Publications by authors named "Sharareh R Niakan Kalhori"

38 Publications

STO: Stroke Ontology for Accelerating Translational Stroke Research.

Neurol Ther 2021 Apr 22. Epub 2021 Apr 22.

Information Technology for Translational Medicine, 4362, Esch-sur-Alzette, Luxembourg.

Introduction: Ontology-based annotation of evidence, using disease-specific ontologies, can accelerate analysis and interpretation of the knowledge domain of diseases. Although many domain-specific disease ontologies have been developed so far, in the area of cardiovascular diseases, there is a lack of ontological representation of the disease knowledge domain of stroke.

Methods: The stroke ontology (STO) was created on the basis of the ontology development life cycle and was built using Protégé ontology editor in the ontology web language format. The ontology was evaluated in terms of structural and functional features, expert evaluation, and competency questions.

Results: The stroke ontology covers a broad range of major biomedical and risk factor concepts. The majority of concepts are enriched by synonyms, definitions, and references. The ontology attempts to incorporate different users' views on the stroke domain such as neuroscientists, molecular biologists, and clinicians. Evaluation of the ontology based on natural language processing showed a high precision (0.94), recall (0.80), and F-score (0.78) values, indicating that STO has an acceptable coverage of the stroke knowledge domain. Performance evaluation using competency questions designed by a clinician showed that the ontology can be used to answer expert questions in light of published evidence.

Conclusions: The stroke ontology is the first, multiple-view ontology in the domain of brain stroke that can be used as a tool for representation, formalization, and standardization of the heterogeneous data related to the stroke domain. Since this is a draft version of the ontology, the contribution of the stroke scientific community can help to improve the usability of the current version.
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http://dx.doi.org/10.1007/s40120-021-00248-1DOI Listing
April 2021

Application and evaluation of virtual technologies for anatomy education to medical students: A review.

Med J Islam Repub Iran 2020 3;34:163. Epub 2020 Dec 3.

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

To learn anatomy, medical students need to look at body structures and manipulate anatomical structures. Simulation-based education is a promising opportunity for the upgrade and sharing of knowledge. The purpose of this review is to investigate the evaluation of virtual technologies in teaching anatomy to medical students.

Methods: In this review, we searched PubMed, Web of Sciences, Scopus, and Embase for relevant articles in November 2018. Information retrieval was done without time limitation. The search was based on the following keywords: virtual reality, medical education, and anatomy.

Results: 2483 articles were identified by searching databases. Finally, the fulltext of 12 articles was reviewed. The results of the review showed that virtual technologies had been used to train internal human anatomy, ear anatomy, nose anatomy, temporal bone anatomy, surgical anatomy, neuroanatomy, and cardiac anatomy.

Conclusion: Virtual reality, augmented reality, and games can enhance students' anatomical learning skills and are proper alternatives to traditional methods in case of no access to the cadavers and mannequin.
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http://dx.doi.org/10.47176/mjiri.34.163DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004573PMC
December 2020

A systematic review of decision aids for mammography screening: Focus on outcomes and characteristics.

Int J Med Inform 2021 Feb 18;149:104406. Epub 2021 Feb 18.

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran. Electronic address:

Purpose: Decision Aid systems (DAs) provide information on the pros and cons of mammography. This study aimed to review the research on mammography DAs, synthesize the findings related to their outcomes and characteristics, and address the existed research gap.

Methods: Relevant studies were identified through a comprehensive search on some e-databases, including PubMed, EMBASE, Scopus, and Web of Science in August 2020; by searching the keywords of "Breast cancer", "Screening", and "Decision aid systems" as well as their synonyms in the titles and abstracts of the papers with no time limits. Among the selected English journal papers with the interventional study design, those measuring outcome values of using mammography DAs were recognized as eligible for being included in this review.

Results: The systematic search results in 16 DAs regarding mammography that were designed and then evaluated from 18 selected studies. The results showed that DAs provide improvements in knowledge and informed choice, the decreased decisional conflicts and decisional confidence, almost without changing any attitude towards mammography, mammography participation rates, psychological issues, anticipated regret, and perceived risk of breast cancer. The DAs' effects on women's inclination to screening were divergent. In other words, the DAs affect individuals' inclination in rare cases; however, on occasion, they could affect women's decision to undergo screening.

Conclusion: DAs could correct the bias attached to the existing knowledge on mammography and breast cancer in women so that they are more likely to make a precise decision. Additionally, it might be of central importance in shared decision-making and assisting health providers, in order to promote the quality of care. Accordingly, performing more studies is needed to develop more professional DAs in various countries with different facilities, cultures, and languages.
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http://dx.doi.org/10.1016/j.ijmedinf.2021.104406DOI Listing
February 2021

Digital Health Solutions to Control the COVID-19 Pandemic in Countries With High Disease Prevalence: Literature Review.

J Med Internet Res 2021 03 10;23(3):e19473. Epub 2021 Mar 10.

Department of Health Information Management, Tehran University of Medical Sciences, Tehran, Iran.

Background: COVID-19, the disease caused by the novel coronavirus SARS-CoV-2, has become a global pandemic, affecting most countries worldwide. Digital health information technologies can be applied in three aspects, namely digital patients, digital devices, and digital clinics, and could be useful in fighting the COVID-19 pandemic.

Objective: Recent reviews have examined the role of digital health in controlling COVID-19 to identify the potential of digital health interventions to fight the disease. However, this study aims to review and analyze the digital technology that is being applied to control the COVID-19 pandemic in the 10 countries with the highest prevalence of the disease.

Methods: For this review, the Google Scholar, PubMed, Web of Science, and Scopus databases were searched in August 2020 to retrieve publications from December 2019 to March 15, 2020. Furthermore, the Google search engine was used to identify additional applications of digital health for COVID-19 pandemic control.

