Publications by authors named "Mowafa Househ"

141 Publications

A comprehensive overview of the COVID-19 literature: A machine learning-based bibliometric analysis.

J Med Internet Res 2020 Nov 24. Epub 2020 Nov 24.

College of Science and Engineering, Hamad Bin Khalifa University, A 105 H, LAS Building, Education City, Doha, QA.

Background: Shortly after the emergence of the novel coronavirus disease (COVID-19), researchers rapidly mobilized to study numerous aspects of the disease such as its evolution, clinical manifestations, effects, treatments, and vaccination. This led to a rapid increase in the number of COVID-19-related publications. Identifying trends and areas of interest using traditional review methods (e.g., scoping review and systematic reviews) for such a large domain area is challenging.

Objective: We aimed to conduct an extensive bibliometric analysis to provide a comprehensive overview of the COVID-19 literature.

Methods: We used the COVID-19 Open Research Dataset (CORD-19) that consists of large number of articles related to all coronaviruses. We used machine learning method to analyze most relevant COVID-19 related articles and extracted most prominent topics. Specifically, we used clustering algorithm to group articles based on similarity of their abstracts to identify the research hotspots and current research directions. We have made our software accessible to the community via GitHub.

Results: Of the 196,630 publications retrieved from the database, we included 28,904 in the analysis. The mean number of weekly publications was 990 (SD=789.3). The country that published the highest number of articles was China (n=2,950). The largest number of documents was published in BioRxiv. Lei Liu affiliated in the Southern University of Science and Technology in China published the highest number of documents (n=46). Based on titles and abstracts alone, we were able to identify 1,515 surveys, 733 systematic reviews, 512 cohort studies, 480 meta-analyses, 362 randomized control trials. We identified 19 different topics addressed by the included studies. The most dominant topic was public health response followed by clinical care practices during COVID-19, its clinical characteristics and risk factors, and epidemic models for its spread.

Conclusions: We provided an overview of the COVID-19 literature and identified current hotspots and research directions. Our findings can be useful for the research community to help prioritize research needs, and recognize leading COVID-19 researchers, institutes, countries, and publishers. This study showed that an AI-based bibliometric analysis has the potential to rapidly explore large corpora of academic publications during a public health crisis. We believe that this work can be used to analyze other eHealth related literature to help clinicians, administrators and policy makers to have a holistic view of the literature and be able to categorize the different topics of existing research for further analysis. It can be further scaled, for instance in time, to clinical summary documentation. Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/23703DOI Listing
November 2020

Perceptions and Opinions of Patients About Mental Health Chatbots: Scoping Review.

J Med Internet Res 2021 Jan 13;23(1):e17828. Epub 2021 Jan 13.

Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.

Background: Chatbots have been used in the last decade to improve access to mental health care services. Perceptions and opinions of patients influence the adoption of chatbots for health care. Many studies have been conducted to assess the perceptions and opinions of patients about mental health chatbots. To the best of our knowledge, there has been no review of the evidence surrounding perceptions and opinions of patients about mental health chatbots.

Objective: This study aims to conduct a scoping review of the perceptions and opinions of patients about chatbots for mental health.

Methods: The scoping review was carried out in line with the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) extension for scoping reviews guidelines. Studies were identified by searching 8 electronic databases (eg, MEDLINE and Embase) in addition to conducting backward and forward reference list checking of the included studies and relevant reviews. In total, 2 reviewers independently selected studies and extracted data from the included studies. Data were synthesized using thematic analysis.

Results: Of 1072 citations retrieved, 37 unique studies were included in the review. The thematic analysis generated 10 themes from the findings of the studies: usefulness, ease of use, responsiveness, understandability, acceptability, attractiveness, trustworthiness, enjoyability, content, and comparisons.

Conclusions: The results demonstrated overall positive perceptions and opinions of patients about chatbots for mental health. Important issues to be addressed in the future are the linguistic capabilities of the chatbots: they have to be able to deal adequately with unexpected user input, provide high-quality responses, and have to show high variability in responses. To be useful for clinical practice, we have to find ways to harmonize chatbot content with individual treatment recommendations, that is, a personalization of chatbot conversations is required.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/17828DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840290PMC
January 2021

Analysis of Diabetes Apps to Assess Privacy-Related Permissions: Systematic Search of Apps.

JMIR Diabetes 2021 Jan 13;6(1):e16146. Epub 2021 Jan 13.

Faculty of Health Sciences, Universitat Oberta de Catalunya, Barcelona, Spain.

Background: Mobile health has become a major vehicle of support for people living with diabetes. Accordingly, the availability of mobile apps for diabetes has been steadily increasing. Most of the previous reviews of diabetes apps have focused on the apps' features and their alignment with clinical guidelines. However, there is a lack of knowledge on the actual compliance of diabetes apps with privacy and data security guidelines.

Objective: The aim of this study was to assess the levels of privacy of mobile apps for diabetes to contribute to the raising of awareness of privacy issues for app users, developers, and governmental data protection regulators.

Methods: We developed a semiautomatic app search module capable of retrieving Android apps' privacy-related information, particularly the dangerous permissions required by apps, with the aim of analyzing privacy aspects related to diabetes apps. Following the research selection criteria, the original 882 apps were narrowed down to 497 apps that were included in the analysis.

Results: Approximately 60% of the analyzed diabetes apps requested potentially dangerous permissions, which pose a significant risk to users' data privacy. In addition, 28.4% (141/497) of the apps did not provide a website for their privacy policy. Moreover, it was found that 40.0% (199/497) of the apps contained advertising, and some apps that claimed not to contain advertisements actually did. Ninety-five percent of the apps were free, and those belonging to the "medical" and "health and fitness" categories were the most popular. However, app users do not always realize that the free apps' business model is largely based on advertising and, consequently, on sharing or selling their private data, either directly or indirectly, to unknown third parties.

Conclusions: The aforementioned findings confirm the necessity of educating patients and health care providers and raising their awareness regarding the privacy aspects of diabetes apps. Therefore, this research recommends properly and comprehensively training users, ensuring that governments and regulatory bodies enforce strict data protection laws, devising much tougher security policies and protocols in Android and in the Google Play Store, and implicating and supervising all stakeholders in the apps' development process.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/16146DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840294PMC
January 2021

Patients' Perspectives About Factors Affecting Their Use of Electronic Personal Health Records in England: Qualitative Analysis.

J Med Internet Res 2021 Jan 13;23(1):e17500. Epub 2021 Jan 13.

School of Pharmacy and Medical Sciences, University of Bradford, Bradford, United Kingdom.

Background: General practices (GPs) in England have recently introduced a nationwide electronic personal health record (ePHR) system called Patient Online or GP online services, which allows patients to view parts of their medical records, book appointments, and request prescription refills. Although this system is free of charge, its adoption rates are low. To improve patients' adoption and implementation success of the system, it is important to understand the factors affecting their use of the system.

Objective: The aim of this study is to explore patients' perspectives of factors affecting their use of ePHRs in England.

Methods: A cross-sectional survey was carried out between August 21 and September 26, 2017. A questionnaire was used in this survey to collect mainly quantitative data through closed-ended questions in addition to qualitative data through an open-ended question. A convenience sample was recruited in 4 GPs in West Yorkshire, England. Given that the quantitative data were analyzed in a previous study, we analyzed the qualitative data using thematic analysis.

Results: Of the 800 eligible patients invited to participate in the survey, 624 (78.0%) returned a fully completed questionnaire. Of those returned questionnaires, the open-ended question was answered by 136/624 (21.8%) participants. A total of 2 meta-themes emerged from participants' responses. The first meta-theme comprises 5 themes about why patients do not use Patient Online: concerns about using Patient Online, lack of awareness of Patient Online, challenges regarding internet and computers, perceived characteristics of nonusers, and preference for personal contact. The second meta-theme contains 1 theme about why patients use Patient Online: encouraging features of Patient Online.

Conclusions: The challenges and concerns that impede the use of Patient Online seem to be of greater importance than the facilitators that encourage its use. There are practical considerations that, if incorporated into the system, are likely to improve its adoption rate: Patient Online should be useful, easy to use, secure, and easy to access. Different channels should be used to increase the awareness of the system, and GPs should ease registration with the system and provide manuals, training sessions, and technical support. More research is needed to assess the effect of the new factors found in this study (eg, lack of trust, difficulty registering with Patient Online) and factors affecting the continuing use of the system.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/17500DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840286PMC
January 2021

A multi-perspective approach to developing the Saudi Health Informatics Competency Framework.

Int J Med Inform 2021 Feb 8;146:104362. Epub 2020 Dec 8.

Preventive Medicine and Clinical Informatics, King Faisal Medical City for Southern Regions, Abha, Saudi Arabia.

Background: Determining the key sets of competencies necessary for a Health Informatics (HI) professional to practice effectively either solo or as a member of a multidisciplinary team has been challenging for the regulator and registration body responsible for the healthcare workforce in Saudi Arabia, which is the Saudi Commission for Health Specialties (SCFHS).

Objective: The aim of this study was to develop a HI competency framework to guide SCFHS to introduce a HI certification program that meets local healthcare needs and is aligned with the national digital health transformation strategy.

Methodology: A two-phase mixed methods approach was used in this study. For phase 1, a scoping review was conducted to identify HI competencies that have been published in the relevant literature. Out of a total 116 articles found relevant, 20 were included for further analysis. For phase 2, Saudi HI stakeholders (N = 24) that included HI professionals, administrators, academics, and healthcare professionals were identified and participated in an online survey, and asked to rank the importance of HI competencies distinguished in phase 1. To further validate and contextualize the competency framework, multiple focus groups and expert panel meetings were undertaken with the key stakeholders.

Results: For phase 1, about 1315 competencies were initially extracted from the included studies. After iterative reviews and refinements of codes and themes, 6 preliminary domains, 23 sub-domains and 152 competencies were identified. In phase 2, a total of 24 experts participated in the online surveys and ranked 58 out of 152 competencies as 'very important/required', each received 75 % or more of votes. The remaining competencies (N = 94) were included in a list for a further discussion in the focus groups. A Total of fourteen HI experts accepted and joined in the focus groups. The multiphase approach resulted in a competency framework that included 92 competencies, that were grouped into 6 domains and 22 subdomains. The six key domains are: Core Principles; Information and Communication Technology (ICT); Health Sciences; Health Data Analytics; Education and Research; Leadership and Management.

Conclusion: The study developed the Saudi Health Informatics Competency Framework (SHICF) that is based on an iterative, evidence-based approach, with validation from key stakeholders. Future work should continue the validation, review, and development of the framework with continued collaboration from relevant stakeholders representing both the healthcare and educational communities. We anticipate that this work will be expanded and adopted by relative professional and scientific bodies in the Gulf Cooperation Council (GCC) region.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ijmedinf.2020.104362DOI Listing
February 2021

Technical Aspects of Developing Chatbots for Medical Applications: Scoping Review.

