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Azita Yazdani, Ali Asghar Safaei, Reza Safdari, Maryam Zahmatkeshan,
Volume 13, Issue 3 (9-2019)
Volume 13, Issue 3 (9-2019)
Abstract
Background and Aim: Breast cancer is the most common type of cancer and the main cause of death from cancer in women worldwide. Technologies such as data mining, have enabled experts in this area to improve decision making in the early diagnosis of the disease. Therefore, the purpose of this research is to develop an automatic diagnostic model for breast cancer by employing data mining methods and selecting the model with the highest accuracy of diagnosis.
Materials and Methods: In this study, 654 available patient records of Motahari breast cancer Clinic in Shiraz" were used as the sample. The number of records was reduced to 621 after the pre-processing operation. These samples had 22 features that ultimately used ten were used as effective features in the design of the model. Three types of Decision tree, Naive Bayes and Artificial neural network were used for diagnosis of breast cancer and 10-fold cross-validation method for constructing and evaluating the model on the collected data set.
Results: The results of the three techniques mentioned all three models showed promising results in detecting breast cancer. Finally, the artificial neural network accounted for the highest accuracy of 94/49%(sensitivity 96/19%, specificity 86/36%) in the diagnosis of breast cancer.
Conclusion: Based on the results of the decision tree, the risk factors such as age, weight, Age of menstruation, menopause, OCP of records duration, and the age of the first pregnancy were among the factors affecting the incidence of breast cancer in women.
Materials and Methods: In this study, 654 available patient records of Motahari breast cancer Clinic in Shiraz" were used as the sample. The number of records was reduced to 621 after the pre-processing operation. These samples had 22 features that ultimately used ten were used as effective features in the design of the model. Three types of Decision tree, Naive Bayes and Artificial neural network were used for diagnosis of breast cancer and 10-fold cross-validation method for constructing and evaluating the model on the collected data set.
Results: The results of the three techniques mentioned all three models showed promising results in detecting breast cancer. Finally, the artificial neural network accounted for the highest accuracy of 94/49%(sensitivity 96/19%, specificity 86/36%) in the diagnosis of breast cancer.
Conclusion: Based on the results of the decision tree, the risk factors such as age, weight, Age of menstruation, menopause, OCP of records duration, and the age of the first pregnancy were among the factors affecting the incidence of breast cancer in women.
Maryam Goodarzi, Seyed Soroush Ghazinoori, Reza Radfar, Abbas Kebriaeezadeh,
Volume 13, Issue 5 (1-2020)
Volume 13, Issue 5 (1-2020)
Abstract
Background and Aim: Given the increasing variety of biological drugs in the world and the significant role of these drugs in patients' quality of life, as well as the high risk of drug productions, biopharmaceutical companies need to revise their business model. The purpose of this study is to review the dimensions and components of biopharmaceutical companies.
Materials and Methods: This is a comprehensive review and is based on the existing studies by searching valid databases such as PubMed, Science Direct, SID, Iran doc and Google Scholar from 2000 to 2019. All the searches were performed based on keywords such as “Components of Business Model”, and “Business Model of Biopharmaceutical Companies”. The initial search yielded 820 articles. After screening, 23 articles were selected for final study.
Results: The overall dimensions of business model in biopharmaceutical companies are identical to other companies, but the components of the business model of these kinds of companies are various based on their performance, and the most important components include the value proposition, key resources, success factors, revenue stream and cost structure.
Conclusion: Introducing the components of business model in this study can be adjusted based on the dimensions of business model and the characteristics of each biopharmaceutical company.
Materials and Methods: This is a comprehensive review and is based on the existing studies by searching valid databases such as PubMed, Science Direct, SID, Iran doc and Google Scholar from 2000 to 2019. All the searches were performed based on keywords such as “Components of Business Model”, and “Business Model of Biopharmaceutical Companies”. The initial search yielded 820 articles. After screening, 23 articles were selected for final study.
Results: The overall dimensions of business model in biopharmaceutical companies are identical to other companies, but the components of the business model of these kinds of companies are various based on their performance, and the most important components include the value proposition, key resources, success factors, revenue stream and cost structure.
Conclusion: Introducing the components of business model in this study can be adjusted based on the dimensions of business model and the characteristics of each biopharmaceutical company.
Raoof Nopour, Mohammad Shirkhoda, Sharareh Rostam Niakan Kalhori,
Volume 14, Issue 2 (5-2020)
Volume 14, Issue 2 (5-2020)
Abstract
Background and Aim: Colorectal cancer is one of the most common gastrointestinal cancers among human beings and the most important cause of death in the world. Based on the risk of colorectal cancer for individuals, using an appropriate screening program can help to prevent the disease. Therefore, the purpose of this study was to design a model for screening colorectal cancer based on risk factors to increase the survival rate of the disease on the one hand and to reduce the mortality rate on the other.
Materials and Methods: By reviewing articles and patients' records, 38 risk factors were detected. To determine the most important risk factors clinically, CVR(content validity ratio) was used; and considering the collected data, Spearman correlation coefficient and logistic regression analysis were applied for statistical analyses. Then, four algorithms -- J-48, J-RIP, PART and REP-Tree -- were used for data mining and rule generation. Finally, the most common model was obtained based on comparing the performance of the algorithms.
Results: After comparing the performance of algorithms, the J-48 algorithm with an F-Measure of 0.889 was found to be better than the others.
Conclusion: The results of evaluating J-48 data mining algorithm performance showed that this algorithm could be considered as the most appropriate model for colorectal cancer risk prediction.
Materials and Methods: By reviewing articles and patients' records, 38 risk factors were detected. To determine the most important risk factors clinically, CVR(content validity ratio) was used; and considering the collected data, Spearman correlation coefficient and logistic regression analysis were applied for statistical analyses. Then, four algorithms -- J-48, J-RIP, PART and REP-Tree -- were used for data mining and rule generation. Finally, the most common model was obtained based on comparing the performance of the algorithms.
Results: After comparing the performance of algorithms, the J-48 algorithm with an F-Measure of 0.889 was found to be better than the others.
Conclusion: The results of evaluating J-48 data mining algorithm performance showed that this algorithm could be considered as the most appropriate model for colorectal cancer risk prediction.
Zahra Mohammadzadeh, Hamid Reza Saeidnia, Ali Ghorbi,
Volume 14, Issue 3 (7-2020)
Volume 14, Issue 3 (7-2020)
Abstract
Background and Aim: A hospital website is an appropriate system for exchanging information and connecting patients, hospitals and medical staff. The purpose of this study was to identify and classify desirable web-based services in websites of Iran's hospitals based on Kano’s Customer Satisfaction Model.
Materials and Methods: This was a survey study. The statistical population of the study consisted of hospital website users, of whom 120 were randomly selected. The data collection tool was a questionnaire based on Kano model. The validity of the questionnaire was confirmed by the information science and health information technology (HIT) professors. Data were analyzed using Kano model evaluation table, Excel software, and descriptive statistics. Cronbach's alpha test was used to determine reliability (a=0.82).
