Related Keywords Research Articles

Bibliometric Analysis of the Published Studies on the Kindling Model between 1980 and 2023

Objective: Kindling is an animal model of epilepsy induced by electrical stimulation of the brain. The present study aimed to present a different perspective with a bibliometric approach by using the literature data on the “Kindling model” related keywords in the Web of Science (WoS) online database between 1980 and 2023.
 Methods: The bibliometric data were obtained from the online database WoS and analyzed and visualized with the VoS Viewer Program. The bibliometric datasets were analyzed and visualized regarding article productivity numbers according to years, article productivity numbers according to countries, the most used keywords according to authors, and cross-country cooperation.
 Result: Considering the results of the analysis of the published datasets, 2022 was determined as the year with the highest article productivity, and an acceleration was observed in the publication increase rate on the subject in general. When the order of the countries in the top three in the number of article productivity was examined, the USA, Germany, and Japan are the main countries, respectively. The most used keywords by the authors were determined as “Epilepsy”, “Kindling”, and “Hippocampus”. In the cooperation among countries, it was found that the USA, Germany, and Japan had more cooperation with other countries, respectively.
 Conclusıon: This study will contribute to the literature by providing a detailed understanding of the research basis, relevant research results, current research boundaries and main research focus in the Kindling Model.

Role of Internet of Things (IoT), Artificial Intelligence and Machine Learning in Musculoskeletal Pain: A Scoping Review.

Artificial intelligence (AI), Internet of Things (IoT),and machine learning (ML) have considerably increased in numerous critical medical sectors and significantly impacted our daily lives. Digital health interventions support cost-effective, accessible, and preferred interventions that meet time and resource constraints for large patient populations. Musculoskeletal conditions significantly impact society, the economy, and people's life. Adults with chronic neck and back pain are frequently the victims, rendering them physically unable to move. They often experience discomfort, necessitating them to take over-the-counter medications or painkilling gels. Technologies driven by AIhave been suggested as an alternative approach to improve adherence to exercise therapy, which in turn helps patients undertake exercises every day to relieve pain associated with the musculoskeletal system. Even though there are many computer-aided evaluations available for physiotherapy rehabilitation, current approaches to computer-aided performance and monitoring lack flexibility and robustness. A thorough literature search was conducted using key databases like PubMed and Google Scholar, as well as Medical Subject Headings (MeSH) terms and related keywords. This research aimed to determine if AI-operated digital health therapies that use cutting-edge IoT, brain imaging, and ML technologies are beneficial in lowering pain and enhancing functional impairment in patients with musculoskeletal diseases. The secondary goal was to ascertain whether solutions driven by machine learning or artificial intelligencecan improve exercise compliance and be viewed as a lifestyle choice.

Was CSR in our minds? The relevance of CSR in the vision and mission of Indian companies through the lens of ownership

PurposeThis study aims to explore the patterns of corporate social responsibility (CSR) practices and investments across different ownership groups and relevance of CSR practices in the vision and mission (V&M) statements of firms.Design/methodology/approachThe paper uses the neo-institutional theory approach, which explains similarities and differences in the CSR practices of organisations embedded within (and between) similar sectoral contexts. The study accounts the CSR activities of the top 100 companies listed on the Bombay Stock exchange (BSE) based on their ownership and checks the overlap of the CSR activities conducted by the companies with the ongoing social development schemes launched in India during the same of time. The time period between 2017 and 2020 is chosen to analyse the CSR studies. The study uses content analysis technique to derive conclusions. A textual analysis of top 100 listed firms across all ownership groups aimed at understanding patterns of CSR practices opted by the different groups and coherence of CSR patterns in the V&M statements. CSR related keywords were analysed in the V&M statements to understand what influence reporting of CSR practices in the strategic communication of firms.FindingsOverall analysis indicated that top 100 firms prefer to invest in the areas of “Education”, “Sustainability” “Skill” where public-owned firms preferred towards “Sanitation” and “Environment/Sustainability” showing concurrence with local development goals. Private and foreign groups preferred to park their CSR funds in “Education” and “Skill” development showing coherence with the global agendas. Public-owned firms tend to report more CSR related specifically “Environment’ and “Sustainability” in the strategic documents. However, private and foreign firms do not pay any significance to CSR related keywords in their V&M statements.Research limitations/implicationsFindings suggest that despite of huge CSR investments, private and foreign-owned firms lack CSR focus and communication in their V&M statements, which may create disintegration in the CSR investment and strategic alignment of near-term and future goals. The paper suggests that private and foreign firms should also communicate their CSR practices through their V&M to stakeholders so that CSR practices may not remain mere 2% mandated expenditure by the Government of India.Originality/valueThe study contributes in confirming the success of the CSR policy mandate in supplementing government’s social development programmes along with indications on the role of family firms in accelerating the process of community development as compared to foreign firms. The study also favours integration of CSR disclosures in the V&M statements to gain long-term benefit out of these investments.

