Iranshahr University

Abstract Background The COVID-19 pandemic has had a significant impact on public mental health. Therefore, monitoring and oversight of the population mental health during crises such as a panedmic is an immediate priority. The aim of this study is to analyze the existing research works and findings in relation to the prevalence of stress, anxiety and depression in the general population during the COVID-19 pandemic. Method In this systematic review and meta-analysis, articles that have focused on stress and anxiety prevalence among the general population during the COVID-19 pandemic were searched in the Science Direct, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases, without a lower time limit and until May 2020. In order to perform a meta-analysis of the collected studies, the random effects model was used, and the heterogeneity of studies was investigated using the I 2 index. Moreover. data analysis was conducted using the Comprehensive Meta-Analysis (CMA) software. Results The prevalence of stress in 5 studies with a total sample size of 9074 is obtained as 29.6% (95% confidence limit: 24.3–35.4), the prevalence of anxiety in 17 studies with a sample size of 63,439 as 31.9% (95% confidence interval: 27.5–36.7), and the prevalence of depression in 14 studies with a sample size of 44,531 people as 33.7% (95% confidence interval: 27.5–40.6). Conclusion COVID-19 not only causes physical health concerns but also results in a number of psychological disorders. The spread of the new coronavirus can impact the mental health of people in different communities. Thus, it is essential to preserve the mental health of individuals and to develop psychological interventions that can improve the mental health of vulnerable groups during the COVID-19 pandemic.

<h3>Importance</h3> Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. <h3>Objective</h3> To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. <h3>Evidence Review</h3> We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. <h3>Findings</h3> In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs). <h3>Conclusions and Relevance</h3> The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care.

IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

Qualitative content analysis consists of conventional, directed and summative approaches for data analysis. They are used for provision of descriptive knowledge and understandings of the phenomenon under study. However, the method underpinning directed qualitative content analysis is insufficiently delineated in international literature. This paper aims to describe and integrate the process of data analysis in directed qualitative content analysis. Various international databases were used to retrieve articles related to directed qualitative content analysis. A review of literature led to the integration and elaboration of a stepwise method of data analysis for directed qualitative content analysis. The proposed 16-step method of data analysis in this paper is a detailed description of analytical steps to be taken in directed qualitative content analysis that covers the current gap of knowledge in international literature regarding the practical process of qualitative data analysis. An example of "the resuscitation team members' motivation for cardiopulmonary resuscitation" based on Victor Vroom's expectancy theory is also presented. The directed qualitative content analysis method proposed in this paper is a reliable, transparent, and comprehensive method for qualitative researchers. It can increase the rigour of qualitative data analysis, make the comparison of the findings of different studies possible and yield practical results.

Abstract Background Osteoporosis affects all sections of society, including families with people affected by osteoporosis, government agencies and medical institutes in various fields. For example, it involves the patient and his/her family members, and government agencies in terms of the cost of treatment and medical care. Providing a comprehensive picture of the prevalence of osteoporosis globally is important for health policymakers to make appropriate decisions. Therefore, this study was conducted to investigate the prevalence of osteoporosis worldwide. Methods A systematic review and meta-analysis were conducted in accordance with the PRISMA criteria. The PubMed, Science Direct, Web of Science, Scopus, Magiran, and Google Scholar databases were searched with no lower time limit up till 26 August 2020. The heterogeneity of the studies was measured using the I 2 test, and the publication bias was assessed by the Begg and Mazumdar’s test at the significance level of 0.1. Results After following the systematic review processes, 86 studies were selected for meta-analysis. The sample size of the study was 103,334,579 people in the age range of 15–105 years. Using meta-analysis, the prevalence of osteoporosis in the world was reported to be 18.3 (95% CI 16.2–20.7). Based on 70 studies and sample size of 800,457 women, and heterogenicity I 2 : 99.8, the prevalence of osteoporosis in women of the world was reported to be 23.1 (95% CI 19.8–26.9), while the prevalence of osteoporosis among men of the world was found to be 11.7 (95% CI 9.6–14.1 which was based on 40 studies and sample size of 453,964 men.). The highest prevalence of osteoporosis was reported in Africa with 39.5% (95% CI 22.3–59.7) and a sample size of 2989 people with the age range 18–95 years. Conclusion According to the medical, economic, and social burden of osteoporosis, providing a robust and comprehensive estimate of the prevalence of osteoporosis in the world can facilitate decisions in health system planning and policymaking, including an overview of the current and outlook for the future; provide the necessary facilities for the treatment of people with osteoporosis; reduce the severe risks that lead to death by preventing fractures; and, finally, monitor the overall state of osteoporosis in the world. This study is the first to report a structured review and meta-analysis of the prevalence of osteoporosis worldwide.

