Global Prevalence of Anxiety, Depression, and Stress Among Patients with Skin Diseases: A Systematic Review and Meta-analysis.

The changes in human lifestyle over the past few decades have impacted the prevalence of skin diseases within different societies. Skin diseases may result in various physical and mental disorders. The most common mental disorders observed among the patients are stress, anxiety, and depression. This study aims to investigate the global prevalence of anxiety, depression, and stress in patients with skin diseases. In this Systematic Review and Meta-Analysis study, the PubMed, Scopus, Science Direct, Embase, Web of science, and Google Scholar repositories were searched without a lower time limit. Heterogeneity among the identified studies was examined using the I2 index, and accordingly random effects model was adopted for analysis. Data analysis was conducted within the Comprehensive Meta-Analysis software (v. 2). In total, 113 studies were included for the final analysis. The overall pooled prevalence of stress, depression, and anxiety in skin disease patients was found to be 39.4%, 27.2% and 28.8%, respectively. Among patients with psoriasis, acne, vitiligo or atopic dermatitis diseases, the highest number of patients suffering from stress was related to patients with acne (75.7%). The highest prevalence of depression, and anxiety was reported in patients with vitiligo (38.3%) and acne (36.5%), respectively. Considering the high prevalence of mental disorders among patients with skin diseases and recognising the impacts of mental health challenges on patients' well-being, the findings of this study provide valuable insights for identifying specific populations that require targeted interventions for the diagnosis, treatment, and prevention of mental illnesses. Accordingly, healthcare policymakers should incorporate psychological treatment and support measures as integral components of comprehensive care strategies for patients with skin diseases.

Global prevalence of major depressive disorder, generalized anxiety, stress, and depression among infertile women: a systematic review and meta-analysis.

BACKGROUND: In recent years, the global prevalence of infertility has increased among women (Talmor and Dunphy, Best Pract Res Clin Obstet Gynaecol 29(4):498-506, 2015) and is considered as a public health concern. One of the impacts of infertility is mental health problems in the patients, which can lead to complications such as stress, anxiety, and depression. The aim of this study is to investigate the global prevalence of major depressive disorder, general anxiety, stress, and depression in infertile women through a systematic review and meta-analysis. METHODS: To identify studies that have reported the prevalence of major depressive disorder, generalized anxiety, stress, and depression in infertile women, the PubMed, Scopus, Web of Science, Embase, ScienceDirect, and Google Scholar repositories were systematically searched. Articles published up until February 2023 were included, while no lower time limit was imposed in the search strategy. Heterogeneity of studies was examined using the I2 test and, thus, random-effects model was used to perform the analysis. Data analysis was conducted within the Comprehensive Meta-Analysis (v.2) software. RESULTS: In the review of 44 studies with a sample size of 53,300 infertile female patients, the overall prevalence of major depressive disorder (clinical depression), generalized anxiety, stress, and depression was found to be 22.9%, 13.3%, 78.8%, and 31.6% respectively. It was also found that mental health complications are more prevalent among infertile women in Asia (continent). CONCLUSION: Considering the prevalence of mental disorders among infertile women, health policymakers can use the results of the present meta-analysis to pay more attention to the mental health of infertile women and devise suitable interventions and programs to reduce and prevent the spread of psychological disorders among infertile women.

Nurses' moral courage and related factors: A systematic review.

BACKGROUND: Nurses face various ethical conflicts when taking care of patients, and such conflicts require moral courage. This systematic review was conducted with the aim of investigating moral courage and its related factors among nurses. METHODS: To find related studies, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The PubMed, Web of Science, Google Scholar, Scopus, Embase and Science Direct databases were searched using keywords such as Courage, Moral Courage, and Nurses, and no lower time limit was imposed when conducting the searches. The identified studies were published between January 2000 and March 2023. Quality of articles was assessed using the STROBE checklist. RESULTS: The pooled sample size for the 19 included studies was 7863. All studies were observational and cross-sectional. The results showed that three categories of factors most related to moral courage are individual, moral, and factors related to the organization. Underlying factors of each category are also provided within this paper. CONCLUSION: Moral courage is an integral part of nursing, which as a profession, is becoming even more challenging with the advancement of science and technology. Therefore, there is a need for nurses and especially nursing managers to be considerate of factors affecting moral courage of nurses, with a view to strengthening the positive factors and reducing the negative impacts.

