فهرست مطالب elham nazari

A significant portion of the population suffers from maladaptive perfectionism, which, without appropriate psychological treatment, can lead to various psychological disorders and impairments in occupational, social, and educational functioning. Therefore, the present study aimed to examine the effectiveness of cognitive-behavioral therapy in reducing perfectionism.

This study utilized a quasi-experimental design with a pretest-posttest and follow-up period, including a control group. The target population consisted of all students of Zanjan University of Medical Sciences in 2020. The sample was selected in two stages: first, 350 individuals were selected from the target population using convenience sampling, and the Frost Multidimensional Perfectionism Scale (FMPS) was administered to them. In the second stage, individuals who scored above the diagnostic cutoff point (score equal to or higher than 90) on the FMPS were selected (n = 314). Finally, based on entry and exit criteria and the progression of subsequent stages, a sample of 40 individuals was randomly assigned to the experimental group (n = 20) and the control group (n = 20). The inclusion criteria included residence in Zanjan at the time of the study, willingness to participate in the research, and scoring above the diagnostic cutoff on the FMPS. The exclusion criteria included the onset of psychiatric illnesses during the intervention, previous experience of cognitive-behavioral interventions, particularly more than 5 sessions of cognitive-behavioral therapy, more than two consecutive absences in the group protocol, failure to participate in one of the three assessment stages, and obtaining a score of 140 or higher on the FMPS. The experimental group received group cognitive-behavioral therapy based on perfectionism once a week for 90 minutes. The participants were assessed at three-time points: pretest, posttest, and two-month follow-up. The data were analyzed using SPSS-25 software and repeated measures analysis of variance.

The results of the analysis indicated that group cognitive-behavioral therapy led to a significant improvement in overall perfectionism scores, particularly in the subscales of concerns over mistakes and parental criticism (p < 0.05). The mean pretest score for overall perfectionism in the experimental group was 83.110, which decreased to 39.98 in the posttest. For the subscale of concerns over mistakes, the mean scores at the pretest and posttest were 72.10 and 22.9, respectively. Finally, for parental criticism, the mean scores at pretest and posttest were 28.8 and 61.7, respectively. These improvements were significant compared to the control group.

The findings of this study support the effectiveness of group cognitive-behavioral therapy as an intervention that can reduce maladaptive perfectionism in individuals with perfectionistic traits. Therefore, therapists can utilize this treatment to improve perfectionism in their clients.

This critical study was aimed to investigate the utility of the Global Health Security Index in predicting the current COVID-19 responses.

Number of infected patients, deaths, incidence and the death rate per 100,000 populations related to 55 countries per week for 26 weeks were extracted. The relationship of GHSI scores and country preparedness for the pandemic was compared.

According to the GHSI, the incidence rate in most prepared countries was higher than the incidence rate in the more prepared countries, and which was higher than the incidence rate in the least prepared countries. However, Prevention, Detection and reporting, Rapid response, Health system, compliance with international norms and Risk environment, as well as Overall, the incidence and death rate per 100,000 people have not been like this.

Due to mismatch between the GHSI score and fact about COVID-19 incidence, it seems necessary to investigate the factors involved in this discrepancy.

Despite the high prevalence of social anxiety disorder and the necessity of conducting etiological studies, the existing measures of social anxiety lack robust factor structure due to methodological flaws, leading to doubtful results.

The present study is aimed to investigate the factor structure, reliability, and convergent validity of the Iranian version of the Social Phobia Inventory (I-SPIN).

This is a cross-sectional, psychometric study. Two large samples (N1=1210, N2=228) have been selected with the convenience sampling method from the student population of the three different universities in Zanjan city (i.e., University of Medical Sciences, Azad, and Payame Noor University) who were studying in those universities from February to July 2020. CAQ-GE, BAI, BDI-II, and IUS-12 were used in the present study. Exploratory and confirmatory factor analysis were conducted using Mplus-7.4 and SPSS-26 was used to perform internal consistency and validity analyses.

Exploratory and confirmatory factor analysis revealed that the two-factor model best fit the data. Besides, the results indicated that the I-SPIN has a positive and significant correlation with anxiety-related measures (p<0.01) and acceptable internal consistency (α=0.92).