Aim: Ovarian cancer is one of the most common gynecologic cancers that has the highest mortality rate. Considering the fact that knowledge on the incidence, mortality of ovarian cancer, as well as its risk factors is necessary for planning and preventing complications, this study was conducted with the aim of examining the epidemiology and risk factors of ovarian cancer in the world. Materials and methods: In order to access the articles, Medline, Web of Science Core Collection, and Scopus databases were searched from their start to the year 2018. Full-text, English observational studies that referred to various aspects of ovarian cancer were included in the study. Results: In total, 125 articles that had been published during the years 1925–2018 were entered into the study. Ovarian cancer is the seventh most common cancer among women. Increased risk factors of cancer have led to an upward trend in the incidence of cancer around the world. In 2018, 4.4% of entire cancer-related mortality among women was attributed to ovarian cancer. Although the incidence of cancer is higher among high Human Development Index (HDI) countries, the trend of mortality rate tends to be reversing. Various factors affect the occurrence of ovarian cancer, from which genetic factor are among the most important ones. Pregnancy, lactation, and oral contraceptive pills play a role in reducing the risk of this disease. Conclusion: This study provides significant evidence about ovarian cancer. Considering the heavy burden of ovarian cancer on women’s health, preventive measures as well as health education and early detection in high risk groups of women are highly recommended. Although some risk factors cannot be changed, a focus on preventable risk factors may reduce the risk of ovarian cancer. More studies are needed to explore the role of unclear risk factors in ovarian cancer occurrence. Keywords: Ovarian cancer, epidemiology, risk factor

Abstract Background Stress, anxiety, and depression are some of the most important research and practice challenges for psychologists, psychiatrists, and behavioral scientists. Due to the importance of issue and the lack of general statistics on these disorders among the Hospital staff treating the COVID-19 patients, this study aims to systematically review and determine the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients. Methods In this research work, the systematic review, meta-analysis and meta-regression approaches are used to approximate the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients. The keywords of prevalence, anxiety, stress, depression, psychopathy, mental illness, mental disorder, doctor, physician, nurse, hospital staff, 2019-nCoV, COVID-19, SARS-CoV-2 and Coronaviruses were used for searching the SID, MagIran, IranMedex, IranDoc, ScienceDirect, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases. The search process was conducted in December 2019 to June 2020. In order to amalgamate and analyze the reported results within the collected studies, the random effects model is used. The heterogeneity of the studies is assessed using the I 2 index. Lastly, the data analysis is performed within the Comprehensive Meta-Analysis software. Results Of the 29 studies with a total sample size of 22,380, 21 papers have reported the prevalence of depression, 23 have reported the prevalence of anxiety, and 9 studies have reported the prevalence of stress. The prevalence of depression is 24.3% (18% CI 18.2–31.6%), the prevalence of anxiety is 25.8% (95% CI 20.5–31.9%), and the prevalence of stress is 45% (95% CI 24.3–67.5%) among the hospitals’ Hospital staff caring for the COVID-19 patients. According to the results of meta-regression analysis, with increasing the sample size, the prevalence of depression and anxiety decreased, and this was statistically significant ( P &lt; 0.05), however, the prevalence of stress increased with increasing the sample size, yet this was not statistically significant ( P = 0.829). Conclusion The results of this study clearly demonstrate that the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients is high. Therefore, the health policy-makers should take measures to control and prevent mental disorders in the Hospital staff.

