Effect of moderate- and high-intensity acute exercise on appetite in obese individuals

Purpose The effect of acute exercise, and exercise intensity, on appetite control in obese individuals requires further study. The aim of this study was to compare the effects of acute isocaloric bouts (250 kcal) of high-intensity intermittent cycling (HIIC) and moderate-intensity continuous cycling (MICC) or short-duration HIIC (S-HIIC) (125 kcal) and a resting control condition on the appetite hormone responses, subjective feelings of appetite, energy intake (EI), and food reward in overweight/obese individuals. Methods This study is a randomized crossover study on 12 overweight/obese volunteers. Participants were assigned to the control, MICC, HIIC, and S-HIIC conditions, 1 wk apart, in a counterbalanced order. Exercise was performed 1 h after a standard breakfast. An ad libitum test lunch was served 3 h after breakfast. Fasting/postprandial plasma samples of insulin, acylated ghrelin, polypeptide YY3–36, and glucagon-like peptide 1 and subjective feelings of appetite were measured every 30 min for 3 h. Nutrient and taste preferences were measured at the beginning and end of each condition using the Leeds Food Preference Questionnaire. Results Insulin levels were significantly reduced, and glucagon-like peptide 1 levels significantly increased during all exercise bouts compared with those during rest. Acylated ghrelin plasma levels were lower in the MICC and HIIC, but not in S-HIIC, compared with those in control. There were no significant differences for polypeptide YY3–36 plasma levels, hunger or fullness ratings, EI, or food reward. Conclusions Our findings suggest that, in overweight/obese individuals, isocaloric bouts of moderate- or high-intensity exercise lead to a similar appetite response. This strengthens previous findings in normal-weight individuals that acute exercise, even at high intensity, does not induce any known physiological adaptation that would lead to increased EI.

Telephone-delivered health coaching improves anxiety outcomes after myocardial infarction: The 'ProActive Heart' trial

Background: Recently, we found a telephone-delivered secondary prevention programme using health coaching (‘ProActive Heart’) to be effective in improving a range of key behavioural outcomes for myocardial infarction (MI) patients. What remains unclear, however, is the extent to which these treatment effects translate to important psychological outcomes such as depression and anxiety outcomes, an issue of clinical significance due to the substantial proportion of MI patients who experience depression and anxiety. The objective of the study was to investigate, as a secondary hypothesis of a larger trial, the effects of a telephone-delivered health coaching programme on depression and anxiety outcomes of MI patients. Design: Two-arm, parallel-group, randomized, controlled design with six-months outcomes. Methods: Patients admitted to one of two tertiary hospitals in Brisbane, Australia following MI were assessed for eligibility. Four hundred and thirty patients were recruited and randomly assigned to usual care or an intervention group comprising up to 10 telephone-delivered ‘health coaching’ sessions (ProActive Heart). Regression analysis compared Hospital Anxiety and Depression Scale scores of completing participants at six months (intervention: n = 141 versus usual care: n = 156). Results: The intervention yielded reductions in anxiety at follow-up (mean difference = −0.7, 95% confidence interval=−1.4,−0.02) compared with usual care. A similar pattern was observed in mean depression scores but was not statistically significant. Conclusions: The ProActive Heart programme effectively improves anxiety outcomes of patients following myocardial infarction. If combined with psychological-specific treatment, this programme could impact anxiety of greater intensity in a clinically meaningful way.

Making stories matter: Using participatory new media storytelling and evaluation to serve marginalised and regional communities

In this chapter, we draw on our experiences facilitating community storytelling workshops in regional Queensland in partnership with the Queensland branch of Oral History Association of Australia (OHAA Qld) in order to develop a best practice model for promoting creative approaches to recording oral narratives using digital tools, informed by creative writing practice and embedded evaluation (Klaebe 2012 & 2013). These experiences offer an insight into how creative approaches to training can facilitate the sharing and preservation of stories in regional communities.

Relocating a flood-affected community : good planning or good politics?

