The utility and challenges of using ICD codes in child maltreatment research : a review of existing literature

Objective: The objectives of this article are to explore the extent to which the International Statistical Classification of Diseases and Related Health Problems (ICD) has been used in child abuse research, to describe how the ICD system has been applied and to assess factors affecting the reliability of ICD coded data in child abuse research.----- Methods: PubMed, CINAHL, PsychInfo and Google Scholar were searched for peer reviewed articles written since 1989 that used ICD as the classification system to identify cases and research child abuse using health databases. Snowballing strategies were also employed by searching the bibliographies of retrieved references to identify relevant associated articles. The papers identified through the search were independently screened by two authors for inclusion, resulting in 47 studies selected for the review. Due to heterogeneity of studies metaanalysis was not performed.----- Results: This paper highlights both utility and limitations of ICD coded data. ICD codes have been widely used to conduct research into child maltreatment in health data systems. The codes appear to be used primarily to determine child maltreatment patterns within identified diagnoses or to identify child maltreatment cases for research.----- Conclusions: A significant impediment to the use of ICD codes in child maltreatment research is the under-ascertainment of child maltreatment by using coded data alone. This is most clearly identified and, to some degree, quantified, in research where data linkage is used. Practice Implications: The importance of improved child maltreatment identification will assist in identifying risk factors and creating programs that can prevent and treat child maltreatment and assist in meeting reporting obligations under the CRC.

Recruiting older adults to health research studies : a systematic review

Objective: To provide a systematic review of papers comparing the effectiveness of different strategies to recruit older adults (aged 50 years and over) to participate in health research studies, to guide successful recruitment in future research. Methods: Four major databases were searched for papers published between 1995 and 2008 with: target group aged 50 years or over; participants allocated to receive one of two or more recruitment strategies; and an outcome measure of response rate or enrolment in study. Results: Twelve papers were included in the review. Conclusion: For postal questionnaires, recruitment strategies used with older adults had comparable outcomes to those used to recruit from the general population. For other types of studies, strategies involving face-to-face contact may be more effective than indirect methods, but this needs to be balanced against feasibility. Overall, little evidence on the topic exists and more rigorous investigation is necessary.

The effective and the evocative : reflecting on practice-led research approaches in art and design

Early in the practice-led research debate, Steven Scrivener (2000, 2002) identified some general differences in the approach of artists and designers undertaking postgraduate research. His distinctions centered on the role of the artefact in problem-based research (associated with design) and creative-production research (associated with artistic practice). Nonetheless, in broader discussions on practice-led research, 'art and design' often continues to be conflated within a single term. In particular, marked differences between art and design methodologies, theoretical framing, research goals and research claims have been underestimated. This paper revisits Scrivener's work and establishes further distinctions between art and design research. It is informed by our own experiences of postgraduate supervision and research methods training, and an empirical study of over sixty postgraduate, practice-led projects completed at the Creative Industries Faculty of QUT between 2002 and 2008. Our reflections have led us to propose that artists and designers work with differing research goals (the evocative and the effective, respectively), which are played out in the questions asked, the creative process, the role of the artefact and the way new knowledge is evidenced. Of course, research projects will have their own idiosyncrasies but, we argue, marking out the poles at each end of the spectrum of art and design provides useful insights for postgraduate candidates, supervisors and methodologists alike.

How relevant is tourism research

One of the definitions of the term myth is ‘an unproved or false collective belief that is used to justify a social institution’ (see http://dictionary.reference.com/browse/myth). Before we are criticized for suggesting such an irreverent thought might apply to tourism academia, readers must recognize that organizations and industries often operate using shared collective myths (see Meyer and Rowan 1977). Institutionalized rules and processes function as myths that provide legitimacy. The question of interest in this paper is not in the context of the quality of tourism academic research output, which is addressed by other papers in this research probe section. Rather, of importance is enhancing understanding of the extent to which our collective knowledge, legitimized through publishing in peer reviewed academic publications, is proving of value to industry stakeholders, an axiom that appears to be largely unquestioned and unproven.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Scheduling trains as a blocking parallel-machine job shop scheduling problem

