Promoting active lifestyles in young children: investigating mothers’ decisions about their child’s physical activity and screen time behaviours

Objectives Given increasing trends of obesity being noted from early in life and that active lifestyles track across time, it is important that children at a very young age be active to combat a foundation of unhealthy behaviours forming. This study investigated, within a theory of planned behaviour (TPB) framework, factors which influence mothers’ decisions about their child’s 1) adequate physical activity (PA) and 2) limited screen time behaviours. Methods Mothers (N = 162) completed a main questionnaire, via on-line or paper-based administration, which comprised standard TPB items in addition to measures of planning and background demographic variables. One week later, consenting mothers completed a follow-up telephone questionnaire which assessed the decisions they had made regarding their child’s PA and screen time behaviours during the previous week. Results Hierarchical multiple regression analyses revealed support for the predictive model, explaining an overall 73% and 78% of the variance in mothers’ intention and 38% and 53% of the variance in mothers’ decisions to ensure their child engages in adequate PA and limited screen time, respectively. Attitude and subjective norms predicted intention in both target behaviours, as did intentions with behaviour. Contrary to predictions, perceived behavioural control (PBC) in PA behaviour and planning in screen time behaviour were not significant predictors of intention, neither was PBC a predictor of either behaviour. Conclusions The findings illustrate the various roles that psycho-social factors play in mothers’ decisions to ensure their child engages in active lifestyle behaviours which can help to inform future intervention programs aimed at combating very young children’s inactivity.

Insider comes out : an artist's inquiry and narrative about the relationship of art and mental health

Background Through an account of prevailing experiences of art and mental illness, this paper aims to raise awareness, open dialogue and create agency about art created by people with experience of mental illness. Methods This paper draws on personal narrative and inquiry by an artist with mental illness and data collected as part of a larger participatory action research project that investigated understandings of identity, art and mental illness. Result An inquiry through art raised awareness and attentiveness to the importance of choice in identity construction and exposed frequent dichotomies in art and mental illness that were negotiated to eschew prescribed social stratification. As an artist, the first author challenged values present in one idea and absent in the other, and the options and concessions available to authorise her own dialogue and agency of being an artist. Conclusion Constructing an identity is an important part of being human, the labels that we choose or are chosen for us attribute to our identity. Reflections and recommendations are offered to consider expanded ways of thinking about art and mental illness and the functions that art play in identity construction.

The IKBALS project: multi-modal reasoning in legal knowledge based systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval. When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers. Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process. Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions. The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.

Reasoning paradigms in legal decision support systems

In this paper we discuss the strengths and weaknesses of a range of artificial intelligence approaches used in legal domains. Symbolic reasoning systems which rely on deductive, inductive and analogical reasoning are described and reviewed. The role of statistical reasoning in law is examined, and the use of neural networks analysed. There is discussion of architectures for, and examples of, systems which combine a number of these reasoning strategies. We conclude that to build intelligent legal decision support systems requires a range of reasoning strategies.

Shaping lecturers’ beliefs about teaching and learning in higher education in the Pacific

The aim of this study was to describe the educational experiences shaping the teaching and learning beliefs held by a group of beginning lecturers in higher education at various tertiary institutions in the Pacific Island Countries (PICs). A total of sixty three essays written by participants in an online course on teaching in higher education comprised the data for the study. A modified version of narrative analysis was used. This is a powerful methodology in qualitative research that can provide remarkable insights into individuals’ beliefs. The critical experiences that were thought to shape their beliefs in teaching and learning were identified and discussed in the light of relevant literature. The participants described a range of influences that shaped their beliefs about teaching and learning including realisation about the need to work harder and know more, the importance of independence, support systems, curriculum, qualities of a teacher, teaching and learning process, teaching and learning strategies, and learning environments. This information was useful in teaching these students and for further courses.

Beyond rule based reasoning - the meaning and use of cases

Commercial legal expert systems are invariably rule based. Such systems are poor at dealing with open texture and the argumentation inherent in law. To overcome these problems we suggest supplementing rule based legal expert systems with case based reasoning or neural networks. Both case based reasoners and neural networks use cases-but in very different ways. We discuss these differences at length. In particular we examine the role of explanation in existing expert systems methodologies. Because neural networks provide poor explanation facilities, we consider the use of Toulmin argument structures to support explanation (S. Toulmin, 1958). We illustrate our ideas with regard to a number of systems built by the authors

Deductive, inductive and analogical reasoning in legal decision support systems

In this paper we provide an overview of a number of fundamental reasoning formalisms in artificial intelligence which can and have been used in modelling legal reasoning. We describe deduction, induction and analogical reasoning formalisms, and show how they can be used separately to model legal reasoning. We argue that these formalisms can be used together to model legal reasoning more accurately, and describe a number of attempts to integrate the approaches.

Non-monotonic Reasoning and the Reversibility of Belief Change

Traditional approaches to nonmonotonic reasoning fail to satisfy a number of plausible axioms for belief revision and suffer from conceptual difficulties as well. Recent work on ranked preferential models (RPMs) promises to overcome some of these difficulties. Here we show that RPMs are not adequate to handle iterated belief change. Specifically, we show that RPMs do not always allow for the reversibility of belief change. This result indicates the need for numerical strengths of belief.

ACE research vignette 033: Learning (about) entrepreneurship through experiential learning opportunities at university

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. In this vignette, Dr Martin Bliemel considers the state of entrepreneurship education in universities and the degree to which students actually internalize what it is like to be an entrepreneur.

Time to face the fats : What can mass spectrometry reveal about the structure of lipids and their interactions with proteins?

Since the 1950s, X-ray crystallography has been the mainstay of structural biology, providing detailed atomic-level structures that continue to revolutionize our understanding of protein function. From recent advances in this discipline, a picture has emerged of intimate and specific interactions between lipids and proteins that has driven renewed interest in the structure of lipids themselves and raised intriguing questions as to the specificity and stoichiometry in lipid-protein complexes. Herein we demonstrate some of the limitations of crystallography in resolving critical structural features of ligated lipids and thus determining how these motifs impact protein binding. As a consequence, mass spectrometry must play an important and complementary role in unraveling the complexities of lipid-protein interactions. We evaluate recent advances and highlight ongoing challenges towards the twin goals of (1) complete structure elucidation of low, abundant, and structurally diverse lipids by mass spectrometry alone, and (2) assignment of stoichiometry and specificity of lipid interactions within protein complexes.

The hard facts : a brilliant memoir about ancestral silence

A review of A History of Silence by Lloyd Jones (Text Publishing, 2013).