Results: First, the desirable web-based services of the hospitals’ websites were identified. Then, 67 identified services were classified into mandatory criteria (29 services), one-dimensional criteria (15 services), attractive criteria (14 services) and indifferent criteria (9 services). Most services were mandatory, attractive, one-dimensional and indifferent in content components.
Conclusion: Most services identified in this study were on the websites of the world's leading hospitals; HIT designers and professionals and hospital managers are expected to use such services in designing hospital websites. Although the comments of site designers and experts were practical in some cases, they attracted a limited number of users due to their unfamiliarity with specialized website design topics.
Materials and Methods: This was a survey study. The statistical population of the study consisted of hospital website users, of whom 120 were randomly selected. The data collection tool was a questionnaire based on Kano model. The validity of the questionnaire was confirmed by the information science and health information technology (HIT) professors. Data were analyzed using Kano model evaluation table, Excel software, and descriptive statistics. Cronbach's alpha test was used to determine reliability (a=0.82).
Results: First, the desirable web-based services of the hospitals’ websites were identified. Then, 67 identified services were classified into mandatory criteria (29 services), one-dimensional criteria (15 services), attractive criteria (14 services) and indifferent criteria (9 services). Most services were mandatory, attractive, one-dimensional and indifferent in content components.
Conclusion: Most services identified in this study were on the websites of the world's leading hospitals; HIT designers and professionals and hospital managers are expected to use such services in designing hospital websites. Although the comments of site designers and experts were practical in some cases, they attracted a limited number of users due to their unfamiliarity with specialized website design topics.
Mahdi Shahraki, Simin Ghaderi,
Volume 14, Issue 4 (10-2020)
Volume 14, Issue 4 (10-2020)
Abstract
Background & Aim: Physicians as human capital and resources are one of the main components of health production. The imbalance of physician supply and demand affects the health and economics. Therefore, this study aimed to estimate and forecast the supply and demand of physician working in Iranian medical universities.
Materials and Methods: This a descriptive-analytical and applied study was conducted at national level for Iran during 1991-2017. The statistical population was physicians working in Iranian medical universities. ARIMA method was used to estimate and forecast physician supply and Vector Error Correction Models was used for physician demand. The data is annual time series that was extracted from the statistical yearbooks of the Statistical Center of Iran and the World Bank database. Eviews 10 software was used to estimate the models.
Results: The results showed that physician demand in Iran was affected by Gross Domestic Product, age structure and hospital beds, and according to the forecast of supply and demand of physicians, we will be faced to the physician shortage in the years 2018-2030.
Conclusion: In the coming years, Iran is facing with physician shortage. Therefore, it is recommended to adopt policies to increase physician capacity in medical universities and to increase strong incentives to retain physicians and prevent their migration.
Materials and Methods: This a descriptive-analytical and applied study was conducted at national level for Iran during 1991-2017. The statistical population was physicians working in Iranian medical universities. ARIMA method was used to estimate and forecast physician supply and Vector Error Correction Models was used for physician demand. The data is annual time series that was extracted from the statistical yearbooks of the Statistical Center of Iran and the World Bank database. Eviews 10 software was used to estimate the models.
Results: The results showed that physician demand in Iran was affected by Gross Domestic Product, age structure and hospital beds, and according to the forecast of supply and demand of physicians, we will be faced to the physician shortage in the years 2018-2030.
Conclusion: In the coming years, Iran is facing with physician shortage. Therefore, it is recommended to adopt policies to increase physician capacity in medical universities and to increase strong incentives to retain physicians and prevent their migration.
Hamzeh Amin-Tahmasbi, Maede Ghasemi,
Volume 14, Issue 4 (10-2020)
Volume 14, Issue 4 (10-2020)
Abstract
Background and Aim: The growing healthcare expenses, technological advancements and increasing competition in healthcare services, brings up new challenges for healthcare industry in providing appropriate services to customers. The Lean methodology, which is a managerial approach, provides tools necessary to eliminate waste and increase customer satisfaction through increasing quality of the services and decreasing the wait times and costs. The Scope of this paper is to determine and rank the lean criteria for hospitals.
Materials and Methods: 22 base criteria for a lean organization was selected and reconciled to hospitals from literature review. Then they were evaluated by experts in the field using Likert scale, leading to 18 criteria. The correlation of these criteria was found using ISM methodology, followed by ranking of these criteria. Lastly, the criteria were categorized utilizing MICMAC analysis.
Results: utilizing MICMAC analysis, the "defining the flow of processes & continuous improvement", "utilizing visual surveillance to understand the situation & exploit the problems" were identified as the most important variables.
Conclusion: In order to increase quality of services and customer satisfaction and to reduce operating costs, hospitals are advised to utilize lean methodology. In which case the management should pay more attention to the two more important criteria derived by MICMAC analysis, "Defining the processes in order to find problems" and "Continuous improvement and utilizing visual surveillance in order to find problems".
Materials and Methods: 22 base criteria for a lean organization was selected and reconciled to hospitals from literature review. Then they were evaluated by experts in the field using Likert scale, leading to 18 criteria. The correlation of these criteria was found using ISM methodology, followed by ranking of these criteria. Lastly, the criteria were categorized utilizing MICMAC analysis.
Results: utilizing MICMAC analysis, the "defining the flow of processes & continuous improvement", "utilizing visual surveillance to understand the situation & exploit the problems" were identified as the most important variables.
Conclusion: In order to increase quality of services and customer satisfaction and to reduce operating costs, hospitals are advised to utilize lean methodology. In which case the management should pay more attention to the two more important criteria derived by MICMAC analysis, "Defining the processes in order to find problems" and "Continuous improvement and utilizing visual surveillance in order to find problems".
Kobra Nakhoda, Mohammad Ali Hosseini, Kamran Mohammadkhani, Nader Gholi Ghorchian,
Volume 14, Issue 4 (10-2020)
Volume 14, Issue 4 (10-2020)
Abstract
Background and Aim: International student satisfaction is a vital element in international universities and one of the promotion methods in the global ranking, and is considered as a competitive factor.
Materials and Methods: The research method is mixed (quantitative-qualitative) of exploratory-confirmatory type. The statistical population includes experts, international department managers and foreign students(1352 people) in three universities of medical sciences in Tehran, Shahid Beheshti and Iran. The sampling method is qualitative, purposeful and the sample size is 21 professors. In a small part of the multi-stage cluster method, 450 international students were selected. The research tool was a semi-structured interview in the qualitative part of the interview and a researcher-made questionnaire in the quantitative part.