Update on the effectiveness of COVID-19 vaccines on different variants of SARS-CoV-2.

It has been more than three years since the first emergence of coronavirus disease 2019 (COVID-19) and millions of lives have been taken to date. Like most pandemics caused by viral infections, massive public vaccination is the most promising approach to cease COVID-19 infection. In this regard, several vaccine platforms including inactivated virus, nucleic acid-based (mRNA and DNA vaccines), adenovirus-based, and protein-based vaccines have been designed and developed for COVID-19 prevention and many of them have received FDA or WHO approval. Fortunately, after global vaccination, the transmission rate, disease severity, and mortality rate of COVID-19 infection have diminished significantly. However, a rapid increase in COVID-19 cases due to the omicron variant in vaccinated countries has raised concerns about the effectiveness of these vaccines. In this review, articles published between January 2020 and January 2023 were reviewed using PubMed, Google Scholar, and Web of Science search engines with appropriate related keywords. The related papers were selected and discussed in detail. The current review mainly focuses on the effectiveness and safety of COVID-19 vaccines against SARS-CoV-2 variants. Along with discussing the available and approved vaccines, characteristics of different variants of COVID-19 have also been discussed in brief. Finally, the currently circulating COVID-19 variant i.e Omicron, along with the effectiveness of available COVID-19 vaccines against these new variants are discussed in detail. In conclusion, based on the available data, administration of newly developed bivalent mRNA COVID-19 vaccines, as booster shots, would be crucial to prevent further circulation of the newly developed variants.

Application of the thrombin generation assay in patients with antiphospholipid syndrome: A systematic review of the literature.

The antiphospholipid syndrome (APS) is classified by the presence of antiphospholipid antibodies (aPL) and thrombotic and/or adverse obstetric outcomes. The diagnosis and risk assessment of APS is challenging. This systematic review investigated if the thrombin generation (TG) assay could be helpful for APS diagnosis and risk assessment. A systemic review was performed by searching two databases (MEDLINE and Embase) until March 31, 2022, using a search strategy with two concepts: APS and TG, and related keywords. Two reviewers independently screened the articles based on predefined inclusion and exclusion criteria. Data extraction and quality assessment with the Newcastle-Ottawa Scale (NOS) were performed independently. Synthesis Without Meta-analysis guidelines were followed for data synthesis reporting. Fourteen studies with 677 APS and 1,349 control subjects were included with variable quality according to the NOS. Twelve studies measured TG via the calibrated automated thrombogram (CAT) method using a fluorogenic substrate, whereas two used a chromogenic substrate-based TG assay. One study compared the CAT assay to the fully-automated ST Genesia® (Stago, France). Two studies initiated TG using platelet-rich plasma, whereas the rest of the studies used platelet-poor plasma. Resistance to activated protein C (aPC) was examined in ten studies. They reported a significant increase in aPC-resistance in APS patients compared to healthy controls, aPL-carriers, and thrombotic controls. Based on two studies, the prevalence of aPC-resistance was higher in APS patients compared to healthy controls and thrombotic controls with odds ratios of 5.9 and 6.8-12.8, respectively (p < 0.05). In contrast, no significant difference in aPC-resistance was found between APS patients and autoimmune disease controls. Furthermore, 7/14 studies reported TG-parameters including peak height, endogenous thrombin potential, lag time, and time to peak, but these outcomes were highly variable between studies. Furthermore, TG methodology between studies differed greatly, impacting the comparability of the studies. aPC-resistance measured with TG was increased in APS patients compared to healthy and thrombotic controls, but the diagnostic and prognostic value is unclear compared to current diagnostic strategies. Studies of other TG-parameters were heterogeneous and more research is needed to identify their potential added value in APS diagnosis. https://www.PROSPERO/, identifier: CRD42022308363.