J Med Internet Res 2020 12 18;22(12):e19127. Epub 2020 Dec 18.

Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.

Background: Chatbots are applications that can conduct natural language conversations with users. In the medical field, chatbots have been developed and used to serve different purposes. They provide patients with timely information that can be critical in some scenarios, such as access to mental health resources. Since the development of the first chatbot, ELIZA, in the late 1960s, much effort has followed to produce chatbots for various health purposes developed in different ways.

Objective: This study aimed to explore the technical aspects and development methodologies associated with chatbots used in the medical field to explain the best methods of development and support chatbot development researchers on their future work.

Methods: We searched for relevant articles in 8 literature databases (IEEE, ACM, Springer, ScienceDirect, Embase, MEDLINE, PsycINFO, and Google Scholar). We also performed forward and backward reference checking of the selected articles. Study selection was performed by one reviewer, and 50% of the selected studies were randomly checked by a second reviewer. A narrative approach was used for result synthesis. Chatbots were classified based on the different technical aspects of their development. The main chatbot components were identified in addition to the different techniques for implementing each module.

Results: The original search returned 2481 publications, of which we identified 45 studies that matched our inclusion and exclusion criteria. The most common language of communication between users and chatbots was English (n=23). We identified 4 main modules: text understanding module, dialog management module, database layer, and text generation module. The most common technique for developing text understanding and dialogue management is the pattern matching method (n=18 and n=25, respectively). The most common text generation is fixed output (n=36). Very few studies relied on generating original output. Most studies kept a medical knowledge base to be used by the chatbot for different purposes throughout the conversations. A few studies kept conversation scripts and collected user data and previous conversations.

Conclusions: Many chatbots have been developed for medical use, at an increasing rate. There is a recent, apparent shift in adopting machine learning-based approaches for developing chatbot systems. Further research can be conducted to link clinical outcomes to different chatbot development techniques and technical characteristics.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/19127DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775817PMC
December 2020

Artificial Intelligence in the Fight Against COVID-19: Scoping Review.

J Med Internet Res 2020 12 15;22(12):e20756. Epub 2020 Dec 15.

Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.

Background: In December 2019, COVID-19 broke out in Wuhan, China, leading to national and international disruptions in health care, business, education, transportation, and nearly every aspect of our daily lives. Artificial intelligence (AI) has been leveraged amid the COVID-19 pandemic; however, little is known about its use for supporting public health efforts.

Objective: This scoping review aims to explore how AI technology is being used during the COVID-19 pandemic, as reported in the literature. Thus, it is the first review that describes and summarizes features of the identified AI techniques and data sets used for their development and validation.

Methods: A scoping review was conducted following the guidelines of PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). We searched the most commonly used electronic databases (eg, MEDLINE, EMBASE, and PsycInfo) between April 10 and 12, 2020. These terms were selected based on the target intervention (ie, AI) and the target disease (ie, COVID-19). Two reviewers independently conducted study selection and data extraction. A narrative approach was used to synthesize the extracted data.

Results: We considered 82 studies out of the 435 retrieved studies. The most common use of AI was diagnosing COVID-19 cases based on various indicators. AI was also employed in drug and vaccine discovery or repurposing and for assessing their safety. Further, the included studies used AI for forecasting the epidemic development of COVID-19 and predicting its potential hosts and reservoirs. Researchers used AI for patient outcome-related tasks such as assessing the severity of COVID-19, predicting mortality risk, its associated factors, and the length of hospital stay. AI was used for infodemiology to raise awareness to use water, sanitation, and hygiene. The most prominent AI technique used was convolutional neural network, followed by support vector machine.

Conclusions: The included studies showed that AI has the potential to fight against COVID-19. However, many of the proposed methods are not yet clinically accepted. Thus, the most rewarding research will be on methods promising value beyond COVID-19. More efforts are needed for developing standardized reporting protocols or guidelines for studies on AI.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/20756DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744141PMC
December 2020

Patients' Adoption of Electronic Personal Health Records in England: Secondary Data Analysis.

J Med Internet Res 2020 10 7;22(10):e17499. Epub 2020 Oct 7.

Amman University College for Banking and Financial Sciences, Al-Balqa Applied University, Amman, Jordan.

Background: In England, almost all general practices (GPs) have implemented GP online services such as electronic personal health records (ePHRs) that allow people to schedule appointments, request repeat prescriptions, and access parts of their medical records. The overall adoption rate of GP online services has been low, reaching just 28% in October 2019. In a previous study, Abd-Alrazaq et al adopted a model to assess the factors that influence patients' use of GP online services in England. According to the previous literature, the predictive power of the Abd-Alrazaq model could be improved by proposing new associations between the existing variables in the model.

Objective: This study aims to improve the predictive power of the Abd-Alrazaq model by proposing new relationships between the existing variables in the model.

Methods: The Abd-Alrazaq model was amended by proposing new direct, mediating, moderating, and moderated mediating effects. The amended model was examined using data from a previous study, which were collected by a cross-sectional survey of a convenience sample of 4 GPs in West Yorkshire, England. Structural equation modeling was used to examine the theoretical model and hypotheses.

Results: The new model accounted for 53% of the variance in performance expectancy (PE), 76% of the variance in behavioral intention (BI), and 49% of the variance in use behavior (UB). In addition to the significant associations found in the previous study, this study found that social influence (SI) and facilitating conditions (FCs) are associated with PE directly and BI indirectly through PE. The association between BI and UB was stronger for younger women with higher levels of education, income, and internet access. The indirect effects of effort expectancy (EE), perceived privacy and security (PPS), and SI on BI were statistically stronger for women without internet access, patients with internet access, and patients without internet access, respectively. The indirect effect of PPS on BI was stronger for patients with college education or diploma than for those with secondary school education and lower, whereas the indirect effect of EE on BI was stronger for patients with secondary school education or lower than for those with college education or a diploma.

Conclusions: The predictive power of the Abd-Alrazaq model improved by virtue of new significant associations that were not examined before in the context of ePHRs. Further studies are required to validate the new model in different contexts and to improve its predictive power by proposing new variables. The influential factors found in this study should be considered to improve patients' use of ePHRs.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/17499DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578819PMC
October 2020

Understanding the stakeholders' preferences on a mobile application to reduce door to balloon time in the management of ST-elevated myocardial infarction patients - a qualitative study.

BMC Med Inform Decis Mak 2020 08 31;20(1):205. Epub 2020 Aug 31.

Prince Sattam Chair for Epidemiology and Public Health Research, Department of Family and Community Medicine, King Saud University, Riyadh, Saudi Arabia.

Background: ST-elevated myocardial infarction (STEMI) is a critical and time-sensitive emergency. The survival depends on prompt initiation of treatment requiring high precision and multi-level coordination between healthcare staff. The use of a mobile application may facilitate prompt management and shorten the door-to-balloon time by capturing information at the point of care and provide immediate feedback to all healthcare staff involved in STEMI management. The objective of the present study has two primary components: (i) to explore the suggestions and opinions of stakeholders in the development of a novel mobile app for code activation in management of STEMI patients (ii) to find out the healthcare workers' expectations including facilitating steps and challenges in the activation process of the proposed mobile app.

Methods: Unstructured interviews were conducted with key informants (n = 2) to identify all stakeholders, who also helped in developing the interview protocol and prototype designs. In-depth, semi-structured, open-ended, face to face interviews were conducted on 22 stakeholders involved in managing STEMI patients. All interviews were recorded and transcribed verbatim. Data were analyzed using ATLAS.ti 8 software, allowing themes and subthemes to emerge.

Results: The 22 participants included in the study were cardiology physicians (n = 3), emergency consultants (n = 4), emergency room (ER) senior nurses (n = 10), and cardiac catheterization lab staff (n = 5). The main themes identified during analysis were workflow and the App. The themes identified from the interviews surrounding the App were: 1) facilitating ideas 2) management steps needed 3) features 4) preferred code activation method 5) steps of integration 6) possible benefits of the App 7) barriers and 8) possible solutions to the suggested barriers. Most of the interviewed stakeholders expressed their acceptance after viewing the proposed mobile app prototype.

Conclusion: The study identified the mandatory features and the management steps needed from the stakeholder's perspectives. The steps for integrating the current paper-based workflow with the suggested mobile app were identified. The expected benefits of the App may include improved and faster management, accuracy, better communication, and improvement in data quality. Moreover, the possible barriers might comprise of doubtful acceptability, device-related issues, and time and data-related challenges.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12911-020-01219-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7457529PMC
August 2020

The benefits and threats of blockchain technology in healthcare: A scoping review.

Int J Med Inform 2020 10 14;142:104246. Epub 2020 Aug 14.

College of Science and Engineering, Hamad Bin Khalifa University, Qatar. Electronic address:

Background: The application of blockchain technology is being explored to improve the interoperability of patient health information between healthcare organisations while maintaining the privacy and security of data.

Objectives: The objective of this scoping review is to explore and categorise the benefits and threats of blockchain technology application in a healthcare system.

Methods: Databases such as PubMed, CINAHL, IEEE, Springer, and ScienceDirect were searched using a combination of terms related to blockchain, healthcare, benefits and threats. Backward-reference list checking was conducted to identify other relevant references. Study selection process was performed in three steps based on PRISMA flow diagram. Extracted data were synthesised and presented narratively using tables and figures.

Results: The search resulted in 84 relevant studies that have been conducted of which only 37 unique studies were included in this review. Eight benefits of blockchain were categorised in either patient related-benefits (security and authorisation, personalised healthcare, patients' health data tracking, and patient's health status monitoring) or organisational-related benefits (health information exchange, pharmaceutical supply chain, clinical trials, and medical insurance management). Meanwhile, eight threats of blockchain were categorised into three groups: organisational threats (installation and transaction costs, interoperability issues, and lack of technical skills), social threats (social acceptance and regulations issues), and technological threats (scalability issues, authorisation and security issues, high energy consumption, and slow processing speeds).

Conclusion: Blockchain is a viable technology that can improve the healthcare data sharing and storing system owing to its decentralisation, immutability, transparency and traceability features. However, many healthcare organisations remain hesitant to adopt blockchain technology due to threats such as security and authorisation issues, interoperability issues and lack of technical skills related to blockchain technology.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ijmedinf.2020.104246DOI Listing
October 2020

The use of technology in tracking soccer players' health performance: a scoping review.

BMC Med Inform Decis Mak 2020 08 11;20(1):184. Epub 2020 Aug 11.

College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

Background: Quantifying soccer players' performance using different types of technologies helps coaches in making tactical decisions and maintaining players' health. Little is known about the relation between the performance measuring technologies and the metrics they measure. The aim of this study is to identify and group the different types of technologies that are used to track the health-related performance metrics of soccer players.

Methods: We conducted a systematic search for articles using IEEE Xplore, PubMed, ACM DL, and papers from the Sports Medicine Journal. The papers were screened and extracted by two reviewers. The included papers had to fall under several criteria, including being about soccer, measuring health-related performance, and using technology to measure players' performance. A total of 1,113 papers were reviewed and 1,069 papers were excluded through the selection process.

Results: We reviewed 44 papers and grouped them based on the technology used and health-related metrics tracked. In terms of technology, we categorized the used technologies into wearable technologies (N=27/44) and in-field technologies (N=14/44). We categorized the tracked health-related metrics into physiological metrics (N=16/44) and physical metrics (N=44/44). We found out that wearable technologies are mainly used to track physical metrics (N=27/27) and are also used to track physiological metrics (N=14/27). In-field technologies are only used to track physical metrics (N=24/24).

Conclusion: Understanding how technology is related to players' performance and how it is used leads to an improvement in the monitoring process and performance outcomes of the players.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12911-020-01156-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7422501PMC
August 2020

Effectiveness and Safety of Using Chatbots to Improve Mental Health: Systematic Review and Meta-Analysis.

J Med Internet Res 2020 07 13;22(7):e16021. Epub 2020 Jul 13.

College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

Background: The global shortage of mental health workers has prompted the utilization of technological advancements, such as chatbots, to meet the needs of people with mental health conditions. Chatbots are systems that are able to converse and interact with human users using spoken, written, and visual language. While numerous studies have assessed the effectiveness and safety of using chatbots in mental health, no reviews have pooled the results of those studies.

Objective: This study aimed to assess the effectiveness and safety of using chatbots to improve mental health through summarizing and pooling the results of previous studies.

Methods: A systematic review was carried out to achieve this objective. The search sources were 7 bibliographic databases (eg, MEDLINE, EMBASE, PsycINFO), the search engine "Google Scholar," and backward and forward reference list checking of the included studies and relevant reviews. Two reviewers independently selected the studies, extracted data from the included studies, and assessed the risk of bias. Data extracted from studies were synthesized using narrative and statistical methods, as appropriate.

Results: Of 1048 citations retrieved, we identified 12 studies examining the effect of using chatbots on 8 outcomes. Weak evidence demonstrated that chatbots were effective in improving depression, distress, stress, and acrophobia. In contrast, according to similar evidence, there was no statistically significant effect of using chatbots on subjective psychological wellbeing. Results were conflicting regarding the effect of chatbots on the severity of anxiety and positive and negative affect. Only two studies assessed the safety of chatbots and concluded that they are safe in mental health, as no adverse events or harms were reported.

Conclusions: Chatbots have the potential to improve mental health. However, the evidence in this review was not sufficient to definitely conclude this due to lack of evidence that their effect is clinically important, a lack of studies assessing each outcome, high risk of bias in those studies, and conflicting results for some outcomes. Further studies are required to draw solid conclusions about the effectiveness and safety of chatbots.

Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42019141219; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019141219.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/16021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7385637PMC
July 2020

Machine Learning Models Reveal the Importance of Clinical Biomarkers for the Diagnosis of Alzheimer's Disease.

Stud Health Technol Inform 2020 Jun;272:478-481

College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Doha, Qatar.

Alzheimer's Disease (AD) is a neurodegenerative disease that causes complications with thinking capability, memory and behavior. AD is a major public health problem among the elderly in developed and developing countries. With the growth of AD around the world, there is a need to further expand our understanding of the roles different clinical measurements can have in the diagnosis of AD. In this work, we propose a machine learning-based technique to distinguish control subjects with no cognitive impairments, AD subjects, and subjects with mild cognitive impairment (MCI), often seen as precursors of AD. We utilized several machine learning (ML) techniques and found that Gradient Boosting Decision Trees achieved the highest performance above 84% classification accuracy. Also, we determined the importance of the features (clinical biomarkers) contributing to the proposed multi-class classification system. Further investigation on the biomarkers will pave the way to introduce better treatment plan for AD patients.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3233/SHTI200599DOI Listing
June 2020

Health Informatics Association of Qatar (HIAQ): Building a Digital Health Ecosystem.

Stud Health Technol Inform 2020 Jun;272:474-477

College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

Qatar's digital health initiatives are growing through the development of research capacity, innovative technologies, and academic programs to serve the national health needs of the country. The digital health community of Qatar lacks the adequate representation of a professional body to serve the needs of the community. The purpose of this paper is to develop a strategic framework for the Health Informatics Association of Qatar (HIAQ) and present the preliminary findings of this effort. We utilized a multi-stage mixed methods approach in the development of HIAQ's strategic framework. We first reviewed the relevant literature, interviewed key stakeholders within the region, validated our findings with local stakeholders, and adapted the strategic directions to conform with Qatari laws. We present the purpose, organizational structure, vision, mission, and aims of HIAQ. Future work will engage the digital health community to further refine and adapt HIAQ's strategic direction to serve the local needs of Qatar.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3233/SHTI200598DOI Listing
June 2020

The Impact of Clinical Decision Support Systems (CDSS) on Physicians: A Scoping Review.

Stud Health Technol Inform 2020 Jun;272:470-473

College of Science & Engineering, Hamad bin Khalifa University, Doha, Qatar.

Clinical Decision Support Systems (CDSSs) are used in a clinical setting to help physicians make decisions to improve clinical performance and patient care. There are many benefits to the implementation and adoption of CDSSs, such as reducing the rate of misdiagnosis, improving efficiency and patient care, and reducing the risk of medication errors. On the other hand, CDSSs can have several disadvantages. For example, physicians can see CDSSs as a threat to their clinical autonomy. CDSSs can also be very costly to adopt, maintain, and support. These advantages and disadvantages can have both positive and negative impacts on physicians. We conducted a scoping review to explore the impact of CDSSs on physicians. We searched the following electronic databases: CINAHL, PubMed, and Google Scholar. Two reviewers independently selected the retrieved studies and extracted data from the included studies. A narrative approach was used to synthesize the extracted data. We included 14 studies of the 300 retrieved studies. We identified the following positive impacts: work efficiency, providing more personalized care, improving care and knowledge, increasing confidence in making decisions, improving prescribing behavior, and reducing the number of ordered laboratory and medical imaging tests. Several negative impacts were also reported by the studies, namely: inefficient documentation, interruption in the patient-physician communication, and an increase in unnecessary referrals.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3233/SHTI200597DOI Listing
June 2020

Cardiovascular Diseases in Qatar: Smoking, Food Habits and Physical Activities Perspectives.

Stud Health Technol Inform 2020 Jun;272:465-469

College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

Cardiovascular diseases (CVDs) trigger a high number of deaths across the world. In this study, we investigate the food, drinking, smoking, and lifestyle-related habits for a Qatari CVD cohort to understand the implication of these factors on CVD. Statistical analysis shows that the CVD group is consuming a lower amount of fast foods, soft drinks, snacks, and meats compared to the control group. Alarmingly, the level of smoking is still higher in the CVD group, and the consumption level of healthy items (e.g., cereal, cornflakes) in breakfast is relatively lower compared to the control group. Interestingly, the CVD cohort is spending more time walking and avoiding heavy sports, compared to the control group, but their involvement in moderate physical activities is lower than the control group. Overall, we conclude that the Qatari CVD cohort is following most of the standard guidelines related to food items and heavy sports; however, the cohort should reduce smoking habits, and may modify the moderate level of physical activity based on physician guidelines.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3233/SHTI200596DOI Listing
June 2020

Semantic Reconciliation of Standard and Localized Medical Terminologies for Knowledge Interoperability.

Stud Health Technol Inform 2020 Jun;272:461-464

College of Science and Engineering, Hamad Bin Khalifa University, Qatar.

The heterogeneous localized concepts of various hospitals reduce interoperability among localized data models of Hospital Information Systems (HIS) and the knowledge bases of clinical decision support systems (CDSS). The leading solution to overcome the interoperability barrier is the reconciliation of standard medical terminologies with localized data models. In this paper, we extend the semantic reconciliation model (SRM) to provide mappings among diverse concepts of localized domain clinical models (DCM) and concepts of standard medical terminologies such as Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT). In the extended SRM, we insert the explicit semantics only into the word vector of the localized DCM concepts instead of the implicit semantics, which enhances the system's accuracy with a lower computational cost. The extended SRM performed well on the datasets of localized DCM and SNOMED CT with a precision of 0.95, a recall of 0.92, and an F-measure of 0.93.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3233/SHTI200595DOI Listing
June 2020

An Efficient Method to Predict Pneumonia from Chest X-Rays Using Deep Learning Approach.

Stud Health Technol Inform 2020 Jun;272:457-460

College of Science and Engineering, Hamad Bin Khalifa University, Qatar.

Pneumonia is a severe health problem causing millions of deaths every year. The aim of this study was to develop an advanced deep learning-based architecture to detect pneumonia using chest X-ray images. We utilized a convolutional neural network (CNN) based on VGG16 architecture consisting of 16 fully connected convolutional layers. A total of 5856 high-resolution frontal view chest X-ray images were used for training, validating, and testing the model. The model achieved an accuracy of 96.6%, sensitivity of 98.1%, specificity of 92.4%, precision of 97.2%, and a F1 Score of 97.6%. This indicates that the model has an excellent performance in classifying pneumonia cases and normal cases. We believe, the proposed model will reduce physician workload, expand the performance of pneumonia screening programs, and improve healthcare service.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3233/SHTI200594DOI Listing
June 2020

Understanding the Food Habits and Physical Activities of Diabetes Cohort in Qatar.

Stud Health Technol Inform 2020 Jun;272:453-456

College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Doha, Qatar.

In this study, we analyze the food and lifestyle-related factors for a Diabetic cohort from Qatar, where the prevalence of diabetes is among the top in the Middle East region. Statistical analysis shows that the diabetic group is consuming a lower amount of fast foods, soft drinks and meats as a meal but a higher amount of vegetables and fruits compared to the control group. Though the diabetic cohort consumes a lower number of snacks and desserts, they consume a higher amount of sugar for tea. Interestingly, we find the diabetes cohort is spending a lower amount of time in sedentary life but their involvement in different physical activities is lower than the control group. Overall, we conclude that the Qatari diabetic cohort, considered in this study, is following standard guidelines for food and drinks but they may need to improve the physical activity level following physician guidelines.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3233/SHTI200593DOI Listing
June 2020

Technical Metrics Used to Evaluate Health Care Chatbots: Scoping Review.