Results: We included 32 papers in this review that reported 37 digital health applications for COVID-19 control. The most common digital health projects to address COVID-19 were telemedicine visits (11/37, 30%). Digital learning packages for informing people about the disease, geographic information systems and quick response code applications for real-time case tracking, and cloud- or mobile-based systems for self-care and patient tracking were in the second rank of digital tool applications (all 7/37, 19%). The projects were deployed in various European countries and in the United States, Australia, and China.

Conclusions: Considering the potential of available information technologies worldwide in the 21st century, particularly in developed countries, it appears that more digital health products with a higher level of intelligence capability remain to be applied for the management of pandemics and health-related crises.
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http://dx.doi.org/10.2196/19473DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7951053PMC
March 2021

A review and content analysis of national apps for COVID-19 management using Mobile Application Rating Scale (MARS).

Inform Health Soc Care 2021 Mar 9;46(1):42-55. Epub 2020 Nov 9.

Centre for Online Health, The University of Queensland , Brisbane, Australia.

The expansion of mobile health apps for the management of COVID-19 grew exponentially in recent months. However, no study has evaluated these apps. The objective of this study was to develop a reliable measure and rate the quality of COVID-19 mobile health apps, to eventually provide a roadmap for future mHealth app development. In this study, we used COVID-related keywords to identify apps for iOS and Android devices. 13 apps (13.5% of the total number of apps identified) were selected for evaluation. App quality was assessed independently using MARS by two reviewers. Search queries yielded a total of 97 potentially relevant apps, of which 13 met our final inclusion criteria. Kendall's coefficient of concordance value for the inter-rater agreement was 0.93 ( = .03). COVID-19 GOV PK app had the highest average MARS score (4.7/5), and all of the apps had acceptable MARS scores (> 3.0). This study suggests that most COVID-related apps meet acceptable criteria for quality, content, or functionality, and they must highlight esthetic and interesting features for overall quality improvement to be welcomed by users.
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http://dx.doi.org/10.1080/17538157.2020.1837838DOI Listing
March 2021

Development and validation of the Neonatal Abstinence Syndrome Minimum Data Set (NAS-MDS): a systematic review, focus group discussion, and Delphi technique.

J Matern Fetal Neonatal Med 2020 Oct 13:1-8. Epub 2020 Oct 13.

Community Based Participatory Research Center, Iranian Institute for Reduction of High-Risk Behaviors, Tehran University of Medical Sciences, Tehran, Iran.

Objectives: Neonatal abstinence syndrome (NAS) is a combination of symptoms in infants exposed to any variety of substances in utero. Information systems and registries help to collect information about these patients; however, there is always a deep gap between complete and accurate information to be collected, understood, and applied in the health care system; thus, defining a minimum data sets (MDS) as one of the primarily steps of designing a registry system is essential. The aim of this study was to develop an MDS of the registry for infants with NAS in Iran.

Methods: This research is a descriptive cross-sectional study. In this study, three steps were carried out to develop the MDS including systematic review, Delphi technique, and focus group discussion. A systematic review was conducted in relevant databases to identify appropriate related data. In the second phase, a focus group discussion was used to classify the extracted data elements by contributing neonatologists. Finally, data elements were chosen through the decision Delphi technique in two distinct rounds. Collected data were analyzed using SPSS 22 (SPSS Inc., Chicago, IL).

Results: By reviewing related papers and available NAS registries in other countries, 145 essential data elements were identified. They were classified into two main categories based on the eight experts' opinions including maternal with two sections and infant with two sections. After applying two rounds of Delphi technique, the final data elements for maternal and infant categories were 42 and 31, respectively. Thus, on completion of the survey, 73 data elements were approved.

Conclusion: The proposed MDS for NAS can help to store an accurate and comprehensive data, document medical records, integrate them with other information systems and registries, and communicate with other healthcare providers and healthcare centers. This MDS can contribute to the provision of high-quality care and better clinical decisions.
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http://dx.doi.org/10.1080/14767058.2020.1730319DOI Listing
October 2020

Quality Evaluation of English Mobile Applications for Gestational Diabetes: App Review using Mobile Application Rating Scale (MARS).

Curr Diabetes Rev 2021 ;17(2):161-168

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Background: Mobile applications and social media serve their users as convenient tools to improve and monitor diseases and conditions such as pregnancy. These tools also exert a positive impact on Gestational diabetes mellitus (GDM) self-management.

Introduction: Despite the expansion of mobile health apps for the management of GDM, no study has evaluated these apps using a valid tool. This study aimed to search and review the apps developed for this purpose, providing overall and specific rating scores for each aspect of MARS.

Methods: Two cases of app stores (IOS and Google Play) were searched in January 2019 for apps related to GDM. Search keywords included "gestational diabetes", "pregnant diabetes", and "Health apps". Eligibility criteria include: capable of running on Android or IOS operating systems, in the English language, especially for GDM, and available in Iran. After removal of duplicates, the apps were reviewed, rated, and evaluated independently by two reviewers with Mobile App Rating Scale (MARS) tools.

Results: Initially, 102 apps were identified after the exclusion process, five selected apps were downloaded and analyzed. All apps were classified into four categories according to contents and their interactive capabilities. In most quadrants of MARS, the Pregnant with Diabetes app received the highest scores. Also, in general, the maximum app quality mean score belonged to Pregnant with Diabetes (3.10 / 5.00).