Bacterial biofilm prevalence in dental unit waterlines: a systematic review and meta-analysis

BackgroundsNumerous studies have shown that dental unit water lines (DUWLs) are often contaminated by a wide range of micro-organisms (bacteria, fungi, protozoa) and various prevalence have been reported for it in previous studies. Therefore, this review study aims to describe the prevalence of bacterial biofilm contamination of DUWLs.MethodsThis is a systematic review and meta-analysis in which the related keywords in different international databases, including Medline (via PubMed) and Scopus were searched. The retrieved studies were screened and the required data were extracted from the included studies. Three standard methods including American Dental Association (ADA), The Center for Disease Control and Prevention (CDC) and contaminated > 100 CFU/ml(C-100) standards were used to assess the bacterial biofilm contamination of DUWLs. All studies that calculated the prevalence of bacterial biofilm contamination of DUWLs, and English full-text studies were included in the meta-analysis. Studies that did not have relevant data or used unusual laboratory methods were excluded. Methodological risk of bias was assessed by a related checklist and finally, the data were pooled by fixed or random-effect models.ResultsSeven hundred and thirty-six studies were identified and screened and 26 related studies were included in the meta-analysis. The oldest included study was published in 1976 and the most recent study was published in 2020. According to the ADA, CDC and C-100 standards, the prevalence of bacterial contamination was estimated to be 85.0% (95% confidence interval (CI): 66.0–94.0%), 77.0% (95%CI: 66.0–85.0%) and 69.0% (95%CI: 67.0–71.0%), respectively. The prevalence of Legionella Pneumophila and Pseudomonas Aeruginosa in DUWLs was estimated to be 12.0% (95%CI: 10.0–14.0%) and 8.0% (95%CI: 2.0–24.0%), respectively.ConclusionThe results of this review study suggested a high prevalence of bacterial biofilm in DUWLs; therefore, the use of appropriate disinfecting protocol is recommended to reduce the prevalence of contamination and reduce the probable cross-infection.

Long-term outcomes of additional surgery versus non-gastrectomy treatment for early gastric cancer after non-curative endoscopic submucosal dissection: a meta-analysis.

Endoscopic resection is increasingly used in the treatment for early gastric cancer (EGC); however, about 15% of endoscopic submucosal dissection (ESD) cases report non-curative resection. The efficacy of different remedial interventions after non-curative ESD for EGC remains controversial. This meta-analysis aimed to compare the long-term outcomes of additional surgery and non-gastrectomy treatment for EGC patients who underwent non-curative ESD. All relevant studies published up to October 2021 were systematically searched in the PubMed, Web of Science, and Embase databases. The medical subject headings terms "early gastric cancer," "gastrectomy," "endoscopic submucosal dissection," and their related free keywords were used to search relevant articles without restrictions on regions, publication types, or languages. The Newcastle-Ottawa Quality Assessment Scale was used to evaluate the quality of the included studies. Odds ratios (ORs) with 95% confidence intervals (CIs) of 5-year overall survival (OS), disease-specific survival (DSS), disease-free survival (DFS) and hazard ratios (HRs) with 95% CIs of OS were calculated using a random- or fixed-effects model. This meta-analysis included 17 retrospective cohort studies with 5880 patients, of whom 3167 underwent additional surgery and 2713 underwent non-gastrectomy. We found that patients receiving additional gastrectomy had better 5-year OS (OR = 3.63, 95% CI = 3.05-4.31), DSS (OR = 3.22, 95% CI = 2.22-4.66), and DFS (OR = 4.39, 95% CI = 1.78-10.82) outcomes than those receiving non-gastrectomy treatments. The pooled HR also showed that gastrectomy following non-curative ESD significantly improved OS (HR = 0.40, 95% CI = 0.33-0.48). In addition, elderly patients benefited from additional surgery in consideration of the 5-year OS (HR = 0.54, 95% CI = 0.41-0.72). Compared with non-gastrectomy treatments, additional surgery offered better long-term survival outcomes for patients with EGC who underwent non-curative ESD.

Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis.

Social media has emerged as a critical mass communication tool, with both health information and misinformation now spread widely on the web. Prior to the COVID-19 pandemic, some public figures promulgated anti-vaccine attitudes, which spread widely on social media platforms. Although anti-vaccine sentiment has pervaded social media throughout the COVID-19 pandemic, it is unclear to what extent interest in public figures is generating anti-vaccine discourse. We examined Twitter messages that included anti-vaccination hashtags and mentions of public figures to assess the connection between interest in these individuals and the possible spread of anti-vaccine messages. We used a data set of COVID-19-related Twitter posts collected from the public streaming application programming interface from March to October 2020 and filtered it for anti-vaccination hashtags "antivaxxing," "antivaxx," "antivaxxers," "antivax," "anti-vaxxer," "discredit," "undermine," "confidence," and "immune." Next, we applied the Biterm Topic model (BTM) to output topic clusters associated with the entire corpus. Topic clusters were manually screened by examining the top 10 posts most highly correlated in each of the 20 clusters, from which we identified 5 clusters most relevant to public figures and vaccination attitudes. We extracted all messages from these clusters and conducted inductive content analysis to characterize the discourse. Our keyword search yielded 118,971 Twitter posts after duplicates were removed, and subsequently, we applied BTM to parse these data into 20 clusters. After removing retweets, we manually screened the top 10 tweets associated with each cluster (200 messages) to identify clusters associated with public figures. Extraction of these clusters yielded 768 posts for inductive analysis. Most messages were either pro-vaccination (n=329, 43%) or neutral about vaccination (n=425, 55%), with only 2% (14/768) including anti-vaccination messages. Three main themes emerged: (1) anti-vaccination accusation, in which the message accused the public figure of holding anti-vaccination beliefs; (2) using "anti-vax" as an epithet; and (3) stating or implying the negative public health impact of anti-vaccination discourse. Most discussions surrounding public figures in common hashtags labelled as "anti-vax" did not reflect anti-vaccination beliefs. We observed that public figures with known anti-vaccination beliefs face scorn and ridicule on Twitter. Accusing public figures of anti-vaccination attitudes is a means of insulting and discrediting the public figure rather than discrediting vaccines. The majority of posts in our sample condemned public figures expressing anti-vax beliefs by undermining their influence, insulting them, or expressing concerns over public health ramifications. This points to a complex information ecosystem, where anti-vax sentiment may not reside in common anti-vax-related keywords or hashtags, necessitating further assessment of the influence that public figures have on this discourse.

AI-Based Knowledge Extraction from the Bioprinting Literature for Identifying Technology Trends.

