Incorporating cognitive-behavioral therapy with occupational therapy: A comparative study with patients with low back pain

This paper reports on the implementation of a psychoeducational program utilizing cognitive-behavioral principles. The efficacy of this psychoeducational treatment program in modifying dysfunctional attitudes in patients with chronic low back pain was examined using a two-group pretest posttest design with a follow-lip at 3 months Thirty patients (average age = 44.37 SD = 13.71) participated in the study, with 15 in the psychoeducational treatment group and 15 in the placebo control group. These two conditions were added on to an existing eclectic inpatient pain management program. After assessment on the IPAM (The Integrated Psychosocial Assessment Model), scores were reduced to multivariate composite scores on the factors of illness behavior depressed and negative cognitions, and acute pain strategies. Results of a group x time repeated measures analysis of variance for the three pain factors revealed a significant main effect for group (F(23,1) = 5.00 p < .04), tempered by a significant interaction between group and rime on the 'depressed and negative' pain factor (F(23,1) = 4.77 p < .04). Patients in the treatment group improved significantly over time and significantly more than the placebo control group patients at posttreatment. Results provide support for the program in increasing patients' feelings of control over their pain and the use of positive coping strategies, while reducing perceived helplessness, depression, disability, and pain intensity.

Aspects of adaptive management of coastal wetlands: Case studies of processes, conservation, restoration, impacts and assessment

Coastal wetlands are dynamic and include the freshwater-intertidal interface. In many parts of the world such wetlands are under pressure from increasing human populations and from predicted sea-level rise. Their complexity and the limited knowledge of processes operating in these systems combine to make them a management challenge.Adaptive management is advocated for complex ecosystem management (Hackney 2000; Meretsky et al. 2000; Thom 2000;National Research Council 2003).Adaptive management identifies management aims,makes an inventory/environmental assessment,plans management actions, implements these, assesses outcomes, and provides feedback to iterate the process (Holling 1978;Walters and Holling 1990). This allows for a dynamic management system that is responsive to change. In the area of wetland management recent adaptive approaches are exemplified by Natuhara et al. (2004) for wild bird management, Bunch and Dudycha (2004) for a river system, Thom (2000) for restoration, and Quinn and Hanna (2003) for seasonal wetlands in California. There are many wetland habitats for which we currently have only rudimentary knowledge (Hackney 2000), emphasizing the need for good information as a prerequisite for effective management. The management framework must also provide a way to incorporate the best available science into management decisions and to use management outcomes as opportunities to improve scientific understanding and provide feedback to the decision system. Figure 9.1 shows a model developed by Anorov (2004) based on the process-response model of Maltby et al. (1994) that forms a framework for the science that underlies an adaptive management system in the wetland context.

Managing the Brisbane River and Moreton Bay: an integrated research/management program to reduce impacts on an Australian estuary

The Brisbane River and Moreton Bay Study, an interdisciplinary study of Moreton Bay and its major tributaries, was initiated to address water quality issues which link sewage and diffuse loading with environmental degradation. Runoff and deposition of fine-grained sediments into Moreton Bay, followed by resuspension, have been linked with increased turbidity and significant loss of seagrass habitat. Sewage-derived nutrient enrichment, particularly nitrogen (N), has been linked to algal blooms by sewage plume maps. Blooms of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay have resulted in significant impacts on human health (e.g., contact dermatitis) and ecological health (e.g., seagrass loss), and the availability of dissolved iron from acid sulfate soil runoff has been hypothesised. The impacts of catchment activities resulting in runoff of sediments, nutrients and dissolved iron on the health of the Moreton Bay waterways are addressed. The Study, established by 6 local councils in association with two state departments in 1994, forms a regional component of a national and state program to achieve ecologically sustainable use of the waterways by protecting and enhancing their health, while maintaining economic and social development. The Study framework illustrates a unique integrated approach to water quality management whereby scientific research, community participation and the strategy development were done in parallel with each other. This collaborative effort resulted in a water quality management strategy which focuses on the integration of socioeconomic and ecological values of the waterways. This work has led to significant cost savings in infrastructure by providing a clear focus on initiatives towards achieving healthy waterways. The Study's Stage 2 initiatives form the basis for this paper.

Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.

Integrating spatial optimization and cellular automata for evaluating urban change

Urban growth and change presents numerous challenges for planners and policy makers. Effective and appropriate strategies for managing growth and change must address issues of social, environmental and economic sustainability. Doing so in practical terms is a difficult task given the uncertainty associated with likely growth trends not to mention the uncertainty associated with how social and environmental structures will respond to such change. An optimization based approach is developed for evaluating growth and change based upon spatial restrictions and impact thresholds. The spatial optimization model is integrated with a cellular automata growth simulation process. Application results are presented and discussed with respect to possible growth scenarios in south east Queensland, Australia.