With the rapid growth of technology, computer learning has become increasingly integrated with artificial intelligence techniques in order to develop more personalized educational systems. These systems are known as Intelligent Tutoring systems (ITSs). This paper focused on the variant characteristics of ITSs developed across different educational fields. The original studies from 2007 to 2017 were extracted from the PubMed, ProQuest, Scopus, Google scholar, Embase, Cochrane, and Web of Science databases. Finally, 53 papers were included in the study based on inclusion criteria. The educational fields in the ITSs were mainly computer sciences (37.73%). Action-condition rule-based reasoning, data mining, and Bayesian network with 33.96%, 22.64%, and 20.75% frequency respectively, were the most frequent artificial intelligent techniques applied in the ITSs. These techniques enable ITSs to deliver adaptive guidance and instruction, evaluate learners, define and update the learner’s model, and classify or cluster learners. Specifically, the performance of the system, learner’s performance, and experiences were used for evaluation of ITSs. Most ITSs were designed for web user interfaces. Although these systems could facilitate reasoning in the learning process, these systems have rarely been applied in experimental courses including problem-solving, decision-making in physics, chemistry, and clinical fields. Due to the important role of a cell phone in facilitating personalized learning and given the low rate of using mobile-based ITSs, this study has recommended the development and evaluation of mobile-based ITSs.

