through the structural and pharmacophoretic properties of the reference inhibitory compound, a number of new ligands were obtained. Then the docking process was performed and the selected top ligands in terms of toxicity, allergy, toxicity and ADME prediction were examined with the help of tools such as molsoft, PKCSM, way2drug and swiss ADME.
Results: Among the four final top ligands obtained, one of the ligands had the most interaction with different residues and with a higher docking binding energy (vina score=-9.7) than the others, and then the other two ligands had a favorable binding energy.Among the effective interacting residues, Asp215, Asp32 and Leu114 were bound to renin enzyme in superior ligands, such as the reference compound.
Conclusion: In general, the selected inhibitory ligands showed a good ability to interact with residues involved in substrate selectivity and catalytic activity and inhibition of renin enzyme activity according to the analysis of bioinformatics tools and their confirmation requires clinical studies.
Zohre Abbaszade Molaei, Aeen Mohammadi, Manijeh Hooshmandja,
Volume 18, Issue 5 (11-2024)
Volume 18, Issue 5 (11-2024)
Abstract
Background and Aim: With the advancement of information technology in the new century, changes are experienced in all aspects of life. One of the reflections of these changes in education is conducting exams electronically instead of paper-and-pencil examinations. The success of virtual education is not achievable without considering the students’ viewpoints towards it. This study aimed to investigate the attitude and performance of students in online exams and their relationship with academic achievement.
Materials and Methods: This research is a mixed-method study (qualitative-quantitative). First, all related articles published, between 2000 to 2022, were extracted from ERIC, PubMed, ScienceDirect databases, and the Google Scholar search engine. Then, the attitude and performance questionnaire was designed and validated based on the literature review results. All BSc and MSc. nursing and midwifery students of Sarivar Nassibeh School filled out the questionnaire. Two hundred and five questionnaires were analyzed with SPSS using descriptive (mean and standard deviation) and inferential (t-test) statistics.
Results: Based on a content analysis of 15 selected articles, the extracted components were structured into 12 items. A preliminary questionnaire was designed with 28 questions across these 12 extracted components. Face validity was assessed using expert opinions, and necessary revisions were made. Both the Content Validity Index (CVI) and Content Validity Ratio (CVR) coefficients were employed for content validity. The final questionnaire comprised 22 items using a five-point Likert scale, ranging from strongly agree (score 5) to strongly disagree (score 1), with an internal consistency of 0.69. Exploratory factor analysis revealed that the questionnaire has six factors: “validity and accuracy”, “technical problems”, “types of questions and announcing the results”, “technique and simplicity”, “motivation and anxiety”, and “speed and error recording” that explain 60.88 percent of the total variance. Correlation results indicated no relationship between students’ attitudes and performance toward electronic examinations and academic achievement (r = 0.055, P-value = 0.432). There was a significant difference between male and female groups, BSc. and MSc. nursing and midwifery students, and semester of study.
Conclusion: The tool for measuring students’ attitudes and performance towards electronic exams has acceptable validity and reliability. This tool can be used to assess online exams and improvement plans.
Materials and Methods: This research is a mixed-method study (qualitative-quantitative). First, all related articles published, between 2000 to 2022, were extracted from ERIC, PubMed, ScienceDirect databases, and the Google Scholar search engine. Then, the attitude and performance questionnaire was designed and validated based on the literature review results. All BSc and MSc. nursing and midwifery students of Sarivar Nassibeh School filled out the questionnaire. Two hundred and five questionnaires were analyzed with SPSS using descriptive (mean and standard deviation) and inferential (t-test) statistics.
Results: Based on a content analysis of 15 selected articles, the extracted components were structured into 12 items. A preliminary questionnaire was designed with 28 questions across these 12 extracted components. Face validity was assessed using expert opinions, and necessary revisions were made. Both the Content Validity Index (CVI) and Content Validity Ratio (CVR) coefficients were employed for content validity. The final questionnaire comprised 22 items using a five-point Likert scale, ranging from strongly agree (score 5) to strongly disagree (score 1), with an internal consistency of 0.69. Exploratory factor analysis revealed that the questionnaire has six factors: “validity and accuracy”, “technical problems”, “types of questions and announcing the results”, “technique and simplicity”, “motivation and anxiety”, and “speed and error recording” that explain 60.88 percent of the total variance. Correlation results indicated no relationship between students’ attitudes and performance toward electronic examinations and academic achievement (r = 0.055, P-value = 0.432). There was a significant difference between male and female groups, BSc. and MSc. nursing and midwifery students, and semester of study.
Conclusion: The tool for measuring students’ attitudes and performance towards electronic exams has acceptable validity and reliability. This tool can be used to assess online exams and improvement plans.