J Med Internet Res 2020 06 5;22(6):e18301. Epub 2020 Jun 5.

Institute for Medical Informatics, Bern University of Applied Sciences, Bern, Switzerland.

Background: Dialog agents (chatbots) have a long history of application in health care, where they have been used for tasks such as supporting patient self-management and providing counseling. Their use is expected to grow with increasing demands on health systems and improving artificial intelligence (AI) capability. Approaches to the evaluation of health care chatbots, however, appear to be diverse and haphazard, resulting in a potential barrier to the advancement of the field.

Objective: This study aims to identify the technical (nonclinical) metrics used by previous studies to evaluate health care chatbots.

Methods: Studies were identified by searching 7 bibliographic databases (eg, MEDLINE and PsycINFO) in addition to conducting backward and forward reference list checking of the included studies and relevant reviews. The studies were independently selected by two reviewers who then extracted data from the included studies. Extracted data were synthesized narratively by grouping the identified metrics into categories based on the aspect of chatbots that the metrics evaluated.

Results: Of the 1498 citations retrieved, 65 studies were included in this review. Chatbots were evaluated using 27 technical metrics, which were related to chatbots as a whole (eg, usability, classifier performance, speed), response generation (eg, comprehensibility, realism, repetitiveness), response understanding (eg, chatbot understanding as assessed by users, word error rate, concept error rate), and esthetics (eg, appearance of the virtual agent, background color, and content).

Conclusions: The technical metrics of health chatbot studies were diverse, with survey designs and global usability metrics dominating. The lack of standardization and paucity of objective measures make it difficult to compare the performance of health chatbots and could inhibit advancement of the field. We suggest that researchers more frequently include metrics computed from conversation logs. In addition, we recommend the development of a framework of technical metrics with recommendations for specific circumstances for their inclusion in chatbot studies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/18301DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305563PMC
June 2020

Ethical Considerations for Participatory Health through Social Media: Healthcare Workforce and Policy Maker Perspectives.

Yearb Med Inform 2020 Aug 17;29(1):71-76. Epub 2020 Apr 17.

Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute, Universitat Pompeu Fabra, Barcelona, Spain.

Objectives: To identify the different ethical issues that should be considered in participatory health through social media from different stakeholder perspectives (i.e., patients/service users, health professionals, health information technology (If) professionals, and policy makers) in any healthcare context.

Methods: We implemented a two-round survey composed of open ended questions in the first round, aggregated into a list of ethical issues rated for importance by participants in the second round, to generate a ranked list of possible ethical issues in participatory health based on healthcare professionals' and policy makers' opinions on both their own point of view and their beliefs for other stakeholders' perspectives.

Results: Twenty-six individuals responded in the first round of the survey. Multiple ethical issues were identified for each perspective. Data privacy, data security, and digital literacy were common themes in all perspectives. Thirty-three individuals completed the second round of the survey. Data privacy and data security were ranked among the three most important ethical issues in all perspectives. Quality assurance was the most important issue from the healthcare professionals' perspective and the second most important issue from the patients' perspective. Data privacy was the most important consideration for patients/service users. Digital literacy was ranked as the fourth most important issue, except for policy makers' perspective.

Conclusions: Different stakeholders' opinions fairly agreed that there are common ethical issues that should be considered across the four groups (patients, healthcare professionals, health IT professionals, policy makers) such as data privacy, security, and quality assurance.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1055/s-0040-1701981DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442531PMC
August 2020

Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study.

J Med Internet Res 2020 04 21;22(4):e19016. Epub 2020 Apr 21.

College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

Background: The recent coronavirus disease (COVID-19) pandemic is taking a toll on the world's health care infrastructure as well as the social, economic, and psychological well-being of humanity. Individuals, organizations, and governments are using social media to communicate with each other on a number of issues relating to the COVID-19 pandemic. Not much is known about the topics being shared on social media platforms relating to COVID-19. Analyzing such information can help policy makers and health care organizations assess the needs of their stakeholders and address them appropriately.

Objective: This study aims to identify the main topics posted by Twitter users related to the COVID-19 pandemic.

Methods: Leveraging a set of tools (Twitter's search application programming interface (API), Tweepy Python library, and PostgreSQL database) and using a set of predefined search terms ("corona," "2019-nCov," and "COVID-19"), we extracted the text and metadata (number of likes and retweets, and user profile information including the number of followers) of public English language tweets from February 2, 2020, to March 15, 2020. We analyzed the collected tweets using word frequencies of single (unigrams) and double words (bigrams). We leveraged latent Dirichlet allocation for topic modeling to identify topics discussed in the tweets. We also performed sentiment analysis and extracted the mean number of retweets, likes, and followers for each topic and calculated the interaction rate per topic.

Results: Out of approximately 2.8 million tweets included, 167,073 unique tweets from 160,829 unique users met the inclusion criteria. Our analysis identified 12 topics, which were grouped into four main themes: origin of the virus; its sources; its impact on people, countries, and the economy; and ways of mitigating the risk of infection. The mean sentiment was positive for 10 topics and negative for 2 topics (deaths caused by COVID-19 and increased racism). The mean for tweet topics of account followers ranged from 2722 (increased racism) to 13,413 (economic losses). The highest mean of likes for the tweets was 15.4 (economic loss), while the lowest was 3.94 (travel bans and warnings).

Conclusions: Public health crisis response activities on the ground and online are becoming increasingly simultaneous and intertwined. Social media provides an opportunity to directly communicate health information to the public. Health systems should work on building national and international disease detection and surveillance systems through monitoring social media. There is also a need for a more proactive and agile public health presence on social media to combat the spread of fake news.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/19016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7175788PMC
April 2020

Use of mobile applications to improve nutrition behaviour: A systematic review.

Comput Methods Programs Biomed 2020 Aug 19;192:105459. Epub 2020 Mar 19.

International Center for Health Information Technology (ICHIT), Taipei Medical University, Taipei, Taiwan; Department of Public Health and Community Medicine, Shaikh Zayed Medical Complex, Lahore, Pakistan; Master's Program in Global Health & Development Dept., PhD Program in Global Health & Health Security Dept., College of Public Health, Taipei Medical University, Taipei, Taiwan. Electronic address:

Background And Objective: Mobile applications could be effectively used for dietary intake assessment, physical activity monitoring, behavior improvement, and nutrition education. The aim of this review is to determine the effectiveness of mobile applications in improving nutrition behaviors through a systematic review of literature.

Methods: The review protocol was registered with PROSPERO: registration number CRD42018118809, and followed PRISMA guidelines. We involved original articles including mobile electronic devices for improving dietary intake, physical activity, and weight management in adult populations in this review. Data were retrieved from January 2010 to December 2018 with PubMed, Web of Science, Excerpta Medica Database (Embase), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) as data sources. Authors individually screened the titles and abstracts, then full articles in order to obtain papers that met inclusion criteria.

Results: The database search yielded 2962 records. After removing the duplicates and analyzing the full text papers a total of 8 original articles were reviewed. Two articles showed obvious bias and were not included in our results or discussion. The remaining six articles with low to moderate bias risk were included in this systematic review. Three selected studies were randomized control trials (RCTs) with over 180 participants each. The other three studies were a nested trial, a case-control trial, and a pilot RCT with 36, 162, and 24 participants respectively. All larger RCTs and the small case control trail showed significant improvements in some nutritional-health objectives measured. The other two trials showed insignificant improvements in outcomes measured between groups.

Conclusion: This study highlights the potential significant health benefits acquirable through mobile health application-assisted nutrition interventions. Some of these studies required significant financial and time input from providers for the application's utilization. Further studies, perhaps with multiple intervention arms, are required to compare across programs the elements that are essential for health benefits observed.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2020.105459DOI Listing
August 2020

The burden of unintentional drowning: global, regional and national estimates of mortality from the Global Burden of Disease 2017 Study.

Authors:
Richard Charles Franklin Amy E Peden Erin B Hamilton Catherine Bisignano Chris D Castle Zachary V Dingels Simon I Hay Zichen Liu Ali H Mokdad Nicholas L S Roberts Dillon O Sylte Theo Vos Gdiom Gebreheat Abady Akine Eshete Abosetugn Rushdia Ahmed Fares Alahdab Catalina Liliana Andrei Carl Abelardo T Antonio Jalal Arabloo Aseb Arba Kinfe Arba Ashish D Badiye Shankar M Bakkannavar Maciej Banach Palash Chandra Banik Amrit Banstola Suzanne Lyn Barker-Collo Akbar Barzegar Mohsen Bayati Pankaj Bhardwaj Soumyadeep Bhaumik Zulfiqar A Bhutta Ali Bijani Archith Boloor Félix Carvalho Mohiuddin Ahsanul Kabir Chowdhury Dinh-Toi Chu Samantha M Colquhoun Henok Dagne Baye Dagnew Lalit Dandona Rakhi Dandona Ahmad Daryani Samath Dhamminda Dharmaratne Zahra Sadat Dibaji Forooshani Hoa Thi Do Tim Robert Driscoll Arielle Wilder Eagan Ziad El-Khatib Eduarda Fernandes Irina Filip Florian Fischer Berhe Gebremichael Gaurav Gupta Juanita A Haagsma Shoaib Hassan Delia Hendrie Chi Linh Hoang Michael K Hole Ramesh Holla Sorin Hostiuc Mowafa Househ Olayinka Stephen Ilesanmi Leeberk Raja Inbaraj Seyed Sina Naghibi Irvani M Mofizul Islam Rebecca Q Ivers Achala Upendra Jayatilleke Farahnaz Joukar Rohollah Kalhor Tanuj Kanchan Neeti Kapoor Amir Kasaeian Maseer Khan Ejaz Ahmad Khan Jagdish Khubchandani Kewal Krishan G Anil Kumar Paolo Lauriola Alan D Lopez Mohammed Madadin Marek Majdan Venkatesh Maled Navid Manafi Ali Manafi Martin McKee Hagazi Gebre Meles Ritesh G Menezes Tuomo J Meretoja Ted R Miller Prasanna Mithra Abdollah Mohammadian-Hafshejani Reza Mohammadpourhodki Farnam Mohebi Mariam Molokhia Ghulam Mustafa Ionut Negoi Cuong Tat Nguyen Huong Lan Thi Nguyen Andrew T Olagunju Tinuke O Olagunju Jagadish Rao Padubidri Keyvan Pakshir Ashish Pathak Suzanne Polinder Dimas Ria Angga Pribadi Navid Rabiee Amir Radfar Saleem Muhammad Rana Jennifer Rickard Saeed Safari Payman Salamati Abdallah M Samy Abdur Razzaque Sarker David C Schwebel Subramanian Senthilkumaran Faramarz Shaahmadi Masood Ali Shaikh Jae Il Shin Pankaj Kumar Singh Amin Soheili Mark A Stokes Hafiz Ansar Rasul Suleria Ingan Ukur Tarigan Mohamad-Hani Temsah Berhe Etsay Tesfay Pascual R Valdez Yousef Veisani Pengpeng Ye Naohiro Yonemoto Chuanhua Yu Hasan Yusefzadeh Sojib Bin Zaman Zhi-Jiang Zhang Spencer L James

Inj Prev 2020 Oct 20;26(Supp 1):i83-i95. Epub 2020 Feb 20.

Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA

Background: Drowning is a leading cause of injury-related mortality globally. Unintentional drowning (International Classification of Diseases (ICD) 10 codes W65-74 and ICD9 E910) is one of the 30 mutually exclusive and collectively exhaustive causes of injury-related mortality in the Global Burden of Disease (GBD) study. This study's objective is to describe unintentional drowning using GBD estimates from 1990 to 2017.

Methods: Unintentional drowning from GBD 2017 was estimated for cause-specific mortality and years of life lost (YLLs), age, sex, country, region, Socio-demographic Index (SDI) quintile, and trends from 1990 to 2017. GBD 2017 used standard GBD methods for estimating mortality from drowning.

Results: Globally, unintentional drowning mortality decreased by 44.5% between 1990 and 2017, from 531 956 (uncertainty interval (UI): 484 107 to 572 854) to 295 210 (284 493 to 306 187) deaths. Global age-standardised mortality rates decreased 57.4%, from 9.3 (8.5 to 10.0) in 1990 to 4.0 (3.8 to 4.1) per 100 000 per annum in 2017. Unintentional drowning-associated mortality was generally higher in children, males and in low-SDI to middle-SDI countries. China, India, Pakistan and Bangladesh accounted for 51.2% of all drowning deaths in 2017. Oceania was the region with the highest rate of age-standardised YLLs in 2017, with 45 434 (40 850 to 50 539) YLLs per 100 000 across both sexes.

Conclusions: There has been a decline in global drowning rates. This study shows that the decline was not consistent across countries. The results reinforce the need for continued and improved policy, prevention and research efforts, with a focus on low- and middle-income countries.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1136/injuryprev-2019-043484DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571364PMC
October 2020

Epidemiology of injuries from fire, heat and hot substances: global, regional and national morbidity and mortality estimates from the Global Burden of Disease 2017 study.

Authors:
Spencer L James Lydia R Lucchesi Catherine Bisignano Chris D Castle Zachary V Dingels Jack T Fox Erin B Hamilton Nathaniel J Henry Darrah McCracken Nicholas L S Roberts Dillon O Sylte Alireza Ahmadi Muktar Beshir Ahmed Fares Alahdab Vahid Alipour Zewudu Andualem Carl Abelardo T Antonio Jalal Arabloo Ashish D Badiye Mojtaba Bagherzadeh Amrit Banstola Till Winfried Bärnighausen Akbar Barzegar Mohsen Bayati Soumyadeep Bhaumik Ali Bijani Gene Bukhman Félix Carvalho Christopher Stephen Crowe Koustuv Dalal Ahmad Daryani Mostafa Dianati Nasab Hoa Thi Do Huyen Phuc Do Aman Yesuf Endries Eduarda Fernandes Irina Filip Florian Fischer Takeshi Fukumoto Ketema Bizuwork Bizuwork Gebremedhin Gebreamlak Gebremedhn Gebremeskel Syed Amir Gilani Juanita A Haagsma Samer Hamidi Sorin Hostiuc Mowafa Househ Ehimario U Igumbor Olayinka Stephen Ilesanmi Seyed Sina Naghibi Irvani Achala Upendra Jayatilleke Amaha Kahsay Neeti Kapoor Amir Kasaeian Yousef Saleh Khader Ibrahim A Khalil Ejaz Ahmad Khan Maryam Khazaee-Pool Yoshihiro Kokubo Alan D Lopez Mohammed Madadin Marek Majdan Venkatesh Maled Reza Malekzadeh Navid Manafi Ali Manafi Srikanth Mangalam Benjamin Ballard Massenburg Hagazi Gebre Meles Ritesh G Menezes Tuomo J Meretoja Bartosz Miazgowski Ted R Miller Abdollah Mohammadian-Hafshejani Reza Mohammadpourhodki Shane Douglas Morrison Ionut Negoi Trang Huyen Nguyen Son Hoang Nguyen Cuong Tat Nguyen Molly R Nixon Andrew T Olagunju Tinuke O Olagunju Jagadish Rao Padubidri Suzanne Polinder Navid Rabiee Mohammad Rabiee Amir Radfar Vafa Rahimi-Movaghar Salman Rawaf David Laith Rawaf Aziz Rezapour Jennifer Rickard Elias Merdassa Roro Nobhojit Roy Roya Safari-Faramani Payman Salamati Abdallah M Samy Maheswar Satpathy Monika Sawhney David C Schwebel Subramanian Senthilkumaran Sadaf G Sepanlou Mika Shigematsu Amin Soheili Mark A Stokes Hamid Reza Tohidinik Bach Xuan Tran Pascual R Valdez Tissa Wijeratne Engida Yisma Zoubida Zaidi Mohammad Zamani Zhi-Jiang Zhang Simon I Hay Ali H Mokdad

Inj Prev 2020 Oct 18;26(Supp 1):i36-i45. Epub 2019 Dec 18.

Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA.

Background: Past research has shown how fires, heat and hot substances are important causes of health loss globally. Detailed estimates of the morbidity and mortality from these injuries could help drive preventative measures and improved access to care.

Methods: We used the Global Burden of Disease 2017 framework to produce three main results. First, we produced results on incidence, prevalence, years lived with disability, deaths, years of life lost and disability-adjusted life years from 1990 to 2017 for 195 countries and territories. Second, we analysed these results to measure mortality-to-incidence ratios by location. Third, we reported the measures above in terms of the cause of fire, heat and hot substances and the types of bodily injuries that result.

Results: Globally, there were 8 991 468 (7 481 218 to 10 740 897) new fire, heat and hot substance injuries in 2017 with 120 632 (101 630 to 129 383) deaths. At the global level, the age-standardised mortality caused by fire, heat and hot substances significantly declined from 1990 to 2017, but regionally there was variability in age-standardised incidence with some regions experiencing an increase (eg, Southern Latin America) and others experiencing a significant decrease (eg, High-income North America).

Conclusions: The incidence and mortality of injuries that result from fire, heat and hot substances affect every region of the world but are most concentrated in middle and lower income areas. More resources should be invested in measuring these injuries as well as in improving infrastructure, advancing safety measures and ensuring access to care.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1136/injuryprev-2019-043299DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571358PMC
October 2020

The epidemiology of domestic violence in Saudi Arabia: a systematic review.

Int J Public Health 2019 Nov 18;64(8):1223-1232. Epub 2019 Oct 18.

College of Public Health and Health Informatics, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guards - Health Affairs, Riyadh, Saudi Arabia.

Objectives: The aim of this study is to review the prevalence, risk factors, and outcomes of domestic violence (DV) in Saudi Arabia.

Methods: Systematic review utilizing PRISMA guidelines conducted on articles focusing on research related to the epidemiology of domestic violence in Saudi Arabia between 2009 and 2017 were identified through electronic databases (PubMed and Embase) and supplemented by cross-referencing and local journal searches.

Results: Eleven studies were conducted in six cities (Riyadh, Jeddah, Madina, Taif, Arar, and Al-Ahsa). Several screening questionnaires were utilized; four studies used the WHO multi-country study questionnaire and found that the lifetime prevalence of DV ranged between 39.3 and 44.5%. The most frequently reported risk factors for DV were the level of education of both the victim and the spouse and alcohol or drug addiction of the spouse.

Conclusions: One in every three women in Saudi Arabia is a victim of domestic violence. Strategies to reduce risk factors, prevent DV, care for victims, and mitigate the effects of DV must be adopted by health care agencies in Saudi Arabia.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00038-019-01303-3DOI Listing
November 2019

An overview of the features of chatbots in mental health: A scoping review.

Int J Med Inform 2019 12 25;132:103978. Epub 2019 Sep 25.

College of Science and Engineering, Hamad Bin Khalifa University, Qatar. Electronic address:

Background: Chatbots are systems that are able to converse and interact with human users using spoken, written, and visual languages. Chatbots have the potential to be useful tools for individuals with mental disorders, especially those who are reluctant to seek mental health advice due to stigmatization. While numerous studies have been conducted about using chatbots for mental health, there is a need to systematically bring this evidence together in order to inform mental health providers and potential users about the main features of chatbots and their potential uses, and to inform future research about the main gaps of the previous literature.

Objective: We aimed to provide an overview of the features of chatbots used by individuals for their mental health as reported in the empirical literature.

Methods: Seven bibliographic databases (Medline, Embase, PsycINFO, Cochrane Central Register of Controlled Trials, IEEE Xplore, ACM Digital Library, and Google Scholar) were used in our search. In addition, backward and forward reference list checking of the included studies and relevant reviews was conducted. Study selection and data extraction were carried out by two reviewers independently. Extracted data were synthesised using a narrative approach. Chatbots were classified according to their purposes, platforms, response generation, dialogue initiative, input and output modalities, embodiment, and targeted disorders.

Results: Of 1039 citations retrieved, 53 unique studies were included in this review. The included studies assessed 41 different chatbots. Common uses of chatbots were: therapy (n = 17), training (n = 12), and screening (n = 10). Chatbots in most studies were rule-based (n = 49) and implemented in stand-alone software (n = 37). In 46 studies, chatbots controlled and led the conversations. While the most frequently used input modality was written language only (n = 26), the most frequently used output modality was a combination of written, spoken and visual languages (n = 28). In the majority of studies, chatbots included virtual representations (n = 44). The most common focus of chatbots was depression (n = 16) or autism (n = 10).

Conclusion: Research regarding chatbots in mental health is nascent. There are numerous chatbots that are used for various mental disorders and purposes. Healthcare providers should compare chatbots found in this review to help guide potential users to the most appropriate chatbot to support their mental health needs. More reviews are needed to summarise the evidence regarding the effectiveness and acceptability of chatbots in mental health.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ijmedinf.2019.103978DOI Listing
December 2019

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017.