Confirmatory factor analysis (CFA) aims to confirm a theoretical model using empirical data and is an element of the broader multivariate technique structural equation modelling (SEM; Alavi et al., 2020). CFA is commonly used across clinical research (Brown, 2015; Kääriäinen et al., 2011) including the development and psychometric evaluation of measurement instruments. The three main uses of CFA in psychometric evaluation studies are construct validity evaluation, response pattern comparison, and competing model comparison (Sun, 2005), with construct validity evaluation the most widely used CFA application. A fundamental characteristic of CFA is its hypothesis-driven approach (Brown, 2015). The researcher first establishes a hypothesis regarding the model structure expressed as particular factor(s) underlying a set of items. Analysis is then performed to determine how much of the covariance between the items would be captured by the hypothesized factor structure (Hooper, Coughlan, & Mullen, 2008). In addition to assessing the covariance captured by the model, evaluating the goodness of fit of the proposed model, which reflects how well the model fits the observed data, is a critical step in CFA (Hooper et al., 2008). Goodness-of fit is evaluated using a range of model fit indices, which assess the relationship between the observed data and the theoretical data which would be expected from the model. Model fit indices can be used with either thresholds or hypothesis testing to reject or retain the proposed model (Costa & Sarmento, 2019). There are several statistical software packages available to estimate model fit, which report a variety of fit indices (e.g. see Jöreskog & Sörbom, 1989). There are two types of model fit indices available for CFA; global and local fit indices (Brown, 2015; Kline, 2005). Global model fit indices measure the global recovery of empirical observations without considering the mean and covariance structure. Local fit indices examine model components including but not limited to factor correlations, inter-item residual covariance, and suggested model re-specification statistics. Global model fit indices fall into three categories; absolute, incremental (also known as comparative or relative), and parsimony fit indices (Hooper et al., 2008; Kline, 2005). Absolute fit indices assess the overall theoretical model against the observed data. They are generated from either a test statistic and/or model residuals, and assess overall fit to the covariance structure of the population. They assess how well the model fits the data compared with no model. In addition to the chi-square (χ2) statistic other examples of absolute fit indices are goodness-of-fit index (GFI), adjusted GFI, root mean square error of approximation (RMSEA), and root mean square residual and standardized root mean square residual (SRMR; Jöreskog & Sörbom, 1989; Steiger, 2007). Incremental fit indices compare a hypothesized model to a baseline or minimal model that specifies no relationships between the variables and contains only variances for observed variables. Hence, the baseline model represents the hypothesis of no meaningful relationships between variables. Incremental fit indices represent the improved fit for the model compared to the assumption of independence of variables. Examples are comparative fit index (CFI), normed-fit index (NFI), and non-normed fit index (Bentler, 1990; Bentler & Bonett, 1980). As parameters are added to a model, the model fit will improve. Parsimonious models with fewer parameters are preferred to complex models which should be taken into account when determining fit. Parsimonious fit indices aim to address this issue by adding a penalty for model complexity. This introduces a trade-off between model fit and degrees of freedom. Parsimony goodness-of-fit index (Mulaik et al., 1989) and the parsimony normed fit index (James, Mulaik, & Brett, 1982) are examples. The many fit indices available introduces issues in the complexity of reporting results and appropriate use of the range of fit indices. It is not expected that all indices would be used or reported in fitting any hypothesized model. The application of each fit index depends on the study purpose and characteristics of the fit indices. The chi-square fit index assesses the fit between the hypothesized model and data from a set of measurement items (the observed variables). The model chi-square is the chi-square statistic obtained using maximum likelihood method. When a model is estimated using maximum likelihood, the likelihood ratio test statistic is commonly used to assess the overall goodness of fit (Jöreskog, 1969; Maydeu-Olivares, Fairchild, & Hall, 2017). Assuming the hypothesized model is correctly specified, the likelihood ratio test statistic would approach a central chi-square distribution. The chi-square test is the most commonly used global fit index in CFA and is also used to generate other fit indices. It tests whether the covariance matrix derived from the model represents the population covariance. Generally, chi-square is used as an absolute fit index, with a low chi-square value relative to the degrees of freedom (and higher p-value) indicating better model fit. Since the test is used to reject a null hypothesis representing perfect fit, chi-square is often referred to as a ‘badness of fit’ or ‘lack of fit index’ (Kline, 2005). The chi-square statistic using a likelihood ratio test can also be used to assess nested models, where one model is a subset of an alternative model created by constraining some of the parameters. The difference in fit between the models is expressed as the difference in chi-square values for each model, which also has a chi-square distribution. For nested likelihood ratio tests the degrees of freedom are the added parameters for the less parsimonious model (Kline, 2005; Tomarken & Waller, 2003). As with all tests the assumptions of the chi-square model fit index must be met including multivariate normality of data, adequate sample size, no systematic missing data, and appropriate specification of the model. There are limitations with using the chi-square statistic as a model fit index. First, it is sensitive to sample size with larger sample sizes decreasing the p-value where there may only be a trivial misfit (Babyak & Green, 2010). Overemphasis on model chi-square may lead to a preference for smaller samples in which the null hypothesis is not rejected. This is more likely to accept poor models and may yield inaccurate or imprecise parameter estimations. Parameter estimates should be given consideration rather than merely model fit indices, as they often hold substantive clinical interest. Adequate sample size in CFA can be assessed several ways. Cut-offs include a minimum sample size of 200, a ratio of sample size to model variables ≥10 or a ratio of sample size to the number of model parameters ≥5 (Myers, Ahn, & Jin, 2011). It is important that the model assumptions of chi-square are assessed when using this fit index. The model statistic does not always follow a chi-square distribution particularly in cases where data are not multivariate normal or when the sample size is small. In addition, as with any statistical test it is often interpreted as a binary result, in this case a fit or no-fit decision resulting in the model being retained or rejected. Assessment of the test statistic itself, which indicates the degree to which a model is discrepant, should be preferred. The chi-square model fit is a non-parsimonious approach and hence the model fit improves as the model size increases (Schermelleh-Engel, Moosbrugger, & Müller, 2003). Increasing the number of parameters may provide unnecessarily complex models, which are more likely to be accepted than parsimonious ones. The complexity of the model needs to be considered when assessing model fit using chi-square. Given that the chi-square fit statistic is affected by large samples, the ratio of the chi-square statistic to the respective degrees of freedom (χ2/df) is preferred (Wheaton, Muthen, Alwin, & Summers, 1977). A ratio of ≤2 indicates a superior fit between the hypothesized model and the sample data (Cole, 1987). Nevertheless, the chi-square statistic can be useful when a CFA model fails to fit. It is common then to enter an exploratory phase which involves inspecting the modification indices of all the pairs of error terms and correlating those pairs with the largest indices until the model fits (Watson et al., 2013). As better fitting models are achieved, the fit indices would improve. The chi-square statistic should decrease but with large sample sizes it will most probably remain statistically significant. Considering the sensitivity of the chi-square statistic to sample size, a wide variety of other indices have been suggested to assess model adequacy. In practice, the chi-square test is “not always the final word in assessing fit” (West, Taylor, & Wu, 2012, p. 211). Kline (2005) suggests that at a minimum the following indices should be reported and assessed in combination: chi-square; RMSEA; CFI; and SRMSR. The use of multiple fit indices provides a more holistic view of goodness of fit, accounting for sample size, model complexity, and other considerations relevant to the particular study. No conflict of interest was declared by the authors in relation to the study itself. Note that Roger Watson is a JAN editor. All authors have agreed on the final version and meet at least one of the following criteria recommended by the ICMJE (http://www.icmje.org/recommendations/): Substantial contributions to conception and design, acquisition of data or analysis and interpretation of data; drafting the article or revising it critically for important intellectual content.