Conclusion: Findings revealed that apps designed for GDM are small in number and poor in quality based on MARS tools. Therefore, considering pregnant women's need for using the capabilities of these apps in pregnancy management and promoting community-based care, it seems essential to develop and design a series of high-quality apps in all four specified categories (only giving comments, obtaining data and giving comments, diagnosis of GDM, and diet calculator).
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http://dx.doi.org/10.2174/1573399816666200703181438DOI Listing
March 2021

Surgical Patients Follow-Up by Smartphone-Based Applications: A Systematic Literature Review.

Stud Health Technol Inform 2020 Jun;271:85-92

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Background: Telemedicine technology with the development of mobile applications (apps) has provided a new approach for the follow-up of patients.

Objectives: This study aims to carry out an overview of the studies related to the use of mobile apps in the follow-up of surgical patients.

Methods: In this study, an electronic search of four databases included PubMed, Scopus, Embase, and web of science was carried out. It included studies in the English language from the beginning of 2009 to June 2019.

Results: Twenty-three articles were selected for the final analysis, that all of them were published from 2015 onwards. In most studies, fourteen to thirty-days follow-up period for different outpatient and inpatient surgeries was planned. Apps' components in the studies mostly include indexes for evaluation of recovery quality, pain level, and the surgical site infection. The most important achievement of studies included feasibility, early detection of complications, reducing unscheduled in-person visits, patients' self-efficiency, and satisfaction.

Conclusions: Our review showed that mHealth-based interventions have potential that may support better management of post-discharge systematic follow-up of surgery patients.
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http://dx.doi.org/10.3233/SHTI200079DOI Listing
June 2020

Optimized Patients' Length of Hospital Stay with Interventions Based on Health Information Technology: A Review Study.

Stud Health Technol Inform 2020 Jun;271:69-76

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Background: Information and communications technologies (ICTs) may facilitate shorting length of stay (LOS) of patients through the optimization of processes and delivery services.

Objectives: This study aims to provide technology-based solutions and interventions based on health information technology (HIT) that have optimization potentials of patients' LOS.

Methods: This review study searched papers in PubMed, Scopus as well as Google Scholar without presuming time limits by the end of 2019. English and Persian Papers were included, which addressed an association between the ICT and LOS as well as its positive effect in shortening LOS.

Results: Identified technologies were finally classified into eleven groups. Based on the findings, common health technologies such as health information systems, telemedicine especially tele-consultation, electronic discharge planning tools, and visual analytical dashboards in order to expedite the process and help to optimize LOS seem appropriate.

Conclusions: HIT-based interventions have potential that may support better management of processes related to patients' admission, hospitalization, and discharge. However consistently evaluation along with using any new technology is necessary.
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http://dx.doi.org/10.3233/SHTI200077DOI Listing
June 2020

Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study.

JMIR Public Health Surveill 2020 04 14;6(2):e18828. Epub 2020 Apr 14.

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Background: The recent global outbreak of coronavirus disease (COVID-19) is affecting many countries worldwide. Iran is one of the top 10 most affected countries. Search engines provide useful data from populations, and these data might be useful to analyze epidemics. Utilizing data mining methods on electronic resources' data might provide a better insight into the COVID-19 outbreak to manage the health crisis in each country and worldwide.

Objective: This study aimed to predict the incidence of COVID-19 in Iran.

Methods: Data were obtained from the Google Trends website. Linear regression and long short-term memory (LSTM) models were used to estimate the number of positive COVID-19 cases. All models were evaluated using 10-fold cross-validation, and root mean square error (RMSE) was used as the performance metric.

Results: The linear regression model predicted the incidence with an RMSE of 7.562 (SD 6.492). The most effective factors besides previous day incidence included the search frequency of handwashing, hand sanitizer, and antiseptic topics. The RMSE of the LSTM model was 27.187 (SD 20.705).

Conclusions: Data mining algorithms can be employed to predict trends of outbreaks. This prediction might support policymakers and health care managers to plan and allocate health care resources accordingly.
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http://dx.doi.org/10.2196/18828DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7159058PMC
April 2020

Supporting colorectal cancer survivors using eHealth: a systematic review and framework suggestion.

Support Care Cancer 2020 Aug 9;28(8):3543-3555. Epub 2020 Mar 9.

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, 3rd Floor, No #17, Farre Danesh Alley, Ghods St, Enghelab Ave., Tehran, Iran.

Purpose: eHealth could potentially support colorectal cancer survivors; however, little is known regarding the overall recent eHealth systems for colorectal cancer survivors. The present study was conducted to address which types of eHealth supports have been provided to colorectal cancer survivors in the past two decades.

Methods: An electronic search was conducted in four databases including Scopus, PubMed, Embase, and Web of Science. The search query was based on two concepts: the first concept represented colorectal cancer and the second one comprised of information technology tools. The search was limited to 20 years (from 19 January 1999 to 19 January 2019). Obtained results were tabulated and represented as a framework.

Results: Fifteen papers were included in this systematic review. Information including intervention type, eHealth tools, main features of the system, and outcomes were extracted from selected papers. Obtained results were characterized using a four-layer framework. This framework included layers of hardware, software, service (educating the patient, medication intake, physical activity, health status monitoring, hospital visit reminder, and discussion group), and outcome. Outcome layer was composed of the following domains: quality of life, psychological and cognitive, physical activity, physical functioning, symptoms, engagement, and the outcome of the process and IT tools.

Conclusion: eHealth could provide useful services for supporting colorectal cancer survivors. Represented framework might be used for a better understanding of current technology and services provided to support these survivors. Also, this framework may be used as a basis for designing eHealth applications for colorectal cancer survivors after further validations.
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http://dx.doi.org/10.1007/s00520-020-05372-6DOI Listing
August 2020

Minimum data set development for a drug poisoning registry system.