Prevalence of suicide attempts across the African continent: A systematic review and meta-analysis.

BACKGROUND: Over 700,000 people worldwide lose their lives through suicide every year. The prevalence of suicide has increased, especially in low- and middle-income countries such as many African countries. For every fatal suicidal attempt, there are approximately 20 other non-fatal suicide attempts within the population. The purpose of this study is to investigate the prevalence of attempts of suicides in the African continent through a systematic review and meta-analysis. METHODS: To identify relevant sources, the PubMed, Scopus, Web of Science, Embase, ScienceDirect and Google Scholar repositories and databases were systematically searched without a lower time limit and until July 2023. The heterogeneity of the studies was checked with the I2 index, and accordingly random effects model was adopted to perform the analysis. Data analysis was conducted within the Comprehensive Meta-Analysis software (v.2). RESULTS: In the review of 48 studies with a sample size of 244,701 people, the prevalence of suicide attempts in Africa was found to be 9.9% (95%CI: 8.5%-11.6%). With the increase in the year of study, the prevalence of suicide attempt in the African continent increases. Also, with the increase in the sample size, the prevalence of suicide attempts in Africa decreases. The suicide attempt prevalence among African men and woman slightly differed with 7.6% and 8.2%, respectively. CONCLUSION: Suicide attempt is an important public health concern in Africa. The findings of this study are important not only for African health policy making, but also to contribute to the accuracy of global estimates with respect to suicide attempts.

Global prevalence of sexual dysfunction among women with metabolic syndrome: a systematic review and meta-analysis.

Background: Sexual dysfunction is a common disorder among women, especially during menopause. Metabolic syndrome is a multifactorial disease that, according to previous studies, there is a relationship between the metabolic syndrome and sexual dysfunction among women. The aim of this systematic review and meta-analysis is to obtain the prevalence of Female Sexual Dysfunction (FSD) among women with metabolic syndrome, and to analyze available related evidence. Methods: In this systematic review and meta-analysis, the keywords of MeSH, female sexual dysfunction, FSD, metabolic syndrome were searched in PubMed, Web of Science, Scopus, Science Direct and Google Scholar. The searches were conducted without a lower time limit and until May 2022. Results: The prevalence of FSD among women with metabolic syndrome was found to be 39.3% (95% CI: 28.3-51.5). In the subgroup analysis and in the review of 4 studies, the prevalence of sexual dysfunction in postmenopausal women with metabolic syndrome was 49.8% (95% CI: 26.1-73.6). Analyzing the results of the meta-regression test in examining the effect of the three factors of sample size, year of the study, age, and BMI of the patients on the heterogeneity of the meta-analysis, showed that with the increase of the sample size, the prevalence of sexual dysfunction among women with metabolic syndrome decreases (p < 0.05). Moreover, the prevalence of sexual dysfunction among women with metabolic syndrome increases (p < 0.05) with the increase in the years of conducting studies and the mean of age of women with metabolic syndrome. Also, with increasing mean of BMI of female patients with metabolic syndrome, the prevalence of sexual dysfunction in these women also increases (p < 0.05). Conclusion: Female sexual dysfunction is a global health problem that can affect women's life to a great extent. Metabolic syndrome, which is a set of factors such as obesity, high blood pressure, and diabetes, affects sexual dysfunction in women. From this study, it can be concluded that there is a close relationship between metabolic syndrome and female sexual dysfunction.

Prevalence of sleep disturbance in patients with ankylosing spondylitis: a systematic review and meta-analysis.

BACKGROUND: Ankylosing Spondylitis (AS) patients face several challenges due to the nature of the disease and its physical and psychological complications. Sleep disorders are among the most important concerns. Sleep disorders can aggravate the signs and symptoms of the disease and ultimately reduce the quality of patients' lives. This study uses a systematic review and meta-analysis to pool the reported prevalence of sleep disorders among AS patients. METHODS: To find related studies, the WoS, PubMed, ScienceDirect, Scopus, Embase, and Google Scholar databases were systematically searched without a lower time limit. Heterogeneity among the identified studies was checked using the I2 index, and the Begg and Mazumdar correlation test examined the existence of published bias. Comprehensive Meta-Analysis (v.2) software was adopted to analyze the data. RESULTS: In the review of 18 studies with a sample size of 5,840, the overall pooled prevalence of sleep disorders among AS patients based on the random effects method was found to be 53% (95% CI: 44.9-61). The highest and lowest prevalence was in Egypt at 90% and Australia at 19.2%, respectively. Our meta-regression results show that with the increase in 'sample size' and 'year of publication', the overall prevalence of sleep disorders in patients with AS decreases (p < 0.05). CONCLUSION: The results of the present study indicate a high and significant prevalence of sleep disorders among AS patients. Thus, health policymakers and healthcare providers must focus on timely diagnosis and effective educational and therapeutic interventions for the prevention and proper treatment of sleep disorders in this population of patients.