Results: According to the research results, the most influential factor in the foreign students' satisfaction model includes virtual services(0.84), loyalty(0.81), university reputation and rank (0.78), admission process(0.75), Research services(0.72), Staff and management services(0.71), International services(0.70), Educational services(0.68), Health services(0.67), Welfare services(0.65), Financial facilities(0.64), university infrastructure(0.63) and cultural services(0.61).
Conclusion: In order to attract financial resources, international competition, improve regional and global ranking, universities should consider and plan the priorities of the proposed satisfaction model to improve the level of satisfaction of foreign students.
Materials and Methods: The research method is mixed (quantitative-qualitative) of exploratory-confirmatory type. The statistical population includes experts, international department managers and foreign students(1352 people) in three universities of medical sciences in Tehran, Shahid Beheshti and Iran. The sampling method is qualitative, purposeful and the sample size is 21 professors. In a small part of the multi-stage cluster method, 450 international students were selected. The research tool was a semi-structured interview in the qualitative part of the interview and a researcher-made questionnaire in the quantitative part.
Results: According to the research results, the most influential factor in the foreign students' satisfaction model includes virtual services(0.84), loyalty(0.81), university reputation and rank (0.78), admission process(0.75), Research services(0.72), Staff and management services(0.71), International services(0.70), Educational services(0.68), Health services(0.67), Welfare services(0.65), Financial facilities(0.64), university infrastructure(0.63) and cultural services(0.61).
Conclusion: In order to attract financial resources, international competition, improve regional and global ranking, universities should consider and plan the priorities of the proposed satisfaction model to improve the level of satisfaction of foreign students.
Somaye Dehghanisanij, Ismaeil Mostafavi, Hamidreza Zarghami, Hojat Soleimani,
Volume 14, Issue 5 (1-2021)
Volume 14, Issue 5 (1-2021)
Abstract
Background and Aim: The field of medical engineering is the flagship interdisciplinary approach in Iran, which, due to its attention to knowledge-based economy, takes a step towards prosperity and smoothing progress and development. The purpose of this study is to investigate the interactions between university, industry and government of Iran in scientific articles in the field of medical engineering using the triple helix model.
Materials and Methods: This is an applied research with a quantitative approach and uses scientometric techniques. The status of dynamic interactions of the main pillars of Iranian innovation in the field of medical engineering in WoS (Web of Science) database has been calculated using the .exe and the 4.exe softwares in the period of 2010-2019, and the transmission degree of uncertainty index in dual and national dimensions has been determined.
Results: The T-index ranking was assigned to university-government(23.38 mb), university-industry(8.47 mb) and industry-government (1.13 mb), respectively, and finally, national interaction(-12.48 mb) was obtained. The interaction between university and industry had an increasing trend and the strongest dual interaction belonged to the university-government. Over the last ten years, national interaction has always had a negative value, which indicates the existence of dynamics in interactions in the national dimension.
Conclusion: The dual university-industry interaction has been increasing in recent years; however, in the long run, the national interaction of the pillars has been facing a declining trend, according to which some science and technology policies, and research and industrial strategies have been proposed as a necessity to promote the university-industry-government innovation network in the field of medical engineering in Iran.
Materials and Methods: This is an applied research with a quantitative approach and uses scientometric techniques. The status of dynamic interactions of the main pillars of Iranian innovation in the field of medical engineering in WoS (Web of Science) database has been calculated using the .exe and the 4.exe softwares in the period of 2010-2019, and the transmission degree of uncertainty index in dual and national dimensions has been determined.
Results: The T-index ranking was assigned to university-government(23.38 mb), university-industry(8.47 mb) and industry-government (1.13 mb), respectively, and finally, national interaction(-12.48 mb) was obtained. The interaction between university and industry had an increasing trend and the strongest dual interaction belonged to the university-government. Over the last ten years, national interaction has always had a negative value, which indicates the existence of dynamics in interactions in the national dimension.
Conclusion: The dual university-industry interaction has been increasing in recent years; however, in the long run, the national interaction of the pillars has been facing a declining trend, according to which some science and technology policies, and research and industrial strategies have been proposed as a necessity to promote the university-industry-government innovation network in the field of medical engineering in Iran.
Niloofar Mohammadzadeh, Ziba Mosayebi, Hamid Beigy, Mohammad Shojaeinia,
Volume 14, Issue 6 (1-2021)
Volume 14, Issue 6 (1-2021)
Abstract
Background and Aim: Sepsis is the most important disease in the first 28 days of life and one of the main causes of infant mortality in the intensive care unit. Its definitive diagnosis is possible by performing blood culture. Neonatal sepsis can be a clinical sign of nosocomial infections that are often resistant to antibiotics. Therefore, the purpose of this study was to create and evaluate a hospital sepsis prediction model and present its results to health care providers.
Materials and Methods: In this descriptive-applied study, the research population includes neonates admitted to the intensive care unit of Valiasr Hospital in Tehran and the research sample is the data of 4196 neonates admitted to this ward from 2016 to August, 2020. The initial features for creating a predictive model of sepsis were prepared by examining the relevant information sources and under the supervision of professors and officials of Valiasr Hospital's mother and fetus research center and its validity was confirmed by 5 neonatal professors of this hospital. In this research, machine learning algorithms have been used to create a sepsis prediction model.
Results: Accuracy and AUROC(area under the ROC curve) parameters were used to evaluate the generated models. The highest values of Accuracy and AUROC are related to Adaptive Boosting and random forest algorithms, respectively.
Conclusion: Learning curves show that using different training examples and more complex selection of combination features improves the performance of the models. Further research is needed to evaluate the clinical effectiveness of machine learning models in a trial.
Materials and Methods: In this descriptive-applied study, the research population includes neonates admitted to the intensive care unit of Valiasr Hospital in Tehran and the research sample is the data of 4196 neonates admitted to this ward from 2016 to August, 2020. The initial features for creating a predictive model of sepsis were prepared by examining the relevant information sources and under the supervision of professors and officials of Valiasr Hospital's mother and fetus research center and its validity was confirmed by 5 neonatal professors of this hospital. In this research, machine learning algorithms have been used to create a sepsis prediction model.
Results: Accuracy and AUROC(area under the ROC curve) parameters were used to evaluate the generated models. The highest values of Accuracy and AUROC are related to Adaptive Boosting and random forest algorithms, respectively.
Conclusion: Learning curves show that using different training examples and more complex selection of combination features improves the performance of the models. Further research is needed to evaluate the clinical effectiveness of machine learning models in a trial.
Reza Dehghan, Hamideh Reshadatjoo, Kambeiz Talebi, Hossein Dargahi,
Volume 14, Issue 6 (1-2021)
Volume 14, Issue 6 (1-2021)
Abstract
Background and Aim: Health tourism is one of the most important tourism types in Iran. Iran has many strengths in health tourism. Also, there are challenges such as communication and information inconsistency in the health tourism industry and the outbreak of COVID-19 disease. Due to the unknown issues about COVID-19, it is important to determine effective strategies to control the consequences and reduce the economic and social effects of the virus in all industries, especially the health tourism industry.
