Supporting fathers in the transition to parenthood

Knowledge of the experience of parenthood is usually from a woman’s perspective. The resulting outcome is that knowledge about the experience of fatherhood has been limited. Fathers are starting to change this situation by sharing their experience as is evidenced by the overall response of 267 fathers to this study. This paper focuses on the exploration of 22 men’s feelings and beliefs about fatherhood; and their expectations and views about parenting. The paper will also investigate how fathers’ antenatal expectations matched the reality of early family life including emotional well-being, attitudes to parenting, adjustment to family life and sources of support. The quantitative and qualitative data of the 22 fathers who responded to both the antenatal and postnatal questionnaires used within this paper are drawn from a larger Queensland survey of women and men during the antenatal and postnatal period.

Open City, Rossellini and neorealism : sixty years on

For Bakhtin, it is always important to know from where one speaks. The place from which I speak is that of a person who grew up in Italy during the economic miracle (pre-1968) in a working class family, watching film matinees on television during school holidays. All sort of films and genres were shown: from film noir to westerns, to Jean Renoir's films, German expressionism, Italian neorealism and Italian comedy. Cinema has come to represent over time a sort of memory extension that supplements lived memory of events, and one which, especially, mediates the intersection of many cultural discourses. When later in life I moved to Australia and started teaching in film studies, my choice of a film that was emblematic of neorealism went naturally to Roma città aperta (Open city hereafter) by Roberto Rossellini (1945), and not to Paisan or Sciuscà or Bicycle Thieves. My choice was certainly grounded in my personal memory - especially those aspects transmitted to me by my parents, who lived through the war and maintained that Open City had truly made them cry. With a mother who voted for the Christian Democratic Party and a father who was a unionist, I thought that this was normal in Italian families and society. In the early 1960s, the Resistance still offered a narrative of suffering and redemption, shared by Catholics or Communists. This construction of psychological realism is what I believe Open City continues to offer in time.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Social justice and high-quality human services : visioning the place of a contemporary professional association

The current world situation is plagued by “wicked problems” and a widespread sense of “things are going to get worse”. We confront the almost imponderable consequences of global habitat destruction and climate change, as well as the meltdown of the financial markets with their largely yet to be seen damage to the “real economy”. These things will have considerable negative impacts on the social system and people's lives, particularly the disadvantaged and socially excluded, and require innovative policy and program responses delivered by caring, intelligent, and committed practitioners. These gargantuan issues put into perspective the difficulties that confront social, welfare, and community work today. Yet, in times of trouble, social work and human services tend to do well. For example, although Australian Social Workers and Welfare and Community Workers have experienced phenomenal job growth over the past 5 years, they also have good prospects for future growth and above average salaries in the seventh and sixth deciles, respectively (Department of Education, Employment and Workplace Relations, 2008). I aim to examine the host of reasons why the pursuit of social justice and high-quality human services is difficult to attain in today's world and then consider how the broadly defined profession of social welfare practitioners may collectively take action to (a) respond in ways that reassert our role in compassionately assisting the downtrodden and (b) reclaim the capacity to be a significant body of professional expertise driving social policy and programs. For too long social work has responded to the wider factors it confronts through a combination of ignoring them, critiquing from a distance, and concentrating on the job at hand and our day-to-day responsibilities. Unfortunately, “holding the line” has proved futile and, little by little, the broad social mandate and role of social welfare has altered until, currently, most social programs entail significant social surveillance of troublesome or dangerous groups, rather than assistance. At times it almost seems like the word “help” has been lost in the political and managerial lexicon, replaced by “manage” and “control”. Our values, beliefs, and ethics are under real threat as guiding principles for social programs.

Childhood and social interaction in everyday life : an epilogue

The epilogue pulls together the conceptual and methodological significance of the papers in the special issue exploring childhood and social interaction in everyday life in Sweden, Norway, United States and Australia. In considering the special issue, four domains of childhood are identified and discussed: childhood is a social construct where children learn how to enter into and participate in their social organizations, competency is best understood when communicative practices are examined in situ, children’s talk and interaction show situated culture in action, and childhood consists of shared social orders between children and adults. Emerging analytic interests are proposed, including investigating how children understand locations and place. Finally, the epilogue highlights the core focus of this special issue, which is showing children’s own methods for making sense of their everyday contexts using the interactional and cultural resources they have to hand.

