Learning to drive with cognitive impairment : the experience of young ADHD diagnosed drivers and their parent supervisors

A subset of novice drivers exhibit executive function impairments which may adversely impact on the learn-to-drive period and subsequent driving experience, potentially explaining their overrepresentation in traffic offences and crashes. This paper presents the results of a qualitative analysis of a small series of in-depth semi-structured interviews undertaken individually with affected young drivers (n = 7) and each of their parent supervisors (n = 6). Young drivers were selected on the basis of their ADHD diagnosis, as a sample particularly affected by executive function impairments. Standardised rating scale measures confirmed the currency of the young drivers’ ADHD symptoms and executive function impairment. Results are discussed in terms of common experiences of the young affected drivers and those of their parents as supervising drivers of the learn-to-drive process and subsequent driving behaviour. Key themes included difficulties that were related to core executive function impairments symptomatic of ADHD. Themes also included common emotions that the young drivers associated with driving, with particular types of impact on their driving behaviour. Common strategies that were used by both the young driver and their parent during this learning process and their perceived effectiveness are also discussed. Those that were perceived to be most effective tended to focus on reducing the cognitive load for the young driver when introducing new information and skills.

The logic of ADHD : a brief review of fallacious reasoning

This paper has two central purposes: the first is to survey some of the more important examples of fallacious argument, and the second is to examine the frequent use of these fallacies in support of the psychological construct: Attention Deficit Hyperactivity Disorder (ADHD). The paper divides 12 familiar fallacies into three different categories—material, psychological and logical—and contends that advocates of ADHD often seem to employ these fallacies to support their position. It is suggested that all researchers, whether into ADHD or otherwise, need to pay much closer attention to the construction of their arguments if they are not to make truth claims unsupported by satisfactory evidence, form or logic.

Merging business process models

This paper addresses the following problem: given two or more business process models, create a process model that is the union of the process models given as input. In other words, the behavior of the produced process model should encompass that of the input models. The paper describes an algorithm that produces a single configurable process model from an arbitrary collection of process models. The algorithm works by extracting the common parts of the input process models, creating a single copy of them, and appending the differences as branches of configurable connectors. This way, the merged process model is kept as small as possible, while still capturing all the behavior of the input models. Moreover, analysts are able to trace back from which original model(s) does a given element in the merged model come from. The algorithm has been prototyped and tested against process models taken from several application domains.

Adjuvant use of nutritional and herbal medicines with antidepressants, mood stabilizers and benzodiazepines

Adjuvant use of nutritional and herbal medicines has potential to increase the efficacy of synthetic pharmaceuticals, and perhaps also decrease their side-effects by allowing lower doses to be prescribed. We evaluated current evidence for adjuvant use of nutritional and herbal medicines with antidepressants, mood stabilizers and benzodiazepines; and explored novel future areas of research. The paper also critiques current evidence for co-administration of St. John’s wort with synthetic antidepressants. We performed a systematic search of MEDLINE, CINAHL, PsycINFO, The Cochrane database, China National Knowledge Infrastructure and the Chinese Science Citation Database. Search results were supplemented by a review of reference lists and a forward search using the Web of Science. Where possible we calculated effect sizes. Encouraging evidence exists for the use of omega-3 fatty acids, SAMe, folic acid and l-tryptophan adjuvantly with antidepressants to enhance response and improve efficacy. Various nutrients also have emerging evidence as effective adjuncts with antipsychotics and mood stabilizers. While some evidence supports nutritional adjuvancy with various psychopharmacotherapies, adjuvant use of herbal therapies has not been sufficiently studied to warrant standard clinical application. This remains a promising area of research via robust, safety-conscious studies.

Clinical supervision in four mental health professions : a review of the evidence

Examines a range of theoretical issues and the empirical evidence relating to clinical supervision in 4 mental health professions: clinical psychology, occupational therapy, social work, and speech pathology. There is widespread acceptance of the value of supervision among practitioners and a large quantity of literature on the topic, but there is very little empirical evidence in this area. To date, there is insufficient evidence to demonstrate which styles of supervision are most beneficial for particular types of staff, in terms of their level of experience or learning style. The data suggest that directive forms of supervision, rather than unstructured approaches, are preferred by relatively inexperienced practitioners, and that experienced clinicians also value direct supervision methods when learning new skills or dealing with complex or crisis situations. The available evidence suggests that supervisors typically receive little training in supervision methods. However, there is little information to guide us as to the most effective ways of training supervisors. While acknowledging the urgent need for research, this paper concludes that supervision is likely to form a valuable component of professional development for mental health professionals.