In this paper, the train scheduling problem is modelled as a blocking parallel-machine job shop scheduling (BPMJSS) problem. In the model, trains, single-track sections and multiple-track sections, respectively, are synonymous with jobs, single machines and parallel machines, and an operation is regarded as the movement/traversal of a train across a section. Due to the lack of buffer space, the real-life case should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold the train until next section on the routing becomes available. Based on literature review and our analysis, it is very hard to find a feasible complete schedule directly for BPMJSS problems. Firstly, a parallel-machine job-shop-scheduling (PMJSS) problem is solved by an improved shifting bottleneck procedure (SBP) algorithm without considering blocking conditions. Inspired by the proposed SBP algorithm, feasibility satisfaction procedure (FSP) algorithm is developed to solve and analyse the BPMJSS problem, by an alternative graph model that is an extension of the classical disjunctive graph models. The proposed algorithms have been implemented and validated using real-world data from Queensland Rail. Sensitivity analysis has been applied by considering train length, upgrading track sections, increasing train speed and changing bottleneck sections. The outcomes show that the proposed methodology would be a very useful tool for the real-life train scheduling problems

Assessing information systems success models : empirical comparison (Research in Progress)

Information System (IS) success may be the most arguable and important dependent variable in the IS field. The purpose of the present study is to address IS success by empirically assess and compare DeLone and McLean’s (1992) and Gable’s et al. (2008) models of IS success in Australian Universities context. The two models have some commonalities and several important distinctions. Both models integrate and interrelate multiple dimensions of IS success. Hence, it would be useful to compare the models to see which is superior; as it is not clear how IS researchers should respond to this controversy.

The importance of a new kind of learning in collaborative networks

There is wide agreement that in order to manage the increasingly complex and uncertain tasks of business, government and community, organizations can no longer operate in supreme isolation, but must develop a more networked approach. Networks are not ‘business as usual’. Of particular note is what has been referred to as collaborative networks. Collaborative networks now constitute a significant part of our institutional infrastructure. A key driver for the proliferation of these multiorganizational arrangements is their ability to facilitate the learning and knowledge necessary to survive or to respond to increasingly complex social issues In this regard the emphasis is on the importance of learning in networks. Learning applies to networks in two different ways. These refer to the kinds of learning that occur as part of the interactive processes of networks. This paper looks at the importance of these two kinds of learning in collaborative networks. The first kind of learning relates to networks as learning networks or communities of practice. In learning networks people exchange ideas with each other and bring back this new knowledge for use in their own organizations. The second type of learning is referred to as network learning. Network learning refers to how people in collaborative networks learn new ways of communicating and behaving with each other. Network learning has been described as transformational in terms of leading to major systems changes and innovation. In order to be effective, all networks need to be involved as learning networks; however, collaborative networks must also be involved in network learning to be effective. In addition to these two kinds of learning in collaborative networks this paper also focuses on the importance of how we learn about collaborative networks. Maximizing the benefits of working through collaborative networks is dependent on understanding their unique characteristics and how this impacts on their operation. This requires a new look at how we specifically teach about collaborative networks and how this is similar to and/or different from how we currently teach about interorgnizational relations.

Airports in their urban settings : towards a conceptual model of interfaces in the Australian context

In Australia, airports have emerged as important sub-regional activity centres and now pose challenges for both airport operation and planning in the surrounding urban and regional environment. The changing nature of airports in their metropolitan context and the emergence of new pressures and problems require the introduction of a fresh conceptual framework to assist the better understanding of these complex roles and spatial interactions. The approach draws upon the meta-concept of interfaces of an ‘airport metropolis’ as an organising device consisting of four main domains: economic development, land use,infrastructure, and governance. The paper uses the framework to further discuss airport and regional interactions and highlights the use of sustainability criteria to operationalise the model. The approach aims to move research and practice beyond the traditionally compartmentalised analysis of airport issues and policy-making by highlighting interdependencies between airports and regions.