Advanced Sentiment Analysis for Managing and Improving Patient Experience: Application for General Practitioner (GP) Classification in Northamptonshire.

This paper presents a novel analytical approach for improving patients' experience in healthcare settings. The analytical tool uses a classifier and a recommend management approach to facilitate decision making in a timely manner. The designed methodology comprises of 4 key stages, which include developing a bot to scrap web data while performing sentiment analysis and extracting keywords from National Health Service (NHS) rate and review webpages, building a classifier with Waikato Environment for Knowledge Analysis (WEKA), analyzing speech with Python, and using Microsoft Excel for analysis. In the selected context, a total of 178 reviews were extracted from General Practitioners (GP) websites within Northamptonshire County, UK. Accordingly, 4764 keywords such as "kind", "exactly", "discharged", "long waits", "impolite staff", "worse", "problem", "happy", "late" and "excellent" were selected. In addition, 178 reviews were analyzed to highlight trends and patterns. The classifier model grouped GPs into gold, silver, and bronze categories. The outlined analytical approach complements the current patient feedback analysis approaches by GPs. This paper solely relied upon the feedback available on the NHS' rate and review webpages. The contribution of the paper is to highlight the integration of easily available tools to perform higher level of analysis that provides understanding about patients' experience. The context and tools used in this study for ranking services within the healthcare domain is novel in nature, since it involves extracting useful insights from the provided feedback.

Global prevalence of drug-resistant tuberculosis: a systematic review and meta-analysis.

BACKGROUND: Tuberculosis is a bacterial infectious disease, which affects different parts of a human body, mainly lungs and can lead to the patient's death. The aim of this study is to investigate the global prevalence of drug-resistant tuberculosis using a systematic review and meta-analysis. METHODS: In this study, the PubMed, Scopus, Web of Science, Embase, ScienceDirect and Google Scholar repositories were systematically searched to find studies reporting the global prevalence of drug-resistant tuberculosis. The search did not entail a lower time limit, and articles published up until August 2022 were considered. Random effects model was used to perform the analysis. The heterogeneity of the studies was examined with the I2 test. Data analysis was conducted within the Comprehensive Meta-Analysis software. RESULTS: In the review of 148 studies with a sample size of 318,430 people, the I2 index showed high heterogeneity (I2 = 99.6), and accordingly random effects method was used to analyze the results. Publication bias was also examined using the Begg and Mazumdar correlation test which indicated the existence of publication bias in the studies (P = 0.008). According to our meta-analysis, the global pooled prevalence of multi-drug resistant TB is 11.6% (95% CI: 9.1-14.5%). CONCLUSIONS: The global prevalence of drug-resistant tuberculosis was found to be very high, thus health authorities should consider ways to control and manage the disease to prevent a wider spread of tuberculosis and potentially subsequent deaths.

Global prevalence of sleep disorders during menopause: a meta-analysis.

BACKGROUND: Sleep disorders are conditions that have long-term effects on health, quality of sexual function, productivity at work, and overall quality of life. Considering that reports on menopausal sleep disorders are heterogeneous, the aim of this research was to determine the global prevalence of sleep disorders during menopause by meta-analysis. METHODS: PubMed, Google Scholar, Scopus, WoS, ScienceDirect, and Embase databases were checked with suitable keywords. All screening stages of articles were reviewed based on PRISMA and their quality was determined based on STROBE. Data analysis, examination of heterogeneity, and publication bias of factors affecting heterogeneity were performed in CMA software. RESULTS: The overall prevalence of sleep disorders among postmenopausal women was 51.6% (95% CI: 44.6-58.5%). The upper prevalence of sleep disorders was among postmenopausal women at 54.7% (95% CI: 47.2-62.1%). The upper prevalence of sleep disorders in the same population category was related to restless legs syndrome with a prevalence of 63.8% (95% CI: 10.6-96.3%). CONCLUSION: In this meta-analysis, sleep disorders during menopause were found to be common and significant. Therefore, it is recommended that health policymakers offer pertinent interventions in relation to the health and hygiene of sleep for women in menopause.