Considering the excellent psychometric properties and a robust factor structure of the I-SPIN in an Iranian college student sample, using this measure would improve the accuracy of future studies and help us broaden our knowledge of the underlying mechanisms of this disorder.

This study was conducted to examine the compliance of the administration of Carbapenems in patients undergoing open heart surgery with antibiotic monitoring guidelines of the Ministry of Health and Medical Education in Iran.

Antibiotic resistance is a significant challenge for healthcare systems and can lead to increased costs, prolonged treatment duration, and higher mortality rates among hospitalized patients.

This cross-sectional descriptive study included 70 patients (35 women and 35 men) who underwent heart surgery between March 2021 and the end of August 2021 at Shahid Rajaei Heart Hospital in Tehran, Iran. Data were collected through direct patient interactions and reviewing patients' medical records and were analyzed using SPSS software version 26.

The data revealed that 81 percent of patients received appropriate Carbapenem prescriptions, while 19 percent received an incorrect prescription. The most prescribed antibiotic, with a frequency of 92.9 percent, was Meropenem, and the average number of antibiotics prescribed for each patient was 1.87. The highest rate of Carbapenem prescription was observed in patients with ventilator-induced pneumonia (55.7 percent) and those undergoing coronary artery bypass graft (CABG) surgery (45.7 percent). Approximately 55.7 percent of patients required dose adjustments 72 hours after receiving Carbapenem due to increased creatinine clearance, and 15.7 percent needed to discontinue the drug. The most common causative infection agents were Candida Albicans, Klebsiella Pneumoniae, and Staphylococcus Aureus, respectively.

Antibiotic management programs can limit the irrational use of antibiotics such as Carbapenems and help improve the treatment of infections by preventing the development of antibiotic resistance.

Injuries are the causes of irreparable damages and costs in urban and rural settings. Preventive procedures are effective if correct related information is gathered and provided. Therefore, this study aimed to investigate the injury patterns and related factors in a large teaching hospital.

The current cross-sectional study was conducted at Edalatian Emergency Center, Mashhad, Iran, in 2016. All study subjects were extracted from the Hospital Information System (HIS).The demographic characteristics and injuries-related factors of 6,350 patients were extracted from the HIS. The extracted variables were emergency severity index (ESI), type of referral, referral reason, insurance organizations, age, anatomic site of injuries, and month of referral. The data were analyzed in SPSS software (version 21) using the descriptive statistics method (frequency and percentage).

The majority of the study population was composed of males (%76.4). In total, 98.3% of the patients were classified into the semi-urgent and non-urgent levels, and 75.6% of the cases were affected in the right upper extremity. The most common age group was between 10-20 (69.4%) years, and the majority of the cases were admitted in June, July, and August.

The current study determined the pattern and most important reasons for injuries' referral to an emergency department. Accordingly, the injuries were more frequent in the young people and active human force in our community. Furthermore, there was a significant difference among the frequencies of injury incidence in the summer holidays. It seems necessary to develop preventive procedures for injuries.

Given, widespread COVID-19 across the world a comprehensive literature review can be used to forecast COVID-19 peak in the countries. The present protocol study aimed to explore epidemic peak prediction models in communicable diseases.

This protocol study was conducted based on Arksey and O'Malley's. This framework encompasses purpose and hypothesis, modeling, model achievements aspects. A systematic search of English in PubMed was conducted to identify relevant studies. In the pilot step, two reviewers independently extracted the variables from 10 eligible studies to develop a primary list of variables and a data extraction form. In the second step, all eligible studies were assessed by researchers. In the third step, two data extraction forms were combined. The data were extracted and categories were created based on frequency. Qualitative and quantitative methods were used to synthesize the extracted data.

The current study were focused on forecasting the epidemic peak time that is a worlds’ concern issue. The results of current scoping review on prediction methods for epidemic disease can provide foundational knowledge, and have important value for the prediction model studies of COVID-19.

Our findings will help researchers by a summary of evidence to present new ideas and further research especially for studies werefocused on COVID-19. Our results can improve the understanding of prediction methods for COVID-19.

