The Experts below are selected from a list of 122517 Experts worldwide ranked by ideXlab platform
Egon Kuster - One of the best experts on this subject based on the ideXlab platform.
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Joint Warrior Interoperability Demonstration (JWID) Web Data Collection Tool (WDCT) User Guide
2004Co-Authors: Egon KusterAbstract:Abstract : This user guide describes the functionality of the Joint Warrior Interoperability Demonstration (JWID) Web Data Collection Tool (WDCT). The WDCT is an online assessment Collection Tool, which can be used to capture analysis information form users who are testing technical demonstrations. Essentially, the WDCT provides the analysis team with a Tool for presenting and managing online questionnaire and analysis gathering. The WDCT provided a mechanism for collecting large amounts of analysis information about demonstrations over a geographically dispersed area with only a small amount of effort on the part of the analyst. This user guide describes the functionality of the WDCT and how to use the system.
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Joint Warrior Interoperability Demonstration (JWID) Web Data Collection Tool (WDCT) Installation Manual
2003Co-Authors: Egon KusterAbstract:Abstract : The Web Data Collection Tool (WDCT) allows for the Collection of demonstration assessment information from geographically disperse locations. This installation manual provides the WDCT administrator with instructions on how to install and configure the WDCT software. The WDCT in the past has been used for the assessment of JWID (Joint Warrior Interoperability Demonstration) and the CINC21 (Commander in Chief for the 21st Century) ACTD (Advanced Concept Technology Demonstrator). WDCT is a web-based Tool that connects to an Oracle Database to store its analysis information and configuration settings. Over the past few years that the WDCT has been used within JWID it has proven to be a valuable Tool in eliciting feedback from the warfighters using the demonstrations being assessed.
Ommolbanin Abbasnezhad - One of the best experts on this subject based on the ideXlab platform.
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development content validity and application feasibility of the Data Collection Tool for forensic section in iranian integrated road traffic injury registry irtir
Journal of Injury and Violence Research, 2019Co-Authors: Bahram Samadirad, Abdolrazagh Barzegar, Fereidun Ashrafian Bonab, Homayun Sadedeghi Bazargani, Artin Kamali, Ommolbanin AbbasnezhadAbstract:Background: The present study was conducted as part of the national project on developing Integrated Road Traffic Registry (IRTIR). The aim of this study was to develop and assess application feasibility and content validity of Data Collection Tool for forensic section in IRTIR. Methods: Data Collection Tools were developed by information retrieved from literature review as well as the current Tool used for traffic fatalities in Forensic Medicine Organization (FMO) and discussion in expert panel. For assessment of content validity, 15 experts in various fields of expertise such as forensic medicine, emergency medicine and neurosurgery, expressed their ideas and gave comments along with scoring the items on relevance, clarity, necessity and feasibility. The Content validity was calculated by the content validity index (CVI) and modified KAPPA. In order to evaluate the application feasibility of the Tool, the information for ten traffic fatal cases were collected by forensic medicine specialists using the developed Tool. Results: The content validity of the Data Collection Tool was confirmed after two rounds of assessment and improvement. It also was found to be feasible for use in forensic investigations. According to the CVI and modified kappa value above 0.87 for all items. The final Tool included in various areas of etiologic and prevention-related information. Conclusion: The present Data Collection Tool for fatal road traffic accidents was more complete and accurate than the current Data Collection Tool and was confirmed to be a valid Tool and suitable to be used in the Iranian Integrated Road Traffic Injury Registry and similar settings.
Bahram Samadirad - One of the best experts on this subject based on the ideXlab platform.
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development content validity and application feasibility of the Data Collection Tool for forensic section in iranian integrated road traffic injury registry irtir
Journal of Injury and Violence Research, 2019Co-Authors: Bahram Samadirad, Abdolrazagh Barzegar, Fereidun Ashrafian Bonab, Homayun Sadedeghi Bazargani, Artin Kamali, Ommolbanin AbbasnezhadAbstract:Background: The present study was conducted as part of the national project on developing Integrated Road Traffic Registry (IRTIR). The aim of this study was to develop and assess application feasibility and content validity of Data Collection Tool for forensic section in IRTIR. Methods: Data Collection Tools were developed by information retrieved from literature review as well as the current Tool used for traffic fatalities in Forensic Medicine Organization (FMO) and discussion in expert panel. For assessment of content validity, 15 experts in various fields of expertise such as forensic medicine, emergency medicine and neurosurgery, expressed their ideas and gave comments along with scoring the items on relevance, clarity, necessity and feasibility. The Content validity was calculated by the content validity index (CVI) and modified KAPPA. In order to evaluate the application feasibility of the Tool, the information for ten traffic fatal cases were collected by forensic medicine specialists using the developed Tool. Results: The content validity of the Data Collection Tool was confirmed after two rounds of assessment and improvement. It also was found to be feasible for use in forensic investigations. According to the CVI and modified kappa value above 0.87 for all items. The final Tool included in various areas of etiologic and prevention-related information. Conclusion: The present Data Collection Tool for fatal road traffic accidents was more complete and accurate than the current Data Collection Tool and was confirmed to be a valid Tool and suitable to be used in the Iranian Integrated Road Traffic Injury Registry and similar settings.