Mahboubeh Fatemi, Mohammad Reza Yaghoobi-Ershadi, Yavar Rassi, Mohammad Mehdi Sedaghat, Hassan Vatandoost, Mahboubeh Bayat, Mehrdad Zarabi, Fatemeh Nikpoor, Amir Ahmad Akhavan,
Volume 18, Issue 5 (11-2024)
Volume 18, Issue 5 (11-2024)
Abstract
Background and Aim: Training and proper distribution of human resources are essential for maintaining and promoting society’s health. The first step in any health-related planning is to assess the current situation to draw a clear picture of the future to balance demand and supply. This research was conducted to assess the current situation of medical entomology and vector control/biology and vector control of the diseases in the country and determine the required human resources till 2025.
Materials and Methods: In this study, a “modified and combination model” was used, including the Hall model, which is location-based, and the Australian health workforce estimation model, which is a needs-based approach. The research was carried out in multiple stages, which included collecting the required data (number of faculty members, students, and graduates), the number of private companies providing spraying, and pest control services in all cities of the country and finally holding meetings with the board members of Biology and vector control of diseases and experts to estimate the human resources required in this field.
Results: Based on the data collected and face-to-face interviews conducted during six sessions with the experts in this field, it has been estimated that a total of 985 graduates have been trained in this discipline to date, while there is a requirement for 1,338 graduates in this area. Consequently, it is essential to train an additional 353 individuals in this field by the year 1404. In light of the country’s sixth five-year development plan, which allocates 30 percent of the total student population to postgraduate studies, it is imperative to prepare 35 individuals at the doctoral level, 71 at the master’s level, and 247 at the undergraduate level.
Conclusion: It seems that by accepting an average of 9 people at the Ph.D. level, 18 people at the master’s level, and 62 people at the bachelor’s level, in addition to matching the amount of demand and supply, there will be no problem for the employment of the graduates of this field.
Materials and Methods: In this study, a “modified and combination model” was used, including the Hall model, which is location-based, and the Australian health workforce estimation model, which is a needs-based approach. The research was carried out in multiple stages, which included collecting the required data (number of faculty members, students, and graduates), the number of private companies providing spraying, and pest control services in all cities of the country and finally holding meetings with the board members of Biology and vector control of diseases and experts to estimate the human resources required in this field.
Results: Based on the data collected and face-to-face interviews conducted during six sessions with the experts in this field, it has been estimated that a total of 985 graduates have been trained in this discipline to date, while there is a requirement for 1,338 graduates in this area. Consequently, it is essential to train an additional 353 individuals in this field by the year 1404. In light of the country’s sixth five-year development plan, which allocates 30 percent of the total student population to postgraduate studies, it is imperative to prepare 35 individuals at the doctoral level, 71 at the master’s level, and 247 at the undergraduate level.
Conclusion: It seems that by accepting an average of 9 people at the Ph.D. level, 18 people at the master’s level, and 62 people at the bachelor’s level, in addition to matching the amount of demand and supply, there will be no problem for the employment of the graduates of this field.
Elham Shakiba, Mahboobeh Sadat Fadavi, Mohammad Ali Nadi,
Volume 18, Issue 5 (11-2024)
Volume 18, Issue 5 (11-2024)
Abstract
Background and Aim: Smart power is the solidarity between science, knowledge and communication. With the advancement of technology, new space has been created in medical sciences. The aim of this research is Explaining the concept of Smart power and identifying its components in Universities of Medical Sciences
Materials and Methods: The current research was done qualitatively in 2023 using the grounded theory method. Deep and semi-structured interview was done with 13 faculty members of Medical Sciences Universities of the country selected through the purposeful and snowball sampling method and reached theoretical saturation. Strauss -Corbin method based on open, axial and selective coding was used for data analysis. To determine the accuracy and validity of the data, after coding the data, the opinions of six interview participants and six university professors who were familiar with the subject and method of the present research were sought.
Results: After the initial concepts were formulated, 77 open codes, 15 core codes, and five selective codes were identified for smart power. Strengthening artificial intelligence, e-health transformation, cross-border activities together constitute health technological responsiveness, are causal factors that affect the phenomenon of smart power. Actions that should be taken for smart power in medical universities, as strategies include technological innovation that is carried out with systematic technology, technological education, and research capacity building. Cyber management with technology-based performance, communication capability enhancement, information management are contextual factors that create special conditions for effective strategies. The conflict between tradition and modernization, information anxiety as organizational risks are intervention factors that interfere with and limit strategies. If the special conditions of strategies are provided and intervention factors are controlled, the outcome of strategies will be technological progress, development of communication network, integration of hard and soft power, and overall comprehensive health.
Conclusion: Using and developing this power, the policy makers of the health system will be able to solve problems such as the non-uniformity of health facilities in different regions, also the use of virtual university and electronic education, which will remove the time and place limitations and provide the opportunity for education to applicants in different parts of the country.