Clinical significance of Mycobacterium asiaticum isolates in Queensland, Australia

Mycobacterium asiaticum was first reported as a cause of human disease in 1982, with only a few cases in the literature to date. This study aims to review the clinical significance of M. asiaticum isolates in Queensland, Australia. A retrospective review (1989 to 2008) of patients with M. asiaticum isolates was conducted. Data were collected through the Queensland TB Control Centre database. Disease was defined in accordance with the American Thoracic Society criteria. Twenty-four patients (13 female) had a positive culture of M. asiaticum, many residing around the Tropic of Capricorn. M. asiaticum was responsible for pulmonary disease (n = 2), childhood lymphadenitis (n = 1), olecranon bursitis (n = 1), 6 cases of possible pulmonary disease, and 2 possible wound infections. Chronic lung disease was a risk factor for pulmonary infection, and wounds/lacerations were a risk factor for extrapulmonary disease. Extrapulmonary disease responded to local measures. Pulmonary disease responded to ethambutol-isoniazid-rifampin plus pyrazinamide for the first 2 months in one patient, and amikacin-azithromycin-minocycline in another patient. While M. asiaticum is rare in Queensland, there appears to be an environmental niche. Although often a colonizer, it can be a cause of pulmonary and extrapulmonary disease. Treatment of pulmonary disease remains challenging. Extrapulmonary disease does not mandate specific nontuberculous mycobacterium (NTM) treatment.

Managing Process Model Complexity - Part I: Concrete Syntax

While Business Process Management (BPM) is an established discipline, the increased adoption of BPM technology in recent years has introduced new challenges. One challenge concerns dealing with process model complexity in order to improve the understanding of a process model by stakeholders and process analysts. Features for dealing with this complexity can be classified in two categories: 1) those that are solely concerned with the appearance of the model, and 2) those that in essence change the structure of the model. In this paper we focus on the former category and present a collection of patterns that generalize and conceptualize various existing features. The paper concludes with a detailed analysis of the degree of support of a number of state-of-the-art languages and language implementations for these patterns.

Improving the Traversal of Large Hierarchical Process Repositories

Business Process Management (BPM) has increased in popularity and maturity in recent years. Large enterprises engage use process management approaches to model, manage and refine repositories of process models that detail the whole enterprise. These process models can run to the thousands in number, and may contain large hierarchies of tasks and control structures that become cumbersome to maintain. Tools are therefore needed to effectively traverse this process model space in an efficient manner, otherwise the repositories remain hard to use, and thus are lowered in their effectiveness. In this paper we analyse a range of BPM tools for their effectiveness in handling large process models. We establish that the present set of commercial tools is lacking in key areas regarding visualisation of, and interaction with, large process models. We then present six tool functionalities for the development of advanced business process visualisation and interaction, presenting a design for a tool that will exploit the latest advances in 2D and 3D computer graphics to enable fast and efficient search, traversal and modification of process models.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

Emergency department triage revisited

Triage is a process that is critical to the effective management of modern emergency departments. Triage systems aim, not only to ensure clinical justice for the patient, but also to provide an effective tool for departmental organisation, monitoring and evaluation. Over the last 20 years, triage systems have been standardised in a number of countries and efforts made to ensure consistency of application. However, the ongoing crowding of emergency departments resulting from access block and increased demand has led to calls for a review of systems of triage. In addition, international variance in triage systems limits the capacity for benchmarking. The aim of this paper is to provide a critical review of the literature pertaining to emergency department triage in order to inform the direction for future research. While education, guidelines and algorithms have been shown to reduce triage variation, there remains significant inconsistency in triage assessment arising from the diversity of factors determining the urgency of any individual patient. It is timely to accept this diversity, what is agreed, and what may be agreeable. It is time to develop and test an International Triage Scale (ITS) which is supported by an international collaborative approach towards a triage research agenda. This agenda would seek to further develop application and moderating tools and to utilise the scales for international benchmarking and research programmes.