Bioprinting is a rapidly evolving field, as represented by the exponential growth of articles and reviews published each year on the topic. As the number of publications increases, there is a need for an automatic tool that can help researchers do more comprehensive literature analysis, standardize the nomenclature, and so accelerate the development of novel manufacturing techniques and materials for the field. In this context, we propose an automatic keyword annotation model, based on Natural Language Processing (NLP) techniques, that can be used to find insights in the bioprinting scientific literature. The approach is based on two main data sources, the abstracts and related author keywords, which are used to train a composite model based on (i) an embeddings part (using the FastText algorithm), which generates word vectors for an input keyword, and (ii) a classifier part (using the Support Vector Machine algorithm), to label the keyword based on its word vector into a manufacturing technique, employed material, or application of the bioprinted product. The composite model was trained and optimized based on a two-stage optimization procedure to yield the best classification performance. The annotated author keywords were then reprojected on the abstract collection to both generate a lexicon of the bioprinting field and extract relevant information, like technology trends and the relationship between manufacturing-material-application. The proposed approach can serve as a basis for more complex NLP-related analysis toward the automated analysis of the bioprinting literature.

Structure or Anarchy

Bibliometric analysis is essential for understanding the growth, health, and trajectory of scientific disciplines. In effect, such analyses help researchers determine if a given field is well-structured or fragmented through anarchy. Prior work examined to what extent cybersecurity education research generated a follow-up study. The goal of the work was to uncover bibliometric features and characteristics linked to overall maturity of the field. The results suggested little, if any, research follow up or extension took place based on the dearth of interlinking between citations. This work continues the line of bibliometric description by investigating if cybersecurity education papers are not extended because of discoverability issues during literature reviews. To answer this question, this work explored structural bibliometric indicators in 163 journal and conference articles. Specifically, we extracted metadata keywords and paper content keywords as input to frequency analyses of the sample articles. The results revealed 12.4% of the sample contains metadata keywords. Further, 18.03% of the sample contained educated related keywords. Lastly, four of the top five sample papers by citation count do not contain keywords at all and papers with content only keywords exhibited more frequent citation than those with only metadata keywords. Based on these results, we offer observational conclusions as well as notions for future work.

Application of Models and Theories of Health Education and Health Promotion in the Prevention of Substance Abuse in Adolescents: A Systematic Review

Introduction: The purpose of this study was to investigate the effectiveness of interventions based on models and theories of health education and promotion in preventing substance abuse in adolescents. Method: A detailed search was performed in Magiran, SID, Web of Science, Scopus, Pubmed, and Google Scholar databases using related keywords to extract all studies published in this field with the time limit of January 1, 2011 to December 21, 2021. After screening the studies, 11 articles that met the inclusion criteria were examined. Results: In this research, there were 7 semi-experimental studies, 3 clinical trials, and 1 unclear study, which were conducted on first- and second-grade high school students. Educational interventions were conducted in 6 articles based on the theory of planned behavior, 2 articles based on the health belief model, 1 article based on the developed theory of rational action, 1 article based on the trans theoretical model, and 1 article based on the family interaction theory. Conclusion: The results showed that the use of different models/theories could have a positive effect on preventing substance abuse and subsequently performing health behaviors. Based on the findings, the structure of attitude and self-efficacy were introduced as the most important and strongest variables in most studies and played a crucial role in preventing substance abuse and health behavior in students

Herbal supplements as treatment options for COVID-19: A call for clinical development of herbal supplements for emerging and re-emerging viral threats in Sub-Saharan Africa

The advent of Corona virus Disease 2019 (COVID-19) distorted health systems of many countries. Efforts have been made to either develop new treatment solutions such as vaccines or repurpose previously adopted drugs. Challenges in accessing available treatment, inadequate, non-existent, or overstretched healthcare facilities, long COVID disease, cultural practices and beliefs about vaccination, vaccine hesitancy, availability, accessibility and perceived safety of herbal supplements seem to be major factors propelling individuals to use herbal supplements. Published reports advocating for clinical development of herbal supplements for COVID-19 and other emerging and re-emerging viral diseases are sparse. This paper aims to review the pathogenesis of COVID-19, use of herbal products during the pandemic and make case for clinical development of herbal supplements through the adoption of modern and acceptable technologies and research processes.This was a scoping review. Database searches of Google Scholar, PubMed and ResearchGate among others were performed using related keywords to identify relevant journals and lists of primary articles. Clinical trial databases:-Clinicaltrial.gov, Pan African Clinical Trial Registry (PACTR) and WHO international clinical trial registry (ICTRP) were reviewed to extract data.The use of herbal supplements during COVID-19 was not only peculiar to individuals living in Sub-Saharan Africa, but a global practice. Herbal supplements recommended to manage COVID-19 have not been validated using clinical trials. Available data showed that the number of herbal supplements undergoing clinical trial for COVID-19 indication in Africa was low.The availability of medicinal plants in Sub-Saharan Africa if well explored has great potentials to address various emerging and re-emerging viral diseases confronting the region. The economic potential of clinically validated herbal supplements are huge, and tapping into this opportunity created by preference of population to herbal supplement could increase export of herbal supplement and gross domestic product (GDP) of respective countries in Africa.