Materials and Methods: The current research was done qualitatively in 2023 using the grounded theory method. Deep and semi-structured interview was done with 13 faculty members of Medical Sciences Universities of the country selected through the purposeful and snowball sampling method and reached theoretical saturation. Strauss -Corbin method based on open, axial and selective coding was used for data analysis. To determine the accuracy and validity of the data, after coding the data, the opinions of six interview participants and six university professors who were familiar with the subject and method of the present research were sought.
Results: After the initial concepts were formulated, 77 open codes, 15 core codes, and five selective codes were identified for smart power. Strengthening artificial intelligence, e-health transformation, cross-border activities together constitute health technological responsiveness, are causal factors that affect the phenomenon of smart power. Actions that should be taken for smart power in medical universities, as strategies include technological innovation that is carried out with systematic technology, technological education, and research capacity building. Cyber management with technology-based performance, communication capability enhancement, information management are contextual factors that create special conditions for effective strategies. The conflict between tradition and modernization, information anxiety as organizational risks are intervention factors that interfere with and limit strategies. If the special conditions of strategies are provided and intervention factors are controlled, the outcome of strategies will be technological progress, development of communication network, integration of hard and soft power, and overall comprehensive health.
Conclusion: Using and developing this power, the policy makers of the health system will be able to solve problems such as the non-uniformity of health facilities in different regions, also the use of virtual university and electronic education, which will remove the time and place limitations and provide the opportunity for education to applicants in different parts of the country.
Najmeh Nazeri, Ali Shabani, Alireza Noruzi, Mostafa Hossini Golkar,
Volume 18, Issue 6 (2-2025)
Volume 18, Issue 6 (2-2025)
Abstract
Background and Aim: One of the pillars of scientific authority is the creation of a process for accessing information, referencing, and applying knowledge. The presence of strong information centers is considered a requirement for supporting this authority. Given the uncertainties of the future, there are various scenarios for accessing information in Iran, each of which requires appropriate measures for the effective application of knowledge. This research aims to understand the needs and requirements of the country’s information sector to achieve scientific authority.
Materials and Methods: Using futures studies methodologies and a combination of quantitative and qualitative methods, the indicators of information centers were first identified. Then, based on expert opinions, measures to achieve scientific authority were determined. The expert panel was purposefully selected from specialists with at least 10 years of experience in relevant fields. Validation of the scenarios and consensus-building were accomplished using an expert panel and focus group.
Results: A conceptual model was identified, comprising five components and 26 factors, which were prioritized based on 10 key drivers. Two critical uncertainties-access and information management, as well as the completion of the information cycle, led to the development of three scenarios: traditional, monopolistic, and democratic. Furthermore, indicators related to scientific authority were estimated based on expert opinions for a ten-year horizon within each scenario. The findings indicated that there was less differentiation among scenarios in the indicators of knowledge exchange and transfer, whereas greater differentiation was observed in the indicators of translation, outsourcing, and knowledge utilization. This highlights the necessity of directing effectiveness toward utility. These changes in the layers of processes and value creation in scientific authority could be traced.
Conclusion: According to the experts’ assessment of the indicators, in the knowledge exploitation stage of the traditional and exclusive scenarios, access to information in the components of knowledge exchange and transfer will not be adequately established. Therefore, to implement knowledge application, the presence of processes for support, promote, and facilitate scientific interaction will play a significant role in establishing scientific authority. Although the dominance of the view of knowledge as power and information as a source of power is expected to continue in the medium term, achieving scientific authority requires a transition to perspectives that offer greater support and provide a better platform for the formation of the information cycle and its broader distribution.
Materials and Methods: Using futures studies methodologies and a combination of quantitative and qualitative methods, the indicators of information centers were first identified. Then, based on expert opinions, measures to achieve scientific authority were determined. The expert panel was purposefully selected from specialists with at least 10 years of experience in relevant fields. Validation of the scenarios and consensus-building were accomplished using an expert panel and focus group.
Results: A conceptual model was identified, comprising five components and 26 factors, which were prioritized based on 10 key drivers. Two critical uncertainties-access and information management, as well as the completion of the information cycle, led to the development of three scenarios: traditional, monopolistic, and democratic. Furthermore, indicators related to scientific authority were estimated based on expert opinions for a ten-year horizon within each scenario. The findings indicated that there was less differentiation among scenarios in the indicators of knowledge exchange and transfer, whereas greater differentiation was observed in the indicators of translation, outsourcing, and knowledge utilization. This highlights the necessity of directing effectiveness toward utility. These changes in the layers of processes and value creation in scientific authority could be traced.
Conclusion: According to the experts’ assessment of the indicators, in the knowledge exploitation stage of the traditional and exclusive scenarios, access to information in the components of knowledge exchange and transfer will not be adequately established. Therefore, to implement knowledge application, the presence of processes for support, promote, and facilitate scientific interaction will play a significant role in establishing scientific authority. Although the dominance of the view of knowledge as power and information as a source of power is expected to continue in the medium term, achieving scientific authority requires a transition to perspectives that offer greater support and provide a better platform for the formation of the information cycle and its broader distribution.
Mojtaba Salimi Bani, Mehdi Ghassabi Chorsi, Roghayeh Ershad Sarabi,
Volume 18, Issue 6 (2-2025)
Volume 18, Issue 6 (2-2025)
Abstract
Background and Aim: Malaria is one of the health challenges in many countries worldwide. Iran is among the countries that have prioritized a malaria elimination program, aiming to interrupt local transmission of the disease by 2025. Health workeres (community health workers) play an important role in primary healthcare for identifying, controlling, and preventing malaria. Keeping their knowledge and skills up-to-date through continuous training can be effective in the success of this program. Virtual training is a modern educational method that facilitates such training courses. This study aimed to investigate the impact of virtual retraining courses on the knowledge, attitude, and performance of konarak health workers in implementing the malaria elimination program in 2022.
Materials and Methods: This research was a quasi-experimental study with a single-group pre-test and post-test design. The population included 69 individuals who were enrolled using a census method. Initially, a pre-test was conducted to assess the baseline level of knowledge, attitude, and performance of participants regarding malaria elimination strategies. Then, the educational intervention was delivered virtually, followed by a post-test to evaluate the outcomes. The educational content was provided in eight 45-minute sessions by an instructor from the Health worker Training Center using the Sky Room platform. Data collection was performed using a researcher-made questionnaire. Content validity of the questionnaire was confirmed, and its reliability was assessed in a pilot study prior to the training by the responsible expert; the Cronbach’s alpha coefficient of the questionnaire items was calculated at an acceptable level (r=0.83). Data were analyzed using SPSS software and paired t-tests.
Results: Out of 69 participants, 40 (58%) were male and 29 (42%) female. Comparison of pre-test and post-test results showed that the mean scores of knowledge, attitude, and performance of health workeres increased by 1.05, 1.2, and 1.17 units respectively after the training, and these differences were statistically significant (P=0.000).
Conclusion: Based on the results, considering the advantages of virtual training such as easy access, lower cost, and wide coverage, this method is recommended as a strategy for educational programs for healthcare staff.
Materials and Methods: This research was a quasi-experimental study with a single-group pre-test and post-test design. The population included 69 individuals who were enrolled using a census method. Initially, a pre-test was conducted to assess the baseline level of knowledge, attitude, and performance of participants regarding malaria elimination strategies. Then, the educational intervention was delivered virtually, followed by a post-test to evaluate the outcomes. The educational content was provided in eight 45-minute sessions by an instructor from the Health worker Training Center using the Sky Room platform. Data collection was performed using a researcher-made questionnaire. Content validity of the questionnaire was confirmed, and its reliability was assessed in a pilot study prior to the training by the responsible expert; the Cronbach’s alpha coefficient of the questionnaire items was calculated at an acceptable level (r=0.83). Data were analyzed using SPSS software and paired t-tests.
Results: Out of 69 participants, 40 (58%) were male and 29 (42%) female. Comparison of pre-test and post-test results showed that the mean scores of knowledge, attitude, and performance of health workeres increased by 1.05, 1.2, and 1.17 units respectively after the training, and these differences were statistically significant (P=0.000).
Conclusion: Based on the results, considering the advantages of virtual training such as easy access, lower cost, and wide coverage, this method is recommended as a strategy for educational programs for healthcare staff.
Akram Hemmatipour, Fatemh Karimi, Azam Jahangirimehr, Elham Abdolahi Shahvali, Mehdi Makvand,
Volume 18, Issue 6 (2-2025)
Volume 18, Issue 6 (2-2025)
Abstract
Background and Aim: One of the most important medical problems in the whole world is chronic pain, which affects millions of people every year and they are not provided with proper treatment. Research shows that one of the consequences of chronic pain is emotional reactions such as anxiety, depression, and stress that occur due to the long-term effects of pain. Therefore, the aim of the present study is to determine the effectiveness of cognitive-behavioral therapy on the mental health and pain intensity level of patients with chronic pain.
Materials and Methods: In this semi-experimental study, 126 patients with chronic musculoskeletal pain and having entry and exit criteria from physiotherapy centers under the supervision of Shoushtar Medical Sciences Faculty were randomly divided into two groups of 63 intervention and control. The intervention group received the intervention based on cognitive behavioral therapy for three months and 12 educational sessions. The patients of both groups completed the data collection tool, which included the numerical pain questionnaire (VAS) and the stress, anxiety and depression level questionnaire DASS21, before the intervention and one week after the completion of the educational intervention. To analyze the data, descriptive and parametric tests (paired t and independent t), Pearson correlation and covariance analysis were used using SPSS software.