Digit Health 2019 Jan-Dec;5:2055207619897155. Epub 2019 Dec 24.

Department of Health Information Management, Tehran University of Medical Sciences (TUMS), Tehran, Iran.

Objective: Drug poisoning is the most prevalent type of poisoning throughout the world that can occur intentional or unintentional. Standard way for data gathering with uniform definitions is a requirement for preventing, controlling and managing of drug poisoning management. The purpose of this study was to develop a minimum data set, as an initial step, for a drug poisoning registry system in Iran.

Methods: This was descriptive and cross-sectional study that was performed in 2019. As the first step a comprehensive literature review was performed to retrieve related resources in Persian and English languages. For the second step the medical records of drug poisoning patients at Afzalipour hospital affiliated to Kerman University of Medical Sciences were assessed. Related data from these two steps were gathered by a checklist. Finally, a questionnaire that was created based on the checklist data elements and had three columns of 'essential,' 'useful, but not essential', and 'not essential' was used to reach a consensus on the data elements. Then the content validity ratio and the mean of experts' judgments were calculated for each data element. The Cronbach's alpha value for the entire questionnaire was obtained 0.9.

Results: The minimum data set of a drug poisoning registry system was categorised into the administrative part with three sections including 32 data elements, and clinical parts with six sections including 81 data elements.

Conclusion: This study provides a minimum data set for development of a drug poisoning registry system. Collecting this minimum data set is critical for helping policy makers and healthcare providers to prevent, control and manage drug poisoning.
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http://dx.doi.org/10.1177/2055207619897155DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6967198PMC
December 2019

Determining minimum set of features for diabetes mobile apps.

J Diabetes Metab Disord 2019 Dec 27;18(2):333-340. Epub 2019 Jun 27.

4Department of Health Education and Health Promotion, School of Public Health, Shiraz University of Medical Sciences, Shiraz, Iran.

Purpose: Interest in mobile health applications (apps) for diabetes self-care is growing. Mobile health is a promising new treatment modality for diabetes, though few smartphone apps have been designed based on a proper study and prioritization. The aim of this study was to determine a minimum set of features for diabetes mobile apps.

Methods: This study was conducted in three steps: 1.A review of the literature to collect all available features, 2. Assessing the validity of suggested features by Content Validity Index (CVI) and Content Validity Ratio (CVR), 3. Examining the importance of features by Friedman test.

Results: We retrieved all features of available mobile apps for type 2 diabetes, which are suggested and discussed in literature and compiled as a single list comprising of 33 features. Then, a survey of expert's opinion produced a set of 23 final minimum features which includes all types of tracking, mealtime tagging, food database, diet management, educational materials, healthy coping, reducing risks, problem solving, Email, color coding, alerts, reminder, target range setting, trend chart view, logbook view, numerical indicators view, customizable theme, preset notes, and custom notes. According to the mean rank which indicates the priority of each feature, the most important one was blood glucose tracking (with 16.71 mean rank) and the least important feature was the numerical indicators like such as standard deviation or average (with 6.50 mean rank).

Conclusions: The present study is the first step towards the development of our mobile apps for people with type II diabetes, and highest the essential features that are required for an optimal self-care comprehensively.
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http://dx.doi.org/10.1007/s40200-019-00417-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6914742PMC
December 2019

Artificial Intelligence Applications in Type 2 Diabetes Mellitus Care: Focus on Machine Learning Methods.

Healthc Inform Res 2019 Oct 31;25(4):248-261. Epub 2019 Oct 31.

Department of Health Information Management and Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Objectives: The incidence of type 2 diabetes mellitus has increased significantly in recent years. With the development of artificial intelligence applications in healthcare, they are used for diagnosis, therapeutic decision making, and outcome prediction, especially in type 2 diabetes mellitus. This study aimed to identify the artificial intelligence (AI) applications for type 2 diabetes mellitus care.

Methods: This is a review conducted in 2018. We searched the PubMed, Web of Science, and Embase scientific databases, based on a combination of related mesh terms. The article selection process was based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Finally, 31 articles were selected after inclusion and exclusion criteria were applied. Data gathering was done by using a data extraction form. Data were summarized and reported based on the study objectives.

Results: The main applications of AI for type 2 diabetes mellitus care were screening and diagnosis in different stages. Among all of the reviewed AI methods, machine learning methods with 71% (n = 22) were the most commonly applied techniques. Many applications were in multi method forms (23%). Among the machine learning algorithms applications, support vector machine (21%) and naive Bayesian (19%) were the most commonly used methods. The most important variables that were used in the selected studies were body mass index, fasting blood sugar, blood pressure, HbA1c, triglycerides, low-density lipoprotein, high-density lipoprotein, and demographic variables.

Conclusions: It is recommended to select optimal algorithms by testing various techniques. Support vector machine and naive Bayesian might achieve better performance than other applications due to the type of variables and targets in diabetes-related outcomes classification.
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http://dx.doi.org/10.4258/hir.2019.25.4.248DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6859270PMC
October 2019

Virtual reality applications for chronic conditions management: A review.

Med J Islam Repub Iran 2019 10;33:67. Epub 2019 Jul 10.