The rate of mobile phone use among people, especially young people is increasing. The proper use of mobile phone for utilizing the advantages and stay away from its complications is essential. To obtain a model and how to use mobile phone will facilitate planning for preventing complications. So, in this article, questionnaire development with aimed at examining the pattern of mobile phone use among students of Iranianuniversities.

In this study a self-administered questionnaire was designed based on a literature review in PubMed, EMBASE, Science Direct, and Google Scholar database and using 2 rounds of the Delphi method with the presence of 10 experts from different fields.

In the first Delphi round 6 questions were obtained and in the second round 15 questions were confirmed. The mean of Content Validity Ratio and Content Validity Index for the questionnaire was 93.32 and 92.70, respectively. Aquestionnaire was designed and developed according to the purpose.

Usingthe designed questionnaire, the mobile usage pattern among student universities can be examined and solutions can be considered for them.This can prevent further consequence.

Recently, with the surge in the availability of relevant data in various industries, the use of Information Fusion technique for data analysis is increasing. This method has several advantages, such as increased accuracy, and the use of meaningful information. In addition, there are certain challenges, including the impact of data type and analytical method on results. The goal of this study is to propose a framework for introducing the advantages and classifying the challenges of this technique. 

We conducted a review of articles published between January 1960 and December 2017 for the design stage and from January 2018 to December 2018 for the evaluation stage. Articles were identified from various databases such as Science Direct, IEEE, Scopus, Web of Science, and Google Scholar, using the keywords decision fusion, information fusion, and symbolic fusion. We report the advantages and challenges of the methodologies described in these articles. Analysis was conducted in accordance with PRISMA guidelines. 

A total of 132 articles were identified in the design stage and 90 articles were identified in the evaluation stage. Categories within the framework for challenges include “hardware and software requirements for processing and maintaining the process”, “data” and “data analysis method”. The categories for advantages include “value modeling”, “preferable management of uncertainty and variability”, “excellent decision making”, “comprehensive interpretation and representation”, “data management” and “simplicity of infrastructure”. Our results indicate using these two frameworks with 95% Confidence interval. 

An overall understanding of the advantages and challenges of the information fusion technique could act as a guide for the researcher for the correct usage of this technique

The coronavirus outbreak has become a serious issue of the entire world. In some ways, the ability to provide outbreak rate prediction is helpful. Therefore the main purpose of this study was to investigate the incidence pattern of Confirmed COVID-19 Cases in Iran, and comparison between countries with high infected person such as China, Italy and South Korea.

In this cross sectional study 126789 infected cases with COVID 19 related countries with highest infection, China, Italy, Iran and South Korea in 30 day timespan was extracted from the cumulative frequency chart at https://www.worldmeters. Info/coronavirus/. The incidence rate pattern was presented.

The findings show the frequency pattern of the infected person’s frequency within 30 days since the first case has observed in Iran are similar. Although incidence rate coronavirus is similar to other countries in during 14 days, but after the 14th day, there is a noticeable difference between the obtained pattern of confirmed cases in Iran and other countries. There is a spectacular difference in the number of patients in Iran and South Korea after the seventh day and between Iran and Italy after the fourteenth day.

The Covid-19 quickly spread across the world and caused varying challenges. Thus the prevention strategies aimed at reducing transmission in the community are a necessity.

The rapid outbreak of Coronavirus has led to the worrying situation. Prevention strategies such as a stay at home offer great opportunities for transmission reduction of the virus. Therefore, the purpose of current study has developed a questionnaire to investigate the reasons for not staying at home in Iran.

In this study a self-administered questionnaire was designed in two Delphi rounds and based on 50 expert and 10 expert opinions from different fields of study.

In the first Delphi round 11 questions were obtained and in the second round 14 questions were confirmed. The mean of CVR and CVI for the questionnaire was 95.33 and 94.67, respectively. A questionnaire was designed and developed according to the purpose.

Using the designed questionnaire, the reasons why some people do not pay attention to home quarantine can be examined and solutions can be considered for them. This can prevent further corona spread.

Decision fusion has emerged as a data management technique due to the diversity and scalability of data in health care. This first-scope review aimed to investigate the use of this technique in health care.