Heart failure and depression: A perspective from bibliometric analysis

Depression commonly occurs in heart failure patients, and negatively influences quality of life and disease prognosis. This study explored heart failure and depression-related research from a bibliometric perspective. Relevant publications were searched on June 24, 2022. The Bibliometrix package in R was used to conduct quantitative analyses including the trends in publications, and related countries, articles, authors and keywords. VOSviewer software was used to conduct the visualization map on co-word, co-author, and institution co-authorship analyses. CiteSpace software was used to illustrate the top keywords with citation burst. A total of 8,221 publications in the heart failure and depression-related research field were published between 1983 and 2022. In this field, the United States had the most publications (N = 3,013; 36.65%) and highest total citation (N = 149, 376), followed by China, Germany, Italy and Japan. Author Moser and Duke University were the most productive author and institution, respectively. Circulation is the most influential journal. Apart from "heart failure" and "depression," "quality of life," "mortality" and "myocardial infarction" were the most frequently used keywords in this research area; whereas more recently, "self care" and "anxiety" have been used more frequently. This bibliometric analysis showed a rapid growth of research related to heart failure and depression from 1989 to 2021, which was mostly led by North America and Europe. Future directions in this research area include issues concerning self-care and anxiety about heart failure. As most of the existing literature were published in English, publications in other languages should be examined in the future.

An Informed Neural Network for Discovering Historical Documentation Assisting the Repatriation of Indigenous Ancestral Human Remains

Among the pressing issues facing Australian and other First Nations peoples is the repatriation of the bodily remains of their ancestors, which are currently held in Western scientific institutions. The success of securing the return of these remains to their communities for reburial depends largely on locating information within scientific and other literature published between 1790 and 1970 documenting their theft, donation, sale, or exchange between institutions. This article reports on collaborative research by data scientists and social science researchers in the Research, Reconcile, Renew Network (RRR) to develop and apply text mining techniques to identify this vital information. We describe our work to date on developing a machine learning-based solution to automate the process of finding and semantically analysing relevant texts. Classification models, particularly deep learning-based models, are known to have low accuracy when trained with small amounts of labelled (i.e. relevant/non-relevant) documents. To improve the accuracy of our detection model, we explore the use of an Informed Neural Network (INN) model that describes documentary content using expert-informed contextual knowledge. Only a few labelled documents are used to provide specificity to the model, using conceptually related keywords identified by RRR experts in provenance research. The results confirm the value of using an INN network model for identifying relevant documents related to the investigation of the global commercial trade in Indigenous human remains. Empirical analysis suggests that this INN model can be generalized for use by other researchers in the social sciences and humanities who want to extract relevant information from large textual corpora.

