Fatigue self-management behaviors in patients with advanced cancer: A prospective longitudinal survey

Purpose: To explore the fatigue self-management behaviors and factors associated with effectiveness of these behaviors in patients with advanced cancer. Design: Prospective longitudinal interviewer-administered survey. Setting: A tertiary cancer center in Queensland Australia. Sample: One hundred fifty two outpatients with metastatic breast, lung, colorectal and prostate cancer experiencing fatigue (>3/10) were recruited. Main Research Variables: Fatigue self-management behaviors outcomes (perceived effectiveness, self-efficacy and frequency), medical/demographic characteristics (including sites of primary cancer and metastasis, comorbidity, performance status), social support, depressive, anxiety, and other symptoms were assessed. Findings: The participants reported moderate levels of fatigue at baseline (M=5.85, SD 1.44), and maintained moderate levels at 4 weeks and 8 weeks. On average, participants consistently used approximately nine behaviors at each time point. Factors significantly associated with higher levels of perceived effectiveness of fatigue self-management behaviors were higher self-efficacy (p<.001), higher education level (p=.02), and lower levels of depressive symptoms (p=.04). Conclusions: The findings of this study demonstrate that patients with cancer, even with advanced disease, still want and are able to use a number of behaviors to control their fatigue. Self-management interventions that aim to enhance self-efficacy and address any concurrent depressive symptoms have the potential to reduce fatigue severity. Implications for Nursing: Nurses are well positioned to play a key role in supporting patients in their fatigue self-management. Knowledge Translation: This study particularly focused on the perspectives of patients about fatigue self-management, highlighting a number of issues requiring further attention in clinical practice and the potential for future research.

User centred design for engineering e-government web usability

E-government provides a platform for governments to implement web enabled services that facilitate communication between citizens and the government. However, technology driven design approach and limited understanding of citizens' requirements, have led to a number of critical usability problems on the government websites. Hitherto, there has been no systematic attempt to analyse the way in which theory of User Centred Design (UCD) can contribute to address the usability issues of government websites. This research seeks to fill this gap by synthesising perspectives drawn from the study of User Centred Design and examining them based on the empirical data derived from case study of the Scottish Executive website. The research employs a qualitative approach in the collection and analysis of data. The triangulated analysis of the findings reveals that e-government web designers take commercial development approach and focus only on technical implementations which lead to websites that do not meet citizens' expectations. The research identifies that e-government practitioners can overcome web usability issues by transferring the theory of UCD to practice.

Making usability affordable in the design of e-government services: User-centred design for public sector websites

E-government provides a platform for governments to implement web-enabled services that facilitate communication between citizens and the government. However, technology-driven design approach and limited understanding of citizens' requirements have led to a number of critical usability problems on the government websites. Hitherto, there has been no systematic attempt to analyse the way in which theory of User-Centred Design (UCD) can contribute to address the usability issues of government websites. This research seeks to fill this gap by synthesising perspectives drawn from the study of UCD and examining them based on the empirical data derived from case study of the Scottish Executive (SE) website. The research employs a qualitative approach in the collection and analysis of data. The triangulated analysis of the findings reveals that e-government web designers take commercial development approach and focus only on technical implementations, which lead to websites that do not meet citizens' expectations. The research identifies that e-government practitioners can overcome web usability issues by transferring the theory of UCD to practice. © Copyright 2010 Inderscience Enterprises Ltd.

Tracking brand positioning for an emerging destination: 2003 to 2015

Few published studies have monitored destination brand image over time. This temporal aspect is an important gap in the literature, given consensus around the role perceptions play in consumers’ decision making, and the ensuing emphasis on imagery in destination branding collateral. Whereas most destination image studies have been a snapshot of perceptions at one point in time, this paper presents findings from a survey implemented four times between 2003 and 2015. Brand image is the core construct in modelling destination branding performance, which has emerged as a relatively new field of research in the past decade. Using the consumer-based brand equity (CBBE) hierarchy, the project has benchmarked and monitored destination brand salience, image and resonance for an emerging regional destination, relative to key competitors, in the domestic Australian market; and the survey instrument has been demonstrated to be reliable in the context of short break holidays by car. What is particularly interesting to date is there has been relatively little change in the market positions of the five destinations, in spite of over a decade of marketing communications by the regional tourism organisations and their stakeholders, and more recently the mass of user-generated travel content on social media. The project didn’t analyse the actual marketing communications for each of the DMOs. Therefore an important implication is that irrespective of the level of marketing undertaken the DMOs seem to have had little control over the perceptions held in their largest market during this time period. Therefore it must be recognised any improvement in perceptions will likely take a long period of time, and so branding needs to be underpinned by a philosophy of a long term financial investment as well as commitment to a consistency of message over time; which given the politics of DMO decision making represents a considerable challenge.