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Virtual Reality (VR) as a computer technology that simulating real environments and situations exploited in numerous healthcare areas such as chronic diseases. The significance of timely treatment and rehabilitation of patients with chronic conditions is high due to the long lasting nature of these conditions. This paper sought to perform a review of published works in the field of VR application in chronic conditions for treatment and rehabilitation purposes. We searched the MEDLINE database through PubMed in April 2016 for retrieving published papers from January 2001 to December 2015. From 117 retrieved papers, 52had the inclusion criteria, and their full texts were accessible. Data were extracted from papers based on following items: the name of the first author, year of the study, applied VR methods, type of condition and disease, number of subjects that participated in the study, and finally the status of success and failure of VR application. Data were analyzed using descriptive analysis. Results of the reviewed investigations have been considered in two main categories including treatment oriented papers (n=38, 73%) while twenty of these papers have been conducted on phobias (53%); also, there are rehabilitation-oriented experiments (n=14, 27%) while thirteen of these papers have been performed on stroke. In 40 papers (77%), the VR technology application reported proper and in 11 papers (21%) the application of VR resulted in relatively proper outcomes and only there is a work (2%) with poor results for VR intervention. VR technology has been increasingly used in recent years for treatment and rehabilitation purposes among patients affected by chronic conditions in order to motivate them for more successful management.
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http://dx.doi.org/10.34171/mjiri.33.67DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6708122PMC
July 2019

A unique framework for the Persian clinical guidelines: addressing an evidence-based CDSS development need.

BMJ Evid Based Med 2020 02 25;25(1):22-26. Epub 2019 May 25.

Health information management department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Background And Aim: One of the prerequisites to develop Computerised Decision Support Systems is Clinical Practice Guidelines (CPGs) which provide a systematic aid to make complex medical decisions. In order to provide an automated CPG, it is needed to have a unique structure for the CPGs. This study aims to propose a unique framework for the Persian guidelines.

Materials And Methods: 20 Persian CPGs were selected and divided into the creation and validation sets (n=10 for each). The first group was studied independently and their headings were listed; wherever possible, the headings were merged into a new heading that was applicable to all the guidelines. The developed framework was validated by the second group of the guidelines.

Results: Studied guidelines had a very heterogeneous structure. The number of original headings was 249; they were reduced to 14 main headings with 16 subheadings in a unique developed framework. The framework is able to represent and cover 100% of the guidelines.

Conclusion: The heterogeneity of guidelines was high as they were not developed based on the unique framework. The proposed framework provides a layout for designing the CPGs with a homogeneous structure. Guideline developers can use this framework to develop structured CPGs. This will facilitate the integration of the guidelines into electronic medical records as well as clinical decision support systems.
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http://dx.doi.org/10.1136/bmjebm-2019-111187DOI Listing
February 2020

Conformity of Diabetes Mobile apps with the Chronic Care Model.

BMJ Health Care Inform 2019 Apr;26(1)

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Science, Tehran, Iran.

Background: Despite the growing use of mobile applications (apps) for chronic disease management, the evidence on the effectiveness of this technology on clinical and behavioural outcomes of the patients is scant. Many studies highlight the importance of the theoretical foundations of mobile-based interventions. One of the most widely accepted models for the management of chronic diseases, such as diabetes, is the Chronic Care Model (CCM). In this study, we investigated the conformity of the selected diabetes mobile apps with CCM.

Method: We searched online journal databases related to diabetes mobile apps to find common features. Then considering the components of the CCM as a reference model, features of some popular and top-ranking apps were compared with CCM.

Results: Among 23 studied apps, 34 per cent of them had medium conformity and 66 per cent of these apps were in weak conformity. The self-management support component is covered by 100 per cent of them. Ninety-five per cent of apps have covered the proactive follow-up component.

Conclusions: App conformance with CCM is generally weak. App developers are recommended to give greater consideration to established theoretical models in their design and implementation.
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http://dx.doi.org/10.1136/bmjhci-2019-000017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062315PMC
April 2019

Questionnaire development and validation for designing a health telemonitoring system for frail elderly people.

Digit Health 2019 Jan-Dec;5:2055207619838940. Epub 2019 Mar 27.

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Iran.

Background: Advancements in information technology have been instrumental in successful recent developments in telemonitoring systems. In this regard, there is a lack of development of valid and reliable tools to determine the requirements and applications of telemonitoring systems used to provide health care for frail elderly people living at home, specifically in a national setting.

Method: A cross-sectional study was carried out in 2018. The statistical population was 15 geriatric and gerontology professionals and 15 health information management experts. Then, content validity ratio (CVR), Cronbach's alpha, and correlation coefficient were calculated for measuring content validity, internal consistency and external reliability (through the test-retest method) respectively. SPSS software was used to analyze the collected data.

Results: Based on the identified items, a draft questionnaire was developed. Using the validity analysis in two stages, 37 items were removed, and 60 items were approved as the essential system requirements. The final questionnaire was organized into five sections with content validity index 99% and internal reliability (Cronbach's alpha coefficient 0.9). Furthermore, the external reliability results of the questionnaire showed that this instrument has a desirable correlation coefficient ( = 0.85, -value<0.05).

Conclusion: Considering the desirable validity and reliability of the questionnaire developed, it is recommended to telemonitoring system designers to determine the usages and requirements of health monitoring systems for frail elderly people living at home. The verified instrument is suitable for use in countries with the same living conditions and level of development as Iran.
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http://dx.doi.org/10.1177/2055207619838940DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437328PMC
March 2019

Words prediction based on N-gram model for free-text entry in electronic health records.

Health Inf Sci Syst 2019 Dec 28;7(1). Epub 2019 Feb 28.

1Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

The process of documentation is one of the most important parts of electronic health records (EHR). It is time-consuming, and up until now, available documentation procedures have not been able to overcome this type of EHR limitations. Thus, entering information into EHR still has remained a challenge. In this study, by applying the trigram language model, we presented a method to predict the next words while typing free texts. It is hypothesized that using this system may save typing time of free text. The words prediction model introduced in this research was trained and tested on the free texts regarding to colonoscopy, transesophageal echocardiogram, and anterior-cervical-decompression. Required time of typing for each of the above-mentioned reports calculated and compared with manual typing of the same words. It is revealed that 33.36% reduction in typing time and 73.53% reduction in keystroke. The designed system reduced the time of typing free text which might be an approach for EHRs improvement in terms of documentation.
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http://dx.doi.org/10.1007/s13755-019-0065-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6395458PMC
December 2019

Modification of the Conventional Influenza Epidemic Models Using Environmental Parameters in Iran.