Problem, research strategy and findings: On January 10, 2011, the town of Grantham, Queensland (Australia), was inundated with a flash flood in which 12 of the town's 370 residents drowned. The overall damage bill in Queensland was AUD∃2.38 billion (USD∃2.4 billion) with 35 deaths, and more than three-quarters of the state was declared a flood disaster zone. In this study, we focus on the unusual and even rare decision to relocate Grantham in March 2011. The Lockyer Valley Regional Council (LVRC) acquired a 377-hectare (932-acre) site to enable a voluntary swap of equivalent-sized lots. In addition, planning regulations were set aside to streamline the relocation of a portion of the town. We review the natural hazard literature as it relates to community relocation, state and local government documents related to Grantham, and reports and newspaper articles related to the flood. We also analyze data from interviews with key stakeholders. We document the process of community relocation, assess the relocation process in Grantham against best practice, examine whether the process of community relocation can be upscaled and if the Grantham relocation is an example of good planning or good politics. Takeaway for practice: Our study reveals two key messages for practice. Community relocation (albeit a small one) is possible, and the process can be done quickly; some Grantham residents moved into their new, relocated homes in December 2012, just 11 months after the flood. Moreover, the role of existing planning regulations can be a hindrance to quick action; political leadership, particularly at the local level, is key to implementing the relocation.

Design thinking frameworks as transformative cross-disciplinary pedagogy

Final report for the Australian Government Office for Learning and Teaching. "This seed project ‘Design thinking frameworks as transformative cross-disciplinary pedagogy’ aimed to examine the way design thinking strategies are used across disciplines to scaffold the development of student attributes in the domain of problem solving and creativity in order to enhance the nation’s capacity for innovation. Generic graduate attributes associated with innovation, creativity and problem solving are considered to be amongst the most important of all targeted attributes (Bradley Review of Higher Education, 2009). The project also aimed to gather data on how academics across disciplines conceptualised design thinking methodologies and strategies. Insights into how design thinking strategies could be embedded at the subject level to improve student outcomes were of particular interest in this regard. A related aim was the investigation of how design thinking strategies could be used by academics when designing new and innovative subjects and courses." Case Study 3: QUT Community Engaged Learning Lab Design Thinking/Design Led Innovation Workshop by Natalie Wright Context "The author, from the discipline area of Interior Design in the QUT School of Design, Faculty of Creative Industries, is a contributing academic and tutor for The Community Engaged Learning Lab, which was initiated at Queensland University of Technology in 2012. The Lab facilitates university-wide service-learning experiences and engages students, academics, and key community organisations in interdisciplinary action research projects to support student learning and to explore complex and ongoing problems nominated by the community partners. In Week 3, Semester One 2013, with the assistance of co-lead Dr Cara Wrigley, Senior Lecturer in Design led Innovation, a Masters of Architecture research student and nine participating industry-embedded Masters of Research (Design led Innovation) facilitators, a Design Thinking/Design led Innovation workshop was conducted for the Community Engaged Learning Lab students, and action research outcomes published at 2013 Tsinghua International Design Management Symposium, December 2013 in Shenzhen, China (Morehen, Wright, & Wrigley, 2013)."

Social media(tion) and the reshaping of public/private boundaries in employment relations

Tensions surrounding social media in the employment relationship are increasingly evident in the media, public rhetoric, and courts and employment tribunals. Yet the underlying causes and dimensions of these tensions have remained largely unexplored. This article firstly reviews the available literature addressing social media and employment, outlining three primary sources of contestation: profiling, disparaging posts and blogs, and private use of social media during work time. In each area, the key dynamics and underlying concerns of the central actors involved are identified. The article then seeks to canvas explanations for these forms of contestation associated with social media at work. It is argued that the architecture of social media disrupts traditional relations in organisational life by driving employer and employee actions that (re)shape and (re)constitute the boundaries between public and private spheres. Although employers and employees are using the same social technologies, their respective concerns about and points of entry to these technologies, in contrast to traditional manifestations of conflict and resistance, are asymmetric. The article concludes with a representational summary of the relative legitimacy of concerns for organisational actors and outlines areas for future research.

Knowledge gain or system benefit in environmental decision making?

