Geekdom for Grrrls health : Australian undergraduate experiences developing and promoting women’s health in cyberspace

There is an increasing global reliance on the Internet for retrieving information on health, illness, and recovery (Sillence et al, 2007; Laurent et al, 2009; Adams, 2010). People suffering from a vast array of illnesses, conditions, and complaints, as well as healthy travelers seeking advice about safe practices abroad, and teens seeking information about safe sexual practices are all now more likely to go to the internet for information than they are to rely solely on a general practitioner or physician (Santor et al, 2007; Moreno et al, 2009; Bartlett et al, 2010). Women in particular seek advice and support online for a number of health-related concerns regarding issues such as puberty, conception, pregnancy, postnatal depression, mothering, breast-cancer recovery, and ageing healthily (van Zutphen, 2008; Raymond et al, 2005). In keeping with this increasing socio-technological trend, the Women’s Health Unit at the Queensland University of Technology (Q.U.T), Brisbane, Australia, introduced the research, design, and development of online information resources for issues affecting the health of Australian women as an assessment item for students in the undergraduate Public Health curriculum. Students were required to research a particular health issue affecting Australian women, including pregnancy, pregnancy terminations, postnatal depression, returning to the work force after having a baby, breast cancer recovery, chronic disease prevention, health and safety for sex-workers, and ageing healthily. Students were required to design and develop websites that supported people living with these conditions, or who were in these situations. The websites were designed for communicating effectively with both women seeking information about their health, and their health practitioners. The pedagogical challenge inherent in this exercise was twofold: firstly, to encourage students to develop the skills to design and maintain software for online health forums; and secondly, to challenge public health students to go beyond generating ‘awareness’ and imparting health information to developing a nuanced understanding of the worlds and perspectives of their audiences, who require supportive networks and options that resonate with their restrictions, capabilities, and dispositions. This latter challenge spanned the realms of research, communication, and aesthetic design. This paper firstly, discusses an increasing reliance on the Internet by women seeking health-related information and the potential health risks and benefits of this trend. Secondly, it applies a post-structural analysis of the de-centred and mobile female self, as online social ‘spaces’ and networks supersede geographical ‘places’ and hierarchies, with implications for democracy, equality, power, and ultimately women’s health. Thirdly, it depicts the processes (learning reflections) and products (developed websites) created within this Women’s Health Unit by the students. Finally, we review this development in the undergraduate curriculum in terms of the importance of providing students with skills in research, communication, and technology in order to share and implement improved health care and social marketing for women as both recipients and providers of health care in the Internet Age.

Ontologies derived from Wikipedia : a framework for comparison

Since its debut in 2001 Wikipedia has attracted the attention of many researchers in different fields. In recent years researchers in the area of ontology learning have realised the huge potential of Wikipedia as a source of semi-structured knowledge and several systems have used it as their main source of knowledge. However, the techniques used to extract semantic information vary greatly, as do the resulting ontologies. This paper introduces a framework to compare ontology learning systems that use Wikipedia as their main source of knowledge. Six prominent systems are compared and contrasted using the framework.

Deliberative assessment of surrogate consent in dementia research

Background Research involving incapacitated persons with dementia entails complex scientific, legal, and ethical issues, making traditional surveys of layperson views on the ethics of such research challenging. We therefore assessed the impact of democratic deliberation (DD), involving balanced, detailed education and peer deliberation, on the views of those responsible for persons with dementia. Methods One hundred and seventy-eight community-recruited caregivers or primary decision-makers for persons with dementia were randomly assigned to either an all-day DD session group or a control group. Educational materials used for the DD session were vetted for balance and accuracy by an interdisciplinary advisory panel. We assessed the acceptability of family-surrogate consent for dementia research (“surrogate-based research”) from a societal policy perspective as well as from the more personal perspectives of deciding for a loved one or for oneself (surrogate and self-perspectives), assessed at baseline, immediately post-DD session, and 1 month after DD date, for four research scenarios of varying risk-benefit profiles. Results At baseline, a majority in both the DD and control groups supported a policy of family consent for dementia research in all research scenarios. The support for a policy of family consent for surrogate-based research increased in the DD group, but not in the control group. The change in the DD group was maintained 1 month later. In the DD group, there were transient changes in attitudes from surrogate or self-perspectives. In the control group, there were no changes from baseline in attitude toward surrogate consent from any perspective. Conclusions Intensive, balanced, and accurate education, along with peer deliberation provided by democratic deliberation, led to a sustained increase in support for a societal policy of family consent in dementia research among those responsible for dementia patients.

Oxycodone or oxycodone plus paracetamol for acute postoperative pain in adults

In this short communication we wanted to find out what is the analgesic effect of single dose oral oxycodone, with or without the addition of paracetamol, for adults with postoperative pain? Oxycodone at doses of 5mg and above is an effective analgesia for patients with moderate to severe postoperative pain. The efficacy of oxycodone is increased with the addition of paracetamol. The use of oxycodone 10mg plus paracetamol 625mg can be considered for use in the pain relief protocol in post-operative settings. Clinicians should consider a range of factors before prescribing or administering oxycodone for acute post-operative pain, including but not limited to, individual patient clinical profile, adverse effects, cost and patient preference.

Cochrane review summary for cancer nursing : drug therapy for cancer-related fatigue

Cancer-related fatigue (CRF) is one of themost debilitating symptoms in patients with cancer. It is prevalent at the time of diagnosis and during and after antineoplastic treatment and in patients with advanced disease. The multifactorial and complex nature of CRF makes it challenging for health professionals to identify a clear underlying mechanism and manage this symptom effectively. Often, the management plan for CRF (whether pharmacological or nonpharmacological) can be further complicated by the coexistence of other symptoms. This systematic review1 is therefore important in informing health professionals on the effectiveness of pharmacological management for CRF.