Healthc Inform Res 2019 Jan 31;25(1):27-32. Epub 2019 Jan 31.

Department of Health Information Management, School of Allied Medical Sciences, Lorestan University of Medical Sciences, Khorramabad, Iran.

Objectives: The association between the spread of infectious diseases and climate parameters has been widely studied in recent decades. In this paper, we formulate, exploit, and compare three variations of the susceptible-infected-recovered (SIR) model incorporating climate data. The SIR model is a well-studied model to investigate the dynamics of influenza viruses; however, the improved versions of the classic model have been developed by introducing external factors into the model.

Methods: The modification models are derived by multiplying a linear combination of three complementary factors, namely, temperature (T), precipitation (P), and humidity (H) by the transmission rate. The performance of these proposed models is evaluated against the standard model for two outbreak seasons.

Results: The values of the root-mean-square error (RMSE) and the Akaike information criterion (AIC) improved as they declined from 8.76 to 7.05 and from 98.12 to 93.01 for season 2013/14, respectively. Similarly, for season 2014/15, the RMSE and AIC decreased from 8.10 to 6.45 and from 117.73 to 107.91, respectively. The estimated values of () in the framework of the standard and modified SIR models are also compared.

Conclusions: Through simulations, we determined that among the studied environmental factors, precipitation showed the strongest correlation with the transmission dynamics of influenza. Moreover, the SIR+P+T model is the most efficient for simulating the behavioral dynamics of influenza in the area of interest.
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http://dx.doi.org/10.4258/hir.2019.25.1.27DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372465PMC
January 2019

Management of Computerized Cognitive Training Programs in Children with ADHD: The Effective Role of Decision Support Systems.

Iran J Public Health 2018 Oct;47(10):1611-1612

Dept. of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6277720PMC
October 2018

Study of challenges to utilise mobile-based health care monitoring systems: A descriptive literature review.

J Telemed Telecare 2018 Dec;24(10):661-668

1 Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Mobile health encompasses remote and wireless applications to provide health services. Despite the advantages of applying mobile-based monitoring systems, there are challenges and limitations; understanding the challenges may assist in identifying available solutions and optimising decision-making to apply mHealth technologies more practically. This study aimed to investigate the main challenges related to mHealth-based systems for health monitoring purposes. This review was carried out through investigation of English evidence from four databases, including Scopus, PubMed, Embase, and Web of Science, using a defined search strategy from 2013 to 2017. Two independent researchers reviewed the results based on PRISMA guidelines, and data was categorised using a bottom-up approach to reach a framework for the most general challenges. Among the 105 papers obtained, eight works were selected. The revealed challenges were categorised into six main branches across a tree (with 55 nodes, four levels) including user-related, infrastructure, process, management, resource and training challenges. Identifying the resolvable and preventable challenges, such as those related to training, design might play a crucial role in preventing loss of resources and in growing the success rate of a project, particularly if considered in national level projects.
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http://dx.doi.org/10.1177/1357633X18804747DOI Listing
December 2018

Prevalence of Stroke Risk Factors and Their Distribution Based on Stroke Subtypes in Gorgan: A Retrospective Hospital-Based Study-2015-2016.

Neurol Res Int 2018 26;2018:2709654. Epub 2018 Jul 26.

Information Technology for Translational Medicine, L-4362 Esch-sur-Alzette, Luxembourg, Luxembourg.

Background: Stroke is a leading cause of death and disability worldwide. According to the Iranian Ministry of Medical Health and Education, out of 100,000 stroke incidents in the country, 25,000 lead to death. Thus, identifying risk factors of stroke can help healthcare providers to establish prevention strategies. This study was conducted to investigate the prevalence of stroke risk factors and their distribution based on stroke subtypes in Sayad Shirazi Hospital, Gorgan, Northeastern Iran.

Material And Methods: A retrospective hospital-based study was conducted at Sayad Shirazi Hospital in Gorgan, the only referral university hospital for stroke patients in Gorgan city. All medical records with a diagnosis of stroke were identified based on the International Classification of Diseases, Revision 10, from August 23, 2015, to August 22, 2016. A valid and reliable data gathering form was used to capture data about demographics, diagnostics, lifestyle, risk factors, and medical history.

Results: Out of 375 cases, two-thirds were marked with ischemic stroke with mean ages (standard deviation) of 66.4 (14.2) for men and 64.6 (14.2) for women. The relationship between stroke subtypes and age groups (P=0.008) and hospital outcome (P=0.0001) was significant. Multiple regression analysis showed that hypertension (Exp. (B) =1.755, P=0.037), diabetes mellitus (Exp. (B) =0.532, P=0.021), and dyslipidemia (Exp. (B) =2.325, P=0.004) significantly increased the risk of ischemic stroke.

Conclusion: Overall, hypertension, diabetes mellitus, and dyslipidemia were the major risk factors of stroke in Gorgan. Establishment of stroke registry (population- or hospital-based) for the province is recommended.
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http://dx.doi.org/10.1155/2018/2709654DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6083549PMC
July 2018

Forecasting zoonotic cutaneous leishmaniasis using meteorological factors in eastern Fars province, Iran: a SARIMA analysis.

Trop Med Int Health 2018 08 11;23(8):860-869. Epub 2018 Jun 11.

Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

Objectives: To predict the occurrence of zoonotic cutaneous leishmaniasis (ZCL) and evaluate the effect of climatic variables on disease incidence in the east of Fars province, Iran using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model.

Methods: The Box-Jenkins approach was applied to fit the SARIMA model for ZCL incidence from 2004 to 2015. Then the model was used to predict the number of ZCL cases for the year 2016. Finally, we assessed the relation of meteorological variables (rainfall, rainy days, temperature, hours of sunshine and relative humidity) with ZCL incidence.

Results: SARIMA(2,0,0) (2,1,0)12 was the preferred model for predicting ZCL incidence in the east of Fars province (validation Root Mean Square Error, RMSE = 0.27). It showed that ZCL incidence in a given month can be estimated by the number of cases occurring 1 and 2 months, as well as 12 and 24 months earlier. The predictive power of SARIMA models was improved by the inclusion of rainfall at a lag of 2 months (β = -0.02), rainy days at a lag of 2 months (β = -0.09) and relative humidity at a lag of 8 months (β = 0.13) as external regressors (P-values < 0.05). The latter was the best climatic variable for predicting ZCL cases (validation RMSE = 0.26).

Conclusions: Time series models can be useful tools to predict the trend of ZCL in Fars province, Iran; thus, they can be used in the planning of public health programmes. Introducing meteorological variables into the models may improve their precision.
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http://dx.doi.org/10.1111/tmi.13079DOI Listing
August 2018

Criteria for assessing the quality of mHealth apps: a systematic review.

J Am Med Inform Assoc 2018 08;25(8):1089-1098

Research and Development Department, DMD Santé, Paris, France.

Objective: Review the existing studies including an assessment tool/method to assess the quality of mHealth apps; extract their criteria; and provide a classification of the collected criteria.

Methods: In accordance with the PRISMA statement, a literature search was conducted in MEDLINE, EMBase, ISI and Scopus for English language citations published from January 1, 2008 to December 22, 2016 for studies including tools or methods for quality assessment of mHealth apps. Two researchers screened the titles and abstracts of all retrieved citations against the inclusion and exclusion criteria. The full text of relevant papers was then individually examined by the same researchers. A senior researcher resolved eventual disagreements and confirmed the relevance of all included papers. The authors, date of publication, subject fields of target mHealth apps, development method, and assessment criteria were extracted from each paper. The extracted assessment criteria were then reviewed, compared, and classified by an expert panel of two medical informatics specialists and two health information management specialists.

Results: Twenty-three papers were included in the review. Thirty-eight main classes of assessment criteria were identified. These were reorganized by expert panel into 7 main classes (Design, Information/Content, Usability, Functionality, Ethical Issues, Security and Privacy, and User-perceived value) with 37 sub-classes of criteria.

Conclusions: There is a wide heterogeneity in assessment criteria for mHealth apps. It is necessary to define the exact meanings and degree of distinctness of each criterion. This will help to improve the existing tools and may lead to achieve a better comprehensive mHealth app assessment tool.
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http://dx.doi.org/10.1093/jamia/ocy050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646896PMC
August 2018

Predicting Length of Stay in Intensive Care Units after Cardiac Surgery: Comparison of Artificial Neural Networks and Adaptive Neuro-fuzzy System.

Healthc Inform Res 2018 Apr 30;24(2):109-117. Epub 2018 Apr 30.

Department of Health Services Management, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.

Objectives: Accurate prediction of patients' length of stay is highly important. This study compared the performance of artificial neural network and adaptive neuro-fuzzy system algorithms to predict patients' length of stay in intensive care units (ICU) after cardiac surgery.

Methods: A cross-sectional, analytical, and applied study was conducted. The required data were collected from 311 cardiac patients admitted to intensive care units after surgery at three hospitals of Shiraz, Iran, through a non-random convenience sampling method during the second quarter of 2016. Following the initial processing of influential factors, models were created and evaluated.

Results: The results showed that the adaptive neuro-fuzzy algorithm (with mean squared error [MSE] = 7 and R = 0.88) resulted in the creation of a more precise model than the artificial neural network (with MSE = 21 and R = 0.60).

Conclusions: The adaptive neuro-fuzzy algorithm produces a more accurate model as it applies both the capabilities of a neural network architecture and experts' knowledge as a hybrid algorithm. It identifies nonlinear components, yielding remarkable results for prediction the length of stay, which is a useful calculation output to support ICU management, enabling higher quality of administration and cost reduction.
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http://dx.doi.org/10.4258/hir.2018.24.2.109DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5944185PMC
April 2018

The Framework of NICU-discharge Plan System for Preterm Infants in Iran: Duties, Components and Capabilities.

Acta Inform Med 2018 ;26(1):46-50

Department of Health Information Management, School Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Introduction: The development of comprehensive discharge plan system Not only, will facilitate the discharge process, increase staff and parent satisfaction, improve the care of preterm infants, also reduce the human error.

Aim: to determine duties, components and capabilities of NICU discharge plan system as a multidimensional tool for facilitating the complex process of transition preterm infants to the home and support parents for post-discharge care.

Method: The descriptive and qualitative study conducted in 2017. Firstly by literature review, components of framework were determined in 38 statements under 3 major themes: duties, components, and capabilities and then related questionnaire was provided. Cronbach's alpha test was used to assess the reliability of the questionnaire. The result was more than 0.82 for all statements of questionnaire. The validity of the instrument was determined based on concepts in the valid scientific texts and comments of experts. The analysis was performed using SPSS software.

Result: In overall, 29 experts participated in the consensus process. In the duties section, all of the statements reach more than 50% consensus. Among statements of the components and capabilities consensus was achieved in 12 out of 17, 12 out of 16 statements respectively.