Materials and Methods: In this systematic review study, 500 published papers from 2018 to 2020 were evaluated. In the group interview section, we used the views of participated health tourism experts in the scientific events in Iran, Turkey, and Oman. Also, the SWOC Analysis model (strengths, weaknesses, opportunities, and challenges) and MAXQDA software were applied.
Results: The results showed that the selected strategies were defensive and competitive. This research showed that the strengths of the health tourism industry overcome the weaknesses and development opportunities outweigh the challenges. Also, the maintenance strategy is the best strategy to support health tourism in the current situation in Iran.
Conclusion: It is necessary to be following issues for the politicians of Iran's health tourism industry to design a comprehensive document of Iran Health Tourism Diplomacy, preparation of a strategic plan for the development of health tourism, establish an independent organization of Iran Health Tourism, develop electronic health in the health tourism industry, design a health tourism insurance system, and…, with the aim of entrance to the current markets and creating new foreign markets.
Materials and Methods: In this systematic review study, 500 published papers from 2018 to 2020 were evaluated. In the group interview section, we used the views of participated health tourism experts in the scientific events in Iran, Turkey, and Oman. Also, the SWOC Analysis model (strengths, weaknesses, opportunities, and challenges) and MAXQDA software were applied.
Results: The results showed that the selected strategies were defensive and competitive. This research showed that the strengths of the health tourism industry overcome the weaknesses and development opportunities outweigh the challenges. Also, the maintenance strategy is the best strategy to support health tourism in the current situation in Iran.
Conclusion: It is necessary to be following issues for the politicians of Iran's health tourism industry to design a comprehensive document of Iran Health Tourism Diplomacy, preparation of a strategic plan for the development of health tourism, establish an independent organization of Iran Health Tourism, develop electronic health in the health tourism industry, design a health tourism insurance system, and…, with the aim of entrance to the current markets and creating new foreign markets.
Niloofar Mohammadzadeh, Dr Seyed Hadi Sajjadi, Seyed Hasan Sajjadi,
Volume 15, Issue 1 (3-2021)
Volume 15, Issue 1 (3-2021)
Abstract
Background and Aim: Social networks that provide users with health data not only educate them but also play an active role in the health decision-making process. Health social networks, in addition to being a good tool for better patient communication with health care providers, can play an effective role in connecting similar patients with each other to receive social support. Social networking is one of the biggest achievements of Web 2, which facilitates communication between people. Despite the spread of social networks, their use in the field of health is still at its early levels. To implement an information system, it is first necessary to identify, design and model the related processes. The main purpose of this study was to provide technical documentation for the development of social networks in the field of health in order to facilitate future developments.
Materials and Methods: This study was an applied research. Due to the review of texts in the first phase, this research was descriptive. It is also a developmental research due to its technological dimensions in modeling and pattern model presentation. First, extracted features were confirmed based on experts’ opinions. Then, according to the identified features, social network modeling was performed at three levels of data, functional and process. Based on the modeling, a prototype model was designed and evaluated.
Results: In this research, technical documents were prepared for the development of social networks in the field of health in the three axes of data modeling, functional modeling and process modeling. In the usability assessment by Nielsen model, the created prototype based on modeling was evaluated. Finally, the number of problems in each case of the Nielsen model was determined. The case of "Visibility of system status" with 26.31 and "Consistency and standards" with 5.27 were associated with the highest and lowest problems, respectively.
Conclusion: The growing need and expansion of the use of social networks has created a good platform for using this tool in the field of health and exploiting its benefits. The present study focuses on providing technical documentation for the development of health social networks and to facilitate the development of social networks in the field of health.
Materials and Methods: This study was an applied research. Due to the review of texts in the first phase, this research was descriptive. It is also a developmental research due to its technological dimensions in modeling and pattern model presentation. First, extracted features were confirmed based on experts’ opinions. Then, according to the identified features, social network modeling was performed at three levels of data, functional and process. Based on the modeling, a prototype model was designed and evaluated.
Results: In this research, technical documents were prepared for the development of social networks in the field of health in the three axes of data modeling, functional modeling and process modeling. In the usability assessment by Nielsen model, the created prototype based on modeling was evaluated. Finally, the number of problems in each case of the Nielsen model was determined. The case of "Visibility of system status" with 26.31 and "Consistency and standards" with 5.27 were associated with the highest and lowest problems, respectively.
Conclusion: The growing need and expansion of the use of social networks has created a good platform for using this tool in the field of health and exploiting its benefits. The present study focuses on providing technical documentation for the development of health social networks and to facilitate the development of social networks in the field of health.
Nida Abdolahi, Mohamad Reza Nili Nili Ahmadabadi, Soghra Ebrahimi Qavam, Khadijeh Aliabadi, Mohammad Asgari,
Volume 15, Issue 1 (3-2021)
Volume 15, Issue 1 (3-2021)
Abstract
Background and Aim: Deep and sustainable learning requires a safe and healthy environment. Moreover, paying attention to the intertwined emotional, motivational, cognitive and social processes in the teaching-learning process is vital. Academic achievement motivation and self-regulated learning (SRL) are two important elements in this process that are influenced by the achievement emotions in the learning environment. Therefore, the aim of this study is to evaluate the effectiveness of instructional design model based on control-value theory of achievement emotions (CVT), on academic achievement motivation and self-regulation learning.
Materials and Methods: The research was quantitative and performed by Nonequlment design control group. The statistical population included female second year high school students in Tehran in the academic year of 1997-98, who were selected by multi-stage cluster random sampling in two experimental and control groups. The experimental group was trained according to the instructional design model based on CVT theory and the control group did not receive this training method. The questionnaire of academic achievement motivation and self-regulated learning was administered to the experimental and control groups as pre-test and post-test before and after the implementation of the model. Data were analyzed by inferential and descriptive statistics using SPSS software and multivariate covariance.
Results: The results of univariate analysis of covariance of group effect on the scores of dependent variables show that there is a significant difference between the experimental and control groups in cognitive strategy (F=11/94, P>0/05, η2=0/14), metacognition strategy (F=56/06, P>0/05, η2=0/44), motivational beliefs (F=6/36, P>0/05, η2=0/08) and academic achievement motivation (F=10/69, P>0/05, η2 =0/13).
Conclusion: The result of this study show that the use of instructional design model based on CVT theory has a positive effect on cognitive strategies, metacognition strategies, motivational beliefs and learners' academic achievement motivation.
Materials and Methods: The research was quantitative and performed by Nonequlment design control group. The statistical population included female second year high school students in Tehran in the academic year of 1997-98, who were selected by multi-stage cluster random sampling in two experimental and control groups. The experimental group was trained according to the instructional design model based on CVT theory and the control group did not receive this training method. The questionnaire of academic achievement motivation and self-regulated learning was administered to the experimental and control groups as pre-test and post-test before and after the implementation of the model. Data were analyzed by inferential and descriptive statistics using SPSS software and multivariate covariance.