Authors:
Roy Burstein Nathaniel J Henry Michael L Collison Laurie B Marczak Amber Sligar Stefanie Watson Neal Marquez Mahdieh Abbasalizad-Farhangi Masoumeh Abbasi Foad Abd-Allah Amir Abdoli Mohammad Abdollahi Ibrahim Abdollahpour Rizwan Suliankatchi Abdulkader Michael R M Abrigo Dilaram Acharya Oladimeji M Adebayo Victor Adekanmbi Davoud Adham Mahdi Afshari Mohammad Aghaali Keivan Ahmadi Mehdi Ahmadi Ehsan Ahmadpour Rushdia Ahmed Chalachew Genet Akal Joshua O Akinyemi Fares Alahdab Noore Alam Genet Melak Alamene Kefyalew Addis Alene Mehran Alijanzadeh Cyrus Alinia Vahid Alipour Syed Mohamed Aljunid Mohammed J Almalki Hesham M Al-Mekhlafi Khalid Altirkawi Nelson Alvis-Guzman Adeladza Kofi Amegah Saeed Amini Arianna Maever Loreche Amit Zohreh Anbari Sofia Androudi Mina Anjomshoa Fereshteh Ansari Carl Abelardo T Antonio Jalal Arabloo Zohreh Arefi Olatunde Aremu Bahram Armoon Amit Arora Al Artaman Anvar Asadi Mehran Asadi-Aliabadi Amir Ashraf-Ganjouei Reza Assadi Bahar Ataeinia Sachin R Atre Beatriz Paulina Ayala Quintanilla Martin Amogre Ayanore Samad Azari Ebrahim Babaee Arefeh Babazadeh Alaa Badawi Soghra Bagheri Mojtaba Bagherzadeh Nafiseh Baheiraei Abbas Balouchi Aleksandra Barac Quique Bassat Bernhard T Baune Mohsen Bayati Neeraj Bedi Ettore Beghi Masoud Behzadifar Meysam Behzadifar Yared Belete Belay Brent Bell Michelle L Bell Dessalegn Ajema Berbada Robert S Bernstein Natalia V Bhattacharjee Suraj Bhattarai Zulfiqar A Bhutta Ali Bijani Somayeh Bohlouli Nicholas J K Breitborde Gabrielle Britton Annie J Browne Sharath Burugina Nagaraja Reinhard Busse Zahid A Butt Josip Car Rosario Cárdenas Carlos A Castañeda-Orjuela Ester Cerin Wagaye Fentahun Chanie Pranab Chatterjee Dinh-Toi Chu Cyrus Cooper Vera M Costa Koustuv Dalal Lalit Dandona Rakhi Dandona Farah Daoud Ahmad Daryani Rajat Das Gupta Ian Davis Nicole Davis Weaver Dragos Virgil Davitoiu Jan-Walter De Neve Feleke Mekonnen Demeke Gebre Teklemariam Demoz Kebede Deribe Rupak Desai Aniruddha Deshpande Hanna Demelash Desyibelew Sagnik Dey Samath Dhamminda Dharmaratne Meghnath Dhimal Daniel Diaz Leila Doshmangir Andre R Duraes Laura Dwyer-Lindgren Lucas Earl Roya Ebrahimi Soheil Ebrahimpour Andem Effiong Aziz Eftekhari Elham Ehsani-Chimeh Iman El Sayed Maysaa El Sayed Zaki Maha El Tantawi Ziad El-Khatib Mohammad Hassan Emamian Shymaa Enany Sharareh Eskandarieh Oghenowede Eyawo Maha Ezalarab Mahbobeh Faramarzi Mohammad Fareed Roghiyeh Faridnia Andre Faro Ali Akbar Fazaeli Mehdi Fazlzadeh Netsanet Fentahun Seyed-Mohammad Fereshtehnejad João C Fernandes Irina Filip Florian Fischer Nataliya A Foigt Masoud Foroutan Joel Msafiri Francis Takeshi Fukumoto Nancy Fullman Silvano Gallus Destallem Gebremedhin Gebre Tsegaye Tewelde Gebrehiwot Gebreamlak Gebremedhn Gebremeskel Bradford D Gessner Birhanu Geta Peter W Gething Reza Ghadimi Keyghobad Ghadiri Mahsa Ghajarzadeh Ahmad Ghashghaee Paramjit Singh Gill Tiffany K Gill Nick Golding Nelson G M Gomes Philimon N Gona Sameer Vali Gopalani Giuseppe Gorini Bárbara Niegia Garcia Goulart Nicholas Graetz Felix Greaves Manfred S Green Yuming Guo Arvin Haj-Mirzaian Arya Haj-Mirzaian Brian James Hall Samer Hamidi Hamidreza Haririan Josep Maria Haro Milad Hasankhani Edris Hasanpoor Amir Hasanzadeh Hadi Hassankhani Hamid Yimam Hassen Mohamed I Hegazy Delia Hendrie Fatemeh Heydarpour Thomas R Hird Chi Linh Hoang Gillian Hollerich Enayatollah Homaie Rad Mojtaba Hoseini-Ghahfarokhi Naznin Hossain Mostafa Hosseini Mehdi Hosseinzadeh Mihaela Hostiuc Sorin Hostiuc Mowafa Househ Mohamed Hsairi Olayinka Stephen Ilesanmi Mohammad Hasan Imani-Nasab Usman Iqbal Seyed Sina Naghibi Irvani Nazrul Islam Sheikh Mohammed Shariful Islam Mikk Jürisson Nader Jafari Balalami Amir Jalali Javad Javidnia Achala Upendra Jayatilleke Ensiyeh Jenabi John S Ji Yash B Jobanputra Kimberly Johnson Jost B Jonas Zahra Jorjoran Shushtari Jacek Jerzy Jozwiak Ali Kabir Amaha Kahsay Hamed Kalani Rohollah Kalhor Manoochehr Karami Surendra Karki Amir Kasaeian Nicholas J Kassebaum Peter Njenga Keiyoro Grant Rodgers Kemp Roghayeh Khabiri Yousef Saleh Khader Morteza Abdullatif Khafaie Ejaz Ahmad Khan Junaid Khan Muhammad Shahzeb Khan Young-Ho Khang Khaled Khatab Amir Khater Mona M Khater Alireza Khatony Mohammad Khazaei Salman Khazaei Maryam Khazaei-Pool Jagdish Khubchandani Neda Kianipour Yun Jin Kim Ruth W Kimokoti Damaris K Kinyoki Adnan Kisa Sezer Kisa Tufa Kolola Soewarta Kosen Parvaiz A Koul Ai Koyanagi Moritz U G Kraemer Kewal Krishan Kris J Krohn Nuworza Kugbey G Anil Kumar Manasi Kumar Pushpendra Kumar Desmond Kuupiel Ben Lacey Sheetal D Lad Faris Hasan Lami Anders O Larsson Paul H Lee Mostafa Leili Aubrey J Levine Shanshan Li Lee-Ling Lim Stefan Listl Joshua Longbottom Jaifred Christian F Lopez Stefan Lorkowski Sameh Magdeldin Hassan Magdy Abd El Razek Muhammed Magdy Abd El Razek Azeem Majeed Afshin Maleki Reza Malekzadeh Deborah Carvalho Malta Abdullah A Mamun Navid Manafi Ana-Laura Manda Morteza Mansourian Francisco Rogerlândio Martins-Melo Anthony Masaka Benjamin Ballard Massenburg Pallab K Maulik Benjamin K Mayala Mohsen Mazidi Martin McKee Ravi Mehrotra Kala M Mehta Gebrekiros Gebremichael Meles Walter Mendoza Ritesh G Menezes Atte Meretoja Tuomo J Meretoja Tomislav Mestrovic Ted R Miller Molly K Miller-Petrie Edward J Mills George J Milne G K Mini Seyed Mostafa Mir Hamed Mirjalali Erkin M Mirrakhimov Efat Mohamadi Dara K Mohammad Aso Mohammad Darwesh Naser Mohammad Gholi Mezerji Ammas Siraj Mohammed Shafiu Mohammed Ali H Mokdad Mariam Molokhia Lorenzo Monasta Yoshan Moodley Mahmood Moosazadeh Ghobad Moradi Masoud Moradi Yousef Moradi Maziar Moradi-Lakeh Mehdi Moradinazar Paula Moraga Lidia Morawska Abbas Mosapour Seyyed Meysam Mousavi Ulrich Otto Mueller Atalay Goshu Muluneh Ghulam Mustafa Behnam Nabavizadeh Mehdi Naderi Ahamarshan Jayaraman Nagarajan Azin Nahvijou Farid Najafi Vinay Nangia Duduzile Edith Ndwandwe Nahid Neamati Ionut Negoi Ruxandra Irina Negoi Josephine W Ngunjiri Huong Lan Thi Nguyen Long Hoang Nguyen Son Hoang Nguyen Katie R Nielsen Dina Nur Anggraini Ningrum Yirga Legesse Nirayo Molly R Nixon Chukwudi A Nnaji Marzieh Nojomi Mehdi Noroozi Shirin Nosratnejad Jean Jacques Noubiap Soraya Nouraei Motlagh Richard Ofori-Asenso Felix Akpojene Ogbo Kelechi E Oladimeji Andrew T Olagunju Meysam Olfatifar Solomon Olum Bolajoko Olubukunola Olusanya Mojisola Morenike Oluwasanu Obinna E Onwujekwe Eyal Oren Doris D V Ortega-Altamirano Alberto Ortiz Osayomwanbo Osarenotor Frank B Osei Aaron E Osgood-Zimmerman Stanislav S Otstavnov Mayowa Ojo Owolabi Mahesh P A Abdol Sattar Pagheh Smita Pakhale Songhomitra Panda-Jonas Animika Pandey Eun-Kee Park Hadi Parsian Tahereh Pashaei Sangram Kishor Patel Veincent Christian Filipino Pepito Alexandre Pereira Samantha Perkins Brandon V Pickering Thomas Pilgrim Majid Pirestani Bakhtiar Piroozi Meghdad Pirsaheb Oleguer Plana-Ripoll Hadi Pourjafar Parul Puri Mostafa Qorbani Hedley Quintana Mohammad Rabiee Navid Rabiee Amir Radfar Alireza Rafiei Fakher Rahim Zohreh Rahimi Vafa Rahimi-Movaghar Shadi Rahimzadeh Fatemeh Rajati Sree Bhushan Raju Azra Ramezankhani Chhabi Lal Ranabhat Davide Rasella Vahid Rashedi Lal Rawal Robert C Reiner Andre M N Renzaho Satar Rezaei Aziz Rezapour Seyed Mohammad Riahi Ana Isabel Ribeiro Leonardo Roever Elias Merdassa Roro Max Roser Gholamreza Roshandel Daem Roshani Ali Rostami Enrico Rubagotti Salvatore Rubino Siamak Sabour Nafis Sadat Ehsan Sadeghi Reza Saeedi Yahya Safari Roya Safari-Faramani Mahdi Safdarian Amirhossein Sahebkar Mohammad Reza Salahshoor Nasir Salam Payman Salamati Farkhonde Salehi Saleh Salehi Zahabi Yahya Salimi Hamideh Salimzadeh Joshua A Salomon Evanson Zondani Sambala Abdallah M Samy Milena M Santric Milicevic Bruno Piassi Sao Jose Sivan Yegnanarayana Iyer Saraswathy Rodrigo Sarmiento-Suárez Benn Sartorius Brijesh Sathian Sonia Saxena Alyssa N Sbarra Lauren E Schaeffer David C Schwebel Sadaf G Sepanlou Seyedmojtaba Seyedmousavi Faramarz Shaahmadi Masood Ali Shaikh Mehran Shams-Beyranvand Amir Shamshirian Morteza Shamsizadeh Kiomars Sharafi Mehdi Sharif Mahdi Sharif-Alhoseini Hamid Sharifi Jayendra Sharma Rajesh Sharma Aziz Sheikh Chloe Shields Mika Shigematsu Rahman Shiri Ivy Shiue Kerem Shuval Tariq J Siddiqi João Pedro Silva Jasvinder A Singh Dhirendra Narain Sinha Malede Mequanent Sisay Solomon Sisay Karen Sliwa David L Smith Ranjani Somayaji Moslem Soofi Joan B Soriano Chandrashekhar T Sreeramareddy Agus Sudaryanto Mu'awiyyah Babale Sufiyan Bryan L Sykes P N Sylaja Rafael Tabarés-Seisdedos Karen M Tabb Takahiro Tabuchi Nuno Taveira Mohamad-Hani Temsah Abdullah Sulieman Terkawi Zemenu Tadesse Tessema Kavumpurathu Raman Thankappan Sathish Thirunavukkarasu Quyen G To Marcos Roberto Tovani-Palone Bach Xuan Tran Khanh Bao Tran Irfan Ullah Muhammad Shariq Usman Olalekan A Uthman Amir Vahedian-Azimi Pascual R Valdez Job F M van Boven Tommi Juhani Vasankari Yasser Vasseghian Yousef Veisani Narayanaswamy Venketasubramanian Francesco S Violante Sergey Konstantinovitch Vladimirov Vasily Vlassov Theo Vos Giang Thu Vu Isidora S Vujcic Yasir Waheed Jon Wakefield Haidong Wang Yafeng Wang Yuan-Pang Wang Joseph L Ward Robert G Weintraub Kidu Gidey Weldegwergs Girmay Teklay Weldesamuel Ronny Westerman Charles Shey Wiysonge Dawit Zewdu Wondafrash Lauren Woyczynski Ai-Min Wu Gelin Xu Abbas Yadegar Tomohide Yamada Vahid Yazdi-Feyzabadi Christopher Sabo Yilgwan Paul Yip Naohiro Yonemoto Javad Yoosefi Lebni Mustafa Z Younis Mahmoud Yousefifard Hebat-Allah Salah A Yousof Chuanhua Yu Hasan Yusefzadeh Erfan Zabeh Telma Zahirian Moghadam Sojib Bin Zaman Mohammad Zamani Hamed Zandian Alireza Zangeneh Taddese Alemu Zerfu Yunquan Zhang Arash Ziapour Sanjay Zodpey Christopher J L Murray Simon I Hay