Currently, medications used to treat rheumatoid arthritis (RA) are glucocorticoids (GCs) and nonsteroidal anti-inflammatory drugs (NSAIDs), predominantly used for controlling the pain and inflammation, disease-modifying antirheumatic drugs (DMARDs), administered as first-line medication for newly diagnosed RA cases, and biological therapies, used to target and inhibit specific molecules of the immune and inflammatory responses. NSAIDs and other GCs are effective in alleviating the pain, inflammation, and stiffness due to RA. DMARDs that are used for RA therapy are hydroxychloroquine, methotrexate, leflunomide, and sulfasalazine. The biological therapies, on the contrary, are chimeric anti-CD20 monoclonal antibody, rituximab, inhibitors of tumor necrosis factor-α (TNF-α) like etanercept, infliximab, and adalimumab, a recombinant inhibitor of interleukin-1 (IL-1), anakinra, and costimulation blocker, abatacept. Moreover, newly under evaluation biological therapies include new TNF-α inhibitors, JAK inhibitors, anti-interleukin-6-receptor monoclonal antibodies (mABs), and antibodies against vital molecules involved in the survival and development of functional B cells. The new strategies to treat RA has improved the course of the disease and most of the patients are successful in remission of the clinical manifestations if the diagnosis of the disease occur early. The probability of remission increase if the diagnosis happens rapidly and treat-to-target approach are implemented. In this review article, we have attempted to go through the treatment strategies for RA therapy both the routine ones and those which have been developed over the past few years and currently under investigation.

PURPOSE: Coronavirus disease 2019 (COVID-19) is an emerging disease that was first reported in Wuhan city, the capital of Hubei province in China, and has subsequently spread worldwide. Risk factors for mortality have not been well summarized. Current meta-analysis of retrospective cohort studies was done to summarize available findings on the association between age, gender, comorbidities and risk of death from COVID-19 infection. METHODS: Online databases including Web of Science, PubMed, Scopus, Cochrane Library and Google scholar were searched to detect relevant publications up to 1 May 2020, using relevant keywords. To pool data, random-effects model was used. Furthermore, sensitivity analysis and publication bias test were also done. RESULTS: < .001), were associated with higher risk of mortality. CONCLUSIONS: Older age (≥65 years old), male gender, hypertension, CVDs, diabetes, COPD and malignancies were associated with greater risk of death from COVID-19 infection. These findings could help clinicians to identify patients with poor prognosis at an early stage.

Abstract Background Osteoporosis is one of the most common bone system diseases that is associated with an increased risk of bone fractures and causes many complications for patients. With age, the prevalence of this disease increases so that it has become a serious problem among the elders. In this study, the prevalence of osteoporosis among elders around the world is examined to gain an understanding of its prevalence pattern. Methods In this systematic review and meta-analysis, articles that have focused on prevalence of osteoporosis in the world’s elders were searched with these key words, such as Prevalence, Osteoporosis, Elders, Older adult in the Science Direct, Embase, Scopus, PubMed, Web of Science (WoS) databases and Google Scholar search engine, and extracted without time limit until March 2020 and transferred to information management software (EndNote). Then, duplicate studies were eliminated and the remaining studies were evaluated in terms of screening, competence and qualitative evaluation based on inclusion and exclusion criteria. Data analysis was performed with Comprehensive Meta-Analysis software (Version 2) and Begg and Mazumdar test was used to check the publication bias and I 2 test was used to check the heterogeneity. Results In a review of 40 studies (31 studies related to Asia, 5 studies related to Europe and 4 studies related to America) with a total sample size of 79,127 people, the prevalence of osteoporosis in the elders of the world; 21.7% (95% confidence interval: 18.8–25%) and the overall prevalence of osteoporosis in older men and women in the world, 35.3% (95% confidence interval: 27.9–43.4%), 12.5% (95% confidence interval: 9.3–16.7%) was reported. Also, the highest prevalence of osteoporosis in the elders was reported in Asia with; 24.3% (95% confidence interval: 20.9–28.1%). Conclusion The results of the present study showed that the prevalence of osteoporosis in the elders and especially elders' women is very high. Osteoporosis was once thought to be an inseparable part of elders’ lives. Nowadays, Osteoporosis can be prevented due to significant scientific advances in its causes, diagnosis, and treatment. Regarding the growing number of elderly people in the world, it is necessary for health policy-makers to think of measures to prevent and treat osteoporosis among the elders.

AIM: We propose that the conceptual orientation of professional identity is a logical consequence of self-concept development by focusing on career and its meaning and presents a measurable set of concepts that can be manipulated to improve retention of student and registered nurses within health service. BACKGROUND: Although professional identity is a term that is commonly written of in nursing literature, its theoretical origins remain unclear, and available empirical evidence of its presence or ability to change is omitted from nursing research. SOURCES OF EVIDENCE: We present a professional identity pathway and explore the factors that influence professional identity throughout a career in nursing. DISCUSSION: Nurses' professional identities develop throughout their lifetimes, from before entering nursing education, throughout their years of study and clinical experience, and continue to evolve during their careers. Education is, however, a key period as it is during this time students gain the knowledge and skills that separate nurses as professional healthcare workers from lay people. CONCLUSION: Finally, a call for longitudinal studies of students to graduates, using conceptually derived and psychometrically proven instruments capable of detecting the subtle changes in the construct over time, is recommended. Further empirical research into the theoretical concepts that underline professional identity, and the factors that influence changes in this important construct in nursing, is required. Ultimately, the practical relevance of such research will lie in the potential it provides for enhanced nursing career support and improved workforce policies.

BACKGROUND: Early childhood caries (ECC) is a type of dental caries in the teeth of infants and children that is represented as one of the most prevalent dental problems in this period. Various studies have reported different types of prevalence of dental caries in primary and permanent teeth in children worldwide. However, there has been no comprehensive study to summarize the results of these studies in general, so this study aimed to determine the prevalence of dental caries in primary and permanent teeth in children in different continents of the world during a systematic review and meta-analysis. METHODS: index. Data were analyzed by using the Comprehensive Meta-Analysis (Version 2) software. FINDINGS: In this study, a total of 164 articles (81 articles on the prevalence of dental caries in primary teeth and 83 articles on the prevalence of dental caries in permanent teeth) were entered the meta-analysis. The prevalence of dental caries in primary teeth in children in the world with a sample size of 80,405 was 46.2% (95% CI: 41.6-50.8%), and the prevalence of dental caries in permanent teeth in children in the world with a sample size of 1,454,871 was 53.8% (95% CI: 50-57.5%). Regarding the heterogeneity on the basis of meta-regression analysis, there was a significant difference in the prevalence of dental caries in primary and permanent teeth in children in different continents of the world. With increasing the sample size and the year of study, dental caries in primary teeth increased and in permanent teeth decreased. CONCLUSION: The results of this study showed that the prevalence of primary and permanent dental caries in children in the world was found to be high. Therefore, appropriate strategies should be implemented to improve the aforementioned situation and to troubleshoot and monitor at all levels by providing feedback to hospitals.