Results: The results of univariate analysis of covariance of group effect on the scores of dependent variables show that there is a significant difference between the experimental and control groups in cognitive strategy (F=11/94, P>0/05, η2=0/14), metacognition strategy (F=56/06, P>0/05, η2=0/44), motivational beliefs (F=6/36, P>0/05, η2=0/08) and academic achievement motivation (F=10/69, P>0/05, η2 =0/13).
Conclusion: The result of this study show that the use of instructional design model based on CVT theory has a positive effect on cognitive strategies, metacognition strategies, motivational beliefs and learners' academic achievement motivation.
Mohammad Reza Mehregan, Shahrokh Yousefzadeh, Ali Reza Hatam Siahkal Mahalle,
Volume 15, Issue 2 (5-2021)
Volume 15, Issue 2 (5-2021)
Abstract
Background and Aim: The overall goal of the medical department is to develop and manage an efficient and effective supply chain. Intrinsic instability and unpredictability of treatment needs to require a flexible supply chain. Agility reflects the hospital's response to environmental changes, and agile hospitals are able to provide appropriate services to the patients. Hospital supply chain management agility needs to find the main aspects affecting the relationship and communication between them and to analyze the dimensions together. The purpose of this study was interpretive-structural modeling and analysis of dimensions of agile hospital supply chain management.
Materials and Methods: The research design combined descriptive - survey exploratory approach to the future. The population study were doctors, nurses and staff at the University of Medical Sciences. The Delphi technique was used to determine the dimensions of agility and the interpretive-structural modeling approach was used for analysis and modeling. Mick Mac software was used to analyze the dimensions of agility.
Results: The final model of agile hospital supply chain management with 16 dimensions had 8 levels, which was at the highest level of cost reduction and at the lowest level of organizational leadership commitment. The results indicate that leadership commitment is the foundation of supply chain agility in the hospital. Knowledge management variable had low impact and effectiveness and was known as a secondary leverage variable. The results showed that most agile supply chain management aspects of the main causes of complex communication and interaction, and the importance of agility in the hospital of the show.
Conclusion: The analysis and interpretation of functional from the aspect of Impact and Influence of agility dimensions in hospital environment Showed that, Dimensions of strategic planning, human resource development and staff skills training, human resource management and employee satisfaction, process management, process integration and organizational transformation, flexibility, organizational communication development and information management integration, service quality management and continuous improvement, acceptance of new technology and new ideas, speed of service, patient understand and satisfaction, monitor, find best responds demand and market sensitivity in the strategic area are located and They cause model instability and With high impact and high influence, They play an important role in the agility of hospital supply chain management.
Materials and Methods: The research design combined descriptive - survey exploratory approach to the future. The population study were doctors, nurses and staff at the University of Medical Sciences. The Delphi technique was used to determine the dimensions of agility and the interpretive-structural modeling approach was used for analysis and modeling. Mick Mac software was used to analyze the dimensions of agility.
Results: The final model of agile hospital supply chain management with 16 dimensions had 8 levels, which was at the highest level of cost reduction and at the lowest level of organizational leadership commitment. The results indicate that leadership commitment is the foundation of supply chain agility in the hospital. Knowledge management variable had low impact and effectiveness and was known as a secondary leverage variable. The results showed that most agile supply chain management aspects of the main causes of complex communication and interaction, and the importance of agility in the hospital of the show.
Conclusion: The analysis and interpretation of functional from the aspect of Impact and Influence of agility dimensions in hospital environment Showed that, Dimensions of strategic planning, human resource development and staff skills training, human resource management and employee satisfaction, process management, process integration and organizational transformation, flexibility, organizational communication development and information management integration, service quality management and continuous improvement, acceptance of new technology and new ideas, speed of service, patient understand and satisfaction, monitor, find best responds demand and market sensitivity in the strategic area are located and They cause model instability and With high impact and high influence, They play an important role in the agility of hospital supply chain management.
Haleh Mohammadiha, Gholam Reza Memarzadeh, Parham Azimi,
Volume 15, Issue 3 (8-2021)
Volume 15, Issue 3 (8-2021)
Abstract
Background and Aim: Health systems have played an important role in improving and increasing life expectancy. However, there is a large gap between health systems’ potential and their current performance, most of which relate to governance issues. The purpose of this study is to provide a model for improving the governance of the country's health system.
Materials and Methods: The present study is applied-developmental in terms of purpose. After reviewing the theoretical foundations and previous research, the governance strategies of the health system were identified. Then, using Fuzzy Delphi Method (FDM) and surveying 13 academic and executive experts who were purposefully selected, the research model was designed. Finally, in order to validate the model, 169 managers and specialists of health system departments in Tehran were interviewed with a questionnaire, and the data were analyzed using structural equation modeling (SEM) and SmartPLS software. At this stage, the sampling method was available and the sample size was calculated by Cochran's method.
Results: According to the research findings, in order to promote health governance, 10 main strategies and 58 sub-strategies should be considered. Identified strategies include strategic orientation, optimal financial resource management, stakeholder partnership development, knowledge resource development, administrative health promotion, technical knowledge development, value and ethical orientation, executive and operational platform development, Service delivery capacity management and Balanced and integrated stewardship. Also, the coefficient of determination for the outcome variable is 0.549 and the intensity of the effect of intervening/ facilitating and contextual factors on governance strategies is equal to 0.610 and 0.533, respectively.
Conclusion: The results showed that the governance of the health system is a multifaceted and complex phenomenon and in order to improve it, a set of strategies must be implemented. In addition, it is suggested that according to the issues and threats facing the health system, a roadmap and a long-term plan should be developed in order to move towards the governance model proposed in the present study.
Materials and Methods: The present study is applied-developmental in terms of purpose. After reviewing the theoretical foundations and previous research, the governance strategies of the health system were identified. Then, using Fuzzy Delphi Method (FDM) and surveying 13 academic and executive experts who were purposefully selected, the research model was designed. Finally, in order to validate the model, 169 managers and specialists of health system departments in Tehran were interviewed with a questionnaire, and the data were analyzed using structural equation modeling (SEM) and SmartPLS software. At this stage, the sampling method was available and the sample size was calculated by Cochran's method.
Results: According to the research findings, in order to promote health governance, 10 main strategies and 58 sub-strategies should be considered. Identified strategies include strategic orientation, optimal financial resource management, stakeholder partnership development, knowledge resource development, administrative health promotion, technical knowledge development, value and ethical orientation, executive and operational platform development, Service delivery capacity management and Balanced and integrated stewardship. Also, the coefficient of determination for the outcome variable is 0.549 and the intensity of the effect of intervening/ facilitating and contextual factors on governance strategies is equal to 0.610 and 0.533, respectively.