Executive protocol designed for new review study called: systematic review and artificial intelligence network meta-analysis (RAIN) with the first application for COVID-19.

Artificial intelligence (AI) as a suite of technologies can complement systematic review and meta-analysis studies and answer questions that cannot be typically answered using traditional review protocols and reporting methods. The purpose of this protocol is to introduce a new protocol to complete systematic review and meta-analysis studies.In this work, systematic review, meta-analysis, and meta-analysis network based on selected AI technique, and for P < 0.05 are followed, with a view to responding to questions and challenges that the global population is facing in light of the COVID-19 pandemic.Finally, it is expected that conducting reviews by following the proposed protocol can provide suitable answers to some of the research questions raised due to COVID-19.

Prevalence of sleep disturbance in patients with ankylosing spondylitis: a systematic review and meta-analysis

Abstract Background Ankylosing Spondylitis (AS) patients face several challenges due to the nature of the disease and its physical and psychological complications. Sleep disorders are among the most important concerns. Sleep disorders can aggravate the signs and symptoms of the disease and ultimately reduce the quality of patients' lives. This study uses a systematic review and meta-analysis to pool the reported prevalence of sleep disorders among AS patients. Methods To find related studies, the WoS, PubMed, ScienceDirect, Scopus, Embase, and Google Scholar databases were systematically searched without a lower time limit. Heterogeneity among the identified studies was checked using the I2 index, and the Begg and Mazumdar correlation test examined the existence of published bias. Comprehensive Meta-Analysis (v.2) software was adopted to analyze the data. Results In the review of 18 studies with a sample size of 5,840, the overall pooled prevalence of sleep disorders among AS patients based on the random effects method was found to be 53% (95% CI: 44.9-61). The highest and lowest prevalence was in Egypt at 90% and Australia at 19.2%, respectively. Our meta-regression results show that with the increase in 'sample size' and 'year of publication', the overall prevalence of sleep disorders in patients with AS decreases (p < 0.05). Conclusion The results of the present study indicate a high and significant prevalence of sleep disorders among AS patients. Thus, health policymakers and healthcare providers must focus on timely diagnosis and effective educational and therapeutic interventions for the prevention and proper treatment of sleep disorders in this population of patients.

Global prevalence of chronic fatigue syndrome among long COVID-19 patients: A systematic review and meta-analysis.

BACKGROUND: Chronic fatigue syndrome is a persistent and debilitating disorder. According to several studies, chronic fatigue syndrome has been identified among recovered COVID-19 patients as the most common symptom of long COVID. The aim of this systematic review and meta-analysis study was to obtain the prevalence of chronic fatigue syndrome in long COVID cases. METHODS: In this systematic review and meta-analysis, we analysed reported results of studies that assessed the occurrence of chronic fatigue syndrome among COVID-19 patients four weeks after the onset of symptoms. The study selection was commenced by searching PubMed, Web of Science, Science Direct, Scopus, Embase, and Google scholar using the keywords of Chronic fatigue syndrome, COVID-19, and post-COVID-19 syndrome. The searches were without a lower time limit and until April 2022. Heterogeneity of studies was assessed using the I2 index, and a random effects model was used for analysis. Data analysis was performed within the Comprehensive Meta-Analysis software (version 2). RESULTS: The pooled prevalence of chronic fatigue syndrome four weeks after the onset of COVID-19 symptoms, in 52 studies with a sample size of 127,117, was 45.2% (95% CI: 34.1-56.9%). Meta-regression analysis in examining the effects of the two factors of sample size, and year of study on the changes in the overall prevalence, showed that with increasing sample size, and year of study, the prevalence of chronic fatigue syndrome among long COVID patients (p < 0.05). CONCLUSION: Our results show that the overall prevalence of chronic fatigue syndrome as a long COVID symptom is 45.2%. Chronic fatigue after infection with COVID-19 can negatively affect personal and social lives. Given such significant negative consequences caused by the syndrome, it is recommended that health policymakers allocate funds to reduce the adverse effects of this syndrome, by creating programs to support long COVID patients.