How do Australian podiatrists manage patients with diabetes The Australian diabetic foot management survey

Background Diabetic foot complications are the leading cause of lower extremity amputation and diabetes-related hospitalisation in Australia. Studies demonstrate significant reductions in amputations and hospitalisation when health professionals implement best practice management. Whilst other nations have surveyed health professionals on specific diabetic foot management, to the best of the authors’ knowledge this appears not to have occurred in Australia. The primary aim of this study was to examine Australian podiatrists’ diabetic foot management compared with best practice recommendations by the Australian National Health Medical Research Council. Methods A 36-item Australian Diabetic Foot Management survey, employing seven-point Likert scales (0 = Never; 7 = Always) to measure multiple aspects of best practice diabetic foot management was developed. The survey was briefly tested for face and content validity. The survey was electronically distributed to Australian podiatrists via professional associations. Demographics including sex, years treating patients with diabetes, employment-sector and patient numbers were also collected. Chi-squared and Mann Whitney U tests were used to test differences between sub-groups. Results Three hundred and eleven podiatrists responded; 222 (71%) were female, 158 (51%) from the public sector and 11–15 years median experience. Participants reported treating a median of 21–30 diabetes patients each week, including 1–5 with foot ulcers. Overall, participants registered median scores of at least “very often” (>6) in their use of most items covering best practice diabetic foot management. Notable exceptions were: “never” (1 (1 – 3)) using total contact casting, “sometimes” (4 (2 – 5)) performing an ankle brachial index, “sometimes” (4 (1 – 6)) using University of Texas Wound Classification System, and “sometimes” (4 (3 – 6) referring to specialist multi-disciplinary foot teams. Public sector podiatrists reported higher use or access on all those items compared to private sector podiatrists (p < 0.01). Conclusions This study provides the first baseline information on Australian podiatrists’ adherence to best practice diabetic foot guidelines. It appears podiatrists manage large caseloads of people with diabetes and are generally implementing best practice guidelines recommendations with some notable exceptions. Further studies are required to identify barriers to implementing these recommendations to ensure all Australians with diabetes have access to best practice care to prevent amputations.

A survey and analysis of the GNSS spoofing threat and countermeasures

Detection and prevention of global network satellite system (GNSS) “spoofing” attacks, or the broadcast of false global navigation satellite system services, has recently attracted much research interest. This survey aims to fill three gaps in the literature: first, to assess in detail the exact nature of threat scenarios posed by spoofing against the most commonly cited targets; second, to investigate the many practical impediments, often underplayed, to carrying out GNSS spoofing attacks in the field; and third, to survey and assess the effectiveness of a wide range of proposed defences against GNSS spoofing. Our conclusion lists promising areas of future research.

Three-User Cognitive Channels with Cumulative Message Sharing: An Achievable Rate Region

In this paper, an achievable rate region for the three-user discrete memoryless interference channel with asymmetric transmitter cooperation is derived. The three-user channel facilitates different ways of message sharing between the transmitters. We introduce a manner of noncausal (genie aided) unidirectional message-sharing, which we term cumulative message sharing. We consider receivers with predetermined decoding capabilities, and define a cognitive interference channel. We then derive an achievable rate region for this channel by employing a coding scheme which is a combination of superposition and Gel'fand-Pinsker coding techniques.

Augmenting process elicitation with visual priming: An empirical exploration of user behaviour and modelling outcomes

Business process models have become an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach to process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions similarly to how they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. An empirical investigation comparing both the modelling outputs and participant behaviour of this virtual world role-play elicitor with an S-BPM process modelling tool found that while the modelling approaches of the two groups varied greatly, the virtual world elicitor may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

Understanding urban rail travel for improved patronage forecasting

Improved forecasting of urban rail patronage is essential for effective policy development and efficient planning for new rail infrastructure. Past modelling and forecasting of urban rail patronage has been based on legacy modelling approaches and often conducted at the general level of public transport demand, rather than being specific to urban rail. This project canvassed current Australian practice and international best practice to develop and estimate time series and cross-sectional models of rail patronage for Australian mainland state capital cities. This involved the implementation of a large online survey of rail riders and non-riders for each of the state capital cities, thereby resulting in a comprehensive database of respondent socio-economic profiles, travel experience, attitudes to rail and other modes of travel, together with stated preference responses to a wide range of urban travel scenarios. Estimation of the models provided a demonstration of their ability to provide information on the major influences on the urban rail travel decision. Rail fares, congestion and rail service supply all have a strong influence on rail patronage, while a number of less significant factors such as fuel price and access to a motor vehicle are also influential. Of note, too, is the relative homogeneity of rail user profiles across the state capitals. Rail users tended to have higher incomes and education levels. They are also younger and more likely to be in full-time employment than non-rail users. The project analysis reported here represents only a small proportion of what could be accomplished utilising the survey database. More comprehensive investigation was beyond the scope of the project and has been left for future work.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Designing for user engagement: The ALTC exchange for higher education

The Australasian Society for Computers in Learning in Tertiary Education (ascilite) has recently completed research to inform development of the ALTC Exchange, a new online service for learning and teaching in Australia. The research investigated resource identification and contribution, engagement with the repository and user community, and associated peer review and commentary processes. This article focuses on the data obtained and recommendations developed for engagement of potential end users. It reports a literature review and findings, including an international perspective on the ALTC Exchange, with specific focus on prospective user needs, contexts of use and policies necessary to facilitate engagement of the higher education sector with the ALTC Exchange

Towards a typology of hashtag publics: A large-scale comparative study of user engagement across trending topics

Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.