Evaluation of a skin self examination attitude scale using an item response theory model approach

Introduction The Skin Self-Examination Attitude Scale (SSEAS) is a brief measure that allows for the assessment of attitudes in relation to skin self-examination. This study evaluated the psychometric properties of the SSEAS using Item Response Theory (IRT) methods in a large sample of men ≥ 50 years in Queensland, Australia. Methods A sample of 831 men (420 intervention and 411 control) completed a telephone assessment at the 13-month follow-up of a randomized-controlled trial of a video-based intervention to improve skin self-examination (SSE) behaviour. Descriptive statistics (mean, standard deviation, item–total correlations, and Cronbach’s alpha) were compiled and difficulty parameters were computed with Winsteps using the polytomous Rasch Rating Scale Model (RRSM). An item person (Wright) map of the SSEAS was examined for content coverage and item targeting. Results The SSEAS have good psychometric properties including good internal consistency (Cronbach’s alpha = 0.80), fit with the model and no evidence for differential item functioning (DIF) due to experimental trial grouping was detected. Conclusions The present study confirms the SSEA scale as a brief, useful and reliable tool for assessing attitudes towards skin self-examination in a population of men 50 years or older in Queensland, Australia. The 8-item scale shows unidimensionality, allowing levels of SSE attitude, and the item difficulties, to be ranked on a single continuous scale. In terms of clinical practice, it is very important to assess skin cancer self-examination attitude to identify people who may need a more extensive intervention to allow early detection of skin cancer.

Digital literacy in theory, policy and practice: Old concerns, new opportunities

The increasing ubiquity and use of digital technologies across social and cultural life is a key challenge for educators engaged in helping students develop a range of literacies useful for school and beyond. Many young people's experience of communication and participation is now shaped by almost constant engagements with digital technologies and media, as well as with global digital cultures. This increasing access and use has given many young people the opportunity to engage deeply with global media cultures via popular music, television and film franchises, the worldwide computer games industry, or countless other subcultures that connect fans and interested others from around the world via the internet. 'Digital literacy' is often the term associated with the ability to traverse these, and other, online and offline worlds; the notion has long been synonymous with the idea that digital technologies now mediate perhaps a majority of our social interactions. These forms of engagement with the world have important implications for educators and school systems which have historically recognised only a very narrow set of legitimate literacies.

“It’s in the syllabus”: Identifying information literacy and data information literacy opportunities using a grounded theory approach

Developing innovative library services requires a real world understanding of faculty members' desired curricular goals. This study aimed to develop a comprehensive and deeper understanding of Purdue's nutrition science and political science faculties' expectations for student learning related to information and data information literacies. Course syllabi were examined using grounded theory techniques that allowed us to identify how faculty were addressing information and data information literacies in their courses, but it also enabled us to understand the interconnectedness of these literacies to other departmental intentions for student learning, such as developing a professional identity or learning to conduct original research. The holistic understanding developed through this research provides the necessary information for designing and suggesting information literacy and data information literacy services to departmental faculty in ways supportive of curricular learning outcomes.

Corporate Social Responsibility Assurance: Theory, Regulations and Practice in China

This chapter aims to provide a comprehensive understanding of the theory, regulations and practice of corporate social responsibility (CSR) assurance in China. Built on stakeholder and related theories, it employs a demand-and-supply analytical framework to illustrate the development and current status of China’s CSR assurance market. It finds that government agencies, stock exchanges, accounting standard setters and industrial associations have collectively shaped the current regulatory framework on CSR reporting and assurance in China. Regarding demand, differences in the social and legal environments across such a large country influence the regional development of CSR assurance. Industries under intensive CSR regulations and/or social reporting pressure—for example, the finance, aviation and mining industries—more actively achieve CSR report assurance. Regarding supply, the CSR assurance market in China is shared by accounting firms and professional certification bodies. Different assurance standards adopted by the two streams of assurance providers have different foci, potentially leading to different assurance coverage and emphases.