The impact of “empirical facts” on legal scholarship and legal research training

Lawyers have traditionally viewed law as a closed system, and doctrinal research has been the research methodology used most widely in the profession. This reflects traditional concepts of legal reasoning. There is a wealth of reliable and valid social science data available to lawyers and judges. Judges in fact often refer to general facts about the world, society, institutions and human behaviour (‘empirical facts’). Legal education needs to prepare our students for this broader legal context. This paper examines how ‘empirical facts’ are used in Australian and other common law courts. Specifically, the paper argues that there is a need for enhanced training in non-doctrinal research methodologies across the law school curriculum. This should encompass a broad introduction to social science methods, with more attention being paid to a cross-section of methodologies such as content analysis, comparative law and surveys that are best applied to law.

Emergency department surge capacity : Recommendations of the Australasian surge strategy working group

Background For more than a decade emergency medicine organizations have produced guidelines, training and leadership for disaster management. However to date, there have been limited guidelines for emergency physicians needing to provide a rapid response to a surge in demand. The aim of this study is to identify strategies which may guide surge management in the Emergency Department. Method A working group of individuals experienced in disaster medicine from the Australasian College for Emergency Medicine Disaster Medicine Subcommittee (the Australasian Surge Strategy Working Group) was established to undertake this work. The Working Group used a modified Delphi technique to examine response actions in surge situations. The Working Group identified underlying assumptions from epidemiological and empirical understanding and then identified remedial strategies from literature and from personal experience and collated these within domains of space, staff, supplies, and system operation. Findings These recommendations detail 22 potential actions available to an emergency physician working in the context of surge. The Working Group also provides detailed guidance on surge recognition, triage, patient flow through the emergency department and clinical goals and practices. Discussion These strategies provide guidance to emergency physicians confronting the challenges of a surge in demand. The paper also identifies areas that merit future research including the measurement of surge capacity, constraints to strategy implementation, validation of surge strategies and measurement of strategy impacts on throughput, cost, and quality of care.

Reciprocity : where art meets the community : action research in response to artistic encounters and relationships

This practice-led research project examines some of the factors and issues facing artists working in the public domain who wish to engage with the community as audience. Using the methodology of action research, the three major creative projects in this study use art as a socio-political tool with the aim of providing an effective vehicle for broadening awareness, understanding forms of social protest and increasing tolerance for diversity. The three projects: Floodline November 7, 2004, Look in, Look out, and The Urban Terrorist Project, dealt with issues of marginalisation of communities, audiences and graffiti artists respectively. The artist/researcher is outlined as both creator and collaborator in the work. Processes included ephemeral elements, such as temporary installation and performance, as well as interactive elements that encouraged direct audience involvement as part of the work. In addition to the roles of creator and collaborator, both of which included audience as well as artist, the presence of an outside entity was evident. Whether local, legal authorities or prevailing attitudes, outside entities had an unavoidable impact on the processes and outcomes of the work. Each project elicited a range of responses from their respective audiences; however, the overarching concept of reciprocity was seen to be the crucial factor in conception, artistic methods and outcomes.

Remote interaction and user research : anaesthetic preadmission activity

In the absence of telehealth technology, rural patients must travel to a regional or metropolitan hospital for a preadmission consultation one week before their surgery. Currently, examination of the patient’s chest using a stethoscope (auscultation) is not possible over a telehealth network as existing digital stethoscopes have been designed for in-person auscultation. We report on the initial phase of research which ultimately aims to design a digital stethoscope for use in the telehealth context. This initial research phase describes the complexity of the activity of preadmission clinics and the implications for the design of the stethoscope. The research is conducted through field studies of existing face-to-face and remote consultations.