Improving the Efficiency of Psychological Treatment using Outcome Feedback Technology

Aims: This study evaluated the impact of applying computerized outcome feedback (OF) technology in a stepped care psychological service offering low and high intensity therapies for depression and anxiety. Methods: A group of therapists were trained to use OF based on routine outcome monitoring using depression (PHQ-9) and anxiety (GAD-7) measures. Therapists regularly reviewed expected treatment response graphs with patients and discussed cases that were “not on track” in clinical supervision. Clinical outcomes data were collected for all patients treated by this group (N = 594), six months before (controls = 349) and six months after the OF training (OF cases = 245). Symptom reductions in PHQ-9 and GAD-7 were compared between controls and OF cases using longitudinal multilevel modelling. Treatment duration and costs were compared using MANOVA. Qualitative interviews with therapists (N = 15) and patients (N = 6) were interpreted using thematic analysis. Results: OF technology was generally acceptable and feasible to integrate in routine practice. No significant between-group differences were found in post-treatment PHQ-9 or GAD-7 measures. However, OF cases had significantly lower average duration and cost of treatment compared to controls. Conclusions: After adopting OF into their practice, this group of therapists attained similar clinical outcomes but within a shorter space of time and at a reduced average cost per treatment episode. We conclude that OF can improve the efficiency of stepped care

Forest 404: Using a BBC drama series to explore the impact of nature’s changing soundscapes on human wellbeing and behavior

Extensive ecosystem degradation and increasing urbanization are altering human relationships with nature. To explore these trends, we created a transdisciplinary, narrative-led podcast series produced by the BBC, called 'Forest 404'. The series explored the implications of a world without nature. An online experimental component mobilized audience participation (n = 7,596) to assess responses to natural soundscapes with and without abiotic, biotic, and poetic elements across five biomes. Conditions featuring the sounds of wildlife, such as bird song, were perceived to be more psychologically restorative than those without. Participants’ personal lived experiences were strongly related to these outcomes; those who had memories triggered by the sounds were more likely to find them psychologically restorative and exhibited a greater motivation to preserve them. Moreover, the effects of both soundscape composition and memories on preservation behavior were partially mediated by restorative potential; respondents were more likely to want to protect the sounds they heard if they thought they might offer therapeutic outcomes. Our findings highlight the value of art-science collaborations and demonstrate how maintaining contact with the natural world can promote wellbeing and foster behaviors that protect planetary health

Intelligent Solutions Sustaining Urban Economies – Master Classes case study

This is an output from the FP7 Regions of Knowledge project THE-ISSUE. This project is developing an EU network in the field of Intelligent Transport Systems that deliver on multiple policy objectives, Transport Health & the Environment. More can be found at www.theissue.euTHE ISSUE is a project within the Regions of Knowledge scheme funded through the European Commission’s Seventh Framework Programme. THE ISSUE focuses on traffic, health and the environment to achieve intelligent solutions for sustaining urban economies by bringing together innovative research-driven clusters to coordinate European research and technology development in six areas. These comprise ITS; transport impacts on urban mobility; transport greening; intermodal regional transport; safety and security of citizens; and associated economic, health and environmental impacts. THE ISSUE project particularly addresses the use of space technologies from satellite remote sensing and navigation, as well as GIS and computer intelligence technologies in transport-related sectors. This paper specifically looks into the planned Master Classes program. THE ISSUE project comprises research clusters from the East Midlands Region in the UK, the Midi-Pyrenees and Aquitaine Regions in France, the Molise Region in Italy and the Mazovia Region in Poland. Each region has set up a three-way partnership between regional authorities, academic partners, and industry contributors working to draw together the industry and academic strengths in the regions and connect the research with the needs of managing traffic, transport, and air quality that the regional bodies are responsible for. The three-year project is supporting scientists, engineers and development agencies from the different regions to work together, using the latest space and information technologies, to develop more effective methods of easing road congestion and improving the urban environment. As part of THE ISSUE project "Master Class" knowledge exchange programmes will be developed using material from the earlier review of applicable technology and expertise within the THE ISSUE consortium. Two variants will be developed, one focussing on senior management and policy/strategy makers and the other with a focus on technical awareness and implementation. The "Master Classes" will be trailed and delivered through workshops for core partners and associates. The case studies, which will be part of the Master Classes, will present information on how cartography, GPS&GIS database applications, navigation and remote sensing are used in urban transport, health and air quality related data. The project is bringing together scientists, engineers, development agencies and bodies responsible for managing traffic, transport and air quality in four European regional clusters using advanced space and information technologies, to develop the most effective methods of easing urban congestion and improving the impact of transport on the local economy, urban environment, climate change and the health of citizens. These Master Classes materials will contribute for the exchange of knowledge and expertise in sustainable traffic solutions between academic, business and public sector partners within and across the five European regions.EU FP

An ocean-colour time series for use in climate studies: the experience of the ocean-colour climate change initiate (OC-CCI)

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea viewingWide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel

Expansion of immunoglobulin-secreting cells and defects in B cell tolerance in Rag-dependent immunodeficiency

The contribution of B cells to the pathology of Omenn syndrome and leaky severe combined immunodeficiency (SCID) has not been previously investigated. We have studied a mut/mut mouse model of leaky SCID with a homozygous Rag1 S723C mutation that impairs, but does not abrogate, V(D)J recombination activity. In spite of a severe block at the pro–B cell stage and profound B cell lymphopenia, significant serum levels of immunoglobulin (Ig) G, IgM, IgA, and IgE and a high proportion of Ig-secreting cells were detected in mut/mut mice. Antibody responses to trinitrophenyl (TNP)-Ficoll and production of high-affinity antibodies to TNP–keyhole limpet hemocyanin were severely impaired, even after adoptive transfer of wild-type CD4+ T cells. Mut/mut mice produced high amounts of low-affinity self-reactive antibodies and showed significant lymphocytic infiltrates in peripheral tissues. Autoantibody production was associated with impaired receptor editing and increased serum B cell–activating factor (BAFF) concentrations. Autoantibodies and elevated BAFF levels were also identified in patients with Omenn syndrome and leaky SCID as a result of hypomorphic RAG mutations. These data indicate that the stochastic generation of an autoreactive B cell repertoire, which is associated with defects in central and peripheral checkpoints of B cell tolerance, is an important, previously unrecognized, aspect of immunodeficiencies associated with hypomorphic RAG mutations

ARSF Data Quality Report 2008

This report describes issues that should be considered when further processing any of the 2008 ARSF datasets