Smarten up! Applying market design theory to housing supply

PROBLEM Cost of delivering medium density apartments impedes supply of new and more affordable housing in established suburbs EXISTING FOCUS - Planning controls - Construction costs, esp labour - Regulation eg sustainability

Early stopping by using stochastic curtailment in a three-arm sequential trial

Summary. Interim analysis is important in a large clinical trial for ethical and cost considerations. Sometimes, an interim analysis needs to be performed at an earlier than planned time point. In that case, methods using stochastic curtailment are useful in examining the data for early stopping while controlling the inflation of type I and type II errors. We consider a three-arm randomized study of treatments to reduce perioperative blood loss following major surgery. Owing to slow accrual, an unplanned interim analysis was required by the study team to determine whether the study should be continued. We distinguish two different cases: when all treatments are under direct comparison and when one of the treatments is a control. We used simulations to study the operating characteristics of five different stochastic curtailment methods. We also considered the influence of timing of the interim analyses on the type I error and power of the test. We found that the type I error and power between the different methods can be quite different. The analysis for the perioperative blood loss trial was carried out at approximately a quarter of the planned sample size. We found that there is little evidence that the active treatments are better than a placebo and recommended closure of the trial.

A Bayesian decision approach for sample size determination in phase II trials

Stallard (1998, Biometrics 54, 279-294) recently used Bayesian decision theory for sample-size determination in phase II trials. His design maximizes the expected financial gains in the development of a new treatment. However, it results in a very high probability (0.65) of recommending an ineffective treatment for phase III testing. On the other hand, the expected gain using his design is more than 10 times that of a design that tightly controls the false positive error (Thall and Simon, 1994, Biometrics 50, 337-349). Stallard's design maximizes the expected gain per phase II trial, but it does not maximize the rate of gain or total gain for a fixed length of time because the rate of gain depends on the proportion: of treatments forwarding to the phase III study. We suggest maximizing the rate of gain, and the resulting optimal one-stage design becomes twice as efficient as Stallard's one-stage design. Furthermore, the new design has a probability of only 0.12 of passing an ineffective treatment to phase III study.

4th International Workshop on Theory and Application of Visualizations and Human-centric Aspects in Processes

This is the fourth TAProViz workshop being run at the 13th International Conference on Business Process Management (BPM). The intention this year is to consolidate on the results of the previous successful workshops by further developing this important topic, identifying the key research topics of interest to the BPM visualization community. Towards this goal, the workshop topics were extended to human computer interaction and related domains. Submitted papers were evaluated by at least three program committee members, in a double blind manner, on the basis of significance, originality, technical quality and exposition. Three full and one position papers were accepted for presentation at the workshop. In addition, we invited a keynote speaker, Jakob Pinggera, a postdoctoral researcher at the Business Process Management Research Cluster at the University of Innsbruck, Austria.

Quantifying progressive anterior overgrowth in the thoracic vertebrae of adolescent idiopathic scoliosis patients

Study design Anterior and posterior vertebral body heights were measured from sequential MRI scans of adolescent idiopathic scoliosis (AIS) patients and healthy controls. Objective To measure changes in vertebral body height over time during scoliosis progression to assess how vertebral body height discrepancies change during growth. Summary of background data Relative anterior overgrowth has been proposed as a potential driver for AIS initiation and progression. This theory proposes that the anterior column grows faster, and the posterior column slower, in AIS patients when compared to healthy controls. There is disagreement in the literature as to whether the anterior vertebral body heights are proportionally greater than posterior vertebral body heights in AIS patients when compared to healthy controls. To some extent, these discrepancies may be attributed to methodological differences. Methods MRI scans of the major curve of 21 AIS patients (mean age 12.5 ± 1.4 years, mean Cobb 32.2 ± 12.8º) and between T4 and T12 of 21 healthy adolescents (mean age 12.1 ± 0.5 years) were captured for this study. Of the 21 AIS patients, 14 had a second scan on average 10.8 ± 4.7 months after the first. Anterior and posterior vertebral body heights were measured from the true sagittal plane of each vertebra such that anterior overgrowth could be quantified. Results The difference between anterior and posterior vertebral body height in healthy, non-scoliotic children was significantly greater than in AIS patients with mild to moderate scoliosis. However there was no significant relationship between the overall anterior-posterior vertebral body height difference in AIS and either severity of the curve or its progression over time. Conclusions Whilst AIS patients have a proportionally longer anterior column than non-scoliotic controls, the degree of anterior overgrowth was not related to the rate of progression or the severity of the scoliotic curve.