Conclusion: The results showed that the governance of the health system is a multifaceted and complex phenomenon and in order to improve it, a set of strategies must be implemented. In addition, it is suggested that according to the issues and threats facing the health system, a roadmap and a long-term plan should be developed in order to move towards the governance model proposed in the present study.
Moslem Soleymanpor, Mohamad Taghi Amini, Yazdan Shirmohammadi, Ali Shahnazari,
Volume 15, Issue 5 (1-2022)
Volume 15, Issue 5 (1-2022)
Abstract
Background and Aim: With the global expansion of Covid 19, the tourism industry has faced one of its biggest operational, commercial and financial crises, and most of the source-destination interactions have been suspended and have changed the view of the host community and their interactions with tourists. The purpose of this study is to provide a model for tourism development during the Covid 19 crisis and beyond.
Materials and Methods: This study was conducted using a combined (qualitative-quantitative) research approach. First, in a qualitative method with the data foundation approach, interviews with academic experts and managers and activists of the tourism industry in East and West Azerbaijan Provinces, and using purposeful and theoretical sampling, 18 people were selected to the point of information saturation. Semi-structured in-depth interviews were used to collect data. Data extracted from interviews were encoded by open, axial and selective coding. Then, to fit and test the obtained model in the second step (quantitative part), the method of structural equation modeling and confirmatory factor analysis were used.
Results: The final model consists of a total of 66 concepts extracted from the interviews, in the form of 14 categories and contextual categories, causal conditions, interventional conditions, strategies and finally, consequences and results of tourism entrepreneurship in pandemic crises and all of them affect this model. Based on the results of combined reliability, extracted variance, model determination coefficient and goodness-of-fit index, the drawn model in the field of path analysis has good experimental-theoretical assumptions and has a very good fit. Based on the obtained path coefficients, it can be concluded that the intervention conditions had the most and the causal conditions had the least impact on the strategic model of the tourism industry in pandemic crises.
Conclusion: Results indicate that strategies such as virtual tourism development, crisis management in the tourism industry, the development of domestic tourism by emphasizing the observance of health protocols and focusing on the development of tourism infrastructure, leads to the realization of consequences such as the maintenance and prosperity of tourism businesses, strengthening the tourism industry and creating a new tourism market for the post-corona era.
Materials and Methods: This study was conducted using a combined (qualitative-quantitative) research approach. First, in a qualitative method with the data foundation approach, interviews with academic experts and managers and activists of the tourism industry in East and West Azerbaijan Provinces, and using purposeful and theoretical sampling, 18 people were selected to the point of information saturation. Semi-structured in-depth interviews were used to collect data. Data extracted from interviews were encoded by open, axial and selective coding. Then, to fit and test the obtained model in the second step (quantitative part), the method of structural equation modeling and confirmatory factor analysis were used.
Results: The final model consists of a total of 66 concepts extracted from the interviews, in the form of 14 categories and contextual categories, causal conditions, interventional conditions, strategies and finally, consequences and results of tourism entrepreneurship in pandemic crises and all of them affect this model. Based on the results of combined reliability, extracted variance, model determination coefficient and goodness-of-fit index, the drawn model in the field of path analysis has good experimental-theoretical assumptions and has a very good fit. Based on the obtained path coefficients, it can be concluded that the intervention conditions had the most and the causal conditions had the least impact on the strategic model of the tourism industry in pandemic crises.
Conclusion: Results indicate that strategies such as virtual tourism development, crisis management in the tourism industry, the development of domestic tourism by emphasizing the observance of health protocols and focusing on the development of tourism infrastructure, leads to the realization of consequences such as the maintenance and prosperity of tourism businesses, strengthening the tourism industry and creating a new tourism market for the post-corona era.
Seyed Amir Reza Nejat, Mahmoud Bigler, Seyedeh Bahareh Kashian,
Volume 16, Issue 1 (3-2022)
Volume 16, Issue 1 (3-2022)
Abstract
Background and Aim: Intellectual capital, with its basic knowledge nature, is an intangible, strategic, unique and competitive advantage resource. The purpose of this study is to investigate the current state of intellectual capital maturity in the field of management and planning of Tehran university of medical sciences.
Materials and Methods: This research was applied in terms of purpose and with a quantitative approach in 1400 and a questionnaire was used to collect information. The statistical population is the middle and basic managers of the Vice Chancellor for Resource Management Development and Planning. Using Morgan table, 57 people were randomly selected and analyzed by t-test and non-parametric statistical tests using SPSS software. Has been. The content validity of the questionnaire was obtained by examining the research background and obtaining the opinions of experts, and the Cronbach’s alpha coefficient was used to assess the reliability, the value of which was 0.874.
Results: Statistical tests show that the five levels of intellectual capital management maturity follow a nonlinear pattern and the level of realization of the initial level characteristics, ie lack of intellectual capital structure, is higher than acceptable, but the statistical test of other levels of maturity Included; Managed, defined, quantified and optimal management is not significant at the significance level of 0.05.
Conclusion: The current situation of intellectual capital in the study population indicates that management is unaware of the importance of intellectual capital and no action has been taken to implement the knowledge capital management process. Although there is a lot of necessary infrastructure in the Vice Chancellor, however, insufficient understanding of the capabilities of intellectual capital management as a strategic resource is evident in this research. To reach the defined level and the next levels, the organization needs to identify, activate and direct the intangible source and then quantify, standardize and manage quantitatively and analyze the strengths and weaknesses and finally the continuous improvement of processes and Focus on innovation.
Materials and Methods: This research was applied in terms of purpose and with a quantitative approach in 1400 and a questionnaire was used to collect information. The statistical population is the middle and basic managers of the Vice Chancellor for Resource Management Development and Planning. Using Morgan table, 57 people were randomly selected and analyzed by t-test and non-parametric statistical tests using SPSS software. Has been. The content validity of the questionnaire was obtained by examining the research background and obtaining the opinions of experts, and the Cronbach’s alpha coefficient was used to assess the reliability, the value of which was 0.874.
Results: Statistical tests show that the five levels of intellectual capital management maturity follow a nonlinear pattern and the level of realization of the initial level characteristics, ie lack of intellectual capital structure, is higher than acceptable, but the statistical test of other levels of maturity Included; Managed, defined, quantified and optimal management is not significant at the significance level of 0.05.
Conclusion: The current situation of intellectual capital in the study population indicates that management is unaware of the importance of intellectual capital and no action has been taken to implement the knowledge capital management process. Although there is a lot of necessary infrastructure in the Vice Chancellor, however, insufficient understanding of the capabilities of intellectual capital management as a strategic resource is evident in this research. To reach the defined level and the next levels, the organization needs to identify, activate and direct the intangible source and then quantify, standardize and manage quantitatively and analyze the strengths and weaknesses and finally the continuous improvement of processes and Focus on innovation.