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Development and psychometric evaluation of Data Collection Tools for Iranian integrated road traffic injury registry: Registrar-station Data Collection Tool
Archives of trauma research, 2019Co-Authors: Homayoun Sadeghi-bazargani, Soudabeh Marin, Faramarz Pourasghar, Alireza Moghisi, Bahram Samadirad, Mashyaneh Haddadi, Davoud Khorasani-zavarehAbstract:Background: Comprehensive and accurate Data are fundamentally needed for effective management of road traffic injuries (RTIs). Existing sources of RTI reports have a huge underestimation and inaccuracy at some levels. The aim of this study was to develop and validate the registrar-station Data Collection Tool as a part of the Iranian Integrated Road Traffic Injury Registry (IRTIR). Materials and Methods: This study was conducted in Tabriz University of Medical Sciences in 2018. A Data Collection Tool was developed to be used by the registrar for inpatient section of IRTIR by information retrieved from the literature review and road traffic experts' need assessment. The content validity of the preliminary Tool was assessed. The feasibility of the Tool was tested in two regional referral injury hospitals. Intra- and inter-rater reliability of the Tool was evaluated using the individual/absolute intra-class correlation coefficient (ICC) and Kappa. Validity was revisited after 1 year of the pilot study. Results: The registrar-station Data Collection Tool of IRTIR included 53 items, in five categories. Content validity was approved (modified content validity index was 0.8-1 and content validity ratio was one for all items). ICC was >0.6 for all items, and kappa index ranged between 0.69 and 0.92. The nurse Data Collection Tool of IRTIR was applicable in the pilot phase. Conclusions: The Registrar-Station Data Collection Tool of IRTIR was confirmed as a valid and reliable Tool for inpatient traffic injuries as a part of the Iranian IRTIR.
Hugo Gamboa - One of the best experts on this subject based on the ideXlab platform.
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Latent: A Flexible Data Collection Tool to Research Human Behavior in the Context of Web Navigation
IEEE Access, 2019Co-Authors: Catia Cepeda, Ricardo Tonet, Daniel Noronha Osorio, Hugo P. Silva, Edouard Battegay, Marcus Cheetham, Hugo GamboaAbstract:Internet usage has grown dramatically since the early years of its inception. The rich field of Data provided by internet users in interaction with digital media content can provide insight into web-based navigation behavior and underlying psychological dimensions. Human-computer interaction in the web is an underutilized source of Data for understanding human online behavior. While researchers and usability testing services do use these sources to analyze human behavior and user experience, access to the diverse range of other potentially useful Data available during web-based interaction for research is limited. In this paper, we propose a novel Tool in the form of a web browser extension, referred to as Latent, which can be used to simultaneously capture information from different sources while users interact with digital content. The Data acquisition capabilities of Latent makes it suitable for various research purposes, ranging from studies of usability to decision-making and personality. A particular advantage of Latent is that the method and control of Data acquisition is completely transparent to the user. We present the architecture of the web browser extension, describe the Data that can be acquired, and report on the residual impact of the Tool on the user's computer processing resources.
Bo Norrving - One of the best experts on this subject based on the ideXlab platform.
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the stroke riskometer tm app validation of a Data Collection Tool and stroke risk predictor
International Journal of Stroke, 2015Co-Authors: Priya Parmar, Rita Krishnamurthi, Arfan M Ikram, Albert Hofman, Saira Saeed Mirza, Yury Varakin, Michael Kravchenko, M A Piradov, Amanda G Thrift, Bo NorrvingAbstract:BackgroundThe greatest potential to reduce the burden of stroke is by primary prevention of first-ever stroke, which constitutes three quarters of all stroke. In addition to population-wide prevention strategies (the mass' approach), the high risk' approach aims to identify individuals at risk of stroke and to modify their risk factors, and risk, accordingly. Current methods of assessing and modifying stroke risk are difficult to access and implement by the general population, amongst whom most future strokes will arise. To help reduce the burden of stroke on individuals and the population a new app, the Stroke Riskometer(TM), has been developed. We aim to explore the validity of the app for predicting the risk of stroke compared with current best methods. Methods752 stroke outcomes from a sample of 9501 individuals across three countries (New Zealand, Russia and the Netherlands) were utilized to investigate the performance of a novel stroke risk prediction Tool algorithm (Stroke Riskometer(TM)) compared with two established stroke risk score prediction algorithms (Framingham Stroke Risk Score [FSRS] and QStroke). We calculated the receiver operating characteristics (ROC) curves and area under the ROC curve (AUROC) with 95% confidence intervals, Harrels C-statistic and D-statistics for measure of discrimination, R-2 statistics to indicate level of variability accounted for by each prediction algorithm, the Hosmer-Lemeshow statistic for calibration, and the sensitivity and specificity of each algorithm. ResultsThe Stroke Riskometer(TM) performed well against the FSRS five-year AUROC for both males (FSRS=750% (95% CI 723%-776%), Stroke Riskometer(TM)=740(95% CI 713%-767%) and females [FSRS=703% (95% CI 679%-728%, Stroke Riskometer(TM)=715% (95% CI 690%-739%)], and better than QStroke [males - 597% (95% CI 573%-620%) and comparable to females=711% (95% CI 690%-731%)]. Discriminative ability of all algorithms was low (C-statistic ranging from 051-056, D-statistic ranging from 001-012). Hosmer-Lemeshow illustrated that all of the predicted risk scores were not well calibrated with the observed event Data (P<0006). ConclusionsThe Stroke Riskometer(TM) is comparable in performance for stroke prediction with FSRS and QStroke. All three algorithms performed equally poorly in predicting stroke events. The Stroke Riskometer(TM) will be continually developed and validated to address the need to improve the current stroke risk scoring systems to more accurately predict stroke, particularly by identifying robust ethnic/race ethnicity group and country specific risk factors. (Less)