Christian Orthodox Fasting as a Traditional Diet with Low Content of Refined Carbohydrates That Promotes Human Health: A Review of the Current Clinical Evidence

Christian Orthodox fasting is a pattern high in complex carbohydrates and low in refined carbohydrates. It has been explored in association with its potential health benefits. The present review aims to comprehensively explore the existing available clinical data concerning the potential favorable impact of the dietary pattern of Christian Orthodox fasting on human health. PubMed database, Web of Science and Google Scholar were extensively searched in order to identify the more appropriate clinical studies that explore the effect of Christian Orthodox fasting on health-related outcomes in humans utilizing relative keywords. We initially retrieved 121 records through database searching. After applying several exclusion criteria, 17 clinical studies were finally included in this review study. Christian Orthodox fasting showed beneficial effects concerning glucose and lipid control, whereas the data for blood pressure remain inconclusive. Concerning weight control, fasters were characterized by lower body mass and lower caloric intake in the course of the fasting periods. During fasting, this pattern is higher in fruits and vegetables, showing the absence of dietary deficiencies for iron and folate. Nevertheless, dietary deficiencies were recorded for calcium and vitamin B2, and also hypovitaminosis D has been noticed in monks. Interestingly, the vast majority of monks do present with both good quality of life and mental health. Overall, Christian Orthodox fasting is a dietary pattern low in refined carbohydrates and high in complex carbohydrates and fiber that may be beneficial for human health promotion and chronic disease prevention. However, further studies are strongly recommended on the impact of long-term religious fasting on HDL cholesterol levels and blood pressure.

Information related to tobacco products in Indian undergraduate college syllabus: a content analysis

Background: Health education through college textbooks is effective in promoting knowledge, reforming, and improving health related behaviours among youths. This study evaluated the amount of tobacco related health and other information among the undergraduate college syllabus in their curriculum. Methods: Under graduate college courses that were enrolled by students in the academic year 2019-2020 according to the All-India survey on higher education were included in the study. A total of 28 undergraduate courses under 12 governing bodies were included for content analysis. These curriculums were analysed by three examiners for the search of tobacco related keywords obtained from the WHO glossary of tobacco terms. The inter examiner reliability was calculated using the Cohen's Kappa in the SPSS software (version 25). Results: Total of 3383 pages of the curriculum from different undergraduate courses were analysed. Results showed that the total number of information related to tobacco appeared in the form of text as 15 and tabulations as 4, to a total of 19. Among the different courses, the tobacco-related contents were higher in MBBS curriculum. Distribution of the tobacco related contents under health information were found to be higher when compared to the tobacco cessation contents and laws. Conclusions: The distribution of tobacco related contents were found to be very less among the undergraduate courses. There is a lack of information regarding the cessation process and guidance against tobacco related habits.

Twitterati on COVID-19 pandemic-environment linkage: Insights from mining one year of tweets

The COVID-19 pandemic seems to have had positive (although short-lived, e.g., reduction in pollution due to lockdown) as well as negative (e.g., increasing plastic pollution due to use of disposable masks, etc.) impacts on the environment. The pandemic-environment linkage also includes circumstances when regions experienced extreme weather events, such as floods and cyclones, and disaster management became challenging. This study aims to examine the trends in public discourses on Twitter on these interactions between the pandemic and environment. The present study follows the most recent literature on understanding public perceptions — which acknowledges Twitter to be an abundant source of information on public discussions on any global issue, including the pandemic. A Python-based code is developed to extract Twitter data spanning over a year, and analyze the presence of covid-environment related keywords and other attributes. It is found that the Twitterati aggressively viewed the impacts (such as economic slowdown and high mortality) of the pandemic as miniatures of the results of future climate change. The community was also highly concerned about the varying air and plastic pollution levels with the change in lockdown and covid prevention policies. Extreme weather events were a high-frequency topic when they impacted countries such as India, the USA, Australia, the Philippines and Vietnam. This study makes a novel attempt to provide an overview of public discourses on the pandemic-environment linkage and; can be a crucial addition to the literature on assessing public perception of environmental threats through Twitter data mining.