Mostafa Shanbehzadeh, Hadi Kazemi-Arpanahi, Raoof Nopour,
Volume 16, Issue 2 (5-2022)
Volume 16, Issue 2 (5-2022)
Abstract
Background and Aim: Breast cancer is one of the most common and aggressive malignancies in women. Timely diagnosis of breast cancer plays an important role in preventing the progression of this disease, timely treatment measures, and aftermath reducing the mortality rate of these patients. Machine learning has the potential ability to diagnose diseases quickly and cost-effectively. This study aims to design a CDSS based on the rules extracted from the decision tree algorithm with the best performance to diagnose breast cancer in a timely and effective manner.
Materials and Methods: The data of 597 suspected people with breast cancer (255 patients and 342 healthy people) were retrospectively extracted from the electronic database of Ayatollah Taleghani Hospital in Abadan city with 24 characteristics, mainly pertained to lifestyle and medical histories. After selecting the most important variables by using the Chi-square Pearson and one-way analysis of variance (P<0.05), the performance of selected data mining algorithms including RF, J-48, DS, RT and XG -Boost was evaluated for breast cancer diagnosis in Weka 3.4 software. Finally, the breast cancer diagnostic system was designed based on the best model and through C# programming language and Dot Net Framework V3.5.4.
Results: Fourteen variables including personal history of breast cancer, breast sampling, and chest X-ray, high blood pressure, increased LDL blood cholesterol, presence of mass in upper inner quadrant of the breast, hormone therapy with estrogen, hormone therapy with Estrogen-progesterone, family history of breast cancer, age, history of other cancers, waist-to-hip ratio and fruit and vegetable consumption showed a significant relationship with the output class at the P<0.05. Based on the results of the performance evaluation of selected algorithms, the RF model with sensitivity, specificity, accuracy, and F- measure equal to 0.97, 0.99, 0.98, 0.974, respectively, AUC=0.936 had higher performance than other selected algorithms and was suggested as the best model for breast cancer diagnosis.
Conclusion: It seems that using modifiable variables such as lifestyle and reproductive-hormonal characteristics as input to the RF algorithm to design the CDSS, can detect breast cancer cases with optimal accuracy. In addition, the proposed system can be effectively adapted in real clinical environments for quick and effective disease diagnosis.
Materials and Methods: The data of 597 suspected people with breast cancer (255 patients and 342 healthy people) were retrospectively extracted from the electronic database of Ayatollah Taleghani Hospital in Abadan city with 24 characteristics, mainly pertained to lifestyle and medical histories. After selecting the most important variables by using the Chi-square Pearson and one-way analysis of variance (P<0.05), the performance of selected data mining algorithms including RF, J-48, DS, RT and XG -Boost was evaluated for breast cancer diagnosis in Weka 3.4 software. Finally, the breast cancer diagnostic system was designed based on the best model and through C# programming language and Dot Net Framework V3.5.4.
Results: Fourteen variables including personal history of breast cancer, breast sampling, and chest X-ray, high blood pressure, increased LDL blood cholesterol, presence of mass in upper inner quadrant of the breast, hormone therapy with estrogen, hormone therapy with Estrogen-progesterone, family history of breast cancer, age, history of other cancers, waist-to-hip ratio and fruit and vegetable consumption showed a significant relationship with the output class at the P<0.05. Based on the results of the performance evaluation of selected algorithms, the RF model with sensitivity, specificity, accuracy, and F- measure equal to 0.97, 0.99, 0.98, 0.974, respectively, AUC=0.936 had higher performance than other selected algorithms and was suggested as the best model for breast cancer diagnosis.
Conclusion: It seems that using modifiable variables such as lifestyle and reproductive-hormonal characteristics as input to the RF algorithm to design the CDSS, can detect breast cancer cases with optimal accuracy. In addition, the proposed system can be effectively adapted in real clinical environments for quick and effective disease diagnosis.
Sakineh Motayerzadeh, Rahim Tahmasebi, Behrooz Kavehie, Azita Noroozi,
Volume 16, Issue 3 (8-2022)
Volume 16, Issue 3 (8-2022)
Abstract
Background and Aim: Vaccination is one of the most effective preventive measures to control of infectious diseases. To create effective interventions for the acceptance of the COVID-19 vaccine, it is important to identify the factors that affect the vaccine acceptance. The aim of this study was to determine the predictive power of the Extended Parallel Process Model (EPPM) for acceptance of Covid-19 vaccine.
Materials and Methods: In this cross-sectional study, 1455 people over 18 years old covered in health centers living in Bushehr province in cities of Bushehr, Genaveh, Tangestan, and Asaluyeh in 2021 were selected by convenience method. Data collection was online by using questionnaire included three sections comprised of demographic factors, questionnaire related to model constructs, and self-administered questionnaire related to acceptance of Covid-19 vaccine. Data were analyzed using chi-square, two independent sample T-test and logistic regression; in SPSS software.
Results: Out of 1455 participants, 1067 persons (73.3%) had been vaccinated. The results showed that men (P=0.006), people with higher education (P=0.001), government employees (P=0.001), single people (P=0.01), people with history of specific disease (P=0.05), individuals with a history of Covid-19 positive test (P=0.001) and their family (P=0.03) were more than other vaccine recipients. Perceived severity, response efficacy and perceived self-efficacy were predictors of vaccine acceptance. Predictive variables and constructs explained 43.8% of changes in vaccine acceptance. Among the participants in the study, 1366 (93.9%) were in the fear control process, in which the highest defense response has been avoided.
Conclusion: In order to increase the acceptance of the vaccine, the efficacy and effectiveness of the vaccine and the severity of the complications of the disease should be emphasized. Therefore, public health campaigns aimed at increasing vaccine acceptance should provide a high level of transparency about the safety and effectiveness of vaccines to the community.
Materials and Methods: In this cross-sectional study, 1455 people over 18 years old covered in health centers living in Bushehr province in cities of Bushehr, Genaveh, Tangestan, and Asaluyeh in 2021 were selected by convenience method. Data collection was online by using questionnaire included three sections comprised of demographic factors, questionnaire related to model constructs, and self-administered questionnaire related to acceptance of Covid-19 vaccine. Data were analyzed using chi-square, two independent sample T-test and logistic regression; in SPSS software.
Results: Out of 1455 participants, 1067 persons (73.3%) had been vaccinated. The results showed that men (P=0.006), people with higher education (P=0.001), government employees (P=0.001), single people (P=0.01), people with history of specific disease (P=0.05), individuals with a history of Covid-19 positive test (P=0.001) and their family (P=0.03) were more than other vaccine recipients. Perceived severity, response efficacy and perceived self-efficacy were predictors of vaccine acceptance. Predictive variables and constructs explained 43.8% of changes in vaccine acceptance. Among the participants in the study, 1366 (93.9%) were in the fear control process, in which the highest defense response has been avoided.