Results: The average age of the participants was (46.12±27.16) years. The effectiveness of cognitive-behavioral therapy was associated with a significant reduction in stress, anxiety, and depression levels (P<0.001) only in the intervention group, and this reduction was seen in the levels of stress (P=0.032), anxiety (P=0.030), and depression (P=0.015) compared to the control group. A significant reduction in pain intensity was observed in both groups (P<0.001). However, this reduction in the intervention group was not statistically different from the control group (P>0.05). Also, there was no significant correlation between the levels of stress, anxiety, and depression and pain disability (P<0.05).
Conclusion: The findings of the present study emphasize the importance of using cognitive behavioral therapy in a group setting to treat stress, anxiety, depression, and pain intensity in patients with chronic musculoskeletal pain.
Materials and Methods: In this semi-experimental study, 126 patients with chronic musculoskeletal pain and having entry and exit criteria from physiotherapy centers under the supervision of Shoushtar Medical Sciences Faculty were randomly divided into two groups of 63 intervention and control. The intervention group received the intervention based on cognitive behavioral therapy for three months and 12 educational sessions. The patients of both groups completed the data collection tool, which included the numerical pain questionnaire (VAS) and the stress, anxiety and depression level questionnaire DASS21, before the intervention and one week after the completion of the educational intervention. To analyze the data, descriptive and parametric tests (paired t and independent t), Pearson correlation and covariance analysis were used using SPSS software.
Results: The average age of the participants was (46.12±27.16) years. The effectiveness of cognitive-behavioral therapy was associated with a significant reduction in stress, anxiety, and depression levels (P<0.001) only in the intervention group, and this reduction was seen in the levels of stress (P=0.032), anxiety (P=0.030), and depression (P=0.015) compared to the control group. A significant reduction in pain intensity was observed in both groups (P<0.001). However, this reduction in the intervention group was not statistically different from the control group (P>0.05). Also, there was no significant correlation between the levels of stress, anxiety, and depression and pain disability (P<0.05).
Conclusion: The findings of the present study emphasize the importance of using cognitive behavioral therapy in a group setting to treat stress, anxiety, depression, and pain intensity in patients with chronic musculoskeletal pain.
Ayoub Mohamadian, Ali Moeini, Mahnaz Sanjari, Zahra Abdullahzade,
Volume 18, Issue 6 (2-2025)
Volume 18, Issue 6 (2-2025)
Abstract
Background and Aim: Smart health, due to its capacity in disease prevention, is a suitable solution for providing osteoporosis fracture prevention services. Also, the existence of close relationships between active organizations for the prevention of this disease requires this area to be examined from the perspective of the ecosystem. Therefore, the purpose of this study is to identify the factors and players of the ecosystem of preventing fractures caused by osteoporosis in smart health.
Materials and Methods: A qualitative systematic review of meta-synthesis was conducted to find resources related to the prevention of osteoporosis-related fractures. For this purpose, scientific databases of Web of Science, Scopus and PubMed were examined and 155 were selected from 10344 sources found. At the end, by using the Shannon entropy method, the categories of each dimension were ranked.
Results: This systematic review demonstrated that the ecosystem for preventing fractures caused by osteoporosis comprises four main categories of factors: lifestyle (nutrition, exercise, fall prevention, cessation of tobacco, alcohol, and caffeine consumption), clinical (screening, diagnosis, and drug therapy), technological (infrastructure, platform, and application), and contextual (cultural, social participation, policy, economic, and education). The application and infrastructure secured the first and second positions in the ranking, while the platform and education collectively ranked third. Ecosystem participants were also categorized into three core layers: the fracture prevention and treatment team members, firms related to fracture prevention and treatment, and other health stakeholders; the extended layer, which includes affected or at-risk individuals, education stakeholders, cultural stakeholders, social stakeholders, and health stakeholders; and the external layer, comprising international organizations and national ministries. In the ranking, affected or at-risk individuals, other health stakeholders, and fracture prevention and treatment team members earned first to third positions, respectively.
Conclusion: The research results showed that “technological”, “contextual”, “lifestyle change” and “clinical” factors are in the first to fourth places, respectively. Also, among the players, the first place was assigned to the extended layer, the main core took the second place, and the external layer took the third place.
Materials and Methods: A qualitative systematic review of meta-synthesis was conducted to find resources related to the prevention of osteoporosis-related fractures. For this purpose, scientific databases of Web of Science, Scopus and PubMed were examined and 155 were selected from 10344 sources found. At the end, by using the Shannon entropy method, the categories of each dimension were ranked.