A query was carried out on PubMed, Science Direct, and EMBASE within 1960-2017 using such keywords as decision fusion, information fusion, symbolic fusion, distributed decisions, expert fusion, and sensor fusion, in conjunction with med-* and health-care. The articles were analyzed in terms of methodology and results.

The literature search yielded 106 articles. Based on the results, in the field of health care, the articles were related to image processing (29%), sensors (22%), diagnosis area(10%), biology (6%), health informatics (8%), and signal process (15%). The majority of articles were published in 2011, 2012, and 2015, and the USA had the largest number of articles. Most of the articles were about engineering and basic sciences. Regarding healthcare, the majority of studies were conducted on the diagnosis of diseases (80%), while 9% and 11% of articles were about prevention and treatment, respectively. These studies applied the following

intelligent methods (44%), new methods (36%), probabilistic (13%), and evidential methods (7%). The dataset was as follows: research project data (49%), online dataset (42%), and simulation (9%). Furthermore, 49% of articles mentioned the applied software, among which classification and interpretation were reportedly the most and the least used methods. Discussion and

Decision fusion is a holistic approach to evaluate all areas of health care and elucidate diverse techniques that can lead to improved quality of care. Innovation: This article is the first scope review article about the application of the decision fusion technique in the field of health care, building on an established protocol. Decision fusion can reduce the cost of care and improve the quality of health care provision. Therefore, this article can help care providers understand the benefits of this technique and overcome challenges in adopting decision fusion technology.

The skilled IT staff about big data analytics can motivate organizations to adopt the big data analytics. The aim of the current study is to present the knowledge, attitude, and challenges of the big data analytics based on IT staffs’ viewpoints in a developing country.

A self-administered semi-structured questionnaire was developed based on a literature review. Content validity and face validity were measured using Delphi technique. The questionnaire comprised of three parts including knowledge, attitude, and challenges. Descriptive statistics were used to summarize the results. The chi-square test was applied to identify associations between knowledge and attitude of participants with the demographic characteristics.

Out of a total of 250 IT staffs, 120 participated in the study. Knowledge levels were low, moderate, and high in 35.0%, 33.3%, and 31.7 % of the participants, respectively. The two most affecting factors on the knowledge level of participants were age groups and sex. IT staffs hold a positive attitude toward big data analytics. The most of IT staffs believed that big data management is necessary for the country and they agreed that big data analyzes can provide many advantages to organization managers. As well, 35 challenges of the big data analytics were identified.

Theresults showedthat the big data analytics face with many problemsin following issues: awareness and education, recruiting skilled specialists, presentation big data analytics benefits to IT managers and policy-makers, conducting research projects, developing a strategic plan at national and local levels.

The coronavirus outbreak has become a serious issue of the entire world. In some ways, the ability to provide outbreak rate prediction is helpful. Therefore the main purpose of this study is to investigate the incidence pattern ofConfirmed COVID-19 Cases in Iran, and comparison between countries with high infected person such as USA, Brazil and others.

A total of 7801401infected cases with COVID 19 related countries with highest infection, USA, Brazil, India, Russia, Peru, Chile, Mexico, Spain, UK, South Africa, Iran and Pakistanin 17 weeks timespan was extracted from the Daily New Cases chart athttps://www.worldmeters. Info/coronavirus/. Also, the incidence rate pattern was presented.The frequency distribution charts usedto compare countries.

In Iran, from the interval of first week to the end of fifth week after observing the 100th case of infection, the trend of identifying patients was upward, and after that, it showed a decreasing tendency until the end of the 10th week. However, it seems that from the 10th to the 12th week, the trend has been increasing and after that it has been almost constant. In countries such as South Africa, India, and Brazil, however, this trend has roughly always been ascending during this period, and in other countries it has been fluctuated.

The Covid-19has become pandemic disease. Finding similarincidence rate with other countries aimed for applyingappropriate intervention is helpful.

One of the challenges of multidisciplinary disciplines such as Medical Informatics, is the lack of familiarity with research fields. Due to the specializations and clinical facilities concentrated in each university, research is being done differently and with variety. Therefore, in this study, in order to identify the most researched fields and the neglected fields of research, the dissertations done in the field of medical informatics in Iranian universities were studied based on the health informatics framework.

