Mindreading and moral awareness in popular and rejected preschoolers

This study sought to examine links among young children's peer relations, their moral understanding in terms of the ability to distinguish lies from mistakes, and their theory-of-mind development. Based on sociometric measures, 109 children with a mean age of 4.8 years were divided into groups of popular and rejected preschoolers. Rejected children who had a stable mutual friend scored higher on measures of moral understanding and theory of mind than did rejected children without such friendships. Similarly, popular children who had a stable mutual friendship outperformed other popular children on mindreading, although their moral understanding was no better than that of the popular group who lacked mutual friends. Hierarchical multiple regression analyses revealed that peer popularity was a significant independent predictor of children's moral understanding after any effects of verbal maturity, age and theory-of-mind were statistically controlled. Moreover, having a reciprocal stable friendship made a significant independent contribution to the explanation of individual differences in mindreading, over and above age and verbal maturity, which also contributed significantly. These results are discussed in terms of conversational, cognitive, and emotional processes in the development of social cognition.

Rapid onset of pituitary apoplexy after goserelin implant for prostate cancer: need for heightened awareness

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An Ethics Core Curriculum for Australasian Medical Schools

Teaching ethics incorporates teaching of knowledge as well as skills and attitudes. Each of these requires different teaching and assessment methods. A core curriculum of ethics knowledge must address both the foundations of ethics and specific ethical topics. Ethical skills teaching focuses on the development of ethical awareness, moral reasoning, communication and collaborative action skills. Attitudes that are important for medical students to develop include honesty, integrity and trustworthiness, empathy and compassion, respect, and responsibility, as well as critical self-appraisal and commitment to lifelong education.

Improving pain management by nurses: A pilot peer intervention program

Significant pain continues to be reported by many hospitalized patients despite the numerous and varied educational programs developed and implemented to improve pain management. A theoretically based Peer Intervention Program was designed from a predictive model to address nurses' beliefs, attitudes, subjective norms, self-efficacy, perceived control and intentions in the management of pain with p.r.n. (as required) narcotic analgesia. The pilot study of this program utilized a quasi-experimental pre-post test design with a patient intervention, nurse and patient intervention and control conditions consisting of 24, 18 and 19 nurses, respectively. One week after the intervention, significant differences were found between the nurse and patient condition and the two other conditions in beliefs, self-efficacy, perceived control, positive trend in attitudes, subjective norms and intentions. The most positive aspects of the program were supportive interactive discussions with peers and an awareness and understanding of beliefs and attitudes and their roles in behavior.

Knowledge and markets

An economy is a coordinated system of distributed knowledge. Economic evolution occurs as knowledge grows and the structure of the system changes. This paper is about the role of markets in this process. Traditionally, the theory of markets has not been a central feature of evolutionary economics. This seems to be due to the orthodox view of markets as information-processing mechanisms for finding equilibria. But in economic evolution markets are actually knowledge-structuring mechanisms. What then is the relation between knowledge, information, markets and mechanisms? I argue that an evolutionary theory of markets, in the manner of Loasby (1999), requires a clear formulation of these relations. I suggest that a conception of knowledge and markets in terms of a graphical theory of complex systems furnishes precisely this.

The investigation of factors underlying deficits in self-awareness and self-regulation

Primary objective: To examine a theoretical model which suggests that a contribution of both psychological and neuropsychological factors underlie deficits in self-awareness and self-regulation. Research design: Multivariate design including correlations and analysis of variance (ANOVA). Methods: Sixty-one subjects with acquired brain injury (ABI) were administered standardized measures of self-awareness and self-regulation. Psychological factors included measures of coping-related denial, personality-related denial and personality change. Neuropsychological factors included an estimate of IQ and two measures of executive functioning that assess capacity for volition and purposive behaviour. Main outcomes and results: The findings indicated that the relative contribution of neuropsychological factors to an outcome of deficits in self-awareness and self-regulation had a more direct effect than psychological factors. In general, measures of executive functioning had a direct relationship, while measures of coping-related and personality-related denial had an indirect relationship with measures of self-awareness and self-regulation. Conclusion: The findings highlighted the importance of measuring both neuropsychological and psychological factors and demonstrated that the relative contribution of these variables varies according to different levels of self-awareness and self-regulation.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

The future role of government in knowledge-based economies

In this article, we draw together aspects of contemporary theories of knowledge (particularly organisational knowledge) and complexity theory to demonstrate how appropriate conceptual rigor enables both the role of government and the directions of policy development in knowledge-based economies to be identified. Specifically we ask, what is the role of government in helping shape the knowledge society of the future? We argue that knowledge policy regimes must go beyond the modes of policy analysis currently used in innovation, information and technology policy because they are based in an industrial rather than post-industrial analytical framework. We also argue that if we are to develop knowledge-based economies, more encompassing images of the future than currently obtain in policy discourse are required. We therefore seek to stimulate and provoke an array of lines of thought about government and policy for such economies. Our objective is to focus on ideas more than argument and persuasion.