Improving the management of building life cycle : a data mining approach

The construction industry has adapted information technology in its processes in terms of computer aided design and drafting, construction documentation and maintenance. The data generated within the construction industry has become increasingly overwhelming. Data mining is a sophisticated data search capability that uses classification algorithms to discover patterns and correlations within a large volume of data. This paper presents the selection and application of data mining techniques on maintenance data of buildings. The results of applying such techniques and potential benefits of utilising their results to identify useful patterns of knowledge and correlations to support decision making of improving the management of building life cycle are presented and discussed.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Using data mining to improve building life cycle

The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.

The impact of perceived stage of cancer on carers’ anxiety and depression during the patients’ final year of life

Objective: This paper explores the effects of perceived stage of cancer (PSOC) on carers' anxiety and depression during the patients' final year. Methods: A consecutive sample of patients and carers (N=98) were surveyed at regular intervals regarding PSOC, and anxiety and depression using the Hospital Anxiety and Depression Scale. Means were compared by gender using the Mann-Whitney U-test. The chi-square was used to analyse categorical data. Agreement between carers' and patients' PSOC was estimated using kappa statistics. Correlations between carers' PSOC and their anxiety and depression were calculated using the Spearman's rank correlation. Results: Over time, an increasing proportion of carers reported that the cancer was advanced, culminating at 43% near death. Agreement regarding PSOC was fair (kappa=0.29-0.34) until near death (kappa=0.21). Carers' anxiety increased over the year; depression increased in the final 6 months. Females were more anxious (p=0.049, 6 months; p=0.009, 3 months) than males, and more depressed until 1 month to death. The proportion of carers reporting moderate-severe anxiety almost doubled over the year to 27%, with more females in this category at 6 months (p=0.05). Carers with moderate-severe depression increased from 6 to 15% over the year. Increased PSOC was weakly correlated with increased anxiety and depression. Conclusions: Carers' anxiety exceeded depression in severity during advanced cancer. Females generally experienced greater anxiety and depression. Carers were more realistic than patients regarding the ultimate outcome, which was reflected in their declining mental health, particularly near the end.

Terminally ill cancer patients’ wish to hasten death

This exploratory study investigated factors associated with the wish to hasten death among a sample of terminally ill cancer patients. Semi-structured interviews conducted on a total of 72 hospice and home palliative care patients were subjected to qualitative analysis using QSRNUDIST. The main themes to emerge suggested that patients with a high wish to hasten death had greater concerns with physical symptoms and psychologica l suffering, perceived themselves to be more of a burden to others, and experienced higher levels of demoralization, while also reporting less confidence in symptom control, fewer social supports, less satisfaction with life experiences and fewer religious beliefs when compared with patients who had a moderate or no wish to hasten death. The implications of these findings will be discussed.

International review of environmental assessment tools and databases

Existing widely known environmental assessment models, primarily those for Life Cycle Assessment of manufactured products and buildings, were reviewed to grasp their characteristics, since the past several years have seen a significant increase in interest and research activity in the development of building environmental assessment methods. Each method or tool was assessed under the headings of description, data requirement, end-use, assessment criteria (scale of assessment and scoring/ weighting system)and present status

Re-invent yourself: from London intensive care nursing and the Nigerian oil fields to an an academic library in Brisbane; a career change worth making.

A complete change of career forces a seismic shift in every aspect of your life. From day one, you have to face the loss of long held beliefs, behaviours, the known world of self, and security. We came from professions that themselves are poles apart, and many of the challenges we faced entering the profession were the same: juggling full-time work, part time study, and family commitmemts, taking a pay cut, and loss of social life. But over a short period of time we both transitioned to our new profession successfully. so what make our successful transition possible?

Whole of life cycle cost analysis in bridge rehabilitation

The report presents a methodology for whole of life cycle cost analysis of alternative treatment options for bridge structures, which require rehabilitation. The methodology has been developed after a review of current methods and establishing that a life cycle analysis based on a probabilistic risk approach has many advantages including the essential ability to consider variability of input parameters. The input parameters for the analysis are identified as initial cost, maintenance, monitoring and repair cost, user cost and failure cost. The methodology utilizes the advanced simulation technique of Monte Carlo simulation to combine a number of probability distributions to establish the distribution of whole of life cycle cost. In performing the simulation, the need for a powerful software package, which would work with spreadsheet program, has been identified. After exploring several products on the market, @RISK software has been selected for the simulation. In conclusion, the report presents a typical decision making scenario considering two alternative treatment options.