Defended dissertations available to master and doctoral students of medical informatics during 2011 to 2019 in the universities of Tehran, Iran, Tarbiat Modares, Shahid Beheshti, Shiraz, Tabriz and Mashhad were collected. Three medical informatics expertsassigned dissertation titles to a competency and an area of skill based on health informatics competencies framework. The second stage of the study was performed by two other experts (different from the previous three experts). Each dissertation title was assigned to a specific competency anda specific area of skill by the majority opinion method.

The results showed that the most of master and doctoral dissertations were in the field of information science and methods, in which area of skill of data analysis and visualization, whichdecision support systems and informatics for participatory healthwere more than others. AmongPhD students, the area of skillof decision support system and architecture of health information systems weremore popular. PhD students at the universities of Mashhad, Tehran and Shahid Beheshti worked in the field of methods and basic principles of activities more than other areas, information and communication technology, biomedical science and health were not considered.

Results of this research could be helpful forfield researchers in terms of conducting new research in the field and can help to design useful, scientific and effective research projects.

Big data analysis has raised controversies today and attracted many students and academics for its dramatic advantages. The present research aims to investigate the extent to which students in different universities of Mashhad are familiar with this type of analysis.

The present cross-sectional research was conducted on university students of different fields of study in Mashhad, Iran. A questionnaire wasdeveloped based on a review of the related literature in PubMed, Google Scholar, Science Direct and EMBAS. The target questionnaire explored students' knowledge of big data analysis. To this aim, 142 students participated in this research and completed the target questionnaire. Their responses were analyzed descriptively.

The majority age of participants ranged between 21 and 28 years. 59% of these participants were female; 27% had less than a year of work experience; the academic grade of the majority of participants was Master's or Ph.D. 42% enjoyed a desirable knowledge of big data analysis. The largest number of hours of scientific and non-scientific studies belonged to basic science students and more specifically that of pharmacology.

Despite the significance and benefits of big data analysis, students' unfamiliarity with the essentiality of these analyses in industries and research is considerable. It seems that the field or grade of studies has no effect on one's knowledge of big data analysis. Probably, the design of specialized educational courses with this concern can help to promote individuals' knowledge of big data analysis.

Nowadays Big Data Analytics has attracted students for research due to its very high capabilities, but there are also obstacles to analyses that need to be addressed. Therefore, the purpose of this study is to investigate the viewpoints of students of different disciplines at Mashhad universities on the challenges of this analysis.

This study is a cross-sectional study conducted on students of different universities and fields such as computer engineering, pharmacy, industry and biology in Mashhad, Iran. A questionnaire based on literature review in Pubmed, Google scholar, and science direct databases was designed by 10 experts from different disciplines using Delphi method. 185 students participated in the study. Students' viewpoints on the challenges were also collected. Descriptive and analytical results were reported using SPSS 21 and Maxqda software.

The age range of most students was 25 - 34 years. 54.2% were female. Most of the participants in this study were students of engineering and medical informatics. Of the participants in this study, 96.4% considered big data analytics necessary, 50.6% were familiar with the benefits of analytics. Lack of awareness, inadequate management, lack of managers' knowledge, lack of expertise, and lack of priority were the most important challenges for students.

Despite the importance and benefits of big data analytics, challenges are a major barrier to use that need to be addressed.

The code of ethics is constantly being reviewed, due to some changes in the professional fields of psychologists and the needs of their target groups. Conducting comparative studies creates sensibilities in experts to meet the challenges of the code of ethics. Therefore, the aim of this study is to compare the code of ethics of psychologists in Iran with the Netherlands and Switzerland's.

The present study is comparative study. Using Science Direct, Pubmed and Google Scholar databases between 2000 and 2019, the keywords of code of ethics, psychology, Iran, Netherlands and Switzerland and their Persian equivalents were searched separately and in combination. The code of ethics of the Netherlands and Switzerland were purposefully selected based on the research gaps in this field; it was also structurally and contently examined, as a basis for comparison, by the Iranian code of ethics.

Structurally, all three codes of ethics have common ground in the introduction and basic principles, but Switzerland and Netherlands ' codes of ethics differ in the code of conduct. In terms of content, Switzerland and Netherlands' codes of ethics are based on clear, definite and operational codes. In addition, they have adapted to the new conditions more than the Iranian code of ethics, especially in the codes related to advertising and resolving ethical issues and they have been able to create organizational and administrative structures. Ethical Considerations: Honesty and fidelity were considered in the reporting of the texts, citing sources and avoiding any bias.

By making new changes in the Iranian code of ethics, especially in the field of clarifying the concepts and basic principles of ethics, as well as providing accurate ethical codes, taking into account the practical aspects and the method of their implementation, some challenges can be addressed.

One of the challenges of multidisciplinary disciplines such as Medical Informatics, Health Information Technology, etc., especially for those who have just begun research in this field, is the lack of familiarity with some of the key terms and applications of software concepts, including frameworks. Worksheets are widely used in the field of health care and have produced valuable results. Considering the framework advantages in health care sector among designing and estimating the systems in standard ways and comparing the systems in principle for identifying the gaps and introducing the capabilities, avoidance of reworking seem necessary. Therefore, after reviewing the  literature we will discuss about meaning, overlapping to the other meanings, components, steps, advantages, challenges, the types of frameworks and their applications in healthcare sector. This study is based on search of databases (Proquest, PubMed, Google Scholar, Scence Direct, Scopus, IranMedex, Irandoc, Magiran, ParsMedline and Scientific Information Database (SID)). This investigation has done with the websites and the specialized books with standard key words. After a careful study, 56 sources were selected and used in edition of final article. The results of this research can help the researchers to do the new research and understand the important concepts of that, thus it can be useful in designing and researching projects for researchers and health care providers as well.

Today, with the advent of technology, due to the growing data in the field of health care, it is difficult to manage and analyze this type of data known as the Big Data. This analysis has many capabilities to improve the quality of care, reduce errors and reduce costs in care services.

This study is based on search of databases (PubMed, Google Scholar, Science
Direct, and Scopus). This investigation has done with the websites and the specialized books with standard key words. After a careful study, 50 sources were in the final article.

Since the Big Data Analysis in the field of health has been growing and also
considered in recent years, this survey identified the necessity of these analyses, the definition of the Big Data, the benefits, resources, architecture, applications, analysis, platforms, Examples and challenges in the field of health care.

Familiarity with the big data concepts in the field of healthcare can help researchers in conducting applied research and thus improve the quality of health care services and reduce costs.

Considering the conditions of Tehran metropolis management, the obstacles to implementation of the Constitution are identified with the aim of establishing a sustainable relationship between national and local sovereignty. Although, the constitution offers a power devolution based on the Soviet system, Tehran's disputes suggests disorderliness in this regard. Since there is a collection of formal and informal political settings, the obstacels can be investigated by the relationship between a set of Structure, Culture, and Agency. Based on the Delphi method, findings are obtained from the views of experts and are assorted by content analysis and ranked by Friedman test after three rounds. The results demonstrated that the barriers are “The centralization of the structure of national sovereignty due to fear of power weakening” and “a political rent-based economy” at the structural level which have caused turmoil in regulating the relationship between the national and local sovereignty in Tehran.

The rapid development of technology over the past 20 years has led to explosive data growth in various industries, including defense industries, healthcare. The analysis of generated Big Data has recently been addressed by many researchers, because today's Big Data analysis are one of the most important and most profitable areas of development in Data Science and companies that are able to extract valuable knowledge among the massive amount of data at logical time can earn significant advantages . Accordingly, in this survey, we investigate definition of the Big Data and the data sources. Also look at advantages, challenges, applications, analysis and platforms used in the Big Data.

In the field of health, information and communication technology plays an important role, the world is experiencing the era of communication, the field of health is not asymmetrical. According to the study, Iran is one of the countries that is at high risk of diabetes, and continues to increase in Iran and in most countries. The purpose of this paper is to review the literature on the effectiveness of Information and Communication Technology (ICTs) in the treatment of type 1 and type 2 diabetes.

This study was conducted as a review and through a search of valid information databases such as PubMed, Science direct, and Google Scholar. After the final extraction from the 106 papers in the cellular field 37% and 36% in telemedicine and 27% in the Internet topic from 2010 to 2018, were finalized.