A thermometer for interdependence: Exploring patterns of interdependence using networks of affordances

Interdependence is a central concept in systems and organizations, yet our methods for measuring it are not well developed. Here, we report on a novel method for transforming digital trace data into networks of events that can be used to visualize and measure interdependence. The edges in the network represent sequential flow and the vertices represent actors, actions and artifacts. We refer to this representation as an affordance network. As with conventional approaches such as process mining, our method uses input from a stream of time-stamped occurrences, but the representation is simpler and more appropriate for exploration and theory building. As digital trace data becomes more widely available, this method may become more useful in information systems research and practice. Like a thermometer, it helps us measure a basic property of a system that would otherwise be difficult to see.

The development of a guideline of care for patients with a Sengstaken-Blakemore Tube insitu in a general Intensive Care Unit using translational change theory

Aims & Objectives - identify and diagnose the current problems associated with patient care with regard to the nursing management of patients with Sengstaken-Blakemore tubes insitu; - Identify current nursing practice currently in place within the ICU and the hospital; identify the method by which the assessment and provision of nursing care is delivered in the ICU

Multi-Hypotheses Tracking using the Dempster–Shafer Theory, application to ambiguous road context

This paper presents a Multi-Hypotheses Tracking (MHT) approach that allows solving ambiguities that arise with previous methods of associating targets and tracks within a highly volatile vehicular environment. The previous approach based on the Dempster–Shafer Theory assumes that associations between tracks and targets are unique; this was shown to allow the formation of ghost tracks when there was too much ambiguity or conflict for the system to take a meaningful decision. The MHT algorithm described in this paper removes this uniqueness condition, allowing the system to include ambiguity and even to prevent making any decision if available data are poor. We provide a general introduction to the Dempster–Shafer Theory and present the previously used approach. Then, we explain our MHT mechanism and provide evidence of its increased performance in reducing the amount of ghost tracks and false positive processed by the tracking system.

A theory of process modelling affordances

This thesis studies how conceptual process models - that is, graphical documentations of an organisation's business processes - can enable and constrain the actions of their users. The results from case study and experiment indicate that model design decisions and people's characteristics influence how these opportunities for action are perceived and acted upon in practice.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

Stress and Resilience in Combat-Related PTSD: Integration of Psychological Theory and Biological Mechanisms

Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder that has a major impact on the ability to function effectively in daily life. PTSD may develop as a response to exposure to an event or events perceived as potentially harmful or life-threatening. It has high prevalence rates in the community, especially among vulnerable groups such as military personnel or those in emergency services. Despite extensive research in this field, the underlying mechanisms of the disorder remain largely unknown. The identification of risk factors for PTSD has posed a particular challenge as there can be delays in onset of the disorder, and most people who are exposed to traumatic events will not meet diagnostic criteria for PTSD. With the advent of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM V), the classification for PTSD has changed from an anxiety disorder into the category of stress- and trauma-related disorders. This has the potential to refocus PTSD research on the nature of stress and the stress response relationship. This review focuses on some of the important findings from psychological and biological research based on early models of stress and resilience. Improving our understanding of PTSD by investigating both genetic and psychological risk and coping factors that influence stress response, as well as their interaction, may provide a basis for more effective and earlier intervention.