Identification of Suitable Drug Combinations for Treating COVID-19 Using a Novel Machine Learning Approach: The RAIN Method.

COVID-19 affects several human genes, each with its own p-value. The combination of drugs associated with these genes with small p-values may lead to an estimation of the combined p-value between COVID-19 and some drug combinations, thereby increasing the effectiveness of these combinations in defeating the disease. Based on human genes, we introduced a new machine learning method that offers an effective drug combination with low combined p-values between them and COVID-19. This study follows an improved approach to systematic reviews, called the Systematic Review and Artificial Intelligence Network Meta-Analysis (RAIN), registered within PROSPERO (CRD42021256797), in which, the PRISMA criterion is still considered. Drugs used in the treatment of COVID-19 were searched in the databases of ScienceDirect, Web of Science (WoS), ProQuest, Embase, Medline (PubMed), and Scopus. In addition, using artificial intelligence and the measurement of the p-value between human genes affected by COVID-19 and drugs that have been suggested by clinical experts, and reported within the identified research papers, suitable drug combinations are proposed for the treatment of COVID-19. During the systematic review process, 39 studies were selected. Our analysis shows that most of the reported drugs, such as azithromycin and hydroxyl-chloroquine on their own, do not have much of an effect on the recovery of COVID-19 patients. Based on the result of the new artificial intelligence, on the other hand, at a significance level of less than 0.05, the combination of the two drugs therapeutic corticosteroid + camostat with a significance level of 0.02, remdesivir + azithromycin with a significance level of 0.03, and interleukin 1 receptor antagonist protein + camostat with a significance level 0.02 are considered far more effective for the treatment of COVID-19 and are therefore recommended. Additionally, at a significance level of less than 0.01, the combination of interleukin 1 receptor antagonist protein + camostat + azithromycin + tocilizumab + oseltamivir with a significance level of 0.006, and the combination of interleukin 1 receptor antagonist protein + camostat + chloroquine + favipiravir + tocilizumab7 with corticosteroid + camostat + oseltamivir + remdesivir + tocilizumab at a significant level of 0.009 are effective in the treatment of patients with COVID-19 and are also recommended. The results of this study provide sets of effective drug combinations for the treatment of patients with COVID-19. In addition, the new artificial intelligence used in the RAIN method could provide a forward-looking approach to clinical trial studies, which could also be used effectively in the treatment of diseases such as cancer.

Global prevalence of polypharmacy among the COVID-19 patients: a comprehensive systematic review and meta-analysis of observational studies.

BACKGROUND: Polypharmacy has traditionally been defined in various texts as the use of 5 or more chronic drugs, the use of inappropriate drugs, or drugs that are not clinically authorized. The aim of this study was to evaluate the prevalence of polypharmacy among the COVID-19 patients, and the side effects, by systematic review and meta-analysis. METHODS: This study was performed by systematic review method and in accordance with PRISMA 2020 criteria. The protocol in this work is registered in PROSPERO (CRD42021281552). Particular databases and repositories have been searched to identify and select relevant studies. The quality of articles was assessed based on the Newcastle-Ottawa Scale checklist. Heterogeneity of the studies was measured using the I2 test. RESULTS: The results of meta-analysis showed that the prevalence of polypharmacy in 14 studies with a sample size of 189,870 patients with COVID-19 is 34.6% (95% CI: 29.6-40). Studies have shown that polypharmacy is associated with side effects, increased morbidity and mortality among patients with COVID-19. The results of meta-regression analysis reported that with increasing age of COVID-19 patients, the prevalence of polypharmacy increases (p < 0.05). DISCUSSION: The most important strength of this study is the updated search to June 2022 and the use of all databases to increase the accuracy and sensitivity of the study. The most important limitation of this study is the lack of proper definition of polypharmacy in some studies and not mentioning the number of drugs used for patients in these studies. CONCLUSION: Polypharmacy is seen in many patients with COVID-19. Since there is no definitive cure for COVID-19, the multiplicity of drugs used to treat this disease can affect the severity of the disease and its side effects as a result of drug interactions. This highlights the importance of controlling and managing prescription drugs for patients with COVID-19.

Patients' Survival with Astrocytoma After Treatment: a Systematic Review and Meta-analysis of Clinical Trial Studies.

