Personality, personnel selection, and job performance

Job Performance: The term job performance can either refer to the objective or subjective outcomes one achieves in a specific job (e.g., the profit of a sales persons, the number of publications of a scientist, the number of successful operations of a surgeon) or to work-related activities (e.g., writing an article, conducting specific surgical acts). In the majority of research on this topic, job performance as an outcome is used. Personnel selection: Personnel selection refers to the process of selecting the best employees for specific jobs. Introduction One major application of personality research is in the area of personnel selection. The key question in this area is to which extent personality can predict how well a candidate will perform on the job he or she is applying for. Most scholars in this area acknowledge that personality has predictive validity for job performance. In line with this, personality assessment is part of the selection procedure in many organizations

Historical Research Approaches to the Analysis of Internationalisation

Historical research methods and approaches can improve understanding of the most appropriate techniques to confront data and test theories in internationalisation research. A critical analysis of all “texts” (sources), time series analyses, comparative methods across time periods and space, counterfactual analysis and the examination of outliers are shown to have the potential to improve research practices. Examples and applications are shown in these key areas of research with special reference to internationalisation processes. Examination of these methods allows us to see internationalisation processes as a sequenced set of decisions in time and space, path dependent to some extent but subject to managerial discretion. Internationalisation process research can benefit from the use of historical research methods in analysis of sources, production of time-lines, using comparative evidence across time and space and in the examination of feasible alternative choices

Losartan therapy in adults with Marfan syndrome: study protocol of the multi-center randomized controlled COMPARE trial

Contains fulltext : 87305.pdf (publisher's version ) (Open Access

Modelling Patient Behaviour Using IoT Sensor Data: a Case Study to Evaluate Techniques for Modelling Domestic Behaviour in Recovery from Total Hip Replacement Surgery

The UK health service sees around 160,000 total hip or knee replacements every year and this number is expected to rise with an ageing population. Expectations of surgical outcomes are changing alongside demographic trends, whilst aftercare may be fractured as a result of resource limitations. Conventional assessments of health outcomes must evolve to keep up with these changing trends. Health outcomes may be assessed largely by self-report using Patient Reported Outcome Measures (PROMs), such as the Oxford Hip or Oxford Knee Score, in the months up to and following surgery. Though widely used, many PROMs have methodological limitations and there is debate about how to interpret results and definitions of clinically meaningful change. With the development of a home-monitoring system, there is opportunity to characterise the relationship between PROMs and behaviour in a natural setting and to develop methods of passive monitoring of outcome and recovery after surgery. In this paper, we discuss the motivation and technology used in long-term continuous observation of movement, sleep and domestic routine for healthcare applications, such as the HEmiSPHERE project for hip and knee replacement patients. In this case study, we evaluate trends evident in data of two patients, collected over a 3-month observation period post-surgery, by comparison with scores from PROMs for sleep and movement quality, and by comparison with a third control home. We find that accelerometer and indoor localisation data correctly highlight long-term trends in sleep and movement quality and can be used to predict sleep and wake times and measure sleep and wake routine variance over time, whilst indoor localisation provides context for the domestic routine and mobility of the patient. Finally, we discuss a visual method of sharing findings with healthcare professionals

Impaired Vascular Contractility and Aortic Wall Degeneration in Fibulin-4 Deficient Mice: Effect of Angiotensin II Type 1 (AT1) Receptor Blockade

Medial degeneration is a key feature of aneurysm disease and aortic dissection. In a murine aneurysm model we investigated the structural and functional characteristics of aortic wall degeneration in adult fibulin-4 deficient mice and the potential therapeutic role of the angiotensin (Ang) II type 1 (AT1) receptor antagonist losartan in preventing aortic media degeneration. Adult mice with 2-fold (heterozygous Fibulin-4+/R) and 4-fold (homozygous Fibulin-4R/R) reduced expression of fibulin-4 displayed the histological features of cystic media degeneration as found in patients with aneurysm or dissection, including elastin fiber fragmentation, loss of smooth muscle cells, and deposition of ground substance in the extracellular matrix of the aortic media. The aortic contractile capacity, determined by isometric force measurements, was diminished, and was associated with dysregulation of contractile genes as shown by aortic transcriptome analysis. These structural and functional alterations were accompanied by upregulation of TGF-β signaling in aortas from fibulin-4 deficient mice, as identified by genome-scaled network analysis as well as by immunohistochemical staining for phosphorylated Smad2, an intracellular mediator of TGF-β. Tissue levels of Ang II, a regulator of TGF-β signaling, were increased. Prenatal treatment with the AT1 receptor antagonist losartan, which blunts TGF-β signaling, prevented elastic fiber fragmentation in the aortic media of newborn Fibulin-4R/R mice. Postnatal losartan treatment reduced haemodynamic stress and improved lifespan of homozygous knockdown fibulin-4 animals, but did not affect aortic vessel wall structure. In conclusion, the AT1 receptor blocker losartan can prevent aortic media degeneration in a non-Marfan syndrome aneurysm mouse model. In established aortic aneurysms, losartan does not affect aortic architecture, but does improve survival. These findings may extend the potential therapeutic application of inhibitors of the renin-angiotensin system to the preventive treatment of aneurysm disease

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases