Describing individual incidents of sexual abuse: a review of research on the effects of multiple sources of information on children's reports

Objective: For successful prosecution of child sexual abuse, children are often required to provide reports about individual, alleged incidents. Although verbally or mentally rehearsing memory of an incident can strengthen memories, children’s report of individual incidents can also be contaminated when they experience other events related to the individual incidents (e.g., informal interviews, dreams of the incident) and/or when they have similar, repeated experiences of an incident, as in cases of multiple abuse.

Method: Research is reviewed on the positive and negative effects of these related experiences on the length, accuracy, and structure of children’s reports of a particular incident.

Results: Children’s memories of a particular incident can be strengthened when exposed to information that does not contradict what they have experienced, thus promoting accurate recall and resistance to false, suggestive influences. When the encountered information differs from children’s experiences of the target incident, however, children can become confused between their experiences—they may remember the content but not the source of their experiences.

Conclusions: We discuss the implications of this research for interviewing children in sexual abuse investigations and provide a set of research-based recommendations for investigative interviewers.

Information sharing between heterogeneous uncertain reasoning models in a multi-agent environment : a case study

The issue of information sharing and exchanging is one of the most important issues in the areas of artificial intelligence and knowledge-based systems (KBSs), or even in the broader areas of computer and information technology. This paper deals with a special case of this issue by carrying out a case study of information sharing between two well-known heterogeneous uncertain reasoning models: the certainty factor model and the subjective Bayesian method. More precisely, this paper discovers a family of exactly isomorphic transformations between these two uncertain reasoning models. More interestingly, among isomorphic transformation functions in this family, different ones can handle different degrees to which a domain expert is positive or negative when performing such a transformation task. The direct motivation of the investigation lies in a realistic consideration. In the past, expert systems exploited mainly these two models to deal with uncertainties. In other words, a lot of stand-alone expert systems which use the two uncertain reasoning models are available. If there is a reasonable transformation mechanism between these two uncertain reasoning models, we can use the Internet to couple these pre-existing expert systems together so that the integrated systems are able to exchange and share useful information with each other, thereby improving their performance through cooperation. Also, the issue of transformation between heterogeneous uncertain reasoning models is significant in the research area of multi-agent systems because different agents in a multi-agent system could employ different expert systems with heterogeneous uncertain reasonings for their action selections and the information sharing and exchanging is unavoidable between different agents. In addition, we make clear the relationship between the certainty factor model and probability theory.

"Information effect" of economic news: SPI futures

The present study investigates the behaviour of Share Price Index (SPI) futures returns, volatility, and trading volume behaviour around the announcement of Current Account Deficit (CAD), Gross Domestic Product (GDP), and Inflation (CPI). The futures market data are sampled at 1-, 5-, and 10-min intervals at the announcement time. After controlling for risk, a significant positive abnormal return can be earned based on the good news release. However, it is unlikely that traders could make an economic profit by exploiting this effect. In this sense, this futures market returns are found to react efficiently to good news. Volatility behaviour around announcements provides the same conclusion. As for the relationship between returns, volatility, and volume upon information arrival, returns are positively related to trading volume, which is inconsistent with the ‘short sales constraint’ theory. Trading volume is found to increase as the level of volatility rises. The redenomination of the SPI futures and options contract from A$100 to A$25 per basis point is found to increase trading volume in excess of that expected due to the redenomination. However, market return and volatility are unaffected by the redenomination.

It takes more than breadcrumbs to learn generic skills : collaborating to improve information literacy

The effective teaching and learning of generic skills is becoming an important component of undergraduate education with the introduction of graduate attribute programmes in some Australian universities. Research shows that contextualised learning of these skills is important, but is a discipline-specific context sufficient to ensure student success in acquiring these skills? This paper studies the effectiveness of information skills
learning by a group of undergraduates using Brookfield’s concept of critical reflection and Critical Incident Questionnaire (CIQ). Most students reported positive experiences where the learning environment encouraged a deep approach to learning and negative experiences where that environment encouraged a surface approach. To ensure that students’ approach to
learning is appropriate for achieving the level of information literacy required of graduates, the study recommends the integration of information skills learning into course curricula through the close collaboration of academic and library staff.

Modeling intelligent agents for web-based information gathering

The recent emergence of intelligent agent technology and advances in information gathering have been the important steps forward in efficiently managing and using the vast amount of information now available on the Web to make informed decisions. There are, however, still many problems that need to be overcome in the information gathering research arena to enable the delivery of relevant information required by end users. Good decisions cannot be made without sufficient, timely, and correct information. Traditionally it is said that knowledge is power, however, nowadays sufficient, timely, and correct information is power. So gathering relevant information to meet user information needs is the crucial step for making good decisions. The ideal goal of information gathering is to obtain only the information that users need (no more and no less). However, the volume of information available, diversity formats of information, uncertainties of information, and distributed locations of information (e.g. World Wide Web) hinder the process of gathering the right information to meet the user needs. Specifically, two fundamental issues in regard to efficiency of information gathering are mismatch and overload. The mismatch means some information that meets user needs has not been gathered (or missed out), whereas, the overload means some gathered information is not what users need. Traditional information retrieval has been developed well in the past twenty years. The introduction of the Web has changed people's perceptions of information retrieval. Usually, the task of information retrieval is considered to have the function of leading the user to those documents that are relevant to his/her information needs. The similar function in information retrieval is to filter out the irrelevant documents (or called information filtering). Research into traditional information retrieval has provided many retrieval models and techniques to represent documents and queries. Nowadays, information is becoming highly distributed, and increasingly difficult to gather. On the other hand, people have found a lot of uncertainties that are contained in the user information needs. These motivate the need for research in agent-based information gathering. Agent-based information systems arise at this moment. In these kinds of systems, intelligent agents will get commitments from their users and act on the users behalf to gather the required information. They can easily retrieve the relevant information from highly distributed uncertain environments because of their merits of intelligent, autonomy and distribution. The current research for agent-based information gathering systems is divided into single agent gathering systems, and multi-agent gathering systems. In both research areas, there are still open problems to be solved so that agent-based information gathering systems can retrieve the uncertain information more effectively from the highly distributed environments. The aim of this thesis is to research the theoretical framework for intelligent agents to gather information from the Web. This research integrates the areas of information retrieval and intelligent agents. The specific research areas in this thesis are the development of an information filtering model for single agent systems, and the development of a dynamic belief model for information fusion for multi-agent systems. The research results are also supported by the construction of real information gathering agents (e.g., Job Agent) for the Internet to help users to gather useful information stored in Web sites. In such a framework, information gathering agents have abilities to describe (or learn) the user information needs, and act like users to retrieve, filter, and/or fuse the information. A rough set based information filtering model is developed to address the problem of overload. The new approach allows users to describe their information needs on user concept spaces rather than on document spaces, and it views a user information need as a rough set over the document space. The rough set decision theory is used to classify new documents into three regions: positive region, boundary region, and negative region. Two experiments are presented to verify this model, and it shows that the rough set based model provides an efficient approach to the overload problem. In this research, a dynamic belief model for information fusion in multi-agent environments is also developed. This model has a polynomial time complexity, and it has been proven that the fusion results are belief (mass) functions. By using this model, a collection fusion algorithm for information gathering agents is presented. The difficult problem for this research is the case where collections may be used by more than one agent. This algorithm, however, uses the technique of cooperation between agents, and provides a solution for this difficult problem in distributed information retrieval systems. This thesis presents the solutions to the theoretical problems in agent-based information gathering systems, including information filtering models, agent belief modeling, and collection fusions. It also presents solutions to some of the technical problems in agent-based information systems, such as document classification, the architecture for agent-based information gathering systems, and the decision in multiple agent environments. Such kinds of information gathering agents will gather relevant information from highly distributed uncertain environments.

Doctoral research and scholarly communication : candidates, supervisors and information literacy

This study investigates information literacy and scholarly communication within the processes of doctoral research and supervision at a distance. Both doctoral candidates and supervisors acknowledge information literacy deficiencies and it is suggested that disintermediation and the proliferation of information may contribute to those deficiencies. Further to this, the influence of pedagogic continuity—particularly in relation to the information seeking behaviour of candidates—is investigated, as is the concomitant aspect of how doctoral researchers practise scholarly communication. The well-documented and enduring problem for candidates of isolation from the research cultures of their universities is also scrutinised. The contentious issue of more formally involving librarians in the doctoral process is also considered, from the perspective of candidates and supervisors. Superimposed upon these topical and timely issues is the theoretical framework of adult learning theory, in particular the tenets of andragogy. The pedagogical-andragogical orientation of candidates and supervisors is established, demonstrating both the differences and similarities between candidates and supervisors, as are a number of independent variables, including a comparison of on-campus and off-campus candidates. Other independent variables include age, gender, DETYA (Department of Education, Training & Youth Affairs) category, enrolment type, stage of candidature, employment and status, type of doctorate, and English/non-English speaking background. The research methodology uses qualitative and quantitative techniques encompassing both data and methodological triangulation. The study uses two sets of questionnaires and a series of in-depth interviews with a sample of on-campus and off-campus doctoral candidates and supervisors from four Australian universities. Major findings include NESB candidates being more pedagogical than their ESB counterparts, and candidates and supervisors from the Sciences are more pedagogical than those from Arts, Humanities and Social Sciences, or Education. Candidates make a transition from a more dependent and pedagogically oriented approach to learning towards more of an independent and andragogical orientation over the duration of their candidature. However, over tune both on-campus and off-campus candidates become more isolated from the research cultures of their universities, and less happy with support received from their supervisors in relation to their literature reviews. Ill The study found large discrepancies in perception between the support supervisors believed they gave to candidates in relation to the literature review, and the support candidates believed they received. Information seeking becomes easier over time, but candidates face a dilemma with the proliferation of information, suggesting that disintermediation has exacerbated the challenges of evaluation and organisation of information. The concept of pedagogic continuity was recognised by supervisors and especially candidates, both negative and positive influences. The findings are critically analysed and synthesised using the metaphor of a scholarly 'Club' of which obtaining a doctorate is a rite of passage. Recommendations are made for changes in professional practice, and topics that may warrant further research are suggested.

Reconstructing the incidence of human immunodeficiency virus (HIV) in Hong Kong by using data from HIV positive tests and diagnoses of acquired immune deficiency syndrome

The human immunodeficiency virus–acquired immune deficiency syndrome (HIV–AIDS) epidemic in Hong Kong has been under surveillance in the form of voluntary reporting since 1984. However, there has been little discussion or research on the reconstruction of the HIV incidence curve. This paper is the first to use a modified back-projection method to estimate the incidence of HIV in Hong Kong on the basis of the number of positive HIV tests only. The model proposed has several advantages over the original back-projection method based on AIDS data only. First, not all HIV-infected individuals will develop AIDS by the time of analysis, but some of them may undertake an HIV test; therefore, the HIV data set contains more information than the AIDS data set. Second, the HIV diagnosis curve usually has a smoother pattern than the AIDS diagnosis curve, as it is not affected by redefinition of AIDS. Third, the time to positive HIV diagnosis is unlikely to be affected by treatment effects, as it is unlikely that an individual receives medication before the diagnosis of HIV. Fourth, the induction period from HIV infection to the first HIV positive test is usually shorter than the incubation period which is from HIV infection to diagnosis of AIDS. With a shorter induction period, more information becomes available for estimating the HIV incidence curve. Finally, this method requires the number of positive HIV diagnoses only, which is readily available from HIV–AIDS surveillance systems in many countries. It is estimated that, in Hong Kong, the cumulative number of HIV infections during the period 1979–2000 is about 2600, whereas an estimate based only on AIDS data seems to give an underestimate.

Enhancing Knowledge Sharing with Information and Communication Technology (ICT)

The acceleration of technological change and trade liberalization in the 1990s have significantly intensified market competition and transformed the world economic infrastructure from a resource- and manufacturing-based economy to one in which knowledge and services are the key drivers of economic growth. In order for an organization to capitalize on its knowledge and truly become a learning organization, it must begin to systematically manage and leverage knowledge existing internally and externally to create and sustain its competitive advantage. Numerous empirical studies on knowledge management have examined the relative effectiveness of various enablers, such as organizational structure, technology, culture, managerial system and strategy on knowledge creation and sharing in organizations. The enablers examined earlier are mostly related to organizational infrastructure that promotes knowledge sharing in organizations. This paper examines specifically the critical role of information and communication technology (ICT) in facilitating and enhancing knowledge sharing and organizational performance. This study adopted a process oriented approach by using Nonaka’s (1994) knowledge sharing model. The results indicate that significant positive effects of ICT support on knowledge sharing and all dimensions of knowledge sharing are significant predictors of organizational performance.

Information technology networks and small business : impact, strategies and changing industry structure

Focuses on the impact of information technology networks on small businesses acting as intermediaries between large enterprises and customers. Explores whether disintermediation is a threat for these small business intermediaries. Investigated factors affecting the use of information technology by small businesses to gain positive outcomes.

Media pressures and corporate disclosure of social responsibility performance information : a study of two global clothing and sports retail companies

This paper investigates the social and environmental disclosure practices of two large multinational companies, specifically Nike and Hennés & Mauritz. Utilising a joint consideration of legitimacy theory and media agenda setting theory, we investigate the linkage between negative media attention, and positive corporate social and environmental disclosures. Our results generally support a view that for those industry-related social and environmental issues attracting the greatest amount of negative media attention, these corporations react by providing positive social and environmental disclosures. The results were particularly significant in relation to labour practices in developing countries - the issue attracting the greatest amount of negative media attention for the companies in question.