The quality of environmental decisions are gauged according to the management objectives of a conservation project. Management objectives are generally about maximising some quantifiable measure of system benefit, for instance population growth rate. They can also be defined in terms of learning about the system in question, in such a case actions would be chosen that maximise knowledge gain, for instance in experimental management sites. Learning about a system can also take place when managing practically. The adaptive management framework (Walters 1986) formally acknowledges this fact by evaluating learning in terms of how it will improve management of the system and therefore future system benefit. This is taken into account when ranking actions using stochastic dynamic programming (SDP). However, the benefits of any management action lie on a spectrum from pure system benefit, when there is nothing to be learned about the system, to pure knowledge gain. The current adaptive management framework does not permit management objectives to evaluate actions over the full range of this spectrum. By evaluating knowledge gain in units distinct to future system benefit this whole spectrum of management objectives can be unlocked. This paper outlines six decision making policies that differ across the spectrum of pure system benefit through to pure learning. The extensions to adaptive management presented allow specification of the relative importance of learning compared to system benefit in management objectives. Such an extension means practitioners can be more specific in the construction of conservation project objectives and be able to create policies for experimental management sites in the same framework as practical management sites.

Making robust decisions for conservation with restricted money and knowledge

1. In conservation decision-making, we operate within the confines of limited funding. Furthermore, we often assume particular relationships between management impact and our investment in management. The structure of these relationships, however, is rarely known with certainty - there is model uncertainty. We investigate how these two fundamentally limiting factors in conservation management, money and knowledge, impact optimal decision-making. 2. We use information-gap decision theory to find strategies for maximizing the number of extant subpopulations of a threatened species that are most immune to failure due to model uncertainty. We thus find a robust framework for exploring optimal decision-making. 3. The performance of every strategy decreases as model uncertainty increases. 4. The strategy most robust to model uncertainty depends not only on what performance is perceived to be acceptable but also on available funding and the time horizon over which extinction is considered. 5. Synthesis and applications. We investigate the impact of model uncertainty on robust decision-making in conservation and how this is affected by available conservation funding. We show that subpopulation triage can be a natural consequence of robust decision-making. We highlight the need for managers to consider triage not as merely giving up, but as a tool for ensuring species persistence in light of the urgency of most conservation requirements, uncertainty and the poor state of conservation funding. We illustrate this theory by a specific application to allocation of funding to reduce poaching impact on the Sumatran tiger Panthera tigris sumatrae in Kerinci Seblat National Park. © 2008 The Authors.

Managing and learning with multiple models: Objectives and optimization algorithms

The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. © 2010 Elsevier Ltd.

Monitoring does not always count

The gross under-resourcing of conservation endeavours has placed an increasing emphasis on spending accountability. Increased accountability has led to monitoring forming a central element of conservation programs. Although there is little doubt that information obtained from monitoring can improve management of biodiversity, the cost (in time and/or money) of gaining this knowledge is rarely considered when making decisions about allocation of resources to monitoring. We present a simple framework allowing managers and policy advisors to make decisions about when to invest in monitoring to improve management. © 2010 Elsevier Ltd.

Optimal allocation of conservation effort among subpopulations of a threatened species: How important is patch quality?

Money is often a limiting factor in conservation, and attempting to conserve endangered species can be costly. Consequently, a framework for optimizing fiscally constrained conservation decisions for a single species is needed. In this paper we find the optimal budget allocation among isolated subpopulations of a threatened species to minimize local extinction probability. We solve the problem using stochastic dynamic programming, derive a useful and simple alternative guideline for allocating funds, and test its performance using forward simulation. The model considers subpopulations that persist in habitat patches of differing quality, which in our model is reflected in different relationships between money invested and extinction risk. We discover that, in most cases, subpopulations that are less efficient to manage should receive more money than those that are more efficient to manage, due to higher investment needed to reduce extinction risk. Our simple investment guideline performs almost as well as the exact optimal strategy. We illustrate our approach with a case study of the management of the Sumatran tiger, Panthera tigris sumatrae, in Kerinci Seblat National Park (KSNP), Indonesia. We find that different budgets should be allocated to the separate tiger subpopulations in KSNP. The subpopulation that is not at risk of extinction does not require any management investment. Based on the combination of risks of extinction and habitat quality, the optimal allocation for these particular tiger subpopulations is an unusual case: subpopulations that occur in higher-quality habitat (more efficient to manage) should receive more funds than the remaining subpopulation that is in lower-quality habitat. Because the yearly budget allocated to the KSNP for tiger conservation is small, to guarantee the persistence of all the subpopulations that are currently under threat we need to prioritize those that are easier to save. When allocating resources among subpopulations of a threatened species, the combined effects of differences in habitat quality, cost of action, and current subpopulation probability of extinction need to be integrated. We provide a useful guideline for allocating resources among isolated subpopulations of any threatened species. © 2010 by the Ecological Society of America.