The findings of the study showed that the recent developments in information technology combined with services for cost optimization have increased and the current use of information technology (IT) offers unique opportunities for patients with diabetes. Internet, mobile phone and telemedicine services can facilitate and improve communication between patients and healthcare professionals and play an important role in managing diabetes. The growing challenge is the proper management of diabetes to play an important role by employing innovative approaches aimed at improving patient outcomes and reducing the incidence of adverse healthcare systems.

This study is an overview of information and communication technology research in diabetes management and can help researchers measure the effectiveness of information and communication technology in diabetes self-care and therapeutic systems in different areas and motivate self-management. Cost reduction, technology acceptance and satisfaction.

Health care data is increasing. The correct analysis of such data will improve the quality of care and reduce costs. This kind of data has certain features such as high volume, variety, high-speed production, etc. It makes it impossible to analyze with ordinary hardware and software platforms. Choosing the right platform for managing this kind of data is very important.
The purpose of this study is to introduce and compare the most popular and most widely used platform for processing Big Data, Apache Hadoop MapReduce, and the two Apache Spark and Apache Flink platforms, which have recently been featured with great prominence.

This study is a survey whose content is based on the subject matter search of the Proquest, PubMed, Google Scholar, Science Direct, Scopus, IranMedex, Irandoc, Magiran, ParsMedline and Scientific Information Database (SID) databases, as well as Web reviews, specialized books with related keywords and standard. Finally, 80 articles related to the subject of the study were reviewed.

The findings showed that each of the studied platforms has features, such as data processing, support for different languages, processing speed, computational model, memory management, optimization, delay, error tolerance, scalability, performance, compatibility, Security and so on. Overall, the findings showed that the Apache Hadoop environment has simplicity, error detection, and scalability management based on clusters, but because its processing is based on batch processing, it works for slow complex analyzes and does not support stream processing, Apache Spark is also distributed as a computational platform that can process a Big Data set in memory with a very fast response time, the Apache Flink allows users to store data in memory and load them multiple times and provide a complex Fault Tolerance mechanism Continuously retrieves data stream status.

The application of Big Data analysis and processing platforms varies according to the needs. In other words, it can be said that each technology is complementary, each of which is applicable in a particular field and cannot be separated from one another and depending on the purpose and the expected expectation, and the platform must be selected for analysis or whether custom tools are designed on these platforms.

Number of diabetic patients are increasing. If the blood glucose not controlled in diabetics, patients will face with complications. Self-care is important to control the blood glucose of diabetic patients and prevention of complications such as neurological complications, heart, eye disease, amputations and so on. Therefore the aim of this study is to identify the effects of Continuous Glucose Monitoring (CGM) on the blood glucose control in type I diabetes.

The study was done on 20 patients chosen from an online data set available in http://www.jaeb-diabetes.net/ . These patients used CGM to test blood glucose and the result of three month test was measured. To analyze the data, the software SPSS 21, independent Mann- Whitney test was used.

The results showed that blood glucose in patients of the experimental group reduced significantly rather than patient of the control group in the second and third month. Also, HbA1C of the patients has reduced.

The CGM has an effective role in controlling blood glucose and prevention of complications. Therefore it is recommended that educational programs on the use of monitoring blood glucose, such as CGM as a requirement to be developed.

The use of healthcare frameworks and, in particular, policy makers is crucial for designing and evaluating systems. Frameworks provide the ability to measure and compare health system functions in different countries in order to make better and more meaningful decisions, to make comparisons within and between countries, identifying gaps, and sharing information. Researchers also have the ability to use the dimensions of the frameworks to measure progress over time. Due to the importance of the subject, the purpose of this study is to describe the framework concepts and the introduction of framework applications in the field of health care.

This study is based on a search of the ProQuest, PubMed, Google Scholar, Science Direct, Scopus, IranMedex, Irandoc, Magiran, ParsMedline and Scientific Information Database (SID) databases, as well as the study of specialized keyword web sites and the standard was done. After a thorough study, 50 sources were selected according to the study objectives and were used to formulate the final article.

The framework can be used to manage health system investments, identify important research areas in the field of health, and define new and useful research.

Given the importance of the health framework, the need to provide a framework for other critical health care sectors is essential.