Incorporating both positive and negative association rules into the analysis of outbound tourism in Hong Kong

This article presents a novel approach to data mining that incorporates both positive and negative association rules into the analysis of outbound travelers. Using datasets collected from three large-scale domestic tourism surveys on Hong Kong residents' outbound pleasure travel, different sets of targeted rules were generated to provide promising information that will allow practitioners and policy makers to better understand the important relationship between condition attributes and target attributes. This article will be of interest to readers who want to understand methods for integrating the latest data mining techniques into tourism research. It will also be of use to marketing managers in destinations to better formulate strategies for receiving outbound travelers from Hong Kong, and possibly elsewhere.

Men’s emotional responses to their partner’s pregnancy and their views on support and information received

The main aim of this study was to extend previous research of men’s experiences of pregnancy; 48 Australian men and their pregnant partners took part. Most men reported feeling positive about the pregnancy, emotionally well supported and well informed. Men reported receiving more valuable information from their partner than from doctors/obstetricians, family or the internet and were accurate observers of women’s depression levels.

Impact of nursing information systems on residential care provision in an aged care provider

The challenge of an ageing population has placed a great pressure on the Australian aged care sector in the coming decades. Technology-enabled solutions such as health information systems (HIS) can be seen as a way to improve care quality, safety and process efficiency. Compared to the overall healthcare sector, the adoption of HIS in the aged care sector has been slower. One reason for this is that aged care providers are not well informed therefore not yet convinced of the positive impacts of technology solutions on their service provision. This paper reports findings from an evaluation of the impact of HIS adoption at an aged care provider in Victoria. The evaluation was conducted in two distinct areas, residential aged care and residential disability services. Overall, the findings show positive impacts of the system on individual work of the care staff and on service provision of the organisation as well as suggesting opportunities for improvement in later implementation stages. The evaluation will also inform other aged care and disability service providers of the benefits of HIS and useful lessons in adoption of technology solutions.

Individuals with chronic low back pain have greater difficulty in engaging in positive lifestyle behaviours than those without back pain : an assessment of health literacy

Background: Despite the large volume of research dedicated to understanding chronic low back pain (CLBP), patient outcomes remain modest while healthcare costs continue to rise, creating a major public health burden. Health literacy - the ability to seek, understand and utilise health information - has been identified as an important factor in the course of other chronic conditions and may be important in the aetiology of CLBP. Many of the currently available health literacy measurement tools are limited since they measure narrow aspects of health literacy. The Health Literacy Measurement Scale (HeLMS) was developed recently to measure broader elements of health literacy. The aim of this study was to measure broad elements of health literacy among individuals with CLBP and without LBP using the HeLMS.
Methods: Thirty-six community-dwelling adults with CLBP and 44 with no history of LBP responded to the HeLMS. Individuals were recruited as part of a larger community-based spinal health study in Western Australia. Scores for the eight domains of the HeLMS as well as individual item responses were compared between the groups.
Results: HeLMS scores were similar between individuals with and without CLBP for seven of the eight health literacy domains (p > 0.05). However, compared to individuals with no history of LBP, those with CLBP had a significantly lower score in the domain ‘Patient attitudes towards their health’ (mean difference [95% CI]: 0.46 [0.11- 0.82]) and significantly lower scores for each of the individual items within this domain (p < 0.05). Moderate effect sizes ranged from d = 0.47-0.65.
Conclusions: Although no differences were identified in HeLMS scores between the groups for seven of the health literacy domains, adults with CLBP reported greater difficulty in engaging in general positive health behaviours. This aspect of health literacy suggests that self-management support initiatives may benefit individuals with CLBP.

Classification and optimization of product review information using soft computing models

A soft computing framework to classify and optimize text-based information extracted from customers' product reviews is proposed in this paper. The soft computing framework performs classification and optimization in two stages. Given a set of keywords extracted from unstructured text-based product reviews, a Support Vector Machine (SVM) is used to classify the reviews into two categories (positive and negative reviews) in the first stage. An ensemble of evolutionary algorithms is deployed to perform optimization in the second stage. Specifically, the Modified micro Genetic Algorithm (MmGA) optimizer is applied to maximize classification accuracy and minimize the number of keywords used in classification. Two Amazon product reviews databases are employed to evaluate the effectiveness of the SVM classifier and the ensemble of MmGA optimizers in classification and optimization of product related keywords. The results are analyzed and compared with those published in the literature. The outputs potentially serve as a list of impression words that contains useful information from the customers' viewpoints. These impression words can be further leveraged for product design and improvement activities in accordance with the Kansei engineering methodology.