Continued use of process modeling grammars : the impact of individual difference factors

Process modeling grammars are used by analysts to describe information systems domains in terms of the business operations an organization is conducting. While prior research has examined the factors that lead to continued usage behavior, little knowledge has been established as to what extent characteristics of the users of process modeling grammars inform usage behavior. In this study, a theoretical model is advanced that incorporates determinants of continued usage behavior as well as key antecedent individual difference factors of the grammar users, such as modeling experience, modeling background and perceived grammar familiarity. Findings from a global survey of 529 grammar users support the hypothesized relationships of the model. The study offers three central contributions. First, it provides a validated theoretical model of post-adoptive modeling grammar usage intentions. Second, it discusses the effects of individual difference factors of grammar users in the context of modeling grammar usage. Third, it provides implications for research and practice.

A fuzzy neural network approach for contractor pre-qualification

Nonlinearity, uncertainty and subjectivity are the three predominant characteristics of contractors prequalification which cause the process more of an art than a scientific evaluation. A fuzzy neural network (FNN) model, amalgamating both the fuzzy set and neural network theories, has been developed aiming to improve the objectiveness of contractor prequalification. Through the FNN theory, the fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be transformed. Eighty-five cases with detailed decision criteria and rules for prequalifying Hong Kong civil engineering contractors were collected. These cases were used for training (calibrating) and testing the FNN model. The performance of the FNN model was compared with the original results produced by the prequalifiers and those generated by the general feedforward neural network (GFNN, i.e. a crisp neural network) approach. Contractor’s ranking orders, the model efficiency (R2) and the mean absolute percentage error (MAPE) were examined during the testing phase. These results indicate the applicability of the neural network approach for contractor prequalification and the benefits of the FNN model over the GFNN model. The FNN is a practical approach for modelling contractor prequalification.

A Conceptualisation of Courseware Development Process in Malaysian Educational Context

Multimedia-based learning has been accepted as an effective learning tool and has broadly prevailed in various types of education around the world. The Malaysian ministry of education has also adopted this information communication technology (ICT) as the means of an education reformation project called, ‘Smart School’ since 1998, aiming to improve all Malaysian Primary and Secondary students’ learning ability, attitudes, achievement, and further enhance teachers’ teaching performance. As a result, Malaysian Ministry of Education has distributed a number of interactive courseware of the key learning domains such as Mathematics, Science, Bahasa Melayu (Malay language), and English. According to recent reports by Malaysian Ministry of Education (MOE), however, the courseware has not been effectively used in schools, and many researchers point out there are vital issues concerning the interface and interaction design. Within this context, this paper presumes that one of the main reasons could derive from a structural aspect of the course development process that is devaluing or ignoring the importance of interface and interaction design. Therefore, it is imperative to conceptualise the courseware development process in terms of creating interactive and quality learning experiences through defining the stakeholders’ needs in terms of better learning and teaching. Within this context, this paper reviews the current development process and proposes a new concept called the interactive communication component which enables courseware developers to embed interactive and quality learning experiences into their courseware development process. The key objective is to provide opportunities to discuss the courseware development process from the different stakeholders’ perspectives of the educational courseware in a Malaysian context.

Clinical efficacy and safety of zoledronic acid in osteoporosis and Paget's disease

Osteoporosis and Paget’s bone disease are the most common diseases of the bone. In addition to glucocorticoid treatment, there are many other secondary causes of osteoporosis. Bisphosphonates are used to treat these bone conditions. Zoledronic acid is the most potent bisphosphonate at inhibiting bone resorption. In osteoporosis, zoledronic acid increases bone mineral density for at least 1 year following a single intravenous administration. The efficacy and safety of zoledronic acid in the treatment of osteoporosis and Paget’s bone disease are reviewed. This article also covers the studies of the effects of zoledronic acid in the bone loss associated with the secondary osteoporosis.

Clinical efficacy and safety of zoledronic acid in prostate and breast cancer

The anti-estrogen treatment for hormone-sensitive breast cancer and the androgen deprivation therapy for prostate cancer can lead to the development of osteoporosis and bone fractures. Metastases associated with prostate and breast cancer can also occur in bone. Bisphosphonates are used in these types of bone dysfunction. Zoledronic acid is the most potent bisphosphonate. In osteoporosis, zoledronic acid inhibits bone reabsorption and increases bone mineral density for at least a year after intravenous administration. The efficacy and safety of zoledronic acid in osteoporosis secondary to hormone-sensitive cancers (prostate and breast), and in the bone metastases associated with these cancers are reviewed.