BACKGROUND: Curcumin is herbal compound that has been shown to have anti-cancer effects in pre-clinical and clinical studies. The anti-cancer effects of curcumin include inhibiting the carcinogenesis, inhibiting angiogenesis, and inhibiting tumour growth. This study aims to determine the Clinical effects of curcumin in different types of cancers using systematic review approach. METHODS: A systematic review methodology is adopted for undertaking detailed analysis of the effects of curcumin in cancer therapy. The results presented in this paper is an outcome of extracting the findings of the studies selected from the articles published in international databases including SID, MagIran, IranMedex, IranDoc, Google Scholar, ScienceDirect, Scopus, PubMed and Web of Science (ISI). These databases were thoroughly searched, and the relevant publications were selected based on the plausible keywords, in accordance with the study aims, as follows: prevalence, curcumin, clinical features, cancer. RESULTS: The results are derived based on several clinical studies on curcumin consumption with chemotherapy drugs, highlighting that curcumin increases the effectiveness of chemotherapy and radiotherapy which results in improving patient's survival time, and increasing the expression of anti-metastatic proteins along with reducing their side effects. CONCLUSION: The comprehensive systematic review presented in this paper confirms that curcumin reduces the side effects of chemotherapy or radiotherapy, resulting in improving patients' quality of life. A number of studies reported that, curcumin has increased patient survival time and decreased tumor markers' level.

Objective: The aim of this study was to estimate the global prevalence of primary ovarian insufficiency (POI) and early menopause (EM).Methods: A comprehensive literature search was performed in several databases to retrieve relevant English articles published between 1980 and 2017. To assess the methodological quality of the studies, the Newcastle-Ottawa Scale was used. The heterogeneity of results across the studies was assessed using Cochran’s Q test and quantified by the I2 statistic. Prevalence estimates of all studies were pooled using a random-effects meta-analysis model at a confidence level of 95%.Results: A total of 8937 potentially relevant articles were identified from the initial searches. Thirty-one studies met the inclusion criteria and were included in this meta-analysis. The pooled prevalence of POI and EM was calculated as 3.7% (95% confidence interval: 3.1, 4.3) and 12.2% (95% confidence interval: 10.5, 14), respectively. The prevalence of POI was higher in medium and low Human Development Index countries. The prevalence trend did not change over time.Conclusion: The prevalence of POI and EM in women is considerable. The results of this study could contribute to consciousness-raising of health policy-makers toward the necessity of prioritizing, planning, and allocating health resources as preventive and treatment interventions for these women.

CONTEXT: The failure and complications of central venous access devices (CVADs) result in interrupted medical treatment, morbidity, and mortality for the patient. The resulting insertion of a new CVAD further contributes to risk and consumes extra resources. OBJECTIVE: To systematically review existing evidence of the incidence of CVAD failure and complications across CVAD types within pediatrics. DATA SOURCES: Central Register of Controlled Trials, PubMed, and Cumulative Index to Nursing and Allied Health databases were systematically searched up to January 2015. STUDY SELECTION: Included studies were of cohort design and examined the incidence of CVAD failure and complications across CVAD type in pediatrics within the last 10 years. CVAD failure was defined as CVAD loss of function before the completion of necessary treatment, and complications were defined as CVAD-associated bloodstream infection, CVAD local infection, dislodgement, occlusion, thrombosis, and breakage. DATA EXTRACTION: Data were independently extracted and critiqued for quality by 2 authors. RESULTS: Seventy-four cohort studies met the inclusion criteria, with mixed quality of reporting and methods. Overall, 25% of CVADs failed before completion of therapy (95% confidence interval [CI] 20.9%-29.2%) at a rate of 1.97 per 1000 catheter days (95% CI 1.71-2.23). The failure per CVAD device was highest proportionally in hemodialysis catheters (46.4% [95% CI 29.6%-63.6%]) and per 1000 catheter days in umbilical catheters (28.6 per 1000 catheter days [95% CI 17.4-39.8]). Totally implanted devices had the lowest rate of failure per 1000 catheter days (0.15 [95% CI 0.09-0.20]). LIMITATIONS: The inclusion of nonrandomized and noncomparator studies may have affected the robustness of the research. CONCLUSIONS: CVAD failure and complications in pediatrics are a significant burden on the health care system internationally.

