The Alcohol Helplessness Scale and its prediction of depression among problem drinkers

Event-specific scales commonly have greater power than generalized scales in prediction of specific disorders and in testing mediator models for predicting such disorders. Therefore, in a preliminary study, a 6-item Alcohol Helplessness Scale was constructed and found to be reliable for a sample of 98 problem drinkers. Hierarchical multiple regression and its derivative path analysis were used to test whether helplessness and self-efficacy moderate or mediate the link between alcohol dependence and depression, A test of a moderation model was not supported, whereas a test of a mediation model was supported. Helplessness and self-efficacy both significantly and independently mediated between alcohol dependence and depression. Nevertheless, a significant direct effect of alcohol dependence on depression also remained.

The Making of knowledge cities : lessons learned from Melbourne

Knowledge cities are seen as fundamental to the economic growth and development of the 21st century cities. The purpose of this paper is to explore the knowledge city concept in depth. This paper discusses the principles of a knowledge city, and portrays its distinguishing characteristics and processes. The paper relates and analyses Melbourne’s experience as a knowledge city and scrutinises Melbourne’s initiatives on science, technology and innovation and policies for economic and social development. It also illustrates how the city administration played a key role in developing Melbourne as a globally recognised, entrepreneurial and competitive knowledge city. Then this paper identifies key success factors and provides some insights to policy makers of the MENA region cities in designing knowledge cities.

Validation of FHWA crash models for rural intersections - Lessons learned

A national-level safety analysis tool is needed to complement existing analytical tools for assessment of the safety impacts of roadway design alternatives. FHWA has sponsored the development of the Interactive Highway Safety Design Model (IHSDM), which is roadway design and redesign software that estimates the safety effects of alternative designs. Considering the importance of IHSDM in shaping the future of safety-related transportation investment decisions, FHWA justifiably sponsored research with the sole intent of independently validating some of the statistical models and algorithms in IHSDM. Statistical model validation aims to accomplish many important tasks, including (a) assessment of the logical defensibility of proposed models, (b) assessment of the transferability of models over future time periods and across different geographic locations, and (c) identification of areas in which future model improvements should be made. These three activities are reported for five proposed types of rural intersection crash prediction models. The internal validation of the model revealed that the crash models potentially suffer from omitted variables that affect safety, site selection and countermeasure selection bias, poorly measured and surrogate variables, and misspecification of model functional forms. The external validation indicated the inability of models to perform on par with model estimation performance. Recommendations for improving the state of the practice from this research include the systematic conduct of carefully designed before-and-after studies, improvements in data standardization and collection practices, and the development of analytical methods to combine the results of before-and-after studies with cross-sectional studies in a meaningful and useful way.

Lessons learned from implementation of a demonstration program to reduce the burden of anemia and hookworm in women in Yen Bai Province, Viet Nam

Background Iron deficiency, anemia and hookworm disease are important public health problems for women of reproductive age living in developing countries and affect the health of newborns and infants. Iron supplementation and deworming treatment are effective in addressing these problems in both pregnant and non-pregnant women. Daily iron supplementation and deworming after the first trimester is recommended for pregnant women although these programs usually do not operate efficiently or effectively. Weekly iron-folic acid supplementation and regular deworming for non-pregnant women may be a viable approach for improving iron status and preventing anemia during the reproductive years. Addressing these diseases at a population level before women become pregnant could significantly improve women's health before and during pregnancy, as well as their infants' growth and development. Methods and Results This paper describes the major processes undertaken in a demonstration intervention of preventive weekly iron-folic acid supplementation with regular deworming for all 52,000 women aged 15–45 years in two districts of Yen Bai province, in northern Viet Nam. The intervention strategy included extensive consultation with community leaders and village, commune, district and provincial health staff, and training for village health workers. Distribution of the drugs was integrated with the existing health service infrastructure and the village health workers were the direct point of contact with women. Iron-folic acid tablets and deworming treatment were provided free of charge from May 2006. An independent Vietnamese NGO was commissioned to evaluate compliance and identify potential problems. The program resulted in effective distribution of iron-folic acid tablets and deworming treatment to all villages in the target districts, with full or partial compliance of 85%. Conclusion Training for health staff, the strong commitment of all partners and the use of appropriate educational materials led to broad support for weekly iron-folic acid supplementation and high participation in the regular deworming days. In March 2008 the program was expanded to all districts in the province, a target population of approximately 250,000 WRA, and management was handed over to provincial authorities.

Online geographic information systems for improving health planning practice : lessons learned from the case study of Logan-Beaudesert, Australia

This study examines the impact of utilising a Decision Support System (DSS) in a practical health planning study. Specifically, it presents a real-world case of a community-based initiative aiming to improve overall public health outcomes. Previous studies have emphasised that because of a lack of effective information, systems and an absence of frameworks for making informed decisions in health planning, it has become imperative to develop innovative approaches and methods in health planning practice. Online Geographical Information Systems (GIS) has been suggested as one of the innovative methods that will inform decision-makers and improve the overall health planning process. However, a number of gaps in knowledge have been identified within health planning practice: lack of methods to develop these tools in a collaborative manner; lack of capacity to use the GIS application among health decision-makers perspectives, and lack of understanding about the potential impact of such systems on users. This study addresses the abovementioned gaps and introduces an online GIS-based Health Decision Support System (HDSS), which has been developed to improve collaborative health planning in the Logan-Beaudesert region of Queensland, Australia. The study demonstrates a participatory and iterative approach undertaken to design and develop the HDSS. It then explores the perceived user satisfaction and impact of the tool on a selected group of health decision makers. Finally, it illustrates how decision-making processes have changed since its implementation. The overall findings suggest that the online GIS-based HDSS is an effective tool, which has the potential to play an important role in the future in terms of improving local community health planning practice. However, the findings also indicate that decision-making processes are not merely informed by using the HDSS tool. Instead, they seem to enhance the overall sense of collaboration in health planning practice. Thus, to support the Healthy Cities approach, communities will need to encourage decision-making based on the use of evidence, participation and consensus, which subsequently transfers into informed actions.

When non-significance maybe significant: lessons learned from a study into the development, implementation and evaluation of a risk assessment tool for fleet settings

Introduction This study reports on the development of a self report assessment tool to increase the efficacy of crash prediction within Australian Fleet settings Over last 20 years an array of measures have been produced (Driver anger scale, Driving Skill Inventory, Manchester Driver Behaviour Questionnaire, Driver Attitude Questionnaire, Driver Stress Inventory, Safety Climate Questionnaire) While these tools are useful, research has demonstrated limited ability to accurately identify individuals most likely to be involved in a crash. Reasons cited include; - Crashes are relatively rare - Other competing factors may influence crash event - Ongoing questions regarding the validity of self report measures (common method variance etc) - Lack of contemporary issues relating to fleet driving performance

Towards teaching in partnership : lessons still to be learned

This article seeks to analyse current dilemmas in responding to calls to narrow 'the gap' between academic and school culture in the area of preservice teacher preparation. It critiques traditional practices and current policies which focus on the narrowly vocational at the expense of the contextual. Further, it acknowledges the problems in the teaching of theory as it has been traditionally understood. Finally, it assesses the benefits for teachers and academics of forms of pedagogical partnership and the likelihood of progress in this area, and suggest that a number of fundamental changes need to be made in academic culture for genuine partnerships to become a reality.