Conclusion: according to survey, checkout infant readiness determined as the main duty of the system. Alarm message for special examination before discharge and parent readiness checklist considered as the most important components. The ability to send alarm message, register and log in system were the key capabilities of the discharge system.
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http://dx.doi.org/10.5455/aim.2018.26.46-50DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5869233PMC
January 2018

Preconceived Stakeholders' Attitude Toward Telepathology: Implications for Successful Implementation.

J Pathol Inform 2017 19;8:50. Epub 2017 Dec 19.

Department of Health Information Technology, Urmia University of Medical Sciences, Urmia, Iran.

Introduction: Telepathology is a subdiscipline of telemedicine. It has opened new horizons to pathology, especially to the field of organizing consultations. This study aims to determine the capabilities and equipment required for the implementation of telepathology from the viewpoints of managers, IT professionals, and pathologists of the hospitals of West Azerbaijan, Iran.

Methods: This is a descriptive-analytical study conducted as a cross-sectional study in 2015. All public and private hospitals of West Azerbaijan were selected as the study sites. The population of the study was the managers, directors, pathologists, and IT professionals of the hospitals. The study population was considered as the study sample. Data were collected using questionnaires. The validity and reliability of the questionnaires were assessed, and data were analyzed using SPSS (Statistical Product and Services Solutions, version 16.0, SPSS Inc, Chicago, IL, USA).

Results: The mean awareness of the study population of telepathology in the studied hospitals was 2.43 with a standard deviation of 0.89. According to analysis results ( = 7.211 and = 0.001), in the studied hospitals, the mean awareness of pathologists, managers, directors, and IT professionals' of telepathology is significant. In addition, the mean awareness of pathologists is higher than that of managers, directors, and IT professionals, and this relation is significant ( = 0.001). According to IT professionals, among the influential dimensions of the implementation of telepathology in the studied hospitals, the effect of all dimensions, except hardware capabilities, was above moderate level.

Conclusion: According to our findings, stakeholders believe that the implementation of telepathology promotes the quality of health-care services and caring patients on the one hand and decreases health-care costs on the other hand. Therefore, it crucial and important to consider users' viewpoints into the process of implementing such systems as they play a vital role in the success or failure, and the accurate estimation of required sources, of the systems.
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http://dx.doi.org/10.4103/jpi.jpi_59_17DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5760844PMC
December 2017

Systematic Review of Data Mining Applications in Patient-Centered Mobile-Based Information Systems.

Healthc Inform Res 2017 Oct 31;23(4):262-270. Epub 2017 Oct 31.

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Objectives: Smartphones represent a promising technology for patient-centered healthcare. It is claimed that data mining techniques have improved mobile apps to address patients' needs at subgroup and individual levels. This study reviewed the current literature regarding data mining applications in patient-centered mobile-based information systems.

Methods: We systematically searched PubMed, Scopus, and Web of Science for original studies reported from 2014 to 2016. After screening 226 records at the title/abstract level, the full texts of 92 relevant papers were retrieved and checked against inclusion criteria. Finally, 30 papers were included in this study and reviewed.

Results: Data mining techniques have been reported in development of mobile health apps for three main purposes: data analysis for follow-up and monitoring, early diagnosis and detection for screening purpose, classification/prediction of outcomes, and risk calculation (n = 27); data collection (n = 3); and provision of recommendations (n = 2). The most accurate and frequently applied data mining method was support vector machine; however, decision tree has shown superior performance to enhance mobile apps applied for patients' self-management.

Conclusions: Embedded data-mining-based feature in mobile apps, such as case detection, prediction/classification, risk estimation, or collection of patient data, particularly during self-management, would save, apply, and analyze patient data during and after care. More intelligent methods, such as artificial neural networks, fuzzy logic, and genetic algorithms, and even the hybrid methods may result in more patients-centered recommendations, providing education, guidance, alerts, and awareness of personalized output.
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http://dx.doi.org/10.4258/hir.2017.23.4.262DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5688025PMC
October 2017

Item Selection and Content Validity of the Risk Factors of Post-Intubation Tracheal Stenosis Observation Questionnaire for ICU-Admitted Patients.

Tanaffos 2017 ;16(1):22-33

Tracheal Diseases Research Center (TDRC), National Research Institute of Tuberculosis and Lung disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Background: Laryngotracheal stenosis as a late complication of prolonged endotracheal intubation is a life-threatening event. In order to determine the related risk factors for this complication, which may vary among different countries, designing a valid questionnaire is necessary. The aim of this study was to select the items and evaluate the face and content validities of a questionnaire developed for assessment of risk factors of post-intubation tracheal stenosis (PITS) in patients admitted in the intensive care unit.

Materials And Methods: A mixed method study design was used in four steps in 2015, i.e., 1) a literature review, 2) focus groups with five experts in the field, 3) consultations with intensive care unit (ICU) specialists and thoracic surgeons, and 4) evaluation of content and face validity with 15 experts in a scientific panel using two self-administered questionnaires. Content validity index (CVI) was computed for individual items as well as the overall scale.

Results: We extracted the items from different sources of information. An initial version of the 52-item questionnaire was developed and classified into four domains including patient characteristics, intubation features, equipment-drugs, and complications. The items with an excellent modified kappa were included in the questionnaire. Five questions received more criticism instead of support and were removed (Item-CVI<0.55, fair modified kappa). The ones with an Item-CVI > 0.60 and a good modified kappa were revised, merged, or retained. The new 43-item questionnaire found a scale-level CVI, averaging (Scale-CVI/Ave) of 0.91.

Conclusion: The PITS risk factors questionnaire was developed and validated through item selection, expert opinions, and content validity index.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5473379PMC
January 2017