Nature 2019 10 16;574(7778):353-358. Epub 2019 Oct 16.

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000-2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41586-019-1545-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6800389PMC
October 2019

Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2017: A Systematic Analysis for the Global Burden of Disease Study.

Authors:
Christina Fitzmaurice Degu Abate Naghmeh Abbasi Hedayat Abbastabar Foad Abd-Allah Omar Abdel-Rahman Ahmed Abdelalim Amir Abdoli Ibrahim Abdollahpour Abdishakur S M Abdulle Nebiyu Dereje Abebe Haftom Niguse Abraha Laith Jamal Abu-Raddad Ahmed Abualhasan Isaac Akinkunmi Adedeji Shailesh M Advani Mohsen Afarideh Mahdi Afshari Mohammad Aghaali Dominic Agius Sutapa Agrawal Ayat Ahmadi Elham Ahmadian Ehsan Ahmadpour Muktar Beshir Ahmed Mohammad Esmaeil Akbari Tomi Akinyemiju Ziyad Al-Aly Assim M AlAbdulKader Fares Alahdab Tahiya Alam Genet Melak Alamene Birhan Tamene T Alemnew Kefyalew Addis Alene Cyrus Alinia Vahid Alipour Syed Mohamed Aljunid Fatemeh Allah Bakeshei Majid Abdulrahman Hamad Almadi Amir Almasi-Hashiani Ubai Alsharif Shirina Alsowaidi Nelson Alvis-Guzman Erfan Amini Saeed Amini Yaw Ampem Amoako Zohreh Anbari Nahla Hamed Anber Catalina Liliana Andrei Mina Anjomshoa Fereshteh Ansari Ansariadi Ansariadi Seth Christopher Yaw Appiah Morteza Arab-Zozani Jalal Arabloo Zohreh Arefi Olatunde Aremu Habtamu Abera Areri Al Artaman Hamid Asayesh Ephrem Tsegay Asfaw Alebachew Fasil Ashagre Reza Assadi Bahar Ataeinia Hagos Tasew Atalay Zerihun Ataro Suleman Atique Marcel Ausloos Leticia Avila-Burgos Euripide F G A Avokpaho Ashish Awasthi Nefsu Awoke Beatriz Paulina Ayala Quintanilla Martin Amogre Ayanore Henok Tadesse Ayele Ebrahim Babaee Umar Bacha Alaa Badawi Mojtaba Bagherzadeh Eleni Bagli Senthilkumar Balakrishnan Abbas Balouchi Till Winfried Bärnighausen Robert J Battista Masoud Behzadifar Meysam Behzadifar Bayu Begashaw Bekele Yared Belete Belay Yaschilal Muche Belayneh Kathleen Kim Sachiko Berfield Adugnaw Berhane Eduardo Bernabe Mircea Beuran Nickhill Bhakta Krittika Bhattacharyya Belete Biadgo Ali Bijani Muhammad Shahdaat Bin Sayeed Charles Birungi Catherine Bisignano Helen Bitew Tone Bjørge Archie Bleyer Kassawmar Angaw Bogale Hunduma Amensisa Bojia Antonio M Borzì Cristina Bosetti Ibrahim R Bou-Orm Hermann Brenner Jerry D Brewer Andrey Nikolaevich Briko Nikolay Ivanovich Briko Maria Teresa Bustamante-Teixeira Zahid A Butt Giulia Carreras Juan J Carrero Félix Carvalho Clara Castro Franz Castro Ferrán Catalá-López Ester Cerin Yazan Chaiah Wagaye Fentahun Chanie Vijay Kumar Chattu Pankaj Chaturvedi Neelima Singh Chauhan Mohammad Chehrazi Peggy Pei-Chia Chiang Tesfaye Yitna Chichiabellu Onyema Greg Chido-Amajuoyi Odgerel Chimed-Ochir Jee-Young J Choi Devasahayam J Christopher Dinh-Toi Chu Maria-Magdalena Constantin Vera M Costa Emanuele Crocetti Christopher Stephen Crowe Maria Paula Curado Saad M A Dahlawi Giovanni Damiani Amira Hamed Darwish Ahmad Daryani José das Neves Feleke Mekonnen Demeke Asmamaw Bizuneh Demis Birhanu Wondimeneh Demissie Gebre Teklemariam Demoz Edgar Denova-Gutiérrez Afshin Derakhshani Kalkidan Solomon Deribe Rupak Desai Beruk Berhanu Desalegn Melaku Desta Subhojit Dey Samath Dhamminda Dharmaratne Meghnath Dhimal Daniel Diaz Mesfin Tadese Tadese Dinberu Shirin Djalalinia David Teye Doku Thomas M Drake Manisha Dubey Eleonora Dubljanin Eyasu Ejeta Duken Hedyeh Ebrahimi Andem Effiong Aziz Eftekhari Iman El Sayed Maysaa El Sayed Zaki Shaimaa I El-Jaafary Ziad El-Khatib Demelash Abewa Elemineh Hajer Elkout Richard G Ellenbogen Aisha Elsharkawy Mohammad Hassan Emamian Daniel Adane Endalew Aman Yesuf Endries Babak Eshrati Ibtihal Fadhil Vahid Fallah Omrani Mahbobeh Faramarzi Mahdieh Abbasalizad Farhangi Andrea Farioli Farshad Farzadfar Netsanet Fentahun Eduarda Fernandes Garumma Tolu Feyissa Irina Filip Florian Fischer James L Fisher Lisa M Force Masoud Foroutan Marisa Freitas Takeshi Fukumoto Neal D Futran Silvano Gallus Fortune Gbetoho Gankpe Reta Tsegaye Gayesa Tsegaye Tewelde Gebrehiwot Gebreamlak Gebremedhn Gebremeskel Getnet Azeze Gedefaw Belayneh K Gelaw Birhanu Geta Sefonias Getachew Kebede Embaye Gezae Mansour Ghafourifard Alireza Ghajar Ahmad Ghashghaee Asadollah Gholamian Paramjit Singh Gill Themba T G Ginindza Alem Girmay Muluken Gizaw Ricardo Santiago Gomez Sameer Vali Gopalani Giuseppe Gorini Bárbara Niegia Garcia Goulart Ayman Grada Maximiliano Ribeiro Guerra Andre Luiz Sena Guimaraes Prakash C Gupta Rahul Gupta Kishor Hadkhale Arvin Haj-Mirzaian Arya Haj-Mirzaian Randah R Hamadeh Samer Hamidi Lolemo Kelbiso Hanfore Josep Maria Haro Milad Hasankhani Amir Hasanzadeh Hamid Yimam Hassen Roderick J Hay Simon I Hay Andualem Henok Nathaniel J Henry Claudiu Herteliu Hagos D Hidru Chi Linh Hoang Michael K Hole Praveen Hoogar Nobuyuki Horita H Dean Hosgood Mostafa Hosseini Mehdi Hosseinzadeh Mihaela Hostiuc Sorin Hostiuc Mowafa Househ Mohammedaman Mama Hussen Bogdan Ileanu Milena D Ilic Kaire Innos Seyed Sina Naghibi Irvani Kufre Robert Iseh Sheikh Mohammed Shariful Islam Farhad Islami Nader Jafari Balalami Morteza Jafarinia Leila Jahangiry Mohammad Ali Jahani Nader Jahanmehr Mihajlo Jakovljevic Spencer L James Mehdi Javanbakht Sudha Jayaraman Sun Ha Jee Ensiyeh Jenabi Ravi Prakash Jha Jost B Jonas Jitendra Jonnagaddala Tamas Joo Suresh Banayya Jungari Mikk Jürisson Ali Kabir Farin Kamangar André Karch Narges Karimi Ansar Karimian Amir Kasaeian Gebremicheal Gebreslassie Kasahun Belete Kassa Tesfaye Dessale Kassa Mesfin Wudu Kassaw Anil Kaul Peter Njenga Keiyoro Abraham Getachew Kelbore Amene Abebe Kerbo Yousef Saleh Khader Maryam Khalilarjmandi Ejaz Ahmad Khan Gulfaraz Khan Young-Ho Khang Khaled Khatab Amir Khater Maryam Khayamzadeh Maryam Khazaee-Pool Salman Khazaei Abdullah T Khoja Mohammad Hossein Khosravi Jagdish Khubchandani Neda Kianipour Daniel Kim Yun Jin Kim Adnan Kisa Sezer Kisa Katarzyna Kissimova-Skarbek Hamidreza Komaki Ai Koyanagi Kristopher J Krohn Burcu Kucuk Bicer Nuworza Kugbey Vivek Kumar Desmond Kuupiel Carlo La Vecchia Deepesh P Lad Eyasu Alem Lake Ayenew Molla Lakew Dharmesh Kumar Lal Faris Hasan Lami Qing Lan Savita Lasrado Paolo Lauriola Jeffrey V Lazarus James Leigh Cheru Tesema Leshargie Yu Liao Miteku Andualem Limenih Stefan Listl Alan D Lopez Platon D Lopukhov Raimundas Lunevicius Mohammed Madadin Sameh Magdeldin Hassan Magdy Abd El Razek Azeem Majeed Afshin Maleki Reza Malekzadeh Ali Manafi Navid Manafi Wondimu Ayele Manamo Morteza Mansourian Mohammad Ali Mansournia Lorenzo Giovanni Mantovani Saman Maroufizadeh Santi Martini S Martini Tivani Phosa Mashamba-Thompson Benjamin Ballard Massenburg Motswadi Titus Maswabi Manu Raj Mathur Colm McAlinden Martin McKee Hailemariam