A systematic literature review on mHealth related research during the COVID-19 outbreak

PurposeUsing smart mobile devices, called mobile health (mHealth), facilitates providing health services, speeds up the process and reduces the costs and complications of direct services. Also, mHealth has many capabilities and applications in epidemic and pandemic outbreaks. This study aimed to systematically review the mHealth adoption researches in epidemic/pandemic outbreaks and provide some suggestions for future research for tackling for COVID-19.Design/methodology/approachThe results produced in this study are based on the literature analysis of 36 articles on mHealth adoption. To find the relevant studies; searches were done in PubMed, Google, Web of Science and Scopus by related keywords during 2020–2022. After selecting the studies based on the inclusion and exclusion criteria, data were collected by using PRIZMA methods for systematically reviewing the literature.FindingsOf the 727 retrieved studies, 36 studies related to mHealth services during the pandemic situation were included. This has been performed by collecting data including demographic details, methodological details, limitations and significance of relationships between the constructs from the available articles based on the mHealth services. All studies emphasized the positive effect of mHealth for usage in epidemic/pandemic outbreaks.Research limitations/implicationsThe main applications of mHealth for epidemic/pandemic outbreaks included public health aspects, data management, educational programs, diagnosis as well as treatment. mHealth is an appropriate method for encountering epidemic/pandemic outbreaks due to its extensive applications. In the pandemic outbreak of COVID-19, mHealth is one of the best choices to use in the patient-physician relationship as Tele-visits, using in fever coach, providing real-time information for healthcare providers, population monitoring and detecting the diseases based on data obtained from different locations. These findings will help the mHealth providers to design their services accordingly.Originality/valueThis study contributes to the researchers and academicians by providing relevant information regarding the mHealth during the COVID-19 pandemic. This is the first time initiative to explore the research questions and future research direction for the researchers during the COVID-19 outbreak. Based on this, we present a comprehensive and actionable research agenda and practical implications.

Analysis of News Regarding on Shared Housing Using Text Mining Techniques

This study was conducted to explore the development direction of shared housing as a sustainable housing product by exploring the perception of shared housing and related words through Big data analysis and examining the correlation between keywords. Data was collected using Big Kinds, a news search service, and sentiment analysis, text mining analysis, N-gram and network analysis, and CONCOR analysis were performed using TEXTOM and UCINET, which are Big data analyses programs. As a result of the analysis. First, shared housing began to be introduced as a new housing type in late 2010 and began to be supplied in earnest in 2013. Second, the sensibility for shared housing has a liking and interest in the new space, but there is also a sense of rejection of living together. Third, as a result of keyword frequency analysis, the frequency of occurrence of related keywords indicating the residence of shared housing such as youth and single-person households and keywords indicating the characteristics of youth housing policy projects was high. Fourth, CONCOR analysis found significant four cluster characteristics: ‘Share house’, ‘Co-living’, ‘Remodeling social housing’, and ‘Young people rental housing’.

Aromatherapy for Postpartum Depression: A Systematic Review and Meta-Analysis.

The incidence and prevalence of postpartum depression is increasing due to multiple factors. Aromatherapy is a widely used complementary and alternative (CAM) therapy in the management of depression. This systematic review and meta-analysis was done to find the effect of aromatherapy on postpartum depression. Electronic databases like PubMed, Scopus, Cochrane Library and Science Direct since inception till February 2021 were searched using related keywords to obtain eligible studies. Randomised controlled trial studies (RCTs) reporting the effects of aromatherapy therapy in women with postpartum depression were included. Aromatherapy studies conducted on population other than postpartum women were excluded. The primary outcome was depression scores obtained by using valid depression scales. Meta-analysis was performed using the random-effects model of Der Simonian and Laird to produce summary treatment effects in terms of Hedges' g effect sizes with 95% confidence interval (CI). A total of 4 RCTs (n=303) were included. The results indicate that aromatherapy (Hedges' g =-0.94, 95 CI= -2.55, 0.61, I2=88%, p<0.01) reduces depression levels among postpartum women without statistical significance. The available evidences suggest aromatherapy may be effective in reducing post-partum depression. The number of scientific evidences currently available are very limited and more studies with robust study designs are required to strongly recommend aromatherapy in the management of post-partum depressions. However, being a safer intervention with no adverse effects being reported in previous studies, aromatherapy could definitely be added as an effective complementary therapy in the management of post-partum depression along with conventional medicine.