When non-significance may be significant : lessons learned from a study of the development, implementation and evaluation of a fleet risk assessment tool

This paper reports on the development and implementation of a self-report risk assessment tool that was developed in an attempt to increase the efficacy of crash prediction within Australian fleet settings. This study forms a part of a broader program of research into work related road safety and identification of driving risk. The first phase of the study involved a series of focus groups being conducted with 217 professional drivers which revealed that the following factors were proposed to influence driving performance: Fatigue, Knowledge of risk, Mood, Impatience and frustration, Speed limits, Experience, Other road users, Passengers, Health, and Culture. The second phase of the study involved piloting the newly developed 38 item Driving Risk Assessment Scale - Work Version (DRAS-WV) with 546 professional drivers. Factor analytic techniques identified a 9 factor solution that was comprised of speeding, aggression, time pressure, distraction, casualness, awareness, maintenance, fatigue and minor damage. Speeding and aggressive driving manoeuvres were identified to be the most frequent aberrant driving behaviours engaged in by the sample. However, a series of logistic regression analyses undertaken to determine the DRAS-WV scale’s ability to predict self-reported crashes revealed limited predictive efficacy e.g., 10% of crashes. This paper outlines proposed reasons for this limited predictive ability of the DRAS-WV as well as provides suggestions regarding the future of research that aims to develop methods to identify “at risk” drivers.

Towards the retrieval of accurate OD matrices from Bluetooth data : lessons learned from 2 years of data

The Bluetooth technology is being increasingly used to track vehicles throughout their trips, within urban networks and across freeway stretches. One important opportunity offered by this type of data is the measurement of Origin-Destination patterns, emerging from the aggregation and clustering of individual trips. In order to obtain accurate estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. These issues mainly stem from the use of the Bluetooth technology amongst drivers, and the physical properties of the Bluetooth sensors themselves. First, not all cars are equipped with discoverable Bluetooth devices and the Bluetooth-enabled vehicles may belong to some small socio-economic groups of users. Second, the Bluetooth datasets include data from various transport modes; such as pedestrian, bicycles, cars, taxi driver, buses and trains. Third, the Bluetooth sensors may fail to detect all of the nearby Bluetooth-enabled vehicles. As a consequence, the exact journey for some vehicles may become a latent pattern that will need to be extracted from the data. Finally, sensors that are in close proximity to each other may have overlapping detection areas, thus making the task of retrieving the correct travelled path even more challenging. The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks.

Unpacking ‘lessons learned’ : investigating failures and considering alternative solutions

One of the most common ways to share project knowledge is to capture the positive and negative aspects of projects in the form of lessons learned (LL). If effectively used, this process can assist project managers in reusing project knowledge and preventing future projects from repeating mistakes. Nevertheless, the process of capturing, storing, reviewing and reusing LL often remains suboptimal. Despite the potential for rich knowledge capture, lessons are often documented as simple, line-item statements devoid of context. Findings from an empirical investigation across four cases revealed a range of reasons related to the perceived quality, process and visibility of LL that lead to their limited use and application. Drawn from the cross-case analysis, this paper investigates an integrated approach to LL involving the use of a collaborative Web-based tool, which is easily accessible, intelligible and user-friendly, allowing more effective sharing of project knowledge and overcoming existing problems with LL.

Scientific visualisations for developing students’ understanding of concepts in chemistry : some findings and some lessons learned

Scientific visualisations such as computer-based animations and simulations are increasingly a feature of high school science instruction. Visualisations are adopted enthusiastically by teachers and embraced by students, and there is good evidence that they are popular and well received. There is limited evidence, however, of how effective they are in enabling students to learn key scientific concepts. This paper reports the results of a quantitative study conducted in Australian chemistry classrooms. The visualisations chosen were from free online sources, intended to model the ways in which classroom teachers use visualisations, but were found to have serious flaws for conceptual learning. There were also challenges in the degree of interactivity available to students using the visualisations. Within these limitations, no significant difference was found for teaching with and without these visualisations. Further study using better designed visualisations and with explicit attention to the pedagogy surrounding the visualisations will be required to gather high quality evidence of the effectiveness of visualisations for conceptual development.