Abiy Alemu Meheretu Ravi Mehrotra Varshil Mehta Toni Meier Yohannes A Melaku Gebrekiros Gebremichael Meles Hagazi Gebre Meles Addisu Melese Mulugeta Melku Peter T N Memiah Walter Mendoza Ritesh G Menezes Shahin Merat Tuomo J Meretoja Tomislav Mestrovic Bartosz Miazgowski Tomasz Miazgowski Kebadnew Mulatu M Mihretie Ted R Miller Edward J Mills Seyed Mostafa Mir Hamed Mirzaei Hamid Reza Mirzaei Rashmi Mishra Babak Moazen Dara K Mohammad Karzan Abdulmuhsin Mohammad Yousef Mohammad Aso Mohammad Darwesh Abolfazl Mohammadbeigi Hiwa Mohammadi Moslem Mohammadi Mahdi Mohammadian Abdollah Mohammadian-Hafshejani Milad Mohammadoo-Khorasani Reza Mohammadpourhodki Ammas Siraj Mohammed Jemal Abdu Mohammed Shafiu Mohammed Farnam Mohebi Ali H Mokdad Lorenzo Monasta Yoshan Moodley Mahmood Moosazadeh Maryam Moossavi Ghobad Moradi Mohammad Moradi-Joo Maziar Moradi-Lakeh Farhad Moradpour Lidia Morawska Joana Morgado-da-Costa Naho Morisaki Shane Douglas Morrison Abbas Mosapour Seyyed Meysam Mousavi Achenef Asmamaw Muche Oumer Sada S Muhammed Jonah Musa Ashraf F Nabhan Mehdi Naderi Ahamarshan Jayaraman Nagarajan Gabriele Nagel Azin Nahvijou Gurudatta Naik Farid Najafi Luigi Naldi Hae Sung Nam Naser Nasiri Javad Nazari Ionut Negoi Subas Neupane Polly A Newcomb Haruna Asura Nggada Josephine W Ngunjiri Cuong Tat Nguyen Leila Nikniaz Dina Nur Anggraini Ningrum Yirga Legesse Nirayo Molly R Nixon Chukwudi A Nnaji Marzieh Nojomi Shirin Nosratnejad Malihe Nourollahpour Shiadeh Mohammed Suleiman Obsa Richard Ofori-Asenso Felix Akpojene Ogbo In-Hwan Oh Andrew T Olagunju Tinuke O Olagunju Mojisola Morenike Oluwasanu Abidemi E Omonisi Obinna E Onwujekwe Anu Mary Oommen Eyal Oren Doris D V Ortega-Altamirano Erika Ota Stanislav S Otstavnov Mayowa Ojo Owolabi Mahesh P A Jagadish Rao Padubidri Smita Pakhale Amir H Pakpour Adrian Pana Eun-Kee Park Hadi Parsian Tahereh Pashaei Shanti Patel Snehal T Patil Alyssa Pennini David M Pereira Cristiano Piccinelli Julian David Pillay Majid Pirestani Farhad Pishgar Maarten J Postma Hadi Pourjafar Farshad Pourmalek Akram Pourshams Swayam Prakash Narayan Prasad Mostafa Qorbani Mohammad Rabiee Navid Rabiee Amir Radfar Alireza Rafiei Fakher Rahim Mahdi Rahimi Muhammad Aziz Rahman Fatemeh Rajati Saleem M Rana Samira Raoofi Goura Kishor Rath David Laith Rawaf Salman Rawaf Robert C Reiner Andre M N Renzaho Nima Rezaei Aziz Rezapour Ana Isabel Ribeiro Daniela Ribeiro Luca Ronfani Elias Merdassa Roro Gholamreza Roshandel Ali Rostami Ragy Safwat Saad Parisa Sabbagh Siamak Sabour Basema Saddik Saeid Safiri Amirhossein Sahebkar Mohammad Reza Salahshoor Farkhonde Salehi Hosni Salem Marwa Rashad Salem Hamideh Salimzadeh Joshua A Salomon Abdallah M Samy Juan Sanabria Milena M Santric Milicevic Benn Sartorius Arash Sarveazad Brijesh Sathian Maheswar Satpathy Miloje Savic Monika Sawhney Mehdi Sayyah Ione J C Schneider Ben Schöttker Mario Sekerija Sadaf G Sepanlou Masood Sepehrimanesh Seyedmojtaba Seyedmousavi Faramarz Shaahmadi Hosein Shabaninejad Mohammad Shahbaz Masood Ali Shaikh Amir Shamshirian Morteza Shamsizadeh Heidar Sharafi Zeinab Sharafi Mehdi Sharif Ali Sharifi Hamid Sharifi Rajesh Sharma Aziz Sheikh Reza Shirkoohi Sharvari Rahul Shukla Si Si Soraya Siabani Diego Augusto Santos Silva Dayane Gabriele Alves Silveira Ambrish Singh Jasvinder A Singh Solomon Sisay Freddy Sitas Eugène Sobngwi Moslem Soofi Joan B Soriano Vasiliki Stathopoulou Mu'awiyyah Babale Sufiyan Rafael Tabarés-Seisdedos Takahiro Tabuchi Ken Takahashi Omid Reza Tamtaji Mohammed Rasoul Tarawneh Segen Gebremeskel Tassew Parvaneh Taymoori Arash Tehrani-Banihashemi Mohamad-Hani Temsah Omar Temsah Berhe Etsay Tesfay Fisaha Haile Tesfay Manaye Yihune Teshale Gizachew Assefa Tessema Subash Thapa Kenean Getaneh Tlaye Roman Topor-Madry Marcos Roberto Tovani-Palone Eugenio Traini Bach Xuan Tran Khanh Bao Tran Afewerki Gebremeskel Tsadik Irfan Ullah Olalekan A Uthman Marco Vacante Maryam Vaezi Patricia Varona Pérez Yousef Veisani Simone Vidale Francesco S Violante Vasily Vlassov Stein Emil Vollset Theo Vos Kia Vosoughi Giang Thu Vu Isidora S Vujcic Henry Wabinga Tesfahun Mulatu Wachamo Fasil Shiferaw Wagnew Yasir Waheed Fitsum Weldegebreal Girmay Teklay Weldesamuel Tissa Wijeratne Dawit Zewdu Wondafrash Tewodros Eshete Wonde Adam Belay Wondmieneh Hailemariam Mekonnen Workie Rajaram Yadav Abbas Yadegar Ali Yadollahpour Mehdi Yaseri Vahid Yazdi-Feyzabadi Alex Yeshaneh Mohammed Ahmed Yimam Ebrahim M Yimer Engida Yisma Naohiro Yonemoto Mustafa Z Younis Bahman Yousefi Mahmoud Yousefifard Chuanhua Yu Erfan Zabeh Vesna Zadnik Telma Zahirian Moghadam Zoubida Zaidi Mohammad Zamani Hamed Zandian Alireza Zangeneh Leila Zaki Kazem Zendehdel Zerihun Menlkalew Zenebe Taye Abuhay Zewale Arash Ziapour Sanjay Zodpey Christopher J L Murray

JAMA Oncol 2019 12;5(12):1749-1768

Institute for Health Metrics and Evaluation, University of Washington, Seattle.

Importance: 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.

Objective: To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning.

Evidence Review: 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.

Findings: 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).

Conclusions And Relevance: 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1001/jamaoncol.2019.2996DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6777271PMC
December 2019

Developing a Saudi Health Informatics Competency Framework: A Comparative Assessment.

Stud Health Technol Inform 2019 Aug;264:1101-1105

King Faisal Medical City for Southern Regions, Abha, Asir Province, Saudi Arabia.

In 2018, the Saudi Commission for Health Specialties (SCFHS) created a national working group composed of key health informatics (HI) professionals, researchers and educators tasked with the development of a draft competency framework for Saudi HI professionals. Over an eight-month period, the research group collected data obtained from literature sources (both academic and grey), international competency standards, participant surveys, focus groups, and expert panel reviews. Through multiple rounds of discussions and graphic visualisation of the information collected using Microsoft PowerPoint and flip charts, the data were summarised and a visual representation of the proposed SHICF was developed. The result of this effort was the development of the first Saudi Health Informatics Competency Framework (SHICF). This paper provides a comparative assessment between the Saudi HI competency framework development and that of other internationally recognised HI competency development frameworks. Challenges related to the development of the SHICF are also discussed.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3233/SHTI190396DOI Listing
August 2019