Mental health conditions are likely to affect almost half of the population at some stage in their lives. Despite the magnitude and potentially serious consequences of mental illness and disorders, access to services is a significant problem. In 2007, the Mental Health Nurse Incentive Program (MHNIP) was implemented to improve access to mental health care in Australia. Mental health nurses are engaged under the MHNIP to work with general practitioners, psychiatrists, and other mental health professionals to treat clients experiencing a mental health condition. This paper presents findings from a qualitative exploration of nurses working under the MHNIP in Australia. In-depth interviews were conducted with 10 nurses currently working under the MHNIP to gain an understanding of their roles and their perceptions of the effectiveness of this new programme. Data were analysed using NVivo. Four major themes emerged: developing the role, a holistic approach, working collaboratively, and benefits to clients. The findings suggest that mental health nurses have the potential to make a significant contribution to enhancing access to, and the quality of, mental health care through flexible and innovative approaches.

BACKGROUND: COVID-19 infection is a new disease that infects a large number of people, killing a ratio of whom every day in the world. Healthcare staff, especially nurses, experience a great deal of psychological distress during care of COVID-19 patients. Detecting factors that disturb nurses' mental health during care of these patients can help to reduce their psychological distress. Therefore, this study aimed to explore nurses' experiences of psychological distress during care of patients with COVID-19. METHODS: The present qualitative research was performed using the conventional content analysis method in Iran from March to May 2020. Participants in this study included the nurses caring for patients with COVID-19, and they were selected based on the purposeful sampling method. The data was collected through 20 phone call interviews and analyzed based on the method proposed by Lundman and Graneheim. RESULTS: Qualitative data analysis revealed 11 categories including death anxiety, anxiety due to the nature of the disease, anxiety caused by corpse burial, fear of infecting the family, distress about time wasting, emotional distress of delivering bad news, fear of being contaminated, the emergence of obsessive thoughts, the bad feeling of wearing personal protective equipment, conflict between fear and conscience, and the public ignorance of preventive measures. CONCLUSION: The data showed that the nurses experienced a variety of psychological distress during care of patients with COVID-19. Through proper planning by authorities, it is possible to manage the risk factors of mental health distress in nurses and improve their mental health status.

BACKGROUND: Social networks have had a major influence on students' performance in recent years. These networks create many opportunities and threats for students in various fields. Addiction to social networking and its impact on students' academic performance caused the researcher to design and conduct this study. The purpose of this study was to investigate the relationship between social networking addiction and academic performance of students in Iran. METHODS: In this cross-sectional study, 360 students were enrolled by stratified random sampling. The study tools included personal information form and the Bergen Social Media Addiction Scale. Also, the students' overall grade obtained in previous educational term was considered as the indicator of academic performance. Data were analyzed using SPSS-18.0 and descriptive and inferential statistics. FINDINGS: The mean social networking addiction was higher in male students (52.65 ± 11.50) than in female students (49.35 ± 13.96) and this difference was statistically significant (P < 0.01). There was a negative and significant relationship between students' addiction to social networking and their academic performance (r = - 0.210, p < 0.01). CONCLUSIONS: The social networking addiction of the students was at moderate level and the male students had a higher level of addiction compared to the female students. There was a negative and significant relationship between the overall use of social networks and academic performance of students. Therefore, it is imperative that the university authorities take interventional steps to help students who are dependent on these networks and, through workshops, inform them about the negative consequences of addiction to social networks.