A Two-stage information filtering based on rough decision rule and pattern mining

Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.

Towards a comprehensive model of driver aggression : a review of the literature and directions for the future

Driver aggression is a road safety issue of growing concern throughout most highly motorised countries, yet to date there is no comprehensive model that deals with this issue in the road safety area. This paper sets out to examine the current state of research and theory on aggressive driving with a view to incorporating useful developments in the area of human aggression from mainstream psychological research. As a first step, evidence regarding the prevalence and incidence of driver aggression, including the impact of the phenomenon on crash rates is reviewed. Inconsistencies in the definition and operationalisation of driver aggression that have hampered research in the area are noted. Existing models of driver aggression are then identified and the need to distinguish and address the role of intentionality as well as the purpose of perpetrating behaviours within both these and research efforts is highlighted. Drawing on recent findings from psychological research into general aggression, it is argued that progress in understanding driver aggression requires models that acknowledge not only the person-related and situational factors, but the cognitive and emotional appraisal processes involved in driver aggression. An effective model is expected to allow the explanation of not only the likelihood and severity of driver aggression behaviours, but also the escalation of incidents within the context of the road environment.

Early relational reasoning and the novice programmer : swapping as the “hello world” of relational reasoning

We report on a longitudinal research study of the development of novice programmers in their first semester of programming. In the third week, almost half of our sample of students could not answer an explain-in-plain-English question, for code consisting of just three assignment statements, which swapped the values in two variables. We regard code that swaps the values of two variables as the simplest case of where a programming student can manifest a SOLO relational response. Our results demonstrate that the problems many students face with understanding code can begin very early, on relatively trivial code. However, using traditional programming exercises, these problems often go undetected until late in the semester. New approaches are required to detect and fix these problems earlier.

A national roll out of an insufficiently evaluated practice : how evidence based are our end-of-life care policies?

There has been increasing international efforts to ensure that health care policies are evidence based. One area where there is a lack of ‘effectiveness’ evidence is in the use of end-of-life care pathways (EOLCP) (1). Despite the lack of evidence supporting the efficacy of the EOCLP, their use has been endorsed in the recent national palliative care strategy document in the UK (2). In addition, a publication endorsed by the Australian Government (titled: Supporting Australians to live well at the End of Life- National Palliative Care Strategy 2010) (3), recommended a national roll out of EOLCP across all sectors (primary, acute and aged care) in Australia. According to this document, it is a measure of “appropriateness” and “effectiveness” for promoting quality end-of-life care.

Work integrated learning : an industry partners’ perspective

In recent years the Australian tertiary education sector may be said to be undergoing a vocational transformation. Vocationalism, that is, an emphasis on learning directed at work related outcomes is increasingly shaping the nature of tertiary education. This paper reports some findings to date of a project that seeks to identify the key issues faced by students, industry and university partners engaged in the provision of WIL within an undergraduate program offered by the Creative Industries faculty of a major metropolitan university. Here, those findings are focussed on some of the motivations and concerns of the industry partners who make their workplaces available for student internships. Businesses are not universities and do not perceive of themselves as primarily learning institutions. However, their perspectives of work integrated learning and their contributions to it need to understand more fully at practical and conceptual levels of learning provision. This paper and the findings presented here suggest that the diversity of industry partner motivations and concerns contributing to WIL provision requires that universities understand and appreciate those partners as contributors with them to a culture of learning provision and support. These industry partner contribution need to be understood as valuing work as learning, not work as something that needs to be integrated with learning to make that learning more authentic and thereby more vocational.

'Which is the best Doctor Who story?' : a case study in value judgements outside the academy'

One of Cultural Studies' most important contributions to academic thinking about culture is the acceptance as axiomatic that we must not simply accept traditional value hierarchies in relation to cultural objects (see, for example, McGuigan, 1992: 157; Brunsdon, 1997: 5; Wark, 2001). Since Richard Hoggart and Raymond Williams took popular culture as a worthy object of study, Cultural Studies practitioners have accepted that the terms in which cultural debate had previously been conducted involved a category error. Opera is not 'better' than pop music, we believe in Cultural Studies - 'better for what?', we would ask. Similarly, Shakespeare is not 'better' than Mills and Boon, unless you can specify the purpose for which you want to use the texts. Shakespeare is indeed better than Mills and Boon for understanding seventeenth century ideas about social organisation; but Mills and Boon is unquestionably better than Shakespeare if you want slightly scandalous, but ultimately reassuring representations of sexual intercourse. The reason that we do not accept traditional hierarchies of cultural value is that we know that the culture that is commonly understood to be 'best' also happens to be that which is preferred by the most educated and most materially well-off people in any given culture (Bourdieu, 1984: 1- 2; Ross, 1989: 211). We can interpret this information in at least two ways. On the one hand, it can be read as proving that the poorer and less well-educated members of a society do indeed have tastes which are innately less worthwhile than those of the material and educational elite. On the other hand, this information can be interpreted as demonstrating that the cultural and material elite publicly represent their own tastes as being the only correct ones. In Cultural Studies, we tend to favour the latter interpretation. We reject the idea that cultural objects have innate value, in terms of beauty, truth, excellence, simply 'there' in the object. That is, we reject 'aesthetic' approaches to culture (Bourdieu, 1984: 6; 485; Hartley, 1994: 6)1. In this, Cultural Studies is similar to other postmodern institutions, where high and popular culture can be mixed in ways unfamiliar to modernist culture (Sim, 1992: 1; Jameson, 1998: 100). So far, so familiar.

Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline.

Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.

Rough sets based reasoning and pattern mining for a two-stage information filtering system

This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.