Conclusion: In order to increase the acceptance of the vaccine, the efficacy and effectiveness of the vaccine and the severity of the complications of the disease should be emphasized. Therefore, public health campaigns aimed at increasing vaccine acceptance should provide a high level of transparency about the safety and effectiveness of vaccines to the community.
Negin Saldar, Rahim Shahbazi,
Volume 17, Issue 2 (5-2023)
Volume 17, Issue 2 (5-2023)
Abstract
Background and Aim: Health literacy plays a role in “reducing human casualties and financial costs” in a society. Emotional intelligence and media literacy also contribute to people’s success in life. Therefore, the aim of this study was to investigate the mediating role of media literacy in the relationship between emotional intelligence and health literacy among graduate students of Azarbaijan Shahid Madani University.
Materials and Methods: This research is based on the nature and general characteristics, quantitative; Based on the purpose, it is applied and based on the research method and data collection method, is a descriptive correlation based on structural equation model. The statistical population was graduate students of Azarbaijan Shahid Madani University in 2020 (2218 students). The statistical sample of the research is 327 people who were selected by stratified random sampling method. To collect data, Emotional Intelligence Questionnaire (1998), Montazeri et al. Health Literacy Questionnaire (2014) and media literacy questionnaire were used. The reliability of the questionnaires was obtained using Cronbach’s alpha coefficient of 0.91, 0.84 and 0.79, respectively. The collected data were analyzed using descriptive statistics and inferential statistics (structural equation model) using SPSS and LISREL software.
Results: The findings showed the mean of emotional intelligence, health literacy and media literacy of graduate students of Azarbaijan Shahid Madani University is 3.10, 3.47 and 3.58, respectively. Also, the results showed a significant relationship between emotional intelligence and students’ health literacy. According to the findings, there is a significant relationship between emotional intelligence with media literacy, and media literacy with health literacy. Also, the media literacy variable plays a mediating role in the relationship between emotional intelligence and health literacy (coefficient) of 0.58 units. The results of the structural equation model test also showed that the proposed conceptual model fits the relationship between emotional intelligence, health literacy and students’ media literacy.
Conclusion: Media literacy can not only directly affect students’ health literacy, but also has a mediating role between emotional intelligence and health literacy. Due to the effect of emotional intelligence on students’ health and media literacy, it is recommended that the necessary planning to be done in graduate education and to strengthen emotional intelligence.
Materials and Methods: This research is based on the nature and general characteristics, quantitative; Based on the purpose, it is applied and based on the research method and data collection method, is a descriptive correlation based on structural equation model. The statistical population was graduate students of Azarbaijan Shahid Madani University in 2020 (2218 students). The statistical sample of the research is 327 people who were selected by stratified random sampling method. To collect data, Emotional Intelligence Questionnaire (1998), Montazeri et al. Health Literacy Questionnaire (2014) and media literacy questionnaire were used. The reliability of the questionnaires was obtained using Cronbach’s alpha coefficient of 0.91, 0.84 and 0.79, respectively. The collected data were analyzed using descriptive statistics and inferential statistics (structural equation model) using SPSS and LISREL software.
Results: The findings showed the mean of emotional intelligence, health literacy and media literacy of graduate students of Azarbaijan Shahid Madani University is 3.10, 3.47 and 3.58, respectively. Also, the results showed a significant relationship between emotional intelligence and students’ health literacy. According to the findings, there is a significant relationship between emotional intelligence with media literacy, and media literacy with health literacy. Also, the media literacy variable plays a mediating role in the relationship between emotional intelligence and health literacy (coefficient) of 0.58 units. The results of the structural equation model test also showed that the proposed conceptual model fits the relationship between emotional intelligence, health literacy and students’ media literacy.
Conclusion: Media literacy can not only directly affect students’ health literacy, but also has a mediating role between emotional intelligence and health literacy. Due to the effect of emotional intelligence on students’ health and media literacy, it is recommended that the necessary planning to be done in graduate education and to strengthen emotional intelligence.
Kourosh Abbasiyan, Mohammad Alimoradnori, Mohammad Bagher Karami,
Volume 18, Issue 2 (5-2024)
Volume 18, Issue 2 (5-2024)
Abstract
Background and Aim: Managers, as the main decision-makers in facing various internal and external organizational problems, play a significant and determining role in the success or even failure of an organization. If competent and experienced managers are positioned at the top of organizations, the success of these organizations in achieving their goals will be guaranteed and an organization can achieve maximum efficiency with minimal resources. The aim of this study was to design a model of managerial competencies for hospital managers.
Materials and Methods: This qualitative research was conducted from year 2020 to 2022. After reviewing studies related to the topic, the extracted competencies were given to 19 experts consisted of relevant academic faculty members and managers with experience in the healthcare system and hospitals. Eventually, a managerial competency model was formulated through the use of the Delphi method and expert panel discussions. Collected data were analyzed in Excel software.
Results: The developed model in this research for the concept of hospital managers’ competencies includes 33 managerial competencies of hospital managers in four main management functions (planning, organizing, leadership and control) and managerial roles, which starts from literature review and performing two Delphi steps and implementing two expert panel plans. In the competency of hospital managers model, the planning dimension consists 4 components, organizing consists 4 components, leadership consists 12 components, control consists 4 components, and managerial roles consists 9 components. Strategic thinking, which is a subset of planning, has the highest weight (0.495) and highest rank among other components, and continuous improvement, which is a subset of managerial roles, has the lowest weight (0.033) and lowest rank among other components.
Conclusion: This study proposes an exclusive and comprehensive model, utilizing practical techniques as a suitable solution for evaluating the managerial competencies of hospital managers. The proposed framework in this study can serve as a standard performance assessment tool for evaluating managers.
Materials and Methods: This qualitative research was conducted from year 2020 to 2022. After reviewing studies related to the topic, the extracted competencies were given to 19 experts consisted of relevant academic faculty members and managers with experience in the healthcare system and hospitals. Eventually, a managerial competency model was formulated through the use of the Delphi method and expert panel discussions. Collected data were analyzed in Excel software.
Results: The developed model in this research for the concept of hospital managers’ competencies includes 33 managerial competencies of hospital managers in four main management functions (planning, organizing, leadership and control) and managerial roles, which starts from literature review and performing two Delphi steps and implementing two expert panel plans. In the competency of hospital managers model, the planning dimension consists 4 components, organizing consists 4 components, leadership consists 12 components, control consists 4 components, and managerial roles consists 9 components. Strategic thinking, which is a subset of planning, has the highest weight (0.495) and highest rank among other components, and continuous improvement, which is a subset of managerial roles, has the lowest weight (0.033) and lowest rank among other components.
Conclusion: This study proposes an exclusive and comprehensive model, utilizing practical techniques as a suitable solution for evaluating the managerial competencies of hospital managers. The proposed framework in this study can serve as a standard performance assessment tool for evaluating managers.
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