About half of the brain tumours are primary and the rest are metastatic. The impact of each of these treatments alone or together on the prognosis of patients with astrocytoma tumours, especially low-grade astrocytoma, is unclear which may pose many challenges in the decision-making of surgeons and patients. Considering the importance of patient's outcomes with astrocytoma and lack of general statistics, this study aimed to determine the survival of patients with high-grade astrocytoma and low-grade astrocytoma after treatments. This study follows a systematic review and a meta-analysis approach. Following a systematic review and meta-analysis method, articles dated from 1982 to March 2020 were extracted from Embase, ScienceDirect, Scopus, PubMed and Web of Science (WoS) international databases. Random effects model was used for analysis, and heterogeneity of studies was investigated considering the I 2 index. Data were analysed using the Comprehensive Meta-Analysis software (version 2). According to a meta-analysis of studies, the mean overall survival in patients with high-grade astrocytoma was 31.9 ± 2.7 months, for 2-year survival, 38.1% (95% CI: 27.5-50.1%) and for 5-year survival was 28.6% (95% CI: 24.1-33.4%). Mean overall survival in patients with low-grade astrocytoma was 64.8 ± 7.4 months, for 2-year survival was 74.3% (95% CI: 32.6-94.5%) and for 5-year survival was 74.4% (95% CI: 57.9-86%). The highest mean for survival in patients with high-grade astrocytoma and in chemotherapy and radiation therapy treatments was 45.2 ± 5.2 months, and also the highest mean for survival in patients with low-grade astrocytoma in surgical treatment was 71.4 ± 8.8 months. The results of this study show that the average survival in patients with low-grade astrocytoma is high following the treatment, and in high-grade astrocytoma, there will be the highest survival rate, if the surgical treatment is combined with chemotherapy and radiation therapy. This study summarizes retrospective studies up to 2020 to evaluate the prognosis and survival of patients with brain astrocytoma tumours, and the results of this meta-analysis can be of interest to surgeons and specialists in this field.

Telemedicine and insomnia: a comprehensive systematic review and meta-analysis.

BACKGROUND: Telemedicine has been introduced as a new and effective method in dealing with public health challenges, improving access to health care, and reducing healthcare costs in today's world. Insomnia is the most common sleep disorder that can be managed with cognitive behavioural therapy, however, access to skilled therapists is an issue. Telemedicine improves access to care and thus, it may facilitate management of insomnia. The aim of this study was to assess whether telemedicine can be as effective as traditional in person sleep medicine service for the diagnosis, follow-up, and treatment of insomnia. METHODS: In this systematic review and meta-analysis, studies related to telemedicine and insomnia were identified and selected, using the keywords of telemedicine, insomnia, sleep disorder, treatment, non-pharmacological treatment. The international databases of Embase, ProQuest, ScienceDirect, Scopus, PubMed and Web of Science (WoS), and Google Scholar were searched without a lower time limit, and until July 12, 2021. Data were analysed within the Comprehensive Meta-Analysis (version 2) software, and the significance level of the test was considered P Ë‚ 0.05. RESULTS: A systematic review of 16 selected studies showed that telemedicine interventions have a positive effect on improving insomnia in different groups. The meta-analysis was performed on 2 studies. Based on the results, CBTI interventions based on telemedicine have a greater effect on improving chronic insomnia than face to face CBTI with an average difference of 2.05 ± 0.66 based on the random effects model. Moreover, the difference between the mean in the telemedicine intervention group and the non-intervention group was 0.65 ± 0.19, which shows the positive effect of the telemedicine intervention. CONCLUSION: The use of telemedicine in treatment of insomnia not only accelerates access to sleep services, but can also improve the efficiency of health services in terms of time and cost, as well as therapeutic effects.

The Activity and Polymorphism of the PON1 in Patients with Chronic Liver Disease: a Systematic Review and Meta-analysis.