Why not the best schools? What we have learned from outstanding schools around the world

Why not the Best Schools? offers a ten-point, ten-year plan for an education revolution that will result in the transformation of Australia’s schools. Expectations have been raised in Australia and comparable countries for an ‘education revolution’ that will secure success for all students in all settings. Such a revolution must ensure the alignment of educational outcomes, the skills required for a strong economy, and the needs of a harmonious society. Why not the Best Schools? goes beyond system characteristics to provide an in-depth account of how transformation occurs in schools. Fifty indicators are provided to help shape strategies for policy makers and practitioners in schools and school systems. Guidelines for leadership and governance ensure a future-focus for those who are determined to ensure that all students will succeed in the twentieth-first century. This book draws on a five-year study culminating in the International Project to Frame the Transformation of Schools conducted in Australia, China, England, Finland, the United States and Wales. The findings are consistent with the McKinsey & Company report on the world’s best performing school systems and those arising from OECD’s PISA.

Improving megasite management performance through incentives : lessons learned from the Shanghai Expo construction

As the biggest expo site in history, construction of the Shanghai Expo site faced a lot of challenges, including involvement of lots of investors, megaconstruction scale, concurrent construction mode, involvement of more than 40,000 migrant workers, and extremely tight completion deadlines, among others. Consequently, these challenges imposed great obstacles on accomplishing the safety, quality, and environmental goals. Through a case study of the Shanghai Expo construction, this paper paper presents the design and implementation of multicriteria incentives in megaprojects to accomplish the safety, quality, and environmental goals. Both quantitative and qualitative findings were triangulated to demonstrate the outcome of the incentives. Six critical success factors (CSFs) for the incentives, rule design, process orientation, top management support, training and promotion, communication in process, and process learning and improvement are identified and validated through case study data and content analysis. It is believed that the findings of this paper can enhance understanding of multicriteria incentive schemes in general and provide insights in implementing these incentive schemes in future megaprojects, particularly in the People’s Republic of China (PRC).

The SEA-CALIPSO volcano imaging experiment at Montserrat : plans, campaigns at sea and on land, scientific results, and lessons learned

Since 1995 the eruption of the andesitic Soufrière Hills Volcano (SHV), Montserrat, has been studied in substantial detail. As an important contribution to this effort, the Seismic Experiment with Airgunsource-Caribbean Andesitic Lava Island Precision Seismo-geodetic Observatory (SEA-CALIPSO) experiment was devised to image the arc crust underlying Montserrat, and, if possible, the magma system at SHV using tomography and reflection seismology. Field operations were carried out in October–December 2007, with deployment of 238 seismometers on land supplementing seven volcano observatory stations, and with an array of 10 ocean-bottom seismometers deployed offshore. The RRS James Cook on NERC cruise JC19 towed a tuned airgun array plus a digital 48-channel streamer on encircling and radial tracks for 77 h about Montserrat during December 2007, firing 4414 airgun shots and yielding about 47 Gb of data. The main objecctives of the experiment were achieved. Preliminary analyses of these data published in 2010 generated images of heterogeneous high-velocity bodies representing the cores of volcanoes and subjacent intrusions, and shallow areas of low velocity on the flanks of the island that reflect volcaniclastic deposits and hydrothermal alteration. The resolution of this preliminary work did not extend beyond 5 km depth. An improved three-dimensional (3D) seismic velocity model was then obtained by inversion of 181 665 first-arrival travel times from a more-complete sampling of the dataset, yielding clear images to 7.5 km depth of a low-velocity volume that was interpreted as the magma chamber which feeds the current eruption, with an estimated volume 13 km3. Coupled thermal and seismic modelling revealed properties of the partly crystallized magma. Seismic reflection analyses aimed at imaging structures under southern Montserrat had limited success, and suggest subhorizontal layering interpreted as sills at a depth of between 6 and 19 km. Seismic reflection profiles collected offshore reveal deep fans of volcaniclastic debris and fault offsets, leading to new tectonic interpretations. This chapter presents the project goals and planning concepts, describes in detail the campaigns at sea and on land, summarizes the major results, and identifies the key lessons learned.