The elicitation of key performance indicators of e-government providers: A bottom-up approach

Copyright @ 2013 EMCIS.Delivering an adequate e-Government service (e-service) is becoming more of a necessity in today's digital world. In order to improve e-services and increase the engagement of both users' and providers' side, studies on the performance evaluation of such provided e-services are taking places. However a clear identification of the key performance indicators from the e-Government providers’ side is not well explored. This shortcoming hampers the conduct of a holistic evaluation of an e-service provision from the perspective of its stakeholders in order to improve e-services as well as to increase e-services take-ups. In this paper, a systematic process to identify indicators is implemented based on a bottom-up approach. The process used three focus-group meetings with providers, users, and academics in Qatar, Lebanon and UK to collect, identify and validate key indicators from the perspective of e-services’ providers. The approach resulted in the identification of five factors levels (service, technology, employees, policy and management and social responsibilities) with fifteen sub-categories of SMART variables. Hence, leading to the development of a new model, STEPS, that can fully explain and predict e-government success from the providers’ point of view. It will work as a strategic management tool to align various stakeholders on common goal and values based on evidence based evaluation of e-services using smart measurable indicators for the improvement of an e-service at the engagement level in the field of e-government. In addition, other fields can benefit from the outcome of this work, such as logistics service providers, who make their services available across new and existing relationships between the Internet commerce firms, their customers, and their vendors

Towards a culture-free model of the Big Five - a cross-cultural investigation of the Orpheus in four different language families

This thesis concerns the development of a practical and theoretical framework for adapting of questionnaires building on van de Vijver and Leung's (1997) Theory of Equivalence and Bias. In contrast to extant research which has largely concentrated on the adaptation of ability measures the present research was operationalised through adapting and translating Orpheus, a work-based Big Five personality questionnaire, into English, Arabic, Chinese (Mandarin) and Spanish. The first phase, 'Quality Control', used a mixed method technique in two studies. Study 1 (Translation and Monitoring) was qualitative and usedforward and back translation followed by dyads and triads. Results from this study (n = 10) reflected the importance of qualitative judgment techniques in test adaptation and showed the emergence of three main types of bias (linguistic, psychological, and conceptual), which were discussed in the literature review but do not constitute part of the Theory of Equivalence and Bias (van de Vijver & Leung, 1997). Study 2 (n = 185) (Pre-Testing) and Study 3 (n = 12) (Cognitive interview) combined quantitative (pre-test) and qualitative techniques (cognitive interviews). Results were inconclusive as to what extent p values or Cohen's d is better at detecting potential problems in adaptation of items. Cognitive interviews were shown to be effective for interpreting statistically significant results as they unravelled many linguistic, psychological, and cultural problems that went unnoticed in back translation dyads/triads. The second phase (,Field Pilot') was laid out over two studies that used the same data but focused on different statistical investigations. Study 4 (n=815) centred on item bias analysis using Logistic Regression as well as ANOVA and showed that 12 items in Arabic, 11 in Chinese and 3 in Spanish were functioning differently than the English version of the items. Study 4 examined the metric equivalence between the four groups using EF A and MG-CF A. Results showed that no model fits the data as it was. Intrinsic test problems and using criterion-related validity as a sole method of validation were identified as two potential causes of model failure

Ethical Priority of the Most Actionable System of Biomolecules: the Metabolome

The metabolome is a system of small biomolecules (metabolites) and a direct result of human bioculture. Consequently, metabolomics is well poised to impact anthropological and biomedical research for the foreseeable future. Overall, we provide a perspective on the ethical, legal, and social implications (ELSI) of metabolomics, which we argue are often more alarming than those of genomics. Given the current mechanisms to fund research, ELSI beyond human DNA is stifled and in need of considerable attention.This publication was primarily supported by the NIH (RM1 HG009042; R01 GM089886). Open Access fees paid for in whole or in part by the University of Oklahoma Libraries.Ye

Pharmacometabolomics reveals racial differences in response to atenolol treatment.

Antihypertensive drugs are among the most commonly prescribed drugs for chronic disease worldwide. The response to antihypertensive drugs varies substantially between individuals and important factors such as race that contribute to this heterogeneity are poorly understood. In this study we use metabolomics, a global biochemical approach to investigate biochemical changes induced by the beta-adrenergic receptor blocker atenolol in Caucasians and African Americans. Plasma from individuals treated with atenolol was collected at baseline (untreated) and after a 9 week treatment period and analyzed using a GC-TOF metabolomics platform. The metabolomic signature of atenolol exposure included saturated (palmitic), monounsaturated (oleic, palmitoleic) and polyunsaturated (arachidonic, linoleic) free fatty acids, which decreased in Caucasians after treatment but were not different in African Americans (p<0.0005, q<0.03). Similarly, the ketone body 3-hydroxybutyrate was significantly decreased in Caucasians by 33% (p<0.0001, q<0.0001) but was unchanged in African Americans. The contribution of genetic variation in genes that encode lipases to the racial differences in atenolol-induced changes in fatty acids was examined. SNP rs9652472 in LIPC was found to be associated with the change in oleic acid in Caucasians (p<0.0005) but not African Americans, whereas the PLA2G4C SNP rs7250148 associated with oleic acid change in African Americans (p<0.0001) but not Caucasians. Together, these data indicate that atenolol-induced changes in the metabolome are dependent on race and genotype. This study represents a first step of a pharmacometabolomic approach to phenotype patients with hypertension and gain mechanistic insights into racial variability in changes that occur with atenolol treatment, which may influence response to the drug

Pretreatment metabotype as a predictor of response to sertraline or placebo in depressed outpatients: a proof of concept

The purpose of this study was to determine whether the baseline metabolic profile (that is, metabotype) of a patient with major depressive disorder (MDD) would define how an individual will respond to treatment. Outpatients with MDD were randomly assigned to sertraline (up to 150 mg per day) (N=43) or placebo (N=46) in a double-blind 4-week trial. Baseline serum samples were profiled using the liquid chromatography electrochemical array; the output was digitized to create a ‘digital map' of the entire measurable response for a particular sample. Response was defined as ⩾50% reduction baseline to week 4 in the 17-item Hamilton Rating Scale for Depression total score. Models were built using the one-out method for cross-validation. Multivariate analyses showed that metabolic profiles partially separated responders and non-responders to sertraline or to placebo. For the sertraline models, the overall correct classification rate was 81% whereas it was 72% for the placebo models. Several pathways were implicated in separation of responders and non-responders on sertraline and on placebo including phenylalanine, tryptophan, purine and tocopherol. Dihydroxyphenylacetic acid, tocopherols and serotonin were common metabolites in separating responders and non-responders to both drug and placebo. Pretreatment metabotypes may predict which depressed patients will respond to acute treatment (4 weeks) with sertraline or placebo. Some pathways were informative for both treatments whereas other pathways were unique in predicting response to either sertraline or placebo. Metabolomics may inform the biochemical basis for the early efficacy of sertraline

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.Acknowledgments. S.C. thanks the FCT for the Ph.D. Grant SFRH/BD/ 80925/2011. The authors thank the FCT Strategic Project of UID/BIO/04469/2013 unit, the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and the project “BioInd - Biotechnology and Bioengineering for improved Industrial and Agro-Food processes”, REF. NORTE-07-0124-FEDER-000028 Co-funded by the Programa Operacional Regional do Norte (ON.2 - O Novo Norte), QREN, FEDER

Generation and quality control of lipidomics data for the alzheimers disease neuroimaging initiative cohort.

Alzheimers disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/

Metabolomics in Early Alzheimer's Disease: Identification of Altered Plasma Sphingolipidome Using Shotgun Lipidomics

The development of plasma biomarkers could facilitate early detection, risk assessment and therapeutic monitoring in Alzheimer's disease (AD). Alterations in ceramides and sphingomyelins have been postulated to play a role in amyloidogensis and inflammatory stress related neuronal apoptosis; however few studies have conducted a comprehensive analysis of the sphingolipidome in AD plasma using analytical platforms with accuracy, sensitivity and reproducibility.We prospectively analyzed plasma from 26 AD patients (mean MMSE 21) and 26 cognitively normal controls in a non-targeted approach using multi-dimensional mass spectrometry-based shotgun lipidomics to determine the levels of over 800 molecular species of lipids. These data were then correlated with diagnosis, apolipoprotein E4 genotype and cognitive performance. Plasma levels of species of sphingolipids were significantly altered in AD. Of the 33 sphingomyelin species tested, 8 molecular species, particularly those containing long aliphatic chains such as 22 and 24 carbon atoms, were significantly lower (p<0.05) in AD compared to controls. Levels of 2 ceramide species (N16:0 and N21:0) were significantly higher in AD (p<0.05) with a similar, but weaker, trend for 5 other species. Ratios of ceramide to sphingomyelin species containing identical fatty acyl chains differed significantly between AD patients and controls. MMSE scores were correlated with altered mass levels of both N20:2 SM and OH-N25:0 ceramides (p<0.004) though lipid abnormalities were observed in mild and moderate AD. Within AD subjects, there were also genotype specific differences.In this prospective study, we used a sensitive multimodality platform to identify and characterize an essentially uniform but opposite pattern of disruption in sphingomyelin and ceramide mass levels in AD plasma. Given the role of brain sphingolipids in neuronal function, our findings provide new insights into the AD sphingolipidome and the potential use of metabolomic signatures as peripheral biomarkers

Using Cognitive Interviewing for the Semantic Enhancement of Multi-Lingual Versions of Personality Questionnaires

We discuss the use of cognitive interviewing with bilinguals as an integral part of cross-cultural adaptation of personality questionnaires. The aim is to maximize semantic equivalence to increase the likelihood of items maintaining the intended structure and meaning in the target language. We refer to this part of adaptation as semantic enhancement, and integrate cognitive interviewing within it as a tool for scrutinizing translations, the connotative meaning, and the psychological impact of items across languages. During the adaptation of a work-based personality questionnaire from English to Arabic, Chinese (Mandarin), and Spanish, we cognitively interviewed 12 bilingual participants about 136 items in different languages (17% of all items), of which 67 were changed. A content analysis categorizing the reasons for amending items elicited eleven errors that affect two identified forms of semantic equivalence. We provide the resultant coding scheme as a framework for designing cognitive interviewing protocols and propose a procedure for implementing them. We discuss implications for theory and practic