BACKGROUND: Liver diseases are among the ten deadliest diseases in the world. Measuring PON1 is a test to assess the degree of liver disorder. There are several preliminary studies on the rate of PON1 activity in people with liver disease, and there are differences between the results of these studies; therefore, the aim of this research work is to determine the level of PON1 activity in people with liver disease using meta-analysis. METHOD: The study searched to select articles that were published electronically from 2002 to 2020, in national and international databases of SID, MagIran, Embase, ScienceDirect, Scopus, PubMed, and Web of Science (WoS). RESULTS: Among the articles included in the meta-analysis, the samples in the case (patients) and control groups were 807 and 2276, respectively. The mean activity of PON1 in individuals with liver disease in the case and control groups were 142.06 ± 7.7 and 272.19 ± 39.6, respectively, and this was statistically significant (P < 0.05). The mean difference analysis highlights a difference of - 2.75 ± 0.48 between the patient and control groups, indicating that liver disease significantly reduces PON1 activity. CONCLUSION: The results of this study demonstrate that the polynomorphism of the PON1 is associated with an increased risk of liver disease, with lower levels of PON1 activity in people with liver disease than in healthy patients and this decrease was more in patients with liver cirrhosis than in other liver diseases. Given the importance of this gene's activity, studies such as this could provide a promising path for better drug design and treatment in future.

Predicting positive organizational behavior based on structural and psychological empowerment among nurses.

BACKGROUND: Positive Organizational Behavior (POB) as an application of positive psychology provides the opportunity to nurses to deliver an effective and high-quality service. This study aims to predict positive organizational behavior based on structural and psychological empowerment among Nurses. METHOD: In this descriptive-analytical study, the selected population was the nurses working in university hospitals affiliated to Kermanshah University of Medical Sciences, of which 152 people were selected using quota sampling strategy and according to the set entry criteria. The research data were collected using the standard questionnaires of Kanter's Structural Empowerment, Spreitzer's Psychological Empowerment, and Luthans' Positive Organizational Behavior, and were then entered into SPSS16 software. RESULTS: There are significant and direct relationships between the elements of structural empowerment with positive organizational behavior (r = 1.496), and psychological empowerment with positive organizational behavior (r = 1.379). Overall structural and psychological empowerment criteria predict 29% of variance in positive organizational behavior among nurses. CONCLUSION: This study highlights the importance of structural and psychological empowerment as strong predictors for positive organizational behavior.

Economic Evaluation of Mental Health Effects of Flooding Using Bayesian Networks.

The appraisal of appropriate levels of investment for devising flooding mitigation and to support recovery interventions is a complex and challenging task. Evaluation must account for social, political, environmental and other conditions, such as flood state expectations and local priorities. The evaluation method should be able to quickly identify evolving investment needs as the incidence and magnitude of flood events continue to grow. Quantification is essential and must consider multiple direct and indirect effects on flood related outcomes. The method proposed is this study is a Bayesian network, which may be used ex-post for evaluation, but also ex-ante for future assessment, and near real-time for the reallocation of investment into interventions. The particular case we study is the effect of flood interventions upon mental health, which is a gap in current investment analyses. Natural events such as floods expose people to negative mental health disorders including anxiety, distress and post-traumatic stress disorder. Such outcomes can be mitigated or exacerbated not only by state funded interventions, but by individual and community skills and experience. Success is also dampened when vulnerable and previously exposed victims are affected. Current measures evaluate solely the effectiveness of interventions to reduce physical damage to people and assets. This paper contributes a design for a Bayesian network that exposes causal pathways and conditional probabilities between interventions and mental health outcomes as well as providing a tool that can readily indicate the level of investment needed in alternative interventions based on desired mental health outcomes.

Contradictions in the promotion of publishing academic and scientific journal articles, and the inability to cope with the new coronavirus (COVID-19).

BACKGROUND: Translating research into practice is a central priority within the National Institutes of Health (NIH) Roadmap. The underlying aim of the NIH Roadmap is to accelerate the movement of scientific findings into practical health care provisions through translational research. MAIN TEXT: Despite the advances in health sciences, emerging infectious diseases have become more frequent in recent decades. Furthermore, emerging and reemerging pathogens have led to several global public health challenges. A question, and to an extent a concern, arises from this: Why our health care system is experiencing several challenges in encountering the coronavirus outbreak, despite the ever-growing advances in sciences, and the exponential rise in the number of published articles in the first quartile journals and even the ones among the top 1%? CONCLUSION: Two responses could be potentially provided to the above question: First, there seems to be a significant gap between our theoretical knowledge and practice. And second that many scholars and scientists publish papers only to have a longer list of publications, and therefore publishing is viewed as a personal objective, rather than for improving communities' public health.