Results: This systematic review demonstrated that the ecosystem for preventing fractures caused by osteoporosis comprises four main categories of factors: lifestyle (nutrition, exercise, fall prevention, cessation of tobacco, alcohol, and caffeine consumption), clinical (screening, diagnosis, and drug therapy), technological (infrastructure, platform, and application), and contextual (cultural, social participation, policy, economic, and education). The application and infrastructure secured the first and second positions in the ranking, while the platform and education collectively ranked third. Ecosystem participants were also categorized into three core layers: the fracture prevention and treatment team members, firms related to fracture prevention and treatment, and other health stakeholders; the extended layer, which includes affected or at-risk individuals, education stakeholders, cultural stakeholders, social stakeholders, and health stakeholders; and the external layer, comprising international organizations and national ministries. In the ranking, affected or at-risk individuals, other health stakeholders, and fracture prevention and treatment team members earned first to third positions, respectively.
Conclusion: The research results showed that “technological”, “contextual”, “lifestyle change” and “clinical” factors are in the first to fourth places, respectively. Also, among the players, the first place was assigned to the extended layer, the main core took the second place, and the external layer took the third place.
Masoud Mohammadi, Ali Mousavizadeh, Maysam Behnampour, Seyed Hassan Faqihi,
Volume 19, Issue 1 (4-2025)
Volume 19, Issue 1 (4-2025)
Abstract
Background and Aim: The COVID-19 pandemic has confronted the world with various problems in the economic, social and political dimensions of health. The present study aimed to investigate control and preventive measures in controlling COVID-19, to investigate the epidemiology and cumulative incidence of COVID-19, as well as management activities, empowerment of personnel, and capacity estimation in Kohgiluyeh and Boyer Ahmad provinces; an attempt was also made to use GIS geographic information to guide policymakers.
Materials and Methods: The present study is a cross-sectional study that was conducted using a review of reliable information within a period of 41 months after the identification of the first case of the disease in the province. The collected information, including sampling cases, hospitalizations, deaths, and COVID-19 vaccination statistics, was collected from the portal of the Center for Infectious Disease Management of the Ministry of Health, the Integrated Health System (SIB), and the Health System Information Observatory of the Ministry of Health, Treatment and Medical Education.
Results: The cumulative number of cases and deaths due to COVID-19 in the province is 130,129 and 1,137, respectively. The total number of doses of vaccine administered in the province, based on the coverage area, according to the Integrated Health System (IHS), was 1,363,703. Also, increasing the bed capacity of the intensive care unit in the province to 55 beds, setting up three CT scanners in the provincial hospitals, and setting up a cellular and molecular laboratory in the two cities of Boyer Ahmad and Kohgiluyeh, in addition to distributing COVID-19 vaccines to all health centers, health bases, and health and medical centers, and sending mobile teams to conduct COVID-19 vaccinations to administer the vaccine door-to-door and in offices and organizations, were among the management activities in the field of COVID-19 control in the province.
Conclusion: Increasing the capacity to sample suspected cases and identify patients in the shortest possible time, isolating them, taking intervention measures to encourage people to get vaccinated, and creating awareness about preventing this disease have reduced the burden caused by it and increased the response capacity of the provincial health system.
Materials and Methods: The present study is a cross-sectional study that was conducted using a review of reliable information within a period of 41 months after the identification of the first case of the disease in the province. The collected information, including sampling cases, hospitalizations, deaths, and COVID-19 vaccination statistics, was collected from the portal of the Center for Infectious Disease Management of the Ministry of Health, the Integrated Health System (SIB), and the Health System Information Observatory of the Ministry of Health, Treatment and Medical Education.
Results: The cumulative number of cases and deaths due to COVID-19 in the province is 130,129 and 1,137, respectively. The total number of doses of vaccine administered in the province, based on the coverage area, according to the Integrated Health System (IHS), was 1,363,703. Also, increasing the bed capacity of the intensive care unit in the province to 55 beds, setting up three CT scanners in the provincial hospitals, and setting up a cellular and molecular laboratory in the two cities of Boyer Ahmad and Kohgiluyeh, in addition to distributing COVID-19 vaccines to all health centers, health bases, and health and medical centers, and sending mobile teams to conduct COVID-19 vaccinations to administer the vaccine door-to-door and in offices and organizations, were among the management activities in the field of COVID-19 control in the province.
Conclusion: Increasing the capacity to sample suspected cases and identify patients in the shortest possible time, isolating them, taking intervention measures to encourage people to get vaccinated, and creating awareness about preventing this disease have reduced the burden caused by it and increased the response capacity of the provincial health system.
Mohammad Mehdi Sepehri, Minoo Fathi, Nasrin Taherkhani, Roghaye Khasha,
Volume 19, Issue 1 (4-2025)
Volume 19, Issue 1 (4-2025)
Abstract
Background and Aim: The development of self-management application for gestational Diabetes based on mobile health, can increase the quality of life of pregnant mothers and reduce the cost of health care and treatment. In order to develop such an application, it is necessary to identify the key players of this system and examine the relationships between them. Then a gestational Diabetes self-management network based on mobile health tools can be presented.
Materials and Methods: The study was conducted in four phases. In the first phase, key players and roles were identified through literature review. In the second phase, interviews with experts were conducted to assess the identified players and their roles. The third phase involved identifying the relationships between players and their roles, accomplished by designing and completing questionnaires that explored the existence or absence of connections between them. In the final phase, the most critical roles and players were determined using social network analysis, employing three centrality indices: degree centrality, betweenness centrality, and closeness centrality.
Results: A total of 22 role players and 17 roles were identified. Based on the results, the Ministry of Health, with a degree centrality index of 41.12, was found to be the most influential and powerful role player in this network. The endocrinologist, nutritionist and obstetrician, with degree centrality indices of 38.52, 36.79, and 31.60. were ranked next. This indicates that the acceptance of this network by the medical community plays a critical role. Additionally, all three centrality indices showed that the role of patient education had the highest values, followed by roles such as education for specialists and healthcare staff, supporting patients in self-care behaviors, and ensuring patient safety and privacy, which were identified as the key roles.
Conclusion: This study aimed to identify various aspects of network design and the influential roles impacting the self-management of gestational Diabetes through mobile health. The Ministry of Health and the National Prevention Committee exhibited the most connections with each other in fulfilling their shared roles. Therefore, the Ministry of Health can fully delegate some roles to the National Prevention. Additionally, recognizing key roles underscores the necessity of prioritizing education and resource allocation for these roles.
Materials and Methods: The study was conducted in four phases. In the first phase, key players and roles were identified through literature review. In the second phase, interviews with experts were conducted to assess the identified players and their roles. The third phase involved identifying the relationships between players and their roles, accomplished by designing and completing questionnaires that explored the existence or absence of connections between them. In the final phase, the most critical roles and players were determined using social network analysis, employing three centrality indices: degree centrality, betweenness centrality, and closeness centrality.
Results: A total of 22 role players and 17 roles were identified. Based on the results, the Ministry of Health, with a degree centrality index of 41.12, was found to be the most influential and powerful role player in this network. The endocrinologist, nutritionist and obstetrician, with degree centrality indices of 38.52, 36.79, and 31.60. were ranked next. This indicates that the acceptance of this network by the medical community plays a critical role. Additionally, all three centrality indices showed that the role of patient education had the highest values, followed by roles such as education for specialists and healthcare staff, supporting patients in self-care behaviors, and ensuring patient safety and privacy, which were identified as the key roles.
Conclusion: This study aimed to identify various aspects of network design and the influential roles impacting the self-management of gestational Diabetes through mobile health. The Ministry of Health and the National Prevention Committee exhibited the most connections with each other in fulfilling their shared roles. Therefore, the Ministry of Health can fully delegate some roles to the National Prevention. Additionally, recognizing key roles underscores the necessity of prioritizing education and resource allocation for these roles.
Fatemeh Abbasi Ghaletaki, Maryam Kazerani, Azam Shahbodaghi,
Volume 19, Issue 1 (4-2025)
Volume 19, Issue 1 (4-2025)
Abstract
Background and Aim: Hospital library services are among the basic infrastructures for promoting e-health readiness. This study evaluated the components of e-health readiness in hospital libraries in Isfahan.
Materials and Methods: This is an applied-descriptive survey. The statistical population is 10 government hospital libraries in Isfahan city. The questionnaire completers are the managers of the aforementioned libraries. The research tool is a researcher-made questionnaire that was prepared by a deep and comprehensive review of related literature. The 61-question questionnaire is based on the Likert scale and has four sections: learning readiness (R1), core readiness (R2), social readiness (R3), and technology readiness (R4). To determine the content validity of the questionnaire, the opinions of professors, specialists, and experts were used and its validity was confirmed. Its reliability was confirmed using Cronbach’s alpha of 0.83. Descriptive statistics were used to examine the data.
Results: Isfahan government hospital libraries are in a good state in terms of learning readiness with a score of 3.77. They were in a moderate state in terms of core readiness with a score of 3.49. Social readiness with a score of 2.47 and technology readiness with a score of 2.48 were reported as poor state. “Literacy level of technology and services related to health care” component with a score of 2.9 from the core readiness, “reimbursement policies” component with a score of 1 from the social readiness, “resources training” component with a score of 1.8 from the learning readiness, and “organization access to ICT education” component with a score of 1.35 from the technology readiness were identified as weak components. In general, all government hospital libraries in Isfahan are in a moderate state in terms of e-health readiness.
Conclusion: Hospital libraries face various challenges in joining the e-health category, including a lack of readiness in the technology sector. The lack of appropriate policies for implementing e-health in libraries, lack of users’ skills in using information and communication technology, users’ ignorance of the e-health services needed in the library, lack of professional human resources, and lack of e-health-related training for users are some of the weaknesses of hospital libraries in the e-health readiness sector.
Materials and Methods: This is an applied-descriptive survey. The statistical population is 10 government hospital libraries in Isfahan city. The questionnaire completers are the managers of the aforementioned libraries. The research tool is a researcher-made questionnaire that was prepared by a deep and comprehensive review of related literature. The 61-question questionnaire is based on the Likert scale and has four sections: learning readiness (R1), core readiness (R2), social readiness (R3), and technology readiness (R4). To determine the content validity of the questionnaire, the opinions of professors, specialists, and experts were used and its validity was confirmed. Its reliability was confirmed using Cronbach’s alpha of 0.83. Descriptive statistics were used to examine the data.
Results: Isfahan government hospital libraries are in a good state in terms of learning readiness with a score of 3.77. They were in a moderate state in terms of core readiness with a score of 3.49. Social readiness with a score of 2.47 and technology readiness with a score of 2.48 were reported as poor state. “Literacy level of technology and services related to health care” component with a score of 2.9 from the core readiness, “reimbursement policies” component with a score of 1 from the social readiness, “resources training” component with a score of 1.8 from the learning readiness, and “organization access to ICT education” component with a score of 1.35 from the technology readiness were identified as weak components. In general, all government hospital libraries in Isfahan are in a moderate state in terms of e-health readiness.
Conclusion: Hospital libraries face various challenges in joining the e-health category, including a lack of readiness in the technology sector. The lack of appropriate policies for implementing e-health in libraries, lack of users’ skills in using information and communication technology, users’ ignorance of the e-health services needed in the library, lack of professional human resources, and lack of e-health-related training for users are some of the weaknesses of hospital libraries in the e-health readiness sector.
Mohammad Ghasembandi, Samaneh Dehghan Abnavi, Negin Larti, Foziye Hamoole Tahmasbi, Jaber Zabihirad,
Volume 19, Issue 1 (4-2025)
Volume 19, Issue 1 (4-2025)
Abstract
Background and Aim: Low back pain (LBP) is one of the most common musculoskeletal disorders among operating room nurses, and numerous studies have well explained its causes and factors. However, studies focusing on the characteristics and dimensions of low back pain and its relationship with influencing factors have not been conducted. Therefore, the aim of this study was to investigate the prevalence of the type of LBP, duration of back pain, and severity of back pain, and their relationship with the demographic characteristics of operating room nurses.
Materials and Methods: This cross-sectional study was conducted on 350 operating room nurses at Ahvaz teaching hospitals in Iran in 2023. Data were collected using a questionnaire that included demographic information and LBP characteristics. Data were analyzed using IBM SPSS.
Results: 64.8% of the subjects were female, 63.5% were married, and their mean age was 33.83±7.02 years. The prevalence of LBP among operating room nurses was 74.3%. In 60.7% of participant who have LBP, the first experience of back pain was in the past 5 years. The most common diagnosis of LBP was muscular disorders (29.9%). Also, 57.3% of them had pain only in the lower back and 42.7% of them had LBP radiating to the legs. We found no statistically significant relationship between the duration and severity of LBP and demographic characteristics (P<0.05). A statistically significant relationship was found between the type of LBP and gender and level of education, as well as between the duration of LBP and severity of LBP (P<0.05).
Conclusion: The findings of this study showed a high prevalence of LBP among operating room nurses, and differences in the type of LBP were observed based on gender and educational level, which may be attributed to individual factors. Additionally, the significant relationship between the duration of LBP and its severity may indicate the effect of the long duration of LBP on its severity, which suggests that providing counseling and treatment programs for nurses who are in the early stages of LBP.
Results: 64.8% of the subjects were female, 63.5% were married, and their mean age was 33.83±7.02 years. The prevalence of LBP among operating room nurses was 74.3%. In 60.7% of participant who have LBP, the first experience of back pain was in the past 5 years. The most common diagnosis of LBP was muscular disorders (29.9%). Also, 57.3% of them had pain only in the lower back and 42.7% of them had LBP radiating to the legs. We found no statistically significant relationship between the duration and severity of LBP and demographic characteristics (P<0.05). A statistically significant relationship was found between the type of LBP and gender and level of education, as well as between the duration of LBP and severity of LBP (P<0.05).
Conclusion: The findings of this study showed a high prevalence of LBP among operating room nurses, and differences in the type of LBP were observed based on gender and educational level, which may be attributed to individual factors. Additionally, the significant relationship between the duration of LBP and its severity may indicate the effect of the long duration of LBP on its severity, which suggests that providing counseling and treatment programs for nurses who are in the early stages of LBP.
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Health Information Management, Health Care Management, Medical Laboratory Sciences, Medical Library & Information Sciences, Radiation Biology (Radiobiology and Radiation